davanstrien/summary-test · Datasets at Hugging Face

datasetId stringlengths 2 117	card stringlengths 19 1.01M
joey234/sst2_100_1	--- dataset_info: features: - name: idx dtype: int64 - name: sentence dtype: string - name: label dtype: int64 splits: - name: train num_bytes: 12846 num_examples: 100 download_size: 11262 dataset_size: 12846 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "sst2_100_1" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
Reindrob/dsc	--- license: unknown ---
autoevaluate/autoeval-staging-eval-project-29af5371-7254762	--- type: predictions tags: - autotrain - evaluation datasets: - conll2003 eval_info: task: entity_extraction model: elastic/distilbert-base-uncased-finetuned-conll03-english dataset_name: conll2003 dataset_config: conll2003 dataset_split: validation col_mapping: tokens: tokens tags: ner_tags --- # Dataset Card for AutoTrain Evaluator This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset: * Task: Token Classification * Model: elastic/distilbert-base-uncased-finetuned-conll03-english * Dataset: conll2003 To run new evaluation jobs, visit Hugging Face's [automatic evaluation service](https://huggingface.co/spaces/autoevaluate/model-evaluator). ## Contributions Thanks to [@douwekiela](https://huggingface.co/douwekiela) for evaluating this model.
sheriftawfikabbas/3oloum_corpus	--- language: - en pretty_name: "3oloum corpus for scientific abstract" tags: - science abstracts - English license: "gpl-3.0" --- # The 3oloum corpus of scientific titles and abstracts This is a corpus of titles and abstracts of 147,673 scientific articles that were scraped from the following scientific journals: - Nature: from year 1870 to 2021 - Science: from year 1960 to 2020 - Science Advances: from year 2015 to 2020 The corpus has been created for the purpose of contributing to natural language processing (NLP) projects. There are currently 21,309,015 words in the corpus, including the text of titles and abstracts, and excluding non-ASCII strings. Every non-ASCII character has been replaced by the string `<non_ascii>` to facilitate text processing. It is being continuously updated. ## Sample data \|Title\|Abstract\| \| :--- \| :--- \| \| Velocity of Light and Measurement of Interplanetary Distances \| The combined availability of atomic clocks and of instrumented planetoids traveling in their own solar orbits will offer the possibility of determining their distance from us, and hence interplanetary distances, in terms of the wavelength of the radiation of atomic frequency standards. It can be anticipated that the accuracy of these measurements will be very high and will not depend upon our less accurate knowledge of the velocity of light in terms of the standard meter, the sidereal second, and so on. \| \| High-Resolution Density Gradient Sedimentation Analysis \| The principle of stability for a sample layered in a density-gradient liquid column is discussed, and a method for separating ribonucleoprotein particles by means of sedimentation in the ultracentrifuge is described. \| \| Daily Light Sensitivity Rhythm in a Rodent \| Single 10-minute light periods can cause a phase shift in the rhythm of the daily locomotor activity of flying squirrels otherwise maintained in constant darkness. A daily rhythm of sensitivity to these standard light periods was found. \| \| Heat-Labile Serum Systems in Fresh-Water Fish \| Serum specimens from 18 specimens of 12 different species of freshwater fish were examined for their ability to kill <i>Toxoplasma</i> nonspecifically. This ability was present in all sera except those of two of three great northern pike. The effect was destroyed by exposure to 53<non_ascii><non_ascii>C, 56<non_ascii><non_ascii>C, or zymosan. Complement was demonstrated in all sera except that from one great northern pike, when rabbit erythrocytes were used in the indicator system. \| \| Chemically Induced Phenocopy of a Tomato Mutant \| Lanceolate, a spontaneous leaf-shape mutant which fails to produce cotyledons and plumule in the homozygous condition, shows development if supplied with either adenine or a diffusate obtained from normal seeds. Similar development occurs in a different genetic background. \| \| Mitotic Arrest by Deuterium Oxide \| In marine invertebrate eggs, where cell divisions occur without growth, deuterium oxide produces arrest of, or serious delay in, mitosis and cytokinesis. All stages requiring assembly or operation of mechanical structures in the cytoplasm are sensitive to D.O. The block is reversible in some cells. \| \| Nonlogarithmic Linear Titration Curves \| Titration curves can be based on linear nonlogarithmic forms of the equilibrium equation of a dissociation reaction. From such curves, in contrast to those based on logarithmic transformations, both the end point of the titration and the dissociation constant can be derived. \| \| On the Function of Corticothalamic Neurons \| The effect of the synchronous discharge of a large population of corticothalamic neurons on activity within the somatosensory relay nuclei has been studied. Thalamic responses to peripheral nerve stimulation are depressed by activity in corticothalamic neurons. A subconvulsive dose of strychnine, given intravenously, changes this depression to enhancement. \| \| Occurrence of Scandium-46 and Cesium-134 in Radioactive Fallout \| Two hitherto unreported induced radionuclides, scandium-46 and cesium-134, have been detected in fallout material. Identification was made by chemical separation and gamma scintillation spectrometry. While the origin of these materials is not known, possible routes of formation from stable elements are suggested. \| \| Degree of Obesity and Serum Cholesterol Level \| No significant correlation was found between the serum cholesterol level and weight, weight corrected for frame size, or thickness of the fat shadow in medical students (mean age, 22 years). \| \| Neural and Hypophyseal Colloid Deposition in the Collared Lemming \| Feral and captive lemmings from Churchill, Manitoba, are subject to a unique pathological process in which colloidal material is deposited in bloodvessel walls at scattered points through the central nervous system. Destruction of nervous tissue at these foci is progressive, and colloidal masses in the vascular lumina of the hypothalamus appear to become fixed in the capillaries of the hypophyseal anterior lobe. Inflammatory reactions are never associated with the lesions, and the latter are larger and more numerous in older animals in warmer environments. \| \| On Pleistocene Surface Temperatures of the North Atlantic and Arctic Oceans \| Two additional interpretations are given for the important data of D. B. Ericson on the correlation of coiling directions of <i>Globigerina pachyderma</i> in late Pleistocene North Atlantic sediments with ocean surface temperatures. One interpretation relates the distribution of this species to the distribution and circulation of ocean water masses. On the basis of our ice-age theory, our second interpretation uses the data and correlations of Ericson to establish temperature limits of a thermal node, a line on which glacial and interglacial temperatures were equal, for the North Atlantic Ocean. This line crosses the strait between Greenland and Scandinavia. Further, Ericson9s interpretation of the 7.2<non_ascii><non_ascii>C isotherm implies that the glacial-stage surface waters of the Arctic Ocean were between 0<non_ascii><non_ascii> and 3.5<non_ascii><non_ascii>C. \| \| Genetic and Environmental Control of Flowering in Trifolium repens in the Tropics \| <i>Trifolium repens</i> at low elevations expressed wide genetic variation in tendency to flower. Clones classified as flowering or nonflowering were subjected to temperatures associated with high elevations. Flowering in "nonflowering" clones was induced under warm-day-cool-night treatments. It is proposed that in the tropics, low temperatures associated with high elevations are an important factor in determining flowering, and therefore ability to persist, in plants which are long-day and temperature sensitive. \| \| Mammalian Liver <non_ascii><non_ascii>-Glucuronidase for Hydrolysis of Steroidal Conjugates \| Although the rate of hydrolysis by mammalian <non_ascii><non_ascii>-glucuronidase appears to be inhibited by methylene chloride or carbon tetrachloride with the standard technique (phenolphthalein glucuronide as a substrate), the release of steroidal conjugates under conditions generally employed does not appear to be affected. \| \| Glucuronidase Activation: Enzyme Action at an Interface \| The potentiating action of chloroform on bacterial <non_ascii><non_ascii>-glucuronidase has been shown to increase as the interface area between the two liquid phases increases. Prior extraction of the enzyme with chloroform causes a loss rather than an increase in activity. It is tentatively suggested that the correlation between activity and interface area may reflect a phenomenon of enzyme action at a liquid/liquid interface. \| \| Characterization of Endogenous Ethanol in the Mammal \| Ethanol has been isolated from the tissues of several animal species in amounts ranging from 23 to 145 <non_ascii><non_ascii>mole/100 gm of tissue. Intestinal bacterial flora appear to be excluded as a source of this ethanol. Radioactivity from pyruvate-2-C<sup>14</sup> appeared in ethanol after incubation with liver slices; this finding indicates an endogenous synthesis. \| \| Reciprocal Inhibition as Indicated by a Differential Staining Reaction \| Neurohistological and neurophysiological studies have shown that the bilaterally represented Mauthner9s cells in teleosts are related both structurally and functionally. The VIIIth nerve afferents, as well as the axoaxonal collaterals, display a distribution pattern which supports the concept of polar function of the neuron. Inasmuch as it is possible to alter the staining reaction of both the Mauthner9s cells by unilateral stimulation of the entering VIIIth nerve roots, it is proposed that the synaptic endings serve principally as activators and that neuronal excitation or inhibition is determined by the chemical state of the dendrites, the cell body, and the axon hillock region. \| \| Orientation of Migratory Restlessness in the White-Crowned Sparrow \| Individuals of two migratory races of white-crowned sparrows (<i>Zonotrichia leucophrys</i>) caged under an open sky showed a pronounced orientation in their night restlessness during normal periods of migration for the species. In August and September 1958 most birds showed a southerly orientation at night; daytime activity was random to somewhat northerly. In April and May 1959 most birds showed a strong northerly orientation at night; daytime activity was random to somewhat southerly (<i>1</i>). \| \| State of Dynamic Equilibrium in Protein of Mammalian Cells \| Labeled strain L cells in suspension tissue culture showed no degradation of protein when maintained in logarithmic growth. Although the protein of these cells was not in dynamic equilibrium, the conclusions cannot be transferred to the intact mammalian organism. \| \| Mosses as Possible Sources of Antibiotics \| An examination of 12 species of mosses has indicated that three produce substances capable of inhibiting the growth of various bacteria and other fungi. The method of extraction included several solvents. The extracts were not consistent in their antagonistic activity against the various species of microorganisms, nor were those that displayed antibiotic action always effective against the same organisms. Results indicate unstable products as well as physiological variation in the mosses. \|
infinityofspace/python_codestyles-random-1k	--- configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* dataset_info: features: - name: code dtype: string - name: code_codestyle dtype: int64 - name: style_context dtype: string - name: style_context_codestyle dtype: int64 - name: label dtype: int64 splits: - name: train num_bytes: 3604934957 num_examples: 308000 - name: test num_bytes: 645620388 num_examples: 56400 download_size: 671035436 dataset_size: 4250555345 license: mit tags: - python - code-style - random size_categories: - 100K<n<1M --- # Dataset Card for "python_codestyles-random-1k" This dataset contains negative and positive examples with python code of compliance with a code style. A positive example represents compliance with the code style (label is 1). Each example is composed of two components, the first component consists of a code that either conforms to the code style or violates it and the second component corresponding to an example code that already conforms to a code style. In total, the dataset contains `1.000` completely different code styles. The code styles differ in at least one codestyle rule, which is called a `random` codestyle dataset variant. The dataset consists of a training and test group, with none of the code styles overlapping between groups. In addition, both groups contain completely different underlying codes. The examples contain source code from the following repositories: \| repository \| tag or commit \| \|:-----------------------------------------------------------------------:\|:----------------------------------------:\| \| [TheAlgorithms/Python](https://github.com/TheAlgorithms/Python) \| f614ed72170011d2d439f7901e1c8daa7deac8c4 \| \| [huggingface/transformers](https://github.com/huggingface/transformers) \| v4.31.0 \| \| [huggingface/datasets](https://github.com/huggingface/datasets) \| 2.13.1 \| \| [huggingface/diffusers](https://github.com/huggingface/diffusers) \| v0.18.2 \| \| [huggingface/accelerate](https://github.com/huggingface/accelerate) \| v0.21.0 \| You can find the corresponding code styles of the examples in the file [additional_data.json](additional_data.json). The code styles in the file are split by training and test group and the index corresponds to the class for the columns `code_codestyle` and `style_context_codestyle` in the dataset. There are 364.400 samples in total and 182.200 positive and 182.200 negative samples.
NTA-Dev/training_pdfs	--- license: apache-2.0 ---
EdiOapsie/TheBlueTireBook	--- license: apache-2.0 ---
Hieu-Pham/cooking_squad	--- license: mit ---
jlbaker361/small_subtraction_decimal	--- configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* dataset_info: features: - name: input dtype: string - name: output dtype: float64 - name: text dtype: string splits: - name: train num_bytes: 2030.2222222222222 num_examples: 40 - name: test num_bytes: 253.77777777777777 num_examples: 5 download_size: 4553 dataset_size: 2284.0 --- # Dataset Card for "small_subtraction_decimal" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
SuperAGI/SAM_Dataset	--- dataset_info: features: - name: Question dtype: string - name: Answer dtype: string splits: - name: train num_bytes: 192091934 num_examples: 135119 download_size: 88166828 dataset_size: 192091934 configs: - config_name: default data_files: - split: train path: data/train-* ---
anan-2024/twitter_dataset_1713023266	--- dataset_info: features: - name: id dtype: string - name: tweet_content dtype: string - name: user_name dtype: string - name: user_id dtype: string - name: created_at dtype: string - name: url dtype: string - name: favourite_count dtype: int64 - name: scraped_at dtype: string - name: image_urls dtype: string splits: - name: train num_bytes: 105089 num_examples: 281 download_size: 58528 dataset_size: 105089 configs: - config_name: default data_files: - split: train path: data/train-* ---
catinthebag/Indo4B-Combined	--- language: - id license: mit dataset_info: features: - name: text dtype: string splits: - name: train num_bytes: 25012332583 num_examples: 232763064 download_size: 15176365901 dataset_size: 25012332583 configs: - config_name: default data_files: - split: train path: data/train-* --- This is the entire Indo4B dataset, combined into a single file. The original dataset can be found here: https://github.com/IndoNLP/indonlu This is a combination of all the different files in the compressed .tar.xz. The goal is so that anyone who's interested in Indonesian NLP can fairly simply load this dataset from huggingface, already combined in full. Note the original files consists of line-separated strings. This dataset just combines them while removing the available blank lines.
3lydatta/Daniel	--- license: openrail ---
joujiboi/japanese-knowledge-base	--- license: cc-by-nc-4.0 task_categories: - question-answering - text-generation language: - en tags: - language - japanese language - nihongo - 日本語 size_categories: - 1K<n<10K pretty_name: Japanese Knowledge Base --- # Japanese Knowledge Base JKB (Japanese Knowledge Base) is a work-in-progress question and answer dataset on the Japanese language. The goal of JKB is to provide training data for large language models to better answer questions about the Japanese language, particularly for learners of Japanese. ## The dataset contains topics about: * N5 to N1 grammar * Structure and word order * The writing systems * Word types * Particles and the commonly confused ones * Conjugation * Verbs and verb types * Adjectives and adjective types * Formality * Name suffixes ## The dataset will not focus on: * Translation * Definitions of words * Sentence nuance ## Sample ``` Question: What is a common usage scenario for 〜たり〜たり? Answer: The 〜たり〜たり structure is for listing actions as examples among various possibilities. It is commonly used to describe routines or plans. For example, one might use it to describe what they typically do on their days off or what they plan to do during a vacation. Question: How do you use 思う with na-adjectives? Answer: For na-adjectives, you can attach だ to the adjective in its plain form and then add と思う. For example, if you think someone is happy, you could say "幸せだと思います". Question: How do you use と思う with i-adjectives? Answer: To use 〜と思う with i-adjectives, you simply take the i-adjective in its plain form and attach と思う to it. For example, if you think something is hot (熱い), you can say "熱いと思う". Question: Is it possible to use 〜たい in a question? Answer: Yes, you can use 〜たい to ask about someone's desires or wishes, but be cautious when using it with superiors or elders as it can be considered impolite. ``` ## Citation This dataset uses the `Creative Commons Attribution Non Commercial 4.0` licence which means you may use my dataset for non-commercial purposes and you must give credit. ``` @misc{Japanese Knowledge Base, title = {Japanese Knowledge Base: A question and answer dataset on the Japanese language}, author = {JawGBoi}, year = {2023}, publisher = {HuggingFace}, journal = {HuggingFace repository}, howpublished = {\url{https://huggingface.co/datasets/joujiboi/japanese-knowledge-base}}, } ```
kpriyanshu256/MultiTabQA-multitable_pretraining-Salesforce-codet5-base_train-html-117000	--- dataset_info: features: - name: input_ids sequence: sequence: int32 - name: attention_mask sequence: sequence: int8 - name: labels sequence: sequence: int64 splits: - name: train num_bytes: 13336000 num_examples: 1000 download_size: 660107 dataset_size: 13336000 configs: - config_name: default data_files: - split: train path: data/train-* ---
TrainingDataPro/hand-gesture-recognition-dataset	--- language: - en license: cc-by-nc-nd-4.0 task_categories: - video-classification tags: - code dataset_info: features: - name: set_id dtype: int32 - name: fist dtype: string - name: four dtype: string - name: me dtype: string - name: one dtype: string - name: small dtype: string splits: - name: train num_bytes: 1736 num_examples: 28 download_size: 1510134076 dataset_size: 1736 --- # Hand Gesture Recognition Dataset The dataset consists of videos showcasing individuals demonstrating 5 different hand gestures ("one", "four", "small", "fist", and "me"). Each video captures a person prominently displaying a single hand gesture, allowing for accurate identification and differentiation of the gestures. The dataset offers a diverse range of individuals performing the gestures, enabling the exploration of variations in hand shapes, sizes, and movements across different individuals. The videos in the dataset are recorded in reasonable lighting conditions and with adequate resolution, to ensure that the hand gestures can be easily observed and studied. ### The dataset's possible applications: - hand gesture recognition - gesture-based control systems - virtual reality interactions - sign language analysis - human pose estimation and action analysis - security and authentication systems ![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F618942%2F02149459e1fc1f76e2575dcdba6ec406%2FMacBook%20Air%20-%201.png?generation=1689667735287012&alt=media) # Get the dataset ### This is just an example of the data Leave a request on [https://trainingdata.pro/data-market](https://trainingdata.pro/data-market?utm_source=huggingface&utm_medium=cpc&utm_campaign=hand-gesture-recognition-dataset) to discuss your requirements, learn about the price and buy the dataset. # Content - files: includes folders corresponding to people and containing videos with 5 different shown gestures, each file is named according to the captured gesture - .csv file: contains information about files in the dataset ### Hand gestures in the dataset: - "one" - "four" - "small" - "clenched fist" - "me" ### File with the extension .csv includes the following information: - set_id: id of the set of videos, - one: link to the video with "one" gesture, - four: link to the video with "four" gesture, - small: link to the video with "small" gesture, - fist: link to the video with "fist" gesture, - me: link to the video with "me" gesture # Videos with hand gestures might be collected in accordance with your requirements. ## [TrainingData](https://trainingdata.pro/data-market?utm_source=huggingface&utm_medium=cpc&utm_campaign=hand-gesture-recognition-dataset) provides high-quality data annotation tailored to your needs More datasets in TrainingData's Kaggle account: https://www.kaggle.com/trainingdatapro/datasets TrainingData's GitHub: https://github.com/Trainingdata-datamarket/TrainingData_All_datasets
thientran/autotrain-data-favs_bot	--- language: - en --- # AutoTrain Dataset for project: favs_bot ## Dataset Descritpion This dataset has been automatically processed by AutoTrain for project favs_bot. ### Languages The BCP-47 code for the dataset's language is en. ## Dataset Structure ### Data Instances A sample from this dataset looks as follows: ```json [ { "feat_id": "13104", "tokens": [ "Jackie", "Frank" ], "feat_pos_tags": [ 21, 21 ], "feat_chunk_tags": [ 5, 16 ], "tags": [ 3, 7 ] }, { "feat_id": "9297", "tokens": [ "U.S.", "lauds", "Russian-Chechen", "deal", "." ], "feat_pos_tags": [ 21, 20, 15, 20, 7 ], "feat_chunk_tags": [ 5, 16, 16, 16, 22 ], "tags": [ 0, 8, 1, 8, 8 ] } ] ``` ### Dataset Fields The dataset has the following fields (also called "features"): ```json { "feat_id": "Value(dtype='string', id=None)", "tokens": "Sequence(feature=Value(dtype='string', id=None), length=-1, id=None)", "feat_pos_tags": "Sequence(feature=ClassLabel(num_classes=47, names=['\"', '#', '$', \"''\", '(', ')', ',', '.', ':', 'CC', 'CD', 'DT', 'EX', 'FW', 'IN', 'JJ', 'JJR', 'JJS', 'LS', 'MD', 'NN', 'NNP', 'NNPS', 'NNS', 'NN\|SYM', 'PDT', 'POS', 'PRP', 'PRP$', 'RB', 'RBR', 'RBS', 'RP', 'SYM', 'TO', 'UH', 'VB', 'VBD', 'VBG', 'VBN', 'VBP', 'VBZ', 'WDT', 'WP', 'WP$', 'WRB', '``'], id=None), length=-1, id=None)", "feat_chunk_tags": "Sequence(feature=ClassLabel(num_classes=23, names=['B-ADJP', 'B-ADVP', 'B-CONJP', 'B-INTJ', 'B-LST', 'B-NP', 'B-PP', 'B-PRT', 'B-SBAR', 'B-UCP', 'B-VP', 'I-ADJP', 'I-ADVP', 'I-CONJP', 'I-INTJ', 'I-LST', 'I-NP', 'I-PP', 'I-PRT', 'I-SBAR', 'I-UCP', 'I-VP', 'O'], id=None), length=-1, id=None)", "tags": "Sequence(feature=ClassLabel(num_classes=9, names=['B-LOC', 'B-MISC', 'B-ORG', 'B-PER', 'I-LOC', 'I-MISC', 'I-ORG', 'I-PER', 'O'], id=None), length=-1, id=None)" } ``` ### Dataset Splits This dataset is split into a train and validation split. The split sizes are as follow: \| Split name \| Num samples \| \| ------------ \| ------------------- \| \| train \| 10013 \| \| valid \| 4029 \|
georgeyw/TinyStoriesV2-GPT4-10k	--- license: cdla-sharing-1.0 ---
quaeast/multimodal_sarcasm_detection	--- language: - en --- copy of [data-of-multimodal-sarcasm-detection](https://github.com/headacheboy/data-of-multimodal-sarcasm-detection) ```python # usage from datasets import load_dataset from transformers import CLIPImageProcessor, CLIPTokenizer from torch.utils.data import DataLoader image_processor = CLIPImageProcessor.from_pretrained(clip_path) tokenizer = CLIPTokenizer.from_pretrained(clip_path) def tokenization(example): text_inputs = tokenizer(example["text"], truncation=True, padding=True, return_tensors="pt") image_inputs = image_processor(example["image"], return_tensors="pt") return {'pixel_values': image_inputs['pixel_values'], 'input_ids': text_inputs['input_ids'], 'attention_mask': text_inputs['attention_mask'], "label": example["label"]} dataset = load_dataset('quaeast/multimodal_sarcasm_detection') dataset.set_transform(tokenization) # get torch dataloader train_dl = DataLoader(dataset['train'], batch_size=256, shuffle=True) test_dl = DataLoader(dataset['test'], batch_size=256, shuffle=True) val_dl = DataLoader(dataset['validation'], batch_size=256, shuffle=True) ```
muhammadravi251001/tydiqaid-nli	--- annotations_creators: - machine-generated - manual-partial-validation language_creators: - expert-generated language: - id license: unknown multilinguality: - monolingual size_categories: - 1K<n<10K source_datasets: - TyDI-QA-ID task_categories: - text-classification task_ids: - natural-language-inference pretty_name: TyDI-QA-ID-NLI dataset_info: features: - name: premise dtype: string - name: hypothesis dtype: string - name: label dtype: class_label: names: '0': entailment '1': neutral '2': contradiction config_name: tydiqaid-nli splits: - name: train num_bytes: 3207000 num_examples: 9695 - name: validation num_bytes: 373750 num_examples: 1131 - name: test num_bytes: 565625 num_examples: 1171 download_size: 4146375 dataset_size: 11997 --- # Dataset Card for TyDI-QA-ID-NLI ## Table of Contents - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Repository: [Hugging Face](https://huggingface.co/datasets/muhammadravi251001/tydiqaid-nli) - Point of Contact: [Hugging Face](https://huggingface.co/datasets/muhammadravi251001/tydiqaid-nli) - Experiment: [Github](https://github.com/muhammadravi251001/multilingual-qas-with-nli) ### Dataset Summary The TyDI-QA-ID-NLI dataset is derived from the TyDI-QA-ID question answering dataset, utilizing named entity recognition (NER), chunking tags, Regex, and embedding similarity techniques to determine its contradiction sets. Collected through this process, the dataset comprises various columns beyond premise, hypothesis, and label, including properties aligned with NER and chunking tags. This dataset is designed to facilitate Natural Language Inference (NLI) tasks and contains information extracted from diverse sources to provide comprehensive coverage. Each data instance encapsulates premise, hypothesis, label, and additional properties pertinent to NLI evaluation. ### Supported Tasks and Leaderboards - Natural Language Inference for Indonesian ### Languages Indonesian ## Dataset Structure ### Data Instances An example of `test` looks as follows. ``` { "premise": "Manuls sering kali terlihat di padang rumput stepa Asia Tengah wilayah Mongolia, Cina dan Dataran Tinggi Tibet, di mana rekor elevasi 5.050 m (16.570 kaki) dilaporkan.[5] Mereka secara luas tersebar di daerah dataran tinggi dan lekukan Intermountain serta padang rumput pegunungan di Kyrgyzstan dan Kazakhstan.[6] Di Rusia, mereka muncul sesekali di Transkaukasus dan daerah Transbaikal, di sepanjang perbatasan dengan utara-timur Kazakhstan, dan di sepanjang perbatasan dengan Mongolia dan Cina di Altai, Tyva Buryatia, dan Chita republik. Pada musim semi 1997, trek yang ditemukan di Timur Sayan pada ketinggian 2.470 m (8.100 kaki) dalam 4,5cm (1,8 in) lapisan salju yang tebal. Trek ini dianggap fakta pertama yang dapat dibuktikan mendiami daerah manuls. Analisis DNA dari kotoran individu ini menegaskan kehadiran spesies.[7] Populasi di barat daya, yaitu wilayah Laut Kaspia, Afghanistan dan Pakistan, berkurang, terisolasi dan jarang [8][9]. Pada tahun 2008, seekor individu terekam kamera di Iran Khojir National Park untuk pertama kalinya [10].,Dimanakah Kucing Pallas pertama kali ditemukan ?", "hypothesis": ",Dimanakah Kucing Pallas pertama kali ditemukan ? 2008", "label": 0 } ``` ### Data Fields The data fields are: - `premise`: a `string` feature - `hypothesis`: a `string` feature - `label`: a classification label, with possible values including `entailment` (0), `neutral` (1), `contradiction` (2). ### Data Splits #TODO The data is split across `train`, `valid`, and `test`. \| split \| # examples \| \|----------\|-------:\| \|train\| 9695\| \|valid\| 1131\| \|test\| 1171\| ## Dataset Creation ### Curation Rationale Indonesian NLP is considered under-resourced. We need NLI dataset to fine-tuning the NLI model to utilizing them for QA models in order to improving the performance of the QA's. ### Source Data #### Initial Data Collection and Normalization We collect the data from the prominent QA dataset in Indonesian. The annotation fully by the original dataset's researcher. #### Who are the source language producers? This synthetic data was produced by machine, but the original data was produced by human. ### Personal and Sensitive Information There might be some personal information coming from Wikipedia and news, especially the information of famous/important people. ## Considerations for Using the Data ### Discussion of Biases The QA dataset (so the NLI-derived from them) is created using premise sentences taken from Wikipedia and news. These data sources may contain some bias. ### Other Known Limitations No other known limitations ## Additional Information ### Dataset Curators This dataset is the result of the collaborative work of Indonesian researchers from the University of Indonesia, Mohamed bin Zayed University of Artificial Intelligence, and the Korea Advanced Institute of Science & Technology. ### Licensing Information The license is Unknown. Please contact authors for any information on the dataset.
pyakymenko/test_repo	--- dataset_info: features: - name: audio dtype: audio - name: sentence dtype: string splits: - name: train num_bytes: 167117.0 num_examples: 3 download_size: 162079 dataset_size: 167117.0 --- # Dataset Card for "test_repo" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
open-llm-leaderboard/details_Muhammad2003__Myriad-7B-Slerp	--- pretty_name: Evaluation run of Muhammad2003/Myriad-7B-Slerp dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [Muhammad2003/Myriad-7B-Slerp](https://huggingface.co/Muhammad2003/Myriad-7B-Slerp)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 63 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the aggregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_Muhammad2003__Myriad-7B-Slerp\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-04-05T21:09:13.517339](https://huggingface.co/datasets/open-llm-leaderboard/details_Muhammad2003__Myriad-7B-Slerp/blob/main/results_2024-04-05T21-09-13.517339.json)(note\ \ that their might be results for other tasks in the repos if successive evals didn't\ \ cover the same tasks. You find each in the results and the \"latest\" split for\ \ each eval):\n\n```python\n{\n \"all\": {\n \"acc\": 0.6498757467364364,\n\ \ \"acc_stderr\": 0.0320415504432472,\n \"acc_norm\": 0.6488639096760553,\n\ \ \"acc_norm_stderr\": 0.032715942329960675,\n \"mc1\": 0.6328029375764994,\n\ \ \"mc1_stderr\": 0.016874805001453184,\n \"mc2\": 0.7800372751713768,\n\ \ \"mc2_stderr\": 0.013681851851800382\n },\n \"harness\|arc:challenge\|25\"\ : {\n \"acc\": 0.712457337883959,\n \"acc_stderr\": 0.013226719056266127,\n\ \ \"acc_norm\": 0.7320819112627986,\n \"acc_norm_stderr\": 0.012942030195136438\n\ \ },\n \"harness\|hellaswag\|10\": {\n \"acc\": 0.717486556462856,\n\ \ \"acc_stderr\": 0.004493015945599716,\n \"acc_norm\": 0.891256721768572,\n\ \ \"acc_norm_stderr\": 0.0031068060075356255\n },\n \"harness\|hendrycksTest-abstract_algebra\|5\"\ : {\n \"acc\": 0.31,\n \"acc_stderr\": 0.04648231987117316,\n \ \ \"acc_norm\": 0.31,\n \"acc_norm_stderr\": 0.04648231987117316\n \ \ },\n \"harness\|hendrycksTest-anatomy\|5\": {\n \"acc\": 0.6370370370370371,\n\ \ \"acc_stderr\": 0.04153948404742398,\n \"acc_norm\": 0.6370370370370371,\n\ \ \"acc_norm_stderr\": 0.04153948404742398\n },\n \"harness\|hendrycksTest-astronomy\|5\"\ : {\n \"acc\": 0.7105263157894737,\n \"acc_stderr\": 0.03690677986137283,\n\ \ \"acc_norm\": 0.7105263157894737,\n \"acc_norm_stderr\": 0.03690677986137283\n\ \ },\n \"harness\|hendrycksTest-business_ethics\|5\": {\n \"acc\": 0.64,\n\ \ \"acc_stderr\": 0.04824181513244218,\n \"acc_norm\": 0.64,\n \ \ \"acc_norm_stderr\": 0.04824181513244218\n },\n \"harness\|hendrycksTest-clinical_knowledge\|5\"\ : {\n \"acc\": 0.7056603773584905,\n \"acc_stderr\": 0.028049186315695255,\n\ \ \"acc_norm\": 0.7056603773584905,\n \"acc_norm_stderr\": 0.028049186315695255\n\ \ },\n \"harness\|hendrycksTest-college_biology\|5\": {\n \"acc\": 0.7708333333333334,\n\ \ \"acc_stderr\": 0.03514697467862388,\n \"acc_norm\": 0.7708333333333334,\n\ \ \"acc_norm_stderr\": 0.03514697467862388\n },\n \"harness\|hendrycksTest-college_chemistry\|5\"\ : {\n \"acc\": 0.49,\n \"acc_stderr\": 0.05024183937956911,\n \ \ \"acc_norm\": 0.49,\n \"acc_norm_stderr\": 0.05024183937956911\n \ \ },\n \"harness\|hendrycksTest-college_computer_science\|5\": {\n \"acc\"\ : 0.56,\n \"acc_stderr\": 0.04988876515698589,\n \"acc_norm\": 0.56,\n\ \ \"acc_norm_stderr\": 0.04988876515698589\n },\n \"harness\|hendrycksTest-college_mathematics\|5\"\ : {\n \"acc\": 0.29,\n \"acc_stderr\": 0.04560480215720684,\n \ \ \"acc_norm\": 0.29,\n \"acc_norm_stderr\": 0.04560480215720684\n \ \ },\n \"harness\|hendrycksTest-college_medicine\|5\": {\n \"acc\": 0.653179190751445,\n\ \ \"acc_stderr\": 0.036291466701596636,\n \"acc_norm\": 0.653179190751445,\n\ \ \"acc_norm_stderr\": 0.036291466701596636\n },\n \"harness\|hendrycksTest-college_physics\|5\"\ : {\n \"acc\": 0.37254901960784315,\n \"acc_stderr\": 0.04810840148082636,\n\ \ \"acc_norm\": 0.37254901960784315,\n \"acc_norm_stderr\": 0.04810840148082636\n\ \ },\n \"harness\|hendrycksTest-computer_security\|5\": {\n \"acc\":\ \ 0.76,\n \"acc_stderr\": 0.04292346959909283,\n \"acc_norm\": 0.76,\n\ \ \"acc_norm_stderr\": 0.04292346959909283\n },\n \"harness\|hendrycksTest-conceptual_physics\|5\"\ : {\n \"acc\": 0.574468085106383,\n \"acc_stderr\": 0.03232146916224468,\n\ \ \"acc_norm\": 0.574468085106383,\n \"acc_norm_stderr\": 0.03232146916224468\n\ \ },\n \"harness\|hendrycksTest-econometrics\|5\": {\n \"acc\": 0.4824561403508772,\n\ \ \"acc_stderr\": 0.04700708033551038,\n \"acc_norm\": 0.4824561403508772,\n\ \ \"acc_norm_stderr\": 0.04700708033551038\n },\n \"harness\|hendrycksTest-electrical_engineering\|5\"\ : {\n \"acc\": 0.5310344827586206,\n \"acc_stderr\": 0.04158632762097828,\n\ \ \"acc_norm\": 0.5310344827586206,\n \"acc_norm_stderr\": 0.04158632762097828\n\ \ },\n \"harness\|hendrycksTest-elementary_mathematics\|5\": {\n \"acc\"\ : 0.41534391534391535,\n \"acc_stderr\": 0.025379524910778398,\n \"\ acc_norm\": 0.41534391534391535,\n \"acc_norm_stderr\": 0.025379524910778398\n\ \ },\n \"harness\|hendrycksTest-formal_logic\|5\": {\n \"acc\": 0.47619047619047616,\n\ \ \"acc_stderr\": 0.04467062628403273,\n \"acc_norm\": 0.47619047619047616,\n\ \ \"acc_norm_stderr\": 0.04467062628403273\n },\n \"harness\|hendrycksTest-global_facts\|5\"\ : {\n \"acc\": 0.3,\n \"acc_stderr\": 0.046056618647183814,\n \ \ \"acc_norm\": 0.3,\n \"acc_norm_stderr\": 0.046056618647183814\n \ \ },\n \"harness\|hendrycksTest-high_school_biology\|5\": {\n \"acc\": 0.7838709677419354,\n\ \ \"acc_stderr\": 0.02341529343356853,\n \"acc_norm\": 0.7838709677419354,\n\ \ \"acc_norm_stderr\": 0.02341529343356853\n },\n \"harness\|hendrycksTest-high_school_chemistry\|5\"\ : {\n \"acc\": 0.5123152709359606,\n \"acc_stderr\": 0.035169204442208966,\n\ \ \"acc_norm\": 0.5123152709359606,\n \"acc_norm_stderr\": 0.035169204442208966\n\ \ },\n \"harness\|hendrycksTest-high_school_computer_science\|5\": {\n \ \ \"acc\": 0.7,\n \"acc_stderr\": 0.046056618647183814,\n \"acc_norm\"\ : 0.7,\n \"acc_norm_stderr\": 0.046056618647183814\n },\n \"harness\|hendrycksTest-high_school_european_history\|5\"\ : {\n \"acc\": 0.7757575757575758,\n \"acc_stderr\": 0.03256866661681102,\n\ \ \"acc_norm\": 0.7757575757575758,\n \"acc_norm_stderr\": 0.03256866661681102\n\ \ },\n \"harness\|hendrycksTest-high_school_geography\|5\": {\n \"acc\"\ : 0.803030303030303,\n \"acc_stderr\": 0.028335609732463362,\n \"\ acc_norm\": 0.803030303030303,\n \"acc_norm_stderr\": 0.028335609732463362\n\ \ },\n \"harness\|hendrycksTest-high_school_government_and_politics\|5\": {\n\ \ \"acc\": 0.9119170984455959,\n \"acc_stderr\": 0.02045374660160103,\n\ \ \"acc_norm\": 0.9119170984455959,\n \"acc_norm_stderr\": 0.02045374660160103\n\ \ },\n \"harness\|hendrycksTest-high_school_macroeconomics\|5\": {\n \ \ \"acc\": 0.658974358974359,\n \"acc_stderr\": 0.024035489676335082,\n \ \ \"acc_norm\": 0.658974358974359,\n \"acc_norm_stderr\": 0.024035489676335082\n\ \ },\n \"harness\|hendrycksTest-high_school_mathematics\|5\": {\n \"\ acc\": 0.3074074074074074,\n \"acc_stderr\": 0.028133252578815632,\n \ \ \"acc_norm\": 0.3074074074074074,\n \"acc_norm_stderr\": 0.028133252578815632\n\ \ },\n \"harness\|hendrycksTest-high_school_microeconomics\|5\": {\n \ \ \"acc\": 0.6722689075630253,\n \"acc_stderr\": 0.03048991141767323,\n \ \ \"acc_norm\": 0.6722689075630253,\n \"acc_norm_stderr\": 0.03048991141767323\n\ \ },\n \"harness\|hendrycksTest-high_school_physics\|5\": {\n \"acc\"\ : 0.36423841059602646,\n \"acc_stderr\": 0.03929111781242742,\n \"\ acc_norm\": 0.36423841059602646,\n \"acc_norm_stderr\": 0.03929111781242742\n\ \ },\n \"harness\|hendrycksTest-high_school_psychology\|5\": {\n \"acc\"\ : 0.8440366972477065,\n \"acc_stderr\": 0.01555580271359017,\n \"\ acc_norm\": 0.8440366972477065,\n \"acc_norm_stderr\": 0.01555580271359017\n\ \ },\n \"harness\|hendrycksTest-high_school_statistics\|5\": {\n \"acc\"\ : 0.5092592592592593,\n \"acc_stderr\": 0.034093869469927006,\n \"\ acc_norm\": 0.5092592592592593,\n \"acc_norm_stderr\": 0.034093869469927006\n\ \ },\n \"harness\|hendrycksTest-high_school_us_history\|5\": {\n \"acc\"\ : 0.8431372549019608,\n \"acc_stderr\": 0.02552472232455335,\n \"\ acc_norm\": 0.8431372549019608,\n \"acc_norm_stderr\": 0.02552472232455335\n\ \ },\n \"harness\|hendrycksTest-high_school_world_history\|5\": {\n \"\ acc\": 0.8143459915611815,\n \"acc_stderr\": 0.025310495376944856,\n \ \ \"acc_norm\": 0.8143459915611815,\n \"acc_norm_stderr\": 0.025310495376944856\n\ \ },\n \"harness\|hendrycksTest-human_aging\|5\": {\n \"acc\": 0.6860986547085202,\n\ \ \"acc_stderr\": 0.031146796482972465,\n \"acc_norm\": 0.6860986547085202,\n\ \ \"acc_norm_stderr\": 0.031146796482972465\n },\n \"harness\|hendrycksTest-human_sexuality\|5\"\ : {\n \"acc\": 0.7938931297709924,\n \"acc_stderr\": 0.03547771004159465,\n\ \ \"acc_norm\": 0.7938931297709924,\n \"acc_norm_stderr\": 0.03547771004159465\n\ \ },\n \"harness\|hendrycksTest-international_law\|5\": {\n \"acc\":\ \ 0.7603305785123967,\n \"acc_stderr\": 0.03896878985070416,\n \"\ acc_norm\": 0.7603305785123967,\n \"acc_norm_stderr\": 0.03896878985070416\n\ \ },\n \"harness\|hendrycksTest-jurisprudence\|5\": {\n \"acc\": 0.7592592592592593,\n\ \ \"acc_stderr\": 0.04133119440243839,\n \"acc_norm\": 0.7592592592592593,\n\ \ \"acc_norm_stderr\": 0.04133119440243839\n },\n \"harness\|hendrycksTest-logical_fallacies\|5\"\ : {\n \"acc\": 0.7852760736196319,\n \"acc_stderr\": 0.032262193772867744,\n\ \ \"acc_norm\": 0.7852760736196319,\n \"acc_norm_stderr\": 0.032262193772867744\n\ \ },\n \"harness\|hendrycksTest-machine_learning\|5\": {\n \"acc\": 0.42857142857142855,\n\ \ \"acc_stderr\": 0.04697113923010212,\n \"acc_norm\": 0.42857142857142855,\n\ \ \"acc_norm_stderr\": 0.04697113923010212\n },\n \"harness\|hendrycksTest-management\|5\"\ : {\n \"acc\": 0.7572815533980582,\n \"acc_stderr\": 0.04245022486384495,\n\ \ \"acc_norm\": 0.7572815533980582,\n \"acc_norm_stderr\": 0.04245022486384495\n\ \ },\n \"harness\|hendrycksTest-marketing\|5\": {\n \"acc\": 0.8760683760683761,\n\ \ \"acc_stderr\": 0.021586494001281365,\n \"acc_norm\": 0.8760683760683761,\n\ \ \"acc_norm_stderr\": 0.021586494001281365\n },\n \"harness\|hendrycksTest-medical_genetics\|5\"\ : {\n \"acc\": 0.7,\n \"acc_stderr\": 0.046056618647183814,\n \ \ \"acc_norm\": 0.7,\n \"acc_norm_stderr\": 0.046056618647183814\n \ \ },\n \"harness\|hendrycksTest-miscellaneous\|5\": {\n \"acc\": 0.8237547892720306,\n\ \ \"acc_stderr\": 0.013625556907993464,\n \"acc_norm\": 0.8237547892720306,\n\ \ \"acc_norm_stderr\": 0.013625556907993464\n },\n \"harness\|hendrycksTest-moral_disputes\|5\"\ : {\n \"acc\": 0.7312138728323699,\n \"acc_stderr\": 0.023868003262500104,\n\ \ \"acc_norm\": 0.7312138728323699,\n \"acc_norm_stderr\": 0.023868003262500104\n\ \ },\n \"harness\|hendrycksTest-moral_scenarios\|5\": {\n \"acc\": 0.4223463687150838,\n\ \ \"acc_stderr\": 0.016519594275297117,\n \"acc_norm\": 0.4223463687150838,\n\ \ \"acc_norm_stderr\": 0.016519594275297117\n },\n \"harness\|hendrycksTest-nutrition\|5\"\ : {\n \"acc\": 0.7156862745098039,\n \"acc_stderr\": 0.02582916327275748,\n\ \ \"acc_norm\": 0.7156862745098039,\n \"acc_norm_stderr\": 0.02582916327275748\n\ \ },\n \"harness\|hendrycksTest-philosophy\|5\": {\n \"acc\": 0.7009646302250804,\n\ \ \"acc_stderr\": 0.02600330111788514,\n \"acc_norm\": 0.7009646302250804,\n\ \ \"acc_norm_stderr\": 0.02600330111788514\n },\n \"harness\|hendrycksTest-prehistory\|5\"\ : {\n \"acc\": 0.7407407407407407,\n \"acc_stderr\": 0.024383665531035454,\n\ \ \"acc_norm\": 0.7407407407407407,\n \"acc_norm_stderr\": 0.024383665531035454\n\ \ },\n \"harness\|hendrycksTest-professional_accounting\|5\": {\n \"\ acc\": 0.4858156028368794,\n \"acc_stderr\": 0.02981549448368206,\n \ \ \"acc_norm\": 0.4858156028368794,\n \"acc_norm_stderr\": 0.02981549448368206\n\ \ },\n \"harness\|hendrycksTest-professional_law\|5\": {\n \"acc\": 0.4771838331160365,\n\ \ \"acc_stderr\": 0.012756933382823698,\n \"acc_norm\": 0.4771838331160365,\n\ \ \"acc_norm_stderr\": 0.012756933382823698\n },\n \"harness\|hendrycksTest-professional_medicine\|5\"\ : {\n \"acc\": 0.6801470588235294,\n \"acc_stderr\": 0.02833295951403121,\n\ \ \"acc_norm\": 0.6801470588235294,\n \"acc_norm_stderr\": 0.02833295951403121\n\ \ },\n \"harness\|hendrycksTest-professional_psychology\|5\": {\n \"\ acc\": 0.6764705882352942,\n \"acc_stderr\": 0.018926082916083383,\n \ \ \"acc_norm\": 0.6764705882352942,\n \"acc_norm_stderr\": 0.018926082916083383\n\ \ },\n \"harness\|hendrycksTest-public_relations\|5\": {\n \"acc\": 0.6727272727272727,\n\ \ \"acc_stderr\": 0.0449429086625209,\n \"acc_norm\": 0.6727272727272727,\n\ \ \"acc_norm_stderr\": 0.0449429086625209\n },\n \"harness\|hendrycksTest-security_studies\|5\"\ : {\n \"acc\": 0.7346938775510204,\n \"acc_stderr\": 0.028263889943784596,\n\ \ \"acc_norm\": 0.7346938775510204,\n \"acc_norm_stderr\": 0.028263889943784596\n\ \ },\n \"harness\|hendrycksTest-sociology\|5\": {\n \"acc\": 0.8407960199004975,\n\ \ \"acc_stderr\": 0.025870646766169136,\n \"acc_norm\": 0.8407960199004975,\n\ \ \"acc_norm_stderr\": 0.025870646766169136\n },\n \"harness\|hendrycksTest-us_foreign_policy\|5\"\ : {\n \"acc\": 0.84,\n \"acc_stderr\": 0.03684529491774709,\n \ \ \"acc_norm\": 0.84,\n \"acc_norm_stderr\": 0.03684529491774709\n \ \ },\n \"harness\|hendrycksTest-virology\|5\": {\n \"acc\": 0.5542168674698795,\n\ \ \"acc_stderr\": 0.03869543323472101,\n \"acc_norm\": 0.5542168674698795,\n\ \ \"acc_norm_stderr\": 0.03869543323472101\n },\n \"harness\|hendrycksTest-world_religions\|5\"\ : {\n \"acc\": 0.8362573099415205,\n \"acc_stderr\": 0.028380919596145866,\n\ \ \"acc_norm\": 0.8362573099415205,\n \"acc_norm_stderr\": 0.028380919596145866\n\ \ },\n \"harness\|truthfulqa:mc\|0\": {\n \"mc1\": 0.6328029375764994,\n\ \ \"mc1_stderr\": 0.016874805001453184,\n \"mc2\": 0.7800372751713768,\n\ \ \"mc2_stderr\": 0.013681851851800382\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.8500394632991318,\n \"acc_stderr\": 0.010034394804580809\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.7028051554207733,\n \ \ \"acc_stderr\": 0.012588685966624177\n }\n}\n```" repo_url: https://huggingface.co/Muhammad2003/Myriad-7B-Slerp leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2024_04_05T21_09_13.517339 path: - '/details_harness\|arc:challenge\|25_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2024-04-05T21-09-13.517339.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '/details_harness\|gsm8k\|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_04_05T21_09_13.517339 path: - '/details_harness\|hellaswag\|10_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-04-05T21-09-13.517339.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '/details_harness\|hendrycksTest-international_law\|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '/details_harness\|hendrycksTest-management\|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '/details_harness\|hendrycksTest-marketing\|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '/details_harness\|hendrycksTest-sociology\|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '/details_harness\|hendrycksTest-virology\|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_04_05T21_09_13.517339 path: - '/details_harness\|truthfulqa:mc\|0_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2024-04-05T21-09-13.517339.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '/details_harness\|winogrande\|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2024-04-05T21-09-13.517339.parquet' - config_name: results data_files: - split: 2024_04_05T21_09_13.517339 path: - results_2024-04-05T21-09-13.517339.parquet - split: latest path: - results_2024-04-05T21-09-13.517339.parquet --- # Dataset Card for Evaluation run of Muhammad2003/Myriad-7B-Slerp <!-- Provide a quick summary of the dataset. --> Dataset automatically created during the evaluation run of model [Muhammad2003/Myriad-7B-Slerp](https://huggingface.co/Muhammad2003/Myriad-7B-Slerp) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_Muhammad2003__Myriad-7B-Slerp", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-04-05T21:09:13.517339](https://huggingface.co/datasets/open-llm-leaderboard/details_Muhammad2003__Myriad-7B-Slerp/blob/main/results_2024-04-05T21-09-13.517339.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval): ```python { "all": { "acc": 0.6498757467364364, "acc_stderr": 0.0320415504432472, "acc_norm": 0.6488639096760553, "acc_norm_stderr": 0.032715942329960675, "mc1": 0.6328029375764994, "mc1_stderr": 0.016874805001453184, "mc2": 0.7800372751713768, "mc2_stderr": 0.013681851851800382 }, "harness\|arc:challenge\|25": { "acc": 0.712457337883959, "acc_stderr": 0.013226719056266127, "acc_norm": 0.7320819112627986, "acc_norm_stderr": 0.012942030195136438 }, "harness\|hellaswag\|10": { "acc": 0.717486556462856, "acc_stderr": 0.004493015945599716, "acc_norm": 0.891256721768572, "acc_norm_stderr": 0.0031068060075356255 }, "harness\|hendrycksTest-abstract_algebra\|5": { "acc": 0.31, "acc_stderr": 0.04648231987117316, "acc_norm": 0.31, "acc_norm_stderr": 0.04648231987117316 }, "harness\|hendrycksTest-anatomy\|5": { "acc": 0.6370370370370371, "acc_stderr": 0.04153948404742398, "acc_norm": 0.6370370370370371, "acc_norm_stderr": 0.04153948404742398 }, "harness\|hendrycksTest-astronomy\|5": { "acc": 0.7105263157894737, "acc_stderr": 0.03690677986137283, "acc_norm": 0.7105263157894737, "acc_norm_stderr": 0.03690677986137283 }, "harness\|hendrycksTest-business_ethics\|5": { "acc": 0.64, "acc_stderr": 0.04824181513244218, "acc_norm": 0.64, "acc_norm_stderr": 0.04824181513244218 }, "harness\|hendrycksTest-clinical_knowledge\|5": { "acc": 0.7056603773584905, "acc_stderr": 0.028049186315695255, "acc_norm": 0.7056603773584905, "acc_norm_stderr": 0.028049186315695255 }, "harness\|hendrycksTest-college_biology\|5": { "acc": 0.7708333333333334, "acc_stderr": 0.03514697467862388, "acc_norm": 0.7708333333333334, "acc_norm_stderr": 0.03514697467862388 }, "harness\|hendrycksTest-college_chemistry\|5": { "acc": 0.49, "acc_stderr": 0.05024183937956911, "acc_norm": 0.49, "acc_norm_stderr": 0.05024183937956911 }, "harness\|hendrycksTest-college_computer_science\|5": { "acc": 0.56, "acc_stderr": 0.04988876515698589, "acc_norm": 0.56, "acc_norm_stderr": 0.04988876515698589 }, "harness\|hendrycksTest-college_mathematics\|5": { "acc": 0.29, "acc_stderr": 0.04560480215720684, "acc_norm": 0.29, "acc_norm_stderr": 0.04560480215720684 }, "harness\|hendrycksTest-college_medicine\|5": { "acc": 0.653179190751445, "acc_stderr": 0.036291466701596636, "acc_norm": 0.653179190751445, "acc_norm_stderr": 0.036291466701596636 }, "harness\|hendrycksTest-college_physics\|5": { "acc": 0.37254901960784315, "acc_stderr": 0.04810840148082636, "acc_norm": 0.37254901960784315, "acc_norm_stderr": 0.04810840148082636 }, "harness\|hendrycksTest-computer_security\|5": { "acc": 0.76, "acc_stderr": 0.04292346959909283, "acc_norm": 0.76, "acc_norm_stderr": 0.04292346959909283 }, "harness\|hendrycksTest-conceptual_physics\|5": { "acc": 0.574468085106383, "acc_stderr": 0.03232146916224468, "acc_norm": 0.574468085106383, "acc_norm_stderr": 0.03232146916224468 }, "harness\|hendrycksTest-econometrics\|5": { "acc": 0.4824561403508772, "acc_stderr": 0.04700708033551038, "acc_norm": 0.4824561403508772, "acc_norm_stderr": 0.04700708033551038 }, "harness\|hendrycksTest-electrical_engineering\|5": { "acc": 0.5310344827586206, "acc_stderr": 0.04158632762097828, "acc_norm": 0.5310344827586206, "acc_norm_stderr": 0.04158632762097828 }, "harness\|hendrycksTest-elementary_mathematics\|5": { "acc": 0.41534391534391535, "acc_stderr": 0.025379524910778398, "acc_norm": 0.41534391534391535, "acc_norm_stderr": 0.025379524910778398 }, "harness\|hendrycksTest-formal_logic\|5": { "acc": 0.47619047619047616, "acc_stderr": 0.04467062628403273, "acc_norm": 0.47619047619047616, "acc_norm_stderr": 0.04467062628403273 }, "harness\|hendrycksTest-global_facts\|5": { "acc": 0.3, "acc_stderr": 0.046056618647183814, "acc_norm": 0.3, "acc_norm_stderr": 0.046056618647183814 }, "harness\|hendrycksTest-high_school_biology\|5": { "acc": 0.7838709677419354, "acc_stderr": 0.02341529343356853, "acc_norm": 0.7838709677419354, "acc_norm_stderr": 0.02341529343356853 }, "harness\|hendrycksTest-high_school_chemistry\|5": { "acc": 0.5123152709359606, "acc_stderr": 0.035169204442208966, "acc_norm": 0.5123152709359606, "acc_norm_stderr": 0.035169204442208966 }, "harness\|hendrycksTest-high_school_computer_science\|5": { "acc": 0.7, "acc_stderr": 0.046056618647183814, "acc_norm": 0.7, "acc_norm_stderr": 0.046056618647183814 }, "harness\|hendrycksTest-high_school_european_history\|5": { "acc": 0.7757575757575758, "acc_stderr": 0.03256866661681102, "acc_norm": 0.7757575757575758, "acc_norm_stderr": 0.03256866661681102 }, "harness\|hendrycksTest-high_school_geography\|5": { "acc": 0.803030303030303, "acc_stderr": 0.028335609732463362, "acc_norm": 0.803030303030303, "acc_norm_stderr": 0.028335609732463362 }, "harness\|hendrycksTest-high_school_government_and_politics\|5": { "acc": 0.9119170984455959, "acc_stderr": 0.02045374660160103, "acc_norm": 0.9119170984455959, "acc_norm_stderr": 0.02045374660160103 }, "harness\|hendrycksTest-high_school_macroeconomics\|5": { "acc": 0.658974358974359, "acc_stderr": 0.024035489676335082, "acc_norm": 0.658974358974359, "acc_norm_stderr": 0.024035489676335082 }, "harness\|hendrycksTest-high_school_mathematics\|5": { "acc": 0.3074074074074074, "acc_stderr": 0.028133252578815632, "acc_norm": 0.3074074074074074, "acc_norm_stderr": 0.028133252578815632 }, "harness\|hendrycksTest-high_school_microeconomics\|5": { "acc": 0.6722689075630253, "acc_stderr": 0.03048991141767323, "acc_norm": 0.6722689075630253, "acc_norm_stderr": 0.03048991141767323 }, "harness\|hendrycksTest-high_school_physics\|5": { "acc": 0.36423841059602646, "acc_stderr": 0.03929111781242742, "acc_norm": 0.36423841059602646, "acc_norm_stderr": 0.03929111781242742 }, "harness\|hendrycksTest-high_school_psychology\|5": { "acc": 0.8440366972477065, "acc_stderr": 0.01555580271359017, "acc_norm": 0.8440366972477065, "acc_norm_stderr": 0.01555580271359017 }, "harness\|hendrycksTest-high_school_statistics\|5": { "acc": 0.5092592592592593, "acc_stderr": 0.034093869469927006, "acc_norm": 0.5092592592592593, "acc_norm_stderr": 0.034093869469927006 }, "harness\|hendrycksTest-high_school_us_history\|5": { "acc": 0.8431372549019608, "acc_stderr": 0.02552472232455335, "acc_norm": 0.8431372549019608, "acc_norm_stderr": 0.02552472232455335 }, "harness\|hendrycksTest-high_school_world_history\|5": { "acc": 0.8143459915611815, "acc_stderr": 0.025310495376944856, "acc_norm": 0.8143459915611815, "acc_norm_stderr": 0.025310495376944856 }, "harness\|hendrycksTest-human_aging\|5": { "acc": 0.6860986547085202, "acc_stderr": 0.031146796482972465, "acc_norm": 0.6860986547085202, "acc_norm_stderr": 0.031146796482972465 }, "harness\|hendrycksTest-human_sexuality\|5": { "acc": 0.7938931297709924, "acc_stderr": 0.03547771004159465, "acc_norm": 0.7938931297709924, "acc_norm_stderr": 0.03547771004159465 }, "harness\|hendrycksTest-international_law\|5": { "acc": 0.7603305785123967, "acc_stderr": 0.03896878985070416, "acc_norm": 0.7603305785123967, "acc_norm_stderr": 0.03896878985070416 }, "harness\|hendrycksTest-jurisprudence\|5": { "acc": 0.7592592592592593, "acc_stderr": 0.04133119440243839, "acc_norm": 0.7592592592592593, "acc_norm_stderr": 0.04133119440243839 }, "harness\|hendrycksTest-logical_fallacies\|5": { "acc": 0.7852760736196319, "acc_stderr": 0.032262193772867744, "acc_norm": 0.7852760736196319, "acc_norm_stderr": 0.032262193772867744 }, "harness\|hendrycksTest-machine_learning\|5": { "acc": 0.42857142857142855, "acc_stderr": 0.04697113923010212, "acc_norm": 0.42857142857142855, "acc_norm_stderr": 0.04697113923010212 }, "harness\|hendrycksTest-management\|5": { "acc": 0.7572815533980582, "acc_stderr": 0.04245022486384495, "acc_norm": 0.7572815533980582, "acc_norm_stderr": 0.04245022486384495 }, "harness\|hendrycksTest-marketing\|5": { "acc": 0.8760683760683761, "acc_stderr": 0.021586494001281365, "acc_norm": 0.8760683760683761, "acc_norm_stderr": 0.021586494001281365 }, "harness\|hendrycksTest-medical_genetics\|5": { "acc": 0.7, "acc_stderr": 0.046056618647183814, "acc_norm": 0.7, "acc_norm_stderr": 0.046056618647183814 }, "harness\|hendrycksTest-miscellaneous\|5": { "acc": 0.8237547892720306, "acc_stderr": 0.013625556907993464, "acc_norm": 0.8237547892720306, "acc_norm_stderr": 0.013625556907993464 }, "harness\|hendrycksTest-moral_disputes\|5": { "acc": 0.7312138728323699, "acc_stderr": 0.023868003262500104, "acc_norm": 0.7312138728323699, "acc_norm_stderr": 0.023868003262500104 }, "harness\|hendrycksTest-moral_scenarios\|5": { "acc": 0.4223463687150838, "acc_stderr": 0.016519594275297117, "acc_norm": 0.4223463687150838, "acc_norm_stderr": 0.016519594275297117 }, "harness\|hendrycksTest-nutrition\|5": { "acc": 0.7156862745098039, "acc_stderr": 0.02582916327275748, "acc_norm": 0.7156862745098039, "acc_norm_stderr": 0.02582916327275748 }, "harness\|hendrycksTest-philosophy\|5": { "acc": 0.7009646302250804, "acc_stderr": 0.02600330111788514, "acc_norm": 0.7009646302250804, "acc_norm_stderr": 0.02600330111788514 }, "harness\|hendrycksTest-prehistory\|5": { "acc": 0.7407407407407407, "acc_stderr": 0.024383665531035454, "acc_norm": 0.7407407407407407, "acc_norm_stderr": 0.024383665531035454 }, "harness\|hendrycksTest-professional_accounting\|5": { "acc": 0.4858156028368794, "acc_stderr": 0.02981549448368206, "acc_norm": 0.4858156028368794, "acc_norm_stderr": 0.02981549448368206 }, "harness\|hendrycksTest-professional_law\|5": { "acc": 0.4771838331160365, "acc_stderr": 0.012756933382823698, "acc_norm": 0.4771838331160365, "acc_norm_stderr": 0.012756933382823698 }, "harness\|hendrycksTest-professional_medicine\|5": { "acc": 0.6801470588235294, "acc_stderr": 0.02833295951403121, "acc_norm": 0.6801470588235294, "acc_norm_stderr": 0.02833295951403121 }, "harness\|hendrycksTest-professional_psychology\|5": { "acc": 0.6764705882352942, "acc_stderr": 0.018926082916083383, "acc_norm": 0.6764705882352942, "acc_norm_stderr": 0.018926082916083383 }, "harness\|hendrycksTest-public_relations\|5": { "acc": 0.6727272727272727, "acc_stderr": 0.0449429086625209, "acc_norm": 0.6727272727272727, "acc_norm_stderr": 0.0449429086625209 }, "harness\|hendrycksTest-security_studies\|5": { "acc": 0.7346938775510204, "acc_stderr": 0.028263889943784596, "acc_norm": 0.7346938775510204, "acc_norm_stderr": 0.028263889943784596 }, "harness\|hendrycksTest-sociology\|5": { "acc": 0.8407960199004975, "acc_stderr": 0.025870646766169136, "acc_norm": 0.8407960199004975, "acc_norm_stderr": 0.025870646766169136 }, "harness\|hendrycksTest-us_foreign_policy\|5": { "acc": 0.84, "acc_stderr": 0.03684529491774709, "acc_norm": 0.84, "acc_norm_stderr": 0.03684529491774709 }, "harness\|hendrycksTest-virology\|5": { "acc": 0.5542168674698795, "acc_stderr": 0.03869543323472101, "acc_norm": 0.5542168674698795, "acc_norm_stderr": 0.03869543323472101 }, "harness\|hendrycksTest-world_religions\|5": { "acc": 0.8362573099415205, "acc_stderr": 0.028380919596145866, "acc_norm": 0.8362573099415205, "acc_norm_stderr": 0.028380919596145866 }, "harness\|truthfulqa:mc\|0": { "mc1": 0.6328029375764994, "mc1_stderr": 0.016874805001453184, "mc2": 0.7800372751713768, "mc2_stderr": 0.013681851851800382 }, "harness\|winogrande\|5": { "acc": 0.8500394632991318, "acc_stderr": 0.010034394804580809 }, "harness\|gsm8k\|5": { "acc": 0.7028051554207733, "acc_stderr": 0.012588685966624177 } } ``` ## Dataset Details ### Dataset Description <!-- Provide a longer summary of what this dataset is. --> - Curated by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] ### Dataset Sources [optional] <!-- Provide the basic links for the dataset. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the dataset is intended to be used. --> ### Direct Use <!-- This section describes suitable use cases for the dataset. --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. --> [More Information Needed] ## Dataset Structure <!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. --> [More Information Needed] ## Dataset Creation ### Curation Rationale <!-- Motivation for the creation of this dataset. --> [More Information Needed] ### Source Data <!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). --> #### Data Collection and Processing <!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. --> [More Information Needed] #### Who are the source data producers? <!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. --> [More Information Needed] ### Annotations [optional] <!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. --> #### Annotation process <!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. --> [More Information Needed] #### Who are the annotators? <!-- This section describes the people or systems who created the annotations. --> [More Information Needed] #### Personal and Sensitive Information <!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations. ## Citation [optional] <!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Dataset Card Authors [optional] [More Information Needed] ## Dataset Card Contact [More Information Needed]
imone/OpenOrca_FLAN	--- license: mit --- This is the [OpenOrca](https://huggingface.co/datasets/Open-Orca/OpenOrca) GPT4 subset with the original FLAN answers. Each even row (indexed starting from 0) contains the OpenOrca GPT4 answer, while each odd row contains the corresponding FLAN answer.
48xrf/prodanca	--- license: wtfpl ---
CyberHarem/lupusregina_beta_overlord	--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of lupusregina_beta_overlord This is the dataset of lupusregina_beta_overlord, containing 102 images and their tags. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)).
jmgb0127/FronxOwnerManual	--- configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* dataset_info: features: - name: context dtype: string - name: question dtype: string - name: answer dtype: string - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 1330685 num_examples: 1177 - name: test num_bytes: 332811 num_examples: 294 download_size: 990561 dataset_size: 1663496 --- # Dataset Card for "FronxOwnerManual" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
jacobbieker/gk2a-kerchunk	--- license: mit ---
liuyanchen1015/MULTI_VALUE_sst2_here_come	--- dataset_info: features: - name: sentence dtype: string - name: label dtype: int64 - name: idx dtype: int64 - name: score dtype: int64 splits: - name: dev num_bytes: 1351 num_examples: 9 - name: test num_bytes: 2306 num_examples: 18 - name: train num_bytes: 30466 num_examples: 263 download_size: 20603 dataset_size: 34123 --- # Dataset Card for "MULTI_VALUE_sst2_here_come" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
wanony/mika	--- license: gpl-3.0 ---
open-llm-leaderboard/details_Aeala__GPT4-x-AlpacaDente-30b	--- pretty_name: Evaluation run of Aeala/GPT4-x-AlpacaDente-30b dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [Aeala/GPT4-x-AlpacaDente-30b](https://huggingface.co/Aeala/GPT4-x-AlpacaDente-30b)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 64 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 2 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the agregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_Aeala__GPT4-x-AlpacaDente-30b\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-09-17T18:13:58.646455](https://huggingface.co/datasets/open-llm-leaderboard/details_Aeala__GPT4-x-AlpacaDente-30b/blob/main/results_2023-09-17T18-13-58.646455.json)(note\ \ that their might be results for other tasks in the repos if successive evals didn't\ \ cover the same tasks. You find each in the results and the \"latest\" split for\ \ each eval):\n\n```python\n{\n \"all\": {\n \"em\": 0.32120385906040266,\n\ \ \"em_stderr\": 0.004781891422636473,\n \"f1\": 0.43280620805369485,\n\ \ \"f1_stderr\": 0.0045611946956929435,\n \"acc\": 0.5439418899180396,\n\ \ \"acc_stderr\": 0.012071731077966974\n },\n \"harness\|drop\|3\": {\n\ \ \"em\": 0.32120385906040266,\n \"em_stderr\": 0.004781891422636473,\n\ \ \"f1\": 0.43280620805369485,\n \"f1_stderr\": 0.0045611946956929435\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.3009855951478393,\n \ \ \"acc_stderr\": 0.012634504465211194\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.7868981846882399,\n \"acc_stderr\": 0.011508957690722754\n\ \ }\n}\n```" repo_url: https://huggingface.co/Aeala/GPT4-x-AlpacaDente-30b leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2023_07_19T23_04_17.245052 path: - '/details_harness\|arc:challenge\|25_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-07-19T23:04:17.245052.parquet' - config_name: harness_drop_3 data_files: - split: 2023_09_17T18_13_58.646455 path: - '/details_harness\|drop\|3_2023-09-17T18-13-58.646455.parquet' - split: latest path: - '/details_harness\|drop\|3_2023-09-17T18-13-58.646455.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_09_17T18_13_58.646455 path: - '/details_harness\|gsm8k\|5_2023-09-17T18-13-58.646455.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2023-09-17T18-13-58.646455.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_07_19T23_04_17.245052 path: - '/details_harness\|hellaswag\|10_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-07-19T23:04:17.245052.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '/details_harness\|hendrycksTest-management\|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '/details_harness\|hendrycksTest-virology\|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_07_19T23_04_17.245052 path: - '/details_harness\|truthfulqa:mc\|0_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-07-19T23:04:17.245052.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_09_17T18_13_58.646455 path: - '/details_harness\|winogrande\|5_2023-09-17T18-13-58.646455.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2023-09-17T18-13-58.646455.parquet' - config_name: results data_files: - split: 2023_07_19T23_04_17.245052 path: - results_2023-07-19T23:04:17.245052.parquet - split: 2023_09_17T18_13_58.646455 path: - results_2023-09-17T18-13-58.646455.parquet - split: latest path: - results_2023-09-17T18-13-58.646455.parquet --- # Dataset Card for Evaluation run of Aeala/GPT4-x-AlpacaDente-30b ## Dataset Description - Homepage: - Repository: https://huggingface.co/Aeala/GPT4-x-AlpacaDente-30b - Paper: - Leaderboard: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard - Point of Contact: clementine@hf.co ### Dataset Summary Dataset automatically created during the evaluation run of model [Aeala/GPT4-x-AlpacaDente-30b](https://huggingface.co/Aeala/GPT4-x-AlpacaDente-30b) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 64 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 2 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the agregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_Aeala__GPT4-x-AlpacaDente-30b", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-09-17T18:13:58.646455](https://huggingface.co/datasets/open-llm-leaderboard/details_Aeala__GPT4-x-AlpacaDente-30b/blob/main/results_2023-09-17T18-13-58.646455.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval): ```python { "all": { "em": 0.32120385906040266, "em_stderr": 0.004781891422636473, "f1": 0.43280620805369485, "f1_stderr": 0.0045611946956929435, "acc": 0.5439418899180396, "acc_stderr": 0.012071731077966974 }, "harness\|drop\|3": { "em": 0.32120385906040266, "em_stderr": 0.004781891422636473, "f1": 0.43280620805369485, "f1_stderr": 0.0045611946956929435 }, "harness\|gsm8k\|5": { "acc": 0.3009855951478393, "acc_stderr": 0.012634504465211194 }, "harness\|winogrande\|5": { "acc": 0.7868981846882399, "acc_stderr": 0.011508957690722754 } } ``` ### Supported Tasks and Leaderboards [More Information Needed] ### Languages [More Information Needed] ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information [More Information Needed] ### Citation Information [More Information Needed] ### Contributions [More Information Needed]
metredo085/drod	--- license: apache-2.0 ---
as-cle-bert/scerevisiae-proteins-reduced	--- license: mit dataset_info: features: - name: label dtype: class_label: names: '0': Verified_Coding '1': Probably_Non_Coding - name: text dtype: string splits: - name: train num_bytes: 343452 num_examples: 480 - name: test num_bytes: 81480 num_examples: 120 download_size: 236731 dataset_size: 424932 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---
ar852/scraped-chatgpt-conversations	--- task_categories: - question-answering - text-generation - conversational size_categories: - 100K<n<1M --- # Dataset Card for Dataset Name ## Dataset Description - Repository: {https://github.com/ar852/chatgpt-scraping} ### Dataset Summary scraped-chatgpt-conversations contains ~100k conversations between a user and chatgpt that were shared online through reddit, twitter, or sharegpt. For sharegpt, the conversations were directly scraped from the website. For reddit and twitter, images were downloaded from submissions, segmented, and run through an OCR pipeline to obtain a conversation list. For information on how the each json file is structured, please see `json_guides.md` ### Languages - twitter 1, twitter 2, and sharegpt json files are multilingual - reddit and twitter 2 json files are english only ## Dataset Structure - refer to json_guide.txt ## Dataset Creation This dataset was created by scraping images from twitter, reddit, and sharegpt.com using the pushshift and twitter APIs, respectively. The images are run through a filter to check if they contain a chatgpt conversation, then the image is processed and run through an OCR pipeline to obtain the conversation text. More info can be found in the repository. ### Source Data - twitter.com - reddit.com - sharegpt.com ## Considerations for Using the Data A significant amount of dicts created from parsing reddit and twitter images may be parsed incorrectly for a number of reasons: cropping done by the image poster, incorrectly classifying the image as containing a chatgpt conversation, incorrect image parsing (segmentation) by the parser, incorrect OCR by pytesseract. ### Licensing Information [More Information Needed] ### Contributions [More Information Needed]
KushT/bbc_news_multiclass_train_val_test	--- license: mit configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* - split: test path: data/test-* dataset_info: features: - name: text dtype: string - name: label dtype: int64 splits: - name: train num_bytes: 3414429 num_examples: 1512 - name: validation num_bytes: 888603 num_examples: 379 - name: test num_bytes: 751863 num_examples: 334 download_size: 0 dataset_size: 5054895 --- Label Names: { 'business': 0, 'entertainment': 1, 'politics': 2, 'sport': 3, 'tech': 4 } Dataset: [Kaggle - BBC Full Text Document Classification](https://www.kaggle.com/datasets/shivamkushwaha/bbc-full-text-document-classification/code)
mespinosami/global230k	--- configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* - split: test path: data/test-* dataset_info: features: - name: image dtype: image - name: label dtype: image splits: - name: train num_bytes: 8623524876.02 num_examples: 162940 - name: validation num_bytes: 1335636495.768 num_examples: 23416 - name: test num_bytes: 2572452087.661 num_examples: 46463 download_size: 10844373816 dataset_size: 12531613459.449 --- # Dataset Card for "global230k" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
Aletos/Peixe	--- license: openrail ---
LennardZuendorf/openlegaldata-processed	--- license: mit dataset_info: features: - name: id dtype: int64 - name: court struct: - name: id dtype: int64 - name: jurisdiction dtype: string - name: level_of_appeal dtype: string - name: name dtype: string - name: state dtype: int64 - name: file_number dtype: string - name: date dtype: timestamp[s] - name: type dtype: string - name: content dtype: string - name: tenor dtype: string - name: facts dtype: string - name: reasoning dtype: string splits: - name: three num_bytes: 169494251 num_examples: 2828 - name: two num_bytes: 183816899 num_examples: 4954 download_size: 172182482 dataset_size: 353311150 task_categories: - text-classification language: - de tags: - legal pretty_name: Edited German Court case decision size_categories: - 1K<n<10K --- # Dataset Card for openlegaldata.io bulk case data ## Dataset Description This is a edit/cleanup of Bulk Data of [openlegaldata.io](https://de.openlegaldata.io/), which I also brought onto Huggingface [here](LennardZuendorf/openlegaldata-bulk-data). #### The Entire Dataset Is In German - Github Repository: [uniArchive-legalis]](https://github.com/LennardZuendorf/uniArchive-legalis) - Repository: [Bulk Data](https://static.openlegaldata.io/dumps/de/) ## Edit Summary I have done some cleaning and splitting of the data and filtered out large parts that were not (easily) usable, cutting down the number of cases to at max 4000 - from 250000. This results in two different splits. Which is because German Courts don't format their case decision the same way. ### Data Fields Independent of the split, most fields are the same, they are: \| id \| court \| file_number \| date \| type \| content \| - \| - \| - \| - \| - \| - \| \| numeric id \| name of the court that made the decision \| file number of the case ("Aktenzeichen") \| decision date \| type of the case decision \| entire content (text) of the case decision Additionally, I added 3 more fields because of the splitting of the content: #### Two Split - Case Decision I could split into two parts: tenor and reasoning. - Which means the three fields tenor, content and facts contain the following: \| tenor \| reasoning \| facts \| - \| - \| - \| \| An abstract, legal summary of the cases decision \| the entire rest of the decision, explaining in detail why the decision has been made \| an empty text field \| #### Three Split - Case Decision I could split into three parts: tenor, reasoning and facts - This Data I have used to create binary labels with the help of ChatGPT, see [legalis](https://huggingface.co/datasets/LennardZuendorf/legalis) for that - The three fields tenor, content and facts contain the following: \| tenor \| reasoning \| facts \| - \| - \| - \| \| An abstract, legal summary of the cases decision \| the entire rest of the decision, explaining in detail why the decision has been made \| the facts and details of a case \| ### Languages - German ## Additional Information ### Licensing/Citation Information The [openlegaldata platform](https://github.com/openlegaldata/oldp) is licensed under the MIT license, you can access the dataset by citing the original source, [openlegaldata.io](https://de.openlegaldata.io/) and me, [Lennard Zündorf](https://github.com/LennardZuendorf) as the editor of this dataset.
7Jes6riv/multiclass	--- dataset_info: features: - name: text dtype: string splits: - name: train num_bytes: 195846200 num_examples: 59168 download_size: 32590912 dataset_size: 195846200 configs: - config_name: default data_files: - split: train path: data/train-* ---
Lucasss876/Tagizzy	--- license: openrail ---
curry99/rampage	--- license: mit ---
mteb/stsbenchmark-sts	--- language: - en ---
lshowway/wikipedia.reorder.sov.pl	--- dataset_info: features: - name: text dtype: string splits: - name: train num_bytes: 1958124685 num_examples: 1772445 download_size: 549518463 dataset_size: 1958124685 --- # Dataset Card for "wikipedia.reorder.sov.pl" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
CyberHarem/chapayev_azurlane	--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of chapayev/チャパエフ/恰巴耶夫 (Azur Lane) This is the dataset of chapayev/チャパエフ/恰巴耶夫 (Azur Lane), containing 289 images and their tags. The core tags of this character are `blue_hair, breasts, short_hair, blue_eyes, large_breasts, mole, mole_on_breast, bangs, hair_ornament, hat, white_headwear, military_hat, peaked_cap, hairclip`, which are pruned in this dataset. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). ## List of Packages \| Name \| Images \| Size \| Download \| Type \| Description \| \|:-----------------\|---------:\|:-----------\|:-------------------------------------------------------------------------------------------------------------------\|:-----------\|:---------------------------------------------------------------------\| \| raw \| 289 \| 483.10 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/chapayev_azurlane/resolve/main/dataset-raw.zip) \| Waifuc-Raw \| Raw data with meta information (min edge aligned to 1400 if larger). \| \| 800 \| 289 \| 250.62 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/chapayev_azurlane/resolve/main/dataset-800.zip) \| IMG+TXT \| dataset with the shorter side not exceeding 800 pixels. \| \| stage3-p480-800 \| 734 \| 552.75 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/chapayev_azurlane/resolve/main/dataset-stage3-p480-800.zip) \| IMG+TXT \| 3-stage cropped dataset with the area not less than 480x480 pixels. \| \| 1200 \| 289 \| 413.48 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/chapayev_azurlane/resolve/main/dataset-1200.zip) \| IMG+TXT \| dataset with the shorter side not exceeding 1200 pixels. \| \| stage3-p480-1200 \| 734 \| 808.74 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/chapayev_azurlane/resolve/main/dataset-stage3-p480-1200.zip) \| IMG+TXT \| 3-stage cropped dataset with the area not less than 480x480 pixels. \| ### Load Raw Dataset with Waifuc We provide raw dataset (including tagged images) for [waifuc](https://deepghs.github.io/waifuc/main/tutorials/installation/index.html) loading. If you need this, just run the following code ```python import os import zipfile from huggingface_hub import hf_hub_download from waifuc.source import LocalSource # download raw archive file zip_file = hf_hub_download( repo_id='CyberHarem/chapayev_azurlane', repo_type='dataset', filename='dataset-raw.zip', ) # extract files to your directory dataset_dir = 'dataset_dir' os.makedirs(dataset_dir, exist_ok=True) with zipfile.ZipFile(zip_file, 'r') as zf: zf.extractall(dataset_dir) # load the dataset with waifuc source = LocalSource(dataset_dir) for item in source: print(item.image, item.meta['filename'], item.meta['tags']) ``` ## List of Clusters List of tag clustering result, maybe some outfits can be mined here. ### Raw Text Version \| # \| Samples \| Img-1 \| Img-2 \| Img-3 \| Img-4 \| Img-5 \| Tags \| \|----:\|----------:\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\| \| 0 \| 47 \| ![](samples/0/clu0-sample0.png) \| ![](samples/0/clu0-sample1.png) \| ![](samples/0/clu0-sample2.png) \| ![](samples/0/clu0-sample3.png) \| ![](samples/0/clu0-sample4.png) \| 1girl, blush, chain, looking_at_viewer, torn_shirt, solo, shackles, short_sleeves, navel, cleavage, smile, sitting, open_mouth \| \| 1 \| 10 \| ![](samples/1/clu1-sample0.png) \| ![](samples/1/clu1-sample1.png) \| ![](samples/1/clu1-sample2.png) \| ![](samples/1/clu1-sample3.png) \| ![](samples/1/clu1-sample4.png) \| 1girl, black_gloves, cleavage, looking_at_viewer, pleated_skirt, smile, solo, white_jacket, blush, chain, long_sleeves, closed_mouth, white_skirt, black_pantyhose \| \| 2 \| 7 \| ![](samples/2/clu2-sample0.png) \| ![](samples/2/clu2-sample1.png) \| ![](samples/2/clu2-sample2.png) \| ![](samples/2/clu2-sample3.png) \| ![](samples/2/clu2-sample4.png) \| 1girl, black_gloves, blush, cleavage, looking_at_viewer, smile, solo, upper_body, white_jacket, closed_mouth, simple_background, white_background \| \| 3 \| 27 \| ![](samples/3/clu3-sample0.png) \| ![](samples/3/clu3-sample1.png) \| ![](samples/3/clu3-sample2.png) \| ![](samples/3/clu3-sample3.png) \| ![](samples/3/clu3-sample4.png) \| 1girl, official_alternate_costume, looking_at_viewer, white_hairband, earrings, solo, cleavage, white_choker, blush, lace-trimmed_dress, white_dress, lying, smile, nightgown, see-through_dress, thigh_strap \| \| 4 \| 10 \| ![](samples/4/clu4-sample0.png) \| ![](samples/4/clu4-sample1.png) \| ![](samples/4/clu4-sample2.png) \| ![](samples/4/clu4-sample3.png) \| ![](samples/4/clu4-sample4.png) \| 1girl, looking_at_viewer, solo, white_dress, elbow_gloves, sitting, white_gloves, bare_shoulders, no_shoes, official_alternate_costume, thighs, toes, white_thighhighs, blush, cleavage, garter_straps, legs, smile, chair, soles, ass, choker, closed_mouth, foot_focus, collarbone, lying \| ### Table Version \| # \| Samples \| Img-1 \| Img-2 \| Img-3 \| Img-4 \| Img-5 \| 1girl \| blush \| chain \| looking_at_viewer \| torn_shirt \| solo \| shackles \| short_sleeves \| navel \| cleavage \| smile \| sitting \| open_mouth \| black_gloves \| pleated_skirt \| white_jacket \| long_sleeves \| closed_mouth \| white_skirt \| black_pantyhose \| upper_body \| simple_background \| white_background \| official_alternate_costume \| white_hairband \| earrings \| white_choker \| lace-trimmed_dress \| white_dress \| lying \| nightgown \| see-through_dress \| thigh_strap \| elbow_gloves \| white_gloves \| bare_shoulders \| no_shoes \| thighs \| toes \| white_thighhighs \| garter_straps \| legs \| chair \| soles \| ass \| choker \| foot_focus \| collarbone \| \|----:\|----------:\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------\|:--------\|:--------\|:--------------------\|:-------------\|:-------\|:-----------\|:----------------\|:--------\|:-----------\|:--------\|:----------\|:-------------\|:---------------\|:----------------\|:---------------\|:---------------\|:---------------\|:--------------\|:------------------\|:-------------\|:--------------------\|:-------------------\|:-----------------------------\|:-----------------\|:-----------\|:---------------\|:---------------------\|:--------------\|:--------\|:------------\|:--------------------\|:--------------\|:---------------\|:---------------\|:-----------------\|:-----------\|:---------\|:-------\|:-------------------\|:----------------\|:-------\|:--------\|:--------\|:------\|:---------\|:-------------\|:-------------\| \| 0 \| 47 \| ![](samples/0/clu0-sample0.png) \| ![](samples/0/clu0-sample1.png) \| ![](samples/0/clu0-sample2.png) \| ![](samples/0/clu0-sample3.png) \| ![](samples/0/clu0-sample4.png) \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 1 \| 10 \| ![](samples/1/clu1-sample0.png) \| ![](samples/1/clu1-sample1.png) \| ![](samples/1/clu1-sample2.png) \| ![](samples/1/clu1-sample3.png) \| ![](samples/1/clu1-sample4.png) \| X \| X \| X \| X \| \| X \| \| \| \| X \| X \| \| \| X \| X \| X \| X \| X \| X \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 2 \| 7 \| ![](samples/2/clu2-sample0.png) \| ![](samples/2/clu2-sample1.png) \| ![](samples/2/clu2-sample2.png) \| ![](samples/2/clu2-sample3.png) \| ![](samples/2/clu2-sample4.png) \| X \| X \| \| X \| \| X \| \| \| \| X \| X \| \| \| X \| \| X \| \| X \| \| \| X \| X \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 3 \| 27 \| ![](samples/3/clu3-sample0.png) \| ![](samples/3/clu3-sample1.png) \| ![](samples/3/clu3-sample2.png) \| ![](samples/3/clu3-sample3.png) \| ![](samples/3/clu3-sample4.png) \| X \| X \| \| X \| \| X \| \| \| \| X \| X \| \| \| \| \| \| \| \| \| \| \| \| \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 4 \| 10 \| ![](samples/4/clu4-sample0.png) \| ![](samples/4/clu4-sample1.png) \| ![](samples/4/clu4-sample2.png) \| ![](samples/4/clu4-sample3.png) \| ![](samples/4/clu4-sample4.png) \| X \| X \| \| X \| \| X \| \| \| \| X \| X \| X \| \| \| \| \| \| X \| \| \| \| \| \| X \| \| \| \| \| X \| X \| \| \| \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \|
freshpearYoon/vr_train_free_43	--- dataset_info: features: - name: audio struct: - name: array sequence: float64 - name: path dtype: string - name: sampling_rate dtype: int64 - name: filename dtype: string - name: NumOfUtterance dtype: int64 - name: text dtype: string - name: samplingrate dtype: int64 - name: begin_time dtype: float64 - name: end_time dtype: float64 - name: speaker_id dtype: string - name: directory dtype: string splits: - name: train num_bytes: 6900570085 num_examples: 10000 download_size: 1224346103 dataset_size: 6900570085 configs: - config_name: default data_files: - split: train path: data/train-* ---
Cohere/wikipedia-22-12-fr-embeddings	--- annotations_creators: - expert-generated language: - fr multilinguality: - multilingual size_categories: [] source_datasets: [] tags: [] task_categories: - text-retrieval license: - apache-2.0 task_ids: - document-retrieval --- # Wikipedia (fr) embedded with cohere.ai `multilingual-22-12` encoder We encoded [Wikipedia (fr)](https://fr.wikipedia.org) using the [cohere.ai](https://txt.cohere.ai/multilingual/) `multilingual-22-12` embedding model. To get an overview how this dataset was created and pre-processed, have a look at [Cohere/wikipedia-22-12](https://huggingface.co/datasets/Cohere/wikipedia-22-12). ## Embeddings We compute for `title+" "+text` the embeddings using our `multilingual-22-12` embedding model, a state-of-the-art model that works for semantic search in 100 languages. If you want to learn more about this model, have a look at [cohere.ai multilingual embedding model](https://txt.cohere.ai/multilingual/). ## Further languages We provide embeddings of Wikipedia in many different languages: [ar](https://huggingface.co/datasets/Cohere/wikipedia-22-12-ar-embeddings), [de](https://huggingface.co/datasets/Cohere/wikipedia-22-12-de-embeddings), [en](https://huggingface.co/datasets/Cohere/wikipedia-22-12-en-embeddings), [es](https://huggingface.co/datasets/Cohere/wikipedia-22-12-es-embeddings), [fr](https://huggingface.co/datasets/Cohere/wikipedia-22-12-fr-embeddings), [hi](https://huggingface.co/datasets/Cohere/wikipedia-22-12-hi-embeddings), [it](https://huggingface.co/datasets/Cohere/wikipedia-22-12-it-embeddings), [ja](https://huggingface.co/datasets/Cohere/wikipedia-22-12-ja-embeddings), [ko](https://huggingface.co/datasets/Cohere/wikipedia-22-12-ko-embeddings), [simple english](https://huggingface.co/datasets/Cohere/wikipedia-22-12-simple-embeddings), [zh](https://huggingface.co/datasets/Cohere/wikipedia-22-12-zh-embeddings), You can find the Wikipedia datasets without embeddings at [Cohere/wikipedia-22-12](https://huggingface.co/datasets/Cohere/wikipedia-22-12). ## Loading the dataset You can either load the dataset like this: ```python from datasets import load_dataset docs = load_dataset(f"Cohere/wikipedia-22-12-fr-embeddings", split="train") ``` Or you can also stream it without downloading it before: ```python from datasets import load_dataset docs = load_dataset(f"Cohere/wikipedia-22-12-fr-embeddings", split="train", streaming=True) for doc in docs: docid = doc['id'] title = doc['title'] text = doc['text'] emb = doc['emb'] ``` ## Search A full search example: ```python #Run: pip install cohere datasets from datasets import load_dataset import torch import cohere co = cohere.Client(f"<<COHERE_API_KEY>>") # Add your cohere API key from www.cohere.com #Load at max 1000 documents + embeddings max_docs = 1000 docs_stream = load_dataset(f"Cohere/wikipedia-22-12-fr-embeddings", split="train", streaming=True) docs = [] doc_embeddings = [] for doc in docs_stream: docs.append(doc) doc_embeddings.append(doc['emb']) if len(docs) >= max_docs: break doc_embeddings = torch.tensor(doc_embeddings) query = 'Who founded Youtube' response = co.embed(texts=[query], model='multilingual-22-12') query_embedding = response.embeddings query_embedding = torch.tensor(query_embedding) # Compute dot score between query embedding and document embeddings dot_scores = torch.mm(query_embedding, doc_embeddings.transpose(0, 1)) top_k = torch.topk(dot_scores, k=3) # Print results print("Query:", query) for doc_id in top_k.indices[0].tolist(): print(docs[doc_id]['title']) print(docs[doc_id]['text'], "\n") ``` ## Performance You can find performance on the MIRACL dataset (a semantic search evaluation dataset) here: [miracl-en-queries-22-12#performance](https://huggingface.co/datasets/Cohere/miracl-en-queries-22-12#performance)
rbiojout/odoo_python_15	--- license: agpl-3.0 dataset_info: features: - name: size dtype: int64 - name: ext dtype: string - name: lang dtype: string - name: branch dtype: string - name: content dtype: string - name: avg_line_length dtype: float64 - name: max_line_length dtype: int64 splits: - name: train num_bytes: 40721998 num_examples: 9349 download_size: 12783255 dataset_size: 40721998 ---
one-sec-cv12/chunk_186	--- dataset_info: features: - name: audio dtype: audio: sampling_rate: 16000 splits: - name: train num_bytes: 12103776864.75 num_examples: 126018 download_size: 9851992082 dataset_size: 12103776864.75 --- # Dataset Card for "chunk_186" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
fadime3/Hayalet	--- license: openrail ---
joey234/mmlu-moral_disputes	--- dataset_info: features: - name: question dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D - name: negate_openai_prompt struct: - name: content dtype: string - name: role dtype: string - name: neg_question dtype: string - name: fewshot_context dtype: string - name: fewshot_context_neg dtype: string splits: - name: dev num_bytes: 4935 num_examples: 5 - name: test num_bytes: 1532082 num_examples: 346 download_size: 153575 dataset_size: 1537017 configs: - config_name: default data_files: - split: dev path: data/dev-* - split: test path: data/test-* --- # Dataset Card for "mmlu-moral_disputes" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
ProfEngel/spieltheorie	--- license: cc-by-nc-4.0 ---
Denilsonic/Datasets	--- license: openrail ---
DanGoldBr/PTT-20230720-WA0159	--- license: openrail ---
open-llm-leaderboard/details_CorticalStack__gemma-7b-ultrachat-sft	--- pretty_name: Evaluation run of CorticalStack/gemma-7b-ultrachat-sft dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [CorticalStack/gemma-7b-ultrachat-sft](https://huggingface.co/CorticalStack/gemma-7b-ultrachat-sft)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 63 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the aggregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_CorticalStack__gemma-7b-ultrachat-sft\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-02-23T17:43:57.046792](https://huggingface.co/datasets/open-llm-leaderboard/details_CorticalStack__gemma-7b-ultrachat-sft/blob/main/results_2024-02-23T17-43-57.046792.json)(note\ \ that their might be results for other tasks in the repos if successive evals didn't\ \ cover the same tasks. You find each in the results and the \"latest\" split for\ \ each eval):\n\n```python\n{\n \"all\": {\n \"acc\": 0.6393700582955444,\n\ \ \"acc_stderr\": 0.03219234730039111,\n \"acc_norm\": 0.6439639463015079,\n\ \ \"acc_norm_stderr\": 0.03283632439673242,\n \"mc1\": 0.3806609547123623,\n\ \ \"mc1_stderr\": 0.016997627871907922,\n \"mc2\": 0.5450293631615253,\n\ \ \"mc2_stderr\": 0.015380202565099867\n },\n \"harness\|arc:challenge\|25\"\ : {\n \"acc\": 0.5878839590443686,\n \"acc_stderr\": 0.014383915302225403,\n\ \ \"acc_norm\": 0.6126279863481229,\n \"acc_norm_stderr\": 0.01423587248790987\n\ \ },\n \"harness\|hellaswag\|10\": {\n \"acc\": 0.6127265484963155,\n\ \ \"acc_stderr\": 0.004861314613286841,\n \"acc_norm\": 0.8082055367456682,\n\ \ \"acc_norm_stderr\": 0.003929076276473383\n },\n \"harness\|hendrycksTest-abstract_algebra\|5\"\ : {\n \"acc\": 0.28,\n \"acc_stderr\": 0.045126085985421296,\n \ \ \"acc_norm\": 0.28,\n \"acc_norm_stderr\": 0.045126085985421296\n \ \ },\n \"harness\|hendrycksTest-anatomy\|5\": {\n \"acc\": 0.6222222222222222,\n\ \ \"acc_stderr\": 0.04188307537595852,\n \"acc_norm\": 0.6222222222222222,\n\ \ \"acc_norm_stderr\": 0.04188307537595852\n },\n \"harness\|hendrycksTest-astronomy\|5\"\ : {\n \"acc\": 0.6776315789473685,\n \"acc_stderr\": 0.03803510248351585,\n\ \ \"acc_norm\": 0.6776315789473685,\n \"acc_norm_stderr\": 0.03803510248351585\n\ \ },\n \"harness\|hendrycksTest-business_ethics\|5\": {\n \"acc\": 0.57,\n\ \ \"acc_stderr\": 0.049756985195624284,\n \"acc_norm\": 0.57,\n \ \ \"acc_norm_stderr\": 0.049756985195624284\n },\n \"harness\|hendrycksTest-clinical_knowledge\|5\"\ : {\n \"acc\": 0.6452830188679245,\n \"acc_stderr\": 0.02944517532819959,\n\ \ \"acc_norm\": 0.6452830188679245,\n \"acc_norm_stderr\": 0.02944517532819959\n\ \ },\n \"harness\|hendrycksTest-college_biology\|5\": {\n \"acc\": 0.7569444444444444,\n\ \ \"acc_stderr\": 0.0358687928008034,\n \"acc_norm\": 0.7569444444444444,\n\ \ \"acc_norm_stderr\": 0.0358687928008034\n },\n \"harness\|hendrycksTest-college_chemistry\|5\"\ : {\n \"acc\": 0.54,\n \"acc_stderr\": 0.05009082659620332,\n \ \ \"acc_norm\": 0.54,\n \"acc_norm_stderr\": 0.05009082659620332\n \ \ },\n \"harness\|hendrycksTest-college_computer_science\|5\": {\n \"acc\"\ : 0.52,\n \"acc_stderr\": 0.050211673156867795,\n \"acc_norm\": 0.52,\n\ \ \"acc_norm_stderr\": 0.050211673156867795\n },\n \"harness\|hendrycksTest-college_mathematics\|5\"\ : {\n \"acc\": 0.35,\n \"acc_stderr\": 0.047937248544110196,\n \ \ \"acc_norm\": 0.35,\n \"acc_norm_stderr\": 0.047937248544110196\n \ \ },\n \"harness\|hendrycksTest-college_medicine\|5\": {\n \"acc\": 0.6878612716763006,\n\ \ \"acc_stderr\": 0.03533133389323657,\n \"acc_norm\": 0.6878612716763006,\n\ \ \"acc_norm_stderr\": 0.03533133389323657\n },\n \"harness\|hendrycksTest-college_physics\|5\"\ : {\n \"acc\": 0.3431372549019608,\n \"acc_stderr\": 0.047240073523838876,\n\ \ \"acc_norm\": 0.3431372549019608,\n \"acc_norm_stderr\": 0.047240073523838876\n\ \ },\n \"harness\|hendrycksTest-computer_security\|5\": {\n \"acc\":\ \ 0.71,\n \"acc_stderr\": 0.045604802157206845,\n \"acc_norm\": 0.71,\n\ \ \"acc_norm_stderr\": 0.045604802157206845\n },\n \"harness\|hendrycksTest-conceptual_physics\|5\"\ : {\n \"acc\": 0.6085106382978723,\n \"acc_stderr\": 0.03190701242326812,\n\ \ \"acc_norm\": 0.6085106382978723,\n \"acc_norm_stderr\": 0.03190701242326812\n\ \ },\n \"harness\|hendrycksTest-econometrics\|5\": {\n \"acc\": 0.40350877192982454,\n\ \ \"acc_stderr\": 0.046151869625837026,\n \"acc_norm\": 0.40350877192982454,\n\ \ \"acc_norm_stderr\": 0.046151869625837026\n },\n \"harness\|hendrycksTest-electrical_engineering\|5\"\ : {\n \"acc\": 0.6413793103448275,\n \"acc_stderr\": 0.039966295748767186,\n\ \ \"acc_norm\": 0.6413793103448275,\n \"acc_norm_stderr\": 0.039966295748767186\n\ \ },\n \"harness\|hendrycksTest-elementary_mathematics\|5\": {\n \"acc\"\ : 0.4470899470899471,\n \"acc_stderr\": 0.025606723995777028,\n \"\ acc_norm\": 0.4470899470899471,\n \"acc_norm_stderr\": 0.025606723995777028\n\ \ },\n \"harness\|hendrycksTest-formal_logic\|5\": {\n \"acc\": 0.46825396825396826,\n\ \ \"acc_stderr\": 0.04463112720677172,\n \"acc_norm\": 0.46825396825396826,\n\ \ \"acc_norm_stderr\": 0.04463112720677172\n },\n \"harness\|hendrycksTest-global_facts\|5\"\ : {\n \"acc\": 0.38,\n \"acc_stderr\": 0.04878317312145633,\n \ \ \"acc_norm\": 0.38,\n \"acc_norm_stderr\": 0.04878317312145633\n \ \ },\n \"harness\|hendrycksTest-high_school_biology\|5\": {\n \"acc\": 0.8064516129032258,\n\ \ \"acc_stderr\": 0.022475258525536057,\n \"acc_norm\": 0.8064516129032258,\n\ \ \"acc_norm_stderr\": 0.022475258525536057\n },\n \"harness\|hendrycksTest-high_school_chemistry\|5\"\ : {\n \"acc\": 0.5270935960591133,\n \"acc_stderr\": 0.03512819077876105,\n\ \ \"acc_norm\": 0.5270935960591133,\n \"acc_norm_stderr\": 0.03512819077876105\n\ \ },\n \"harness\|hendrycksTest-high_school_computer_science\|5\": {\n \ \ \"acc\": 0.66,\n \"acc_stderr\": 0.04760952285695237,\n \"acc_norm\"\ : 0.66,\n \"acc_norm_stderr\": 0.04760952285695237\n },\n \"harness\|hendrycksTest-high_school_european_history\|5\"\ : {\n \"acc\": 0.7575757575757576,\n \"acc_stderr\": 0.03346409881055953,\n\ \ \"acc_norm\": 0.7575757575757576,\n \"acc_norm_stderr\": 0.03346409881055953\n\ \ },\n \"harness\|hendrycksTest-high_school_geography\|5\": {\n \"acc\"\ : 0.8484848484848485,\n \"acc_stderr\": 0.025545650426603617,\n \"\ acc_norm\": 0.8484848484848485,\n \"acc_norm_stderr\": 0.025545650426603617\n\ \ },\n \"harness\|hendrycksTest-high_school_government_and_politics\|5\": {\n\ \ \"acc\": 0.8601036269430051,\n \"acc_stderr\": 0.025033870583015184,\n\ \ \"acc_norm\": 0.8601036269430051,\n \"acc_norm_stderr\": 0.025033870583015184\n\ \ },\n \"harness\|hendrycksTest-high_school_macroeconomics\|5\": {\n \ \ \"acc\": 0.6692307692307692,\n \"acc_stderr\": 0.02385479568097112,\n \ \ \"acc_norm\": 0.6692307692307692,\n \"acc_norm_stderr\": 0.02385479568097112\n\ \ },\n \"harness\|hendrycksTest-high_school_mathematics\|5\": {\n \"\ acc\": 0.37777777777777777,\n \"acc_stderr\": 0.029560707392465708,\n \ \ \"acc_norm\": 0.37777777777777777,\n \"acc_norm_stderr\": 0.029560707392465708\n\ \ },\n \"harness\|hendrycksTest-high_school_microeconomics\|5\": {\n \ \ \"acc\": 0.6932773109243697,\n \"acc_stderr\": 0.02995382389188703,\n \ \ \"acc_norm\": 0.6932773109243697,\n \"acc_norm_stderr\": 0.02995382389188703\n\ \ },\n \"harness\|hendrycksTest-high_school_physics\|5\": {\n \"acc\"\ : 0.3841059602649007,\n \"acc_stderr\": 0.03971301814719197,\n \"\ acc_norm\": 0.3841059602649007,\n \"acc_norm_stderr\": 0.03971301814719197\n\ \ },\n \"harness\|hendrycksTest-high_school_psychology\|5\": {\n \"acc\"\ : 0.8256880733944955,\n \"acc_stderr\": 0.016265675632010333,\n \"\ acc_norm\": 0.8256880733944955,\n \"acc_norm_stderr\": 0.016265675632010333\n\ \ },\n \"harness\|hendrycksTest-high_school_statistics\|5\": {\n \"acc\"\ : 0.5694444444444444,\n \"acc_stderr\": 0.03376922151252335,\n \"\ acc_norm\": 0.5694444444444444,\n \"acc_norm_stderr\": 0.03376922151252335\n\ \ },\n \"harness\|hendrycksTest-high_school_us_history\|5\": {\n \"acc\"\ : 0.8137254901960784,\n \"acc_stderr\": 0.02732547096671632,\n \"\ acc_norm\": 0.8137254901960784,\n \"acc_norm_stderr\": 0.02732547096671632\n\ \ },\n \"harness\|hendrycksTest-high_school_world_history\|5\": {\n \"\ acc\": 0.8185654008438819,\n \"acc_stderr\": 0.025085961144579647,\n \ \ \"acc_norm\": 0.8185654008438819,\n \"acc_norm_stderr\": 0.025085961144579647\n\ \ },\n \"harness\|hendrycksTest-human_aging\|5\": {\n \"acc\": 0.6995515695067265,\n\ \ \"acc_stderr\": 0.03076935200822915,\n \"acc_norm\": 0.6995515695067265,\n\ \ \"acc_norm_stderr\": 0.03076935200822915\n },\n \"harness\|hendrycksTest-human_sexuality\|5\"\ : {\n \"acc\": 0.7175572519083969,\n \"acc_stderr\": 0.03948406125768361,\n\ \ \"acc_norm\": 0.7175572519083969,\n \"acc_norm_stderr\": 0.03948406125768361\n\ \ },\n \"harness\|hendrycksTest-international_law\|5\": {\n \"acc\":\ \ 0.8347107438016529,\n \"acc_stderr\": 0.03390780612972776,\n \"\ acc_norm\": 0.8347107438016529,\n \"acc_norm_stderr\": 0.03390780612972776\n\ \ },\n \"harness\|hendrycksTest-jurisprudence\|5\": {\n \"acc\": 0.7870370370370371,\n\ \ \"acc_stderr\": 0.039578354719809805,\n \"acc_norm\": 0.7870370370370371,\n\ \ \"acc_norm_stderr\": 0.039578354719809805\n },\n \"harness\|hendrycksTest-logical_fallacies\|5\"\ : {\n \"acc\": 0.7668711656441718,\n \"acc_stderr\": 0.0332201579577674,\n\ \ \"acc_norm\": 0.7668711656441718,\n \"acc_norm_stderr\": 0.0332201579577674\n\ \ },\n \"harness\|hendrycksTest-machine_learning\|5\": {\n \"acc\": 0.42857142857142855,\n\ \ \"acc_stderr\": 0.04697113923010212,\n \"acc_norm\": 0.42857142857142855,\n\ \ \"acc_norm_stderr\": 0.04697113923010212\n },\n \"harness\|hendrycksTest-management\|5\"\ : {\n \"acc\": 0.8446601941747572,\n \"acc_stderr\": 0.03586594738573974,\n\ \ \"acc_norm\": 0.8446601941747572,\n \"acc_norm_stderr\": 0.03586594738573974\n\ \ },\n \"harness\|hendrycksTest-marketing\|5\": {\n \"acc\": 0.8846153846153846,\n\ \ \"acc_stderr\": 0.02093019318517933,\n \"acc_norm\": 0.8846153846153846,\n\ \ \"acc_norm_stderr\": 0.02093019318517933\n },\n \"harness\|hendrycksTest-medical_genetics\|5\"\ : {\n \"acc\": 0.7,\n \"acc_stderr\": 0.046056618647183814,\n \ \ \"acc_norm\": 0.7,\n \"acc_norm_stderr\": 0.046056618647183814\n \ \ },\n \"harness\|hendrycksTest-miscellaneous\|5\": {\n \"acc\": 0.8314176245210728,\n\ \ \"acc_stderr\": 0.013387895731543604,\n \"acc_norm\": 0.8314176245210728,\n\ \ \"acc_norm_stderr\": 0.013387895731543604\n },\n \"harness\|hendrycksTest-moral_disputes\|5\"\ : {\n \"acc\": 0.7023121387283237,\n \"acc_stderr\": 0.024617055388676992,\n\ \ \"acc_norm\": 0.7023121387283237,\n \"acc_norm_stderr\": 0.024617055388676992\n\ \ },\n \"harness\|hendrycksTest-moral_scenarios\|5\": {\n \"acc\": 0.29720670391061454,\n\ \ \"acc_stderr\": 0.015285313353641597,\n \"acc_norm\": 0.29720670391061454,\n\ \ \"acc_norm_stderr\": 0.015285313353641597\n },\n \"harness\|hendrycksTest-nutrition\|5\"\ : {\n \"acc\": 0.7189542483660131,\n \"acc_stderr\": 0.025738854797818723,\n\ \ \"acc_norm\": 0.7189542483660131,\n \"acc_norm_stderr\": 0.025738854797818723\n\ \ },\n \"harness\|hendrycksTest-philosophy\|5\": {\n \"acc\": 0.6752411575562701,\n\ \ \"acc_stderr\": 0.026596782287697043,\n \"acc_norm\": 0.6752411575562701,\n\ \ \"acc_norm_stderr\": 0.026596782287697043\n },\n \"harness\|hendrycksTest-prehistory\|5\"\ : {\n \"acc\": 0.75,\n \"acc_stderr\": 0.02409347123262133,\n \ \ \"acc_norm\": 0.75,\n \"acc_norm_stderr\": 0.02409347123262133\n \ \ },\n \"harness\|hendrycksTest-professional_accounting\|5\": {\n \"acc\"\ : 0.4787234042553192,\n \"acc_stderr\": 0.029800481645628693,\n \"\ acc_norm\": 0.4787234042553192,\n \"acc_norm_stderr\": 0.029800481645628693\n\ \ },\n \"harness\|hendrycksTest-professional_law\|5\": {\n \"acc\": 0.46936114732724904,\n\ \ \"acc_stderr\": 0.012746237711716634,\n \"acc_norm\": 0.46936114732724904,\n\ \ \"acc_norm_stderr\": 0.012746237711716634\n },\n \"harness\|hendrycksTest-professional_medicine\|5\"\ : {\n \"acc\": 0.6507352941176471,\n \"acc_stderr\": 0.02895975519682487,\n\ \ \"acc_norm\": 0.6507352941176471,\n \"acc_norm_stderr\": 0.02895975519682487\n\ \ },\n \"harness\|hendrycksTest-professional_psychology\|5\": {\n \"\ acc\": 0.6454248366013072,\n \"acc_stderr\": 0.0193533605475537,\n \ \ \"acc_norm\": 0.6454248366013072,\n \"acc_norm_stderr\": 0.0193533605475537\n\ \ },\n \"harness\|hendrycksTest-public_relations\|5\": {\n \"acc\": 0.6727272727272727,\n\ \ \"acc_stderr\": 0.04494290866252092,\n \"acc_norm\": 0.6727272727272727,\n\ \ \"acc_norm_stderr\": 0.04494290866252092\n },\n \"harness\|hendrycksTest-security_studies\|5\"\ : {\n \"acc\": 0.7020408163265306,\n \"acc_stderr\": 0.029279567411065677,\n\ \ \"acc_norm\": 0.7020408163265306,\n \"acc_norm_stderr\": 0.029279567411065677\n\ \ },\n \"harness\|hendrycksTest-sociology\|5\": {\n \"acc\": 0.845771144278607,\n\ \ \"acc_stderr\": 0.025538433368578337,\n \"acc_norm\": 0.845771144278607,\n\ \ \"acc_norm_stderr\": 0.025538433368578337\n },\n \"harness\|hendrycksTest-us_foreign_policy\|5\"\ : {\n \"acc\": 0.84,\n \"acc_stderr\": 0.03684529491774708,\n \ \ \"acc_norm\": 0.84,\n \"acc_norm_stderr\": 0.03684529491774708\n \ \ },\n \"harness\|hendrycksTest-virology\|5\": {\n \"acc\": 0.5240963855421686,\n\ \ \"acc_stderr\": 0.03887971849597264,\n \"acc_norm\": 0.5240963855421686,\n\ \ \"acc_norm_stderr\": 0.03887971849597264\n },\n \"harness\|hendrycksTest-world_religions\|5\"\ : {\n \"acc\": 0.8421052631578947,\n \"acc_stderr\": 0.02796678585916089,\n\ \ \"acc_norm\": 0.8421052631578947,\n \"acc_norm_stderr\": 0.02796678585916089\n\ \ },\n \"harness\|truthfulqa:mc\|0\": {\n \"mc1\": 0.3806609547123623,\n\ \ \"mc1_stderr\": 0.016997627871907922,\n \"mc2\": 0.5450293631615253,\n\ \ \"mc2_stderr\": 0.015380202565099867\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.7813733228097869,\n \"acc_stderr\": 0.011616198215773225\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.44655041698256254,\n \ \ \"acc_stderr\": 0.01369356654974314\n }\n}\n```" repo_url: https://huggingface.co/CorticalStack/gemma-7b-ultrachat-sft leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2024_02_23T17_43_57.046792 path: - '/details_harness\|arc:challenge\|25_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2024-02-23T17-43-57.046792.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '/details_harness\|gsm8k\|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_02_23T17_43_57.046792 path: - '/details_harness\|hellaswag\|10_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-02-23T17-43-57.046792.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '/details_harness\|hendrycksTest-international_law\|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '/details_harness\|hendrycksTest-management\|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '/details_harness\|hendrycksTest-marketing\|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '/details_harness\|hendrycksTest-sociology\|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '/details_harness\|hendrycksTest-virology\|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_02_23T17_43_57.046792 path: - '/details_harness\|truthfulqa:mc\|0_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2024-02-23T17-43-57.046792.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '/details_harness\|winogrande\|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2024-02-23T17-43-57.046792.parquet' - config_name: results data_files: - split: 2024_02_23T17_43_57.046792 path: - results_2024-02-23T17-43-57.046792.parquet - split: latest path: - results_2024-02-23T17-43-57.046792.parquet --- # Dataset Card for Evaluation run of CorticalStack/gemma-7b-ultrachat-sft <!-- Provide a quick summary of the dataset. --> Dataset automatically created during the evaluation run of model [CorticalStack/gemma-7b-ultrachat-sft](https://huggingface.co/CorticalStack/gemma-7b-ultrachat-sft) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_CorticalStack__gemma-7b-ultrachat-sft", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-02-23T17:43:57.046792](https://huggingface.co/datasets/open-llm-leaderboard/details_CorticalStack__gemma-7b-ultrachat-sft/blob/main/results_2024-02-23T17-43-57.046792.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval): ```python { "all": { "acc": 0.6393700582955444, "acc_stderr": 0.03219234730039111, "acc_norm": 0.6439639463015079, "acc_norm_stderr": 0.03283632439673242, "mc1": 0.3806609547123623, "mc1_stderr": 0.016997627871907922, "mc2": 0.5450293631615253, "mc2_stderr": 0.015380202565099867 }, "harness\|arc:challenge\|25": { "acc": 0.5878839590443686, "acc_stderr": 0.014383915302225403, "acc_norm": 0.6126279863481229, "acc_norm_stderr": 0.01423587248790987 }, "harness\|hellaswag\|10": { "acc": 0.6127265484963155, "acc_stderr": 0.004861314613286841, "acc_norm": 0.8082055367456682, "acc_norm_stderr": 0.003929076276473383 }, "harness\|hendrycksTest-abstract_algebra\|5": { "acc": 0.28, "acc_stderr": 0.045126085985421296, "acc_norm": 0.28, "acc_norm_stderr": 0.045126085985421296 }, "harness\|hendrycksTest-anatomy\|5": { "acc": 0.6222222222222222, "acc_stderr": 0.04188307537595852, "acc_norm": 0.6222222222222222, "acc_norm_stderr": 0.04188307537595852 }, "harness\|hendrycksTest-astronomy\|5": { "acc": 0.6776315789473685, "acc_stderr": 0.03803510248351585, "acc_norm": 0.6776315789473685, "acc_norm_stderr": 0.03803510248351585 }, "harness\|hendrycksTest-business_ethics\|5": { "acc": 0.57, "acc_stderr": 0.049756985195624284, "acc_norm": 0.57, "acc_norm_stderr": 0.049756985195624284 }, "harness\|hendrycksTest-clinical_knowledge\|5": { "acc": 0.6452830188679245, "acc_stderr": 0.02944517532819959, "acc_norm": 0.6452830188679245, "acc_norm_stderr": 0.02944517532819959 }, "harness\|hendrycksTest-college_biology\|5": { "acc": 0.7569444444444444, "acc_stderr": 0.0358687928008034, "acc_norm": 0.7569444444444444, "acc_norm_stderr": 0.0358687928008034 }, "harness\|hendrycksTest-college_chemistry\|5": { "acc": 0.54, "acc_stderr": 0.05009082659620332, "acc_norm": 0.54, "acc_norm_stderr": 0.05009082659620332 }, "harness\|hendrycksTest-college_computer_science\|5": { "acc": 0.52, "acc_stderr": 0.050211673156867795, "acc_norm": 0.52, "acc_norm_stderr": 0.050211673156867795 }, "harness\|hendrycksTest-college_mathematics\|5": { "acc": 0.35, "acc_stderr": 0.047937248544110196, "acc_norm": 0.35, "acc_norm_stderr": 0.047937248544110196 }, "harness\|hendrycksTest-college_medicine\|5": { "acc": 0.6878612716763006, "acc_stderr": 0.03533133389323657, "acc_norm": 0.6878612716763006, "acc_norm_stderr": 0.03533133389323657 }, "harness\|hendrycksTest-college_physics\|5": { "acc": 0.3431372549019608, "acc_stderr": 0.047240073523838876, "acc_norm": 0.3431372549019608, "acc_norm_stderr": 0.047240073523838876 }, "harness\|hendrycksTest-computer_security\|5": { "acc": 0.71, "acc_stderr": 0.045604802157206845, "acc_norm": 0.71, "acc_norm_stderr": 0.045604802157206845 }, "harness\|hendrycksTest-conceptual_physics\|5": { "acc": 0.6085106382978723, "acc_stderr": 0.03190701242326812, "acc_norm": 0.6085106382978723, "acc_norm_stderr": 0.03190701242326812 }, "harness\|hendrycksTest-econometrics\|5": { "acc": 0.40350877192982454, "acc_stderr": 0.046151869625837026, "acc_norm": 0.40350877192982454, "acc_norm_stderr": 0.046151869625837026 }, "harness\|hendrycksTest-electrical_engineering\|5": { "acc": 0.6413793103448275, "acc_stderr": 0.039966295748767186, "acc_norm": 0.6413793103448275, "acc_norm_stderr": 0.039966295748767186 }, "harness\|hendrycksTest-elementary_mathematics\|5": { "acc": 0.4470899470899471, "acc_stderr": 0.025606723995777028, "acc_norm": 0.4470899470899471, "acc_norm_stderr": 0.025606723995777028 }, "harness\|hendrycksTest-formal_logic\|5": { "acc": 0.46825396825396826, "acc_stderr": 0.04463112720677172, "acc_norm": 0.46825396825396826, "acc_norm_stderr": 0.04463112720677172 }, "harness\|hendrycksTest-global_facts\|5": { "acc": 0.38, "acc_stderr": 0.04878317312145633, "acc_norm": 0.38, "acc_norm_stderr": 0.04878317312145633 }, "harness\|hendrycksTest-high_school_biology\|5": { "acc": 0.8064516129032258, "acc_stderr": 0.022475258525536057, "acc_norm": 0.8064516129032258, "acc_norm_stderr": 0.022475258525536057 }, "harness\|hendrycksTest-high_school_chemistry\|5": { "acc": 0.5270935960591133, "acc_stderr": 0.03512819077876105, "acc_norm": 0.5270935960591133, "acc_norm_stderr": 0.03512819077876105 }, "harness\|hendrycksTest-high_school_computer_science\|5": { "acc": 0.66, "acc_stderr": 0.04760952285695237, "acc_norm": 0.66, "acc_norm_stderr": 0.04760952285695237 }, "harness\|hendrycksTest-high_school_european_history\|5": { "acc": 0.7575757575757576, "acc_stderr": 0.03346409881055953, "acc_norm": 0.7575757575757576, "acc_norm_stderr": 0.03346409881055953 }, "harness\|hendrycksTest-high_school_geography\|5": { "acc": 0.8484848484848485, "acc_stderr": 0.025545650426603617, "acc_norm": 0.8484848484848485, "acc_norm_stderr": 0.025545650426603617 }, "harness\|hendrycksTest-high_school_government_and_politics\|5": { "acc": 0.8601036269430051, "acc_stderr": 0.025033870583015184, "acc_norm": 0.8601036269430051, "acc_norm_stderr": 0.025033870583015184 }, "harness\|hendrycksTest-high_school_macroeconomics\|5": { "acc": 0.6692307692307692, "acc_stderr": 0.02385479568097112, "acc_norm": 0.6692307692307692, "acc_norm_stderr": 0.02385479568097112 }, "harness\|hendrycksTest-high_school_mathematics\|5": { "acc": 0.37777777777777777, "acc_stderr": 0.029560707392465708, "acc_norm": 0.37777777777777777, "acc_norm_stderr": 0.029560707392465708 }, "harness\|hendrycksTest-high_school_microeconomics\|5": { "acc": 0.6932773109243697, "acc_stderr": 0.02995382389188703, "acc_norm": 0.6932773109243697, "acc_norm_stderr": 0.02995382389188703 }, "harness\|hendrycksTest-high_school_physics\|5": { "acc": 0.3841059602649007, "acc_stderr": 0.03971301814719197, "acc_norm": 0.3841059602649007, "acc_norm_stderr": 0.03971301814719197 }, "harness\|hendrycksTest-high_school_psychology\|5": { "acc": 0.8256880733944955, "acc_stderr": 0.016265675632010333, "acc_norm": 0.8256880733944955, "acc_norm_stderr": 0.016265675632010333 }, "harness\|hendrycksTest-high_school_statistics\|5": { "acc": 0.5694444444444444, "acc_stderr": 0.03376922151252335, "acc_norm": 0.5694444444444444, "acc_norm_stderr": 0.03376922151252335 }, "harness\|hendrycksTest-high_school_us_history\|5": { "acc": 0.8137254901960784, "acc_stderr": 0.02732547096671632, "acc_norm": 0.8137254901960784, "acc_norm_stderr": 0.02732547096671632 }, "harness\|hendrycksTest-high_school_world_history\|5": { "acc": 0.8185654008438819, "acc_stderr": 0.025085961144579647, "acc_norm": 0.8185654008438819, "acc_norm_stderr": 0.025085961144579647 }, "harness\|hendrycksTest-human_aging\|5": { "acc": 0.6995515695067265, "acc_stderr": 0.03076935200822915, "acc_norm": 0.6995515695067265, "acc_norm_stderr": 0.03076935200822915 }, "harness\|hendrycksTest-human_sexuality\|5": { "acc": 0.7175572519083969, "acc_stderr": 0.03948406125768361, "acc_norm": 0.7175572519083969, "acc_norm_stderr": 0.03948406125768361 }, "harness\|hendrycksTest-international_law\|5": { "acc": 0.8347107438016529, "acc_stderr": 0.03390780612972776, "acc_norm": 0.8347107438016529, "acc_norm_stderr": 0.03390780612972776 }, "harness\|hendrycksTest-jurisprudence\|5": { "acc": 0.7870370370370371, "acc_stderr": 0.039578354719809805, "acc_norm": 0.7870370370370371, "acc_norm_stderr": 0.039578354719809805 }, "harness\|hendrycksTest-logical_fallacies\|5": { "acc": 0.7668711656441718, "acc_stderr": 0.0332201579577674, "acc_norm": 0.7668711656441718, "acc_norm_stderr": 0.0332201579577674 }, "harness\|hendrycksTest-machine_learning\|5": { "acc": 0.42857142857142855, "acc_stderr": 0.04697113923010212, "acc_norm": 0.42857142857142855, "acc_norm_stderr": 0.04697113923010212 }, "harness\|hendrycksTest-management\|5": { "acc": 0.8446601941747572, "acc_stderr": 0.03586594738573974, "acc_norm": 0.8446601941747572, "acc_norm_stderr": 0.03586594738573974 }, "harness\|hendrycksTest-marketing\|5": { "acc": 0.8846153846153846, "acc_stderr": 0.02093019318517933, "acc_norm": 0.8846153846153846, "acc_norm_stderr": 0.02093019318517933 }, "harness\|hendrycksTest-medical_genetics\|5": { "acc": 0.7, "acc_stderr": 0.046056618647183814, "acc_norm": 0.7, "acc_norm_stderr": 0.046056618647183814 }, "harness\|hendrycksTest-miscellaneous\|5": { "acc": 0.8314176245210728, "acc_stderr": 0.013387895731543604, "acc_norm": 0.8314176245210728, "acc_norm_stderr": 0.013387895731543604 }, "harness\|hendrycksTest-moral_disputes\|5": { "acc": 0.7023121387283237, "acc_stderr": 0.024617055388676992, "acc_norm": 0.7023121387283237, "acc_norm_stderr": 0.024617055388676992 }, "harness\|hendrycksTest-moral_scenarios\|5": { "acc": 0.29720670391061454, "acc_stderr": 0.015285313353641597, "acc_norm": 0.29720670391061454, "acc_norm_stderr": 0.015285313353641597 }, "harness\|hendrycksTest-nutrition\|5": { "acc": 0.7189542483660131, "acc_stderr": 0.025738854797818723, "acc_norm": 0.7189542483660131, "acc_norm_stderr": 0.025738854797818723 }, "harness\|hendrycksTest-philosophy\|5": { "acc": 0.6752411575562701, "acc_stderr": 0.026596782287697043, "acc_norm": 0.6752411575562701, "acc_norm_stderr": 0.026596782287697043 }, "harness\|hendrycksTest-prehistory\|5": { "acc": 0.75, "acc_stderr": 0.02409347123262133, "acc_norm": 0.75, "acc_norm_stderr": 0.02409347123262133 }, "harness\|hendrycksTest-professional_accounting\|5": { "acc": 0.4787234042553192, "acc_stderr": 0.029800481645628693, "acc_norm": 0.4787234042553192, "acc_norm_stderr": 0.029800481645628693 }, "harness\|hendrycksTest-professional_law\|5": { "acc": 0.46936114732724904, "acc_stderr": 0.012746237711716634, "acc_norm": 0.46936114732724904, "acc_norm_stderr": 0.012746237711716634 }, "harness\|hendrycksTest-professional_medicine\|5": { "acc": 0.6507352941176471, "acc_stderr": 0.02895975519682487, "acc_norm": 0.6507352941176471, "acc_norm_stderr": 0.02895975519682487 }, "harness\|hendrycksTest-professional_psychology\|5": { "acc": 0.6454248366013072, "acc_stderr": 0.0193533605475537, "acc_norm": 0.6454248366013072, "acc_norm_stderr": 0.0193533605475537 }, "harness\|hendrycksTest-public_relations\|5": { "acc": 0.6727272727272727, "acc_stderr": 0.04494290866252092, "acc_norm": 0.6727272727272727, "acc_norm_stderr": 0.04494290866252092 }, "harness\|hendrycksTest-security_studies\|5": { "acc": 0.7020408163265306, "acc_stderr": 0.029279567411065677, "acc_norm": 0.7020408163265306, "acc_norm_stderr": 0.029279567411065677 }, "harness\|hendrycksTest-sociology\|5": { "acc": 0.845771144278607, "acc_stderr": 0.025538433368578337, "acc_norm": 0.845771144278607, "acc_norm_stderr": 0.025538433368578337 }, "harness\|hendrycksTest-us_foreign_policy\|5": { "acc": 0.84, "acc_stderr": 0.03684529491774708, "acc_norm": 0.84, "acc_norm_stderr": 0.03684529491774708 }, "harness\|hendrycksTest-virology\|5": { "acc": 0.5240963855421686, "acc_stderr": 0.03887971849597264, "acc_norm": 0.5240963855421686, "acc_norm_stderr": 0.03887971849597264 }, "harness\|hendrycksTest-world_religions\|5": { "acc": 0.8421052631578947, "acc_stderr": 0.02796678585916089, "acc_norm": 0.8421052631578947, "acc_norm_stderr": 0.02796678585916089 }, "harness\|truthfulqa:mc\|0": { "mc1": 0.3806609547123623, "mc1_stderr": 0.016997627871907922, "mc2": 0.5450293631615253, "mc2_stderr": 0.015380202565099867 }, "harness\|winogrande\|5": { "acc": 0.7813733228097869, "acc_stderr": 0.011616198215773225 }, "harness\|gsm8k\|5": { "acc": 0.44655041698256254, "acc_stderr": 0.01369356654974314 } } ``` ## Dataset Details ### Dataset Description <!-- Provide a longer summary of what this dataset is. --> - Curated by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] ### Dataset Sources [optional] <!-- Provide the basic links for the dataset. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the dataset is intended to be used. --> ### Direct Use <!-- This section describes suitable use cases for the dataset. --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. --> [More Information Needed] ## Dataset Structure <!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. --> [More Information Needed] ## Dataset Creation ### Curation Rationale <!-- Motivation for the creation of this dataset. --> [More Information Needed] ### Source Data <!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). --> #### Data Collection and Processing <!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. --> [More Information Needed] #### Who are the source data producers? <!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. --> [More Information Needed] ### Annotations [optional] <!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. --> #### Annotation process <!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. --> [More Information Needed] #### Who are the annotators? <!-- This section describes the people or systems who created the annotations. --> [More Information Needed] #### Personal and Sensitive Information <!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). 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Eduardovco/Edu	--- license: openrail ---
open-llm-leaderboard/details_Azure99__blossom-v4-mistral-7b	--- pretty_name: Evaluation run of Azure99/blossom-v4-mistral-7b dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [Azure99/blossom-v4-mistral-7b](https://huggingface.co/Azure99/blossom-v4-mistral-7b)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 63 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the aggregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_Azure99__blossom-v4-mistral-7b\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-12-28T11:10:20.298869](https://huggingface.co/datasets/open-llm-leaderboard/details_Azure99__blossom-v4-mistral-7b/blob/main/results_2023-12-28T11-10-20.298869.json)(note\ \ that their might be results for other tasks in the repos if successive evals didn't\ \ cover the same tasks. You find each in the results and the \"latest\" split for\ \ each eval):\n\n```python\n{\n \"all\": {\n \"acc\": 0.6235420002967518,\n\ \ \"acc_stderr\": 0.03272388603364805,\n \"acc_norm\": 0.6281854377869052,\n\ \ \"acc_norm_stderr\": 0.03338061598239654,\n \"mc1\": 0.36964504283965727,\n\ \ \"mc1_stderr\": 0.016898180706973888,\n \"mc2\": 0.5384391963865467,\n\ \ \"mc2_stderr\": 0.015414673673859326\n },\n \"harness\|arc:challenge\|25\"\ : {\n \"acc\": 0.5793515358361775,\n \"acc_stderr\": 0.014426211252508397,\n\ \ \"acc_norm\": 0.6203071672354948,\n \"acc_norm_stderr\": 0.014182119866974872\n\ \ },\n \"harness\|hellaswag\|10\": {\n \"acc\": 0.6390161322445728,\n\ \ \"acc_stderr\": 0.004793042992396035,\n \"acc_norm\": 0.8290181238797052,\n\ \ \"acc_norm_stderr\": 0.0037572368063973345\n },\n \"harness\|hendrycksTest-abstract_algebra\|5\"\ : {\n \"acc\": 0.28,\n \"acc_stderr\": 0.04512608598542129,\n \ \ \"acc_norm\": 0.28,\n \"acc_norm_stderr\": 0.04512608598542129\n \ \ },\n \"harness\|hendrycksTest-anatomy\|5\": {\n \"acc\": 0.5851851851851851,\n\ \ \"acc_stderr\": 0.04256193767901409,\n \"acc_norm\": 0.5851851851851851,\n\ \ \"acc_norm_stderr\": 0.04256193767901409\n },\n \"harness\|hendrycksTest-astronomy\|5\"\ : {\n \"acc\": 0.6381578947368421,\n \"acc_stderr\": 0.03910525752849724,\n\ \ \"acc_norm\": 0.6381578947368421,\n \"acc_norm_stderr\": 0.03910525752849724\n\ \ },\n \"harness\|hendrycksTest-business_ethics\|5\": {\n \"acc\": 0.62,\n\ \ \"acc_stderr\": 0.048783173121456316,\n \"acc_norm\": 0.62,\n \ \ \"acc_norm_stderr\": 0.048783173121456316\n },\n \"harness\|hendrycksTest-clinical_knowledge\|5\"\ : {\n \"acc\": 0.6943396226415094,\n \"acc_stderr\": 0.028353298073322666,\n\ \ \"acc_norm\": 0.6943396226415094,\n \"acc_norm_stderr\": 0.028353298073322666\n\ \ },\n \"harness\|hendrycksTest-college_biology\|5\": {\n \"acc\": 0.7152777777777778,\n\ \ \"acc_stderr\": 0.03773809990686934,\n \"acc_norm\": 0.7152777777777778,\n\ \ \"acc_norm_stderr\": 0.03773809990686934\n },\n \"harness\|hendrycksTest-college_chemistry\|5\"\ : {\n \"acc\": 0.45,\n \"acc_stderr\": 0.05,\n \"acc_norm\"\ : 0.45,\n \"acc_norm_stderr\": 0.05\n },\n \"harness\|hendrycksTest-college_computer_science\|5\"\ : {\n \"acc\": 0.5,\n \"acc_stderr\": 0.050251890762960605,\n \ \ \"acc_norm\": 0.5,\n \"acc_norm_stderr\": 0.050251890762960605\n \ \ },\n \"harness\|hendrycksTest-college_mathematics\|5\": {\n \"acc\": 0.36,\n\ \ \"acc_stderr\": 0.04824181513244218,\n \"acc_norm\": 0.36,\n \ \ \"acc_norm_stderr\": 0.04824181513244218\n },\n \"harness\|hendrycksTest-college_medicine\|5\"\ : {\n \"acc\": 0.5838150289017341,\n \"acc_stderr\": 0.03758517775404947,\n\ \ \"acc_norm\": 0.5838150289017341,\n \"acc_norm_stderr\": 0.03758517775404947\n\ \ },\n \"harness\|hendrycksTest-college_physics\|5\": {\n \"acc\": 0.4019607843137255,\n\ \ \"acc_stderr\": 0.048786087144669955,\n \"acc_norm\": 0.4019607843137255,\n\ \ \"acc_norm_stderr\": 0.048786087144669955\n },\n \"harness\|hendrycksTest-computer_security\|5\"\ : {\n \"acc\": 0.74,\n \"acc_stderr\": 0.0440844002276808,\n \ \ \"acc_norm\": 0.74,\n \"acc_norm_stderr\": 0.0440844002276808\n },\n\ \ \"harness\|hendrycksTest-conceptual_physics\|5\": {\n \"acc\": 0.5787234042553191,\n\ \ \"acc_stderr\": 0.03227834510146268,\n \"acc_norm\": 0.5787234042553191,\n\ \ \"acc_norm_stderr\": 0.03227834510146268\n },\n \"harness\|hendrycksTest-econometrics\|5\"\ : {\n \"acc\": 0.49122807017543857,\n \"acc_stderr\": 0.04702880432049615,\n\ \ \"acc_norm\": 0.49122807017543857,\n \"acc_norm_stderr\": 0.04702880432049615\n\ \ },\n \"harness\|hendrycksTest-electrical_engineering\|5\": {\n \"acc\"\ : 0.5724137931034483,\n \"acc_stderr\": 0.04122737111370333,\n \"\ acc_norm\": 0.5724137931034483,\n \"acc_norm_stderr\": 0.04122737111370333\n\ \ },\n \"harness\|hendrycksTest-elementary_mathematics\|5\": {\n \"acc\"\ : 0.41005291005291006,\n \"acc_stderr\": 0.02533120243894443,\n \"\ acc_norm\": 0.41005291005291006,\n \"acc_norm_stderr\": 0.02533120243894443\n\ \ },\n \"harness\|hendrycksTest-formal_logic\|5\": {\n \"acc\": 0.3968253968253968,\n\ \ \"acc_stderr\": 0.04375888492727061,\n \"acc_norm\": 0.3968253968253968,\n\ \ \"acc_norm_stderr\": 0.04375888492727061\n },\n \"harness\|hendrycksTest-global_facts\|5\"\ : {\n \"acc\": 0.4,\n \"acc_stderr\": 0.049236596391733084,\n \ \ \"acc_norm\": 0.4,\n \"acc_norm_stderr\": 0.049236596391733084\n \ \ },\n \"harness\|hendrycksTest-high_school_biology\|5\": {\n \"acc\": 0.7322580645161291,\n\ \ \"acc_stderr\": 0.025189006660212378,\n \"acc_norm\": 0.7322580645161291,\n\ \ \"acc_norm_stderr\": 0.025189006660212378\n },\n \"harness\|hendrycksTest-high_school_chemistry\|5\"\ : {\n \"acc\": 0.5270935960591133,\n \"acc_stderr\": 0.03512819077876106,\n\ \ \"acc_norm\": 0.5270935960591133,\n \"acc_norm_stderr\": 0.03512819077876106\n\ \ },\n \"harness\|hendrycksTest-high_school_computer_science\|5\": {\n \ \ \"acc\": 0.68,\n \"acc_stderr\": 0.04688261722621505,\n \"acc_norm\"\ : 0.68,\n \"acc_norm_stderr\": 0.04688261722621505\n },\n \"harness\|hendrycksTest-high_school_european_history\|5\"\ : {\n \"acc\": 0.7696969696969697,\n \"acc_stderr\": 0.0328766675860349,\n\ \ \"acc_norm\": 0.7696969696969697,\n \"acc_norm_stderr\": 0.0328766675860349\n\ \ },\n \"harness\|hendrycksTest-high_school_geography\|5\": {\n \"acc\"\ : 0.7828282828282829,\n \"acc_stderr\": 0.029376616484945627,\n \"\ acc_norm\": 0.7828282828282829,\n \"acc_norm_stderr\": 0.029376616484945627\n\ \ },\n \"harness\|hendrycksTest-high_school_government_and_politics\|5\": {\n\ \ \"acc\": 0.8549222797927462,\n \"acc_stderr\": 0.025416343096306433,\n\ \ \"acc_norm\": 0.8549222797927462,\n \"acc_norm_stderr\": 0.025416343096306433\n\ \ },\n \"harness\|hendrycksTest-high_school_macroeconomics\|5\": {\n \ \ \"acc\": 0.6153846153846154,\n \"acc_stderr\": 0.024666744915187208,\n\ \ \"acc_norm\": 0.6153846153846154,\n \"acc_norm_stderr\": 0.024666744915187208\n\ \ },\n \"harness\|hendrycksTest-high_school_mathematics\|5\": {\n \"\ acc\": 0.3148148148148148,\n \"acc_stderr\": 0.028317533496066468,\n \ \ \"acc_norm\": 0.3148148148148148,\n \"acc_norm_stderr\": 0.028317533496066468\n\ \ },\n \"harness\|hendrycksTest-high_school_microeconomics\|5\": {\n \ \ \"acc\": 0.6554621848739496,\n \"acc_stderr\": 0.030868682604121622,\n\ \ \"acc_norm\": 0.6554621848739496,\n \"acc_norm_stderr\": 0.030868682604121622\n\ \ },\n \"harness\|hendrycksTest-high_school_physics\|5\": {\n \"acc\"\ : 0.32450331125827814,\n \"acc_stderr\": 0.03822746937658753,\n \"\ acc_norm\": 0.32450331125827814,\n \"acc_norm_stderr\": 0.03822746937658753\n\ \ },\n \"harness\|hendrycksTest-high_school_psychology\|5\": {\n \"acc\"\ : 0.8018348623853211,\n \"acc_stderr\": 0.017090573804217902,\n \"\ acc_norm\": 0.8018348623853211,\n \"acc_norm_stderr\": 0.017090573804217902\n\ \ },\n \"harness\|hendrycksTest-high_school_statistics\|5\": {\n \"acc\"\ : 0.4675925925925926,\n \"acc_stderr\": 0.03402801581358966,\n \"\ acc_norm\": 0.4675925925925926,\n \"acc_norm_stderr\": 0.03402801581358966\n\ \ },\n \"harness\|hendrycksTest-high_school_us_history\|5\": {\n \"acc\"\ : 0.8235294117647058,\n \"acc_stderr\": 0.026756401538078966,\n \"\ acc_norm\": 0.8235294117647058,\n \"acc_norm_stderr\": 0.026756401538078966\n\ \ },\n \"harness\|hendrycksTest-high_school_world_history\|5\": {\n \"\ acc\": 0.7721518987341772,\n \"acc_stderr\": 0.027303484599069422,\n \ \ \"acc_norm\": 0.7721518987341772,\n \"acc_norm_stderr\": 0.027303484599069422\n\ \ },\n \"harness\|hendrycksTest-human_aging\|5\": {\n \"acc\": 0.6502242152466368,\n\ \ \"acc_stderr\": 0.03200736719484503,\n \"acc_norm\": 0.6502242152466368,\n\ \ \"acc_norm_stderr\": 0.03200736719484503\n },\n \"harness\|hendrycksTest-human_sexuality\|5\"\ : {\n \"acc\": 0.7633587786259542,\n \"acc_stderr\": 0.03727673575596913,\n\ \ \"acc_norm\": 0.7633587786259542,\n \"acc_norm_stderr\": 0.03727673575596913\n\ \ },\n \"harness\|hendrycksTest-international_law\|5\": {\n \"acc\":\ \ 0.7603305785123967,\n \"acc_stderr\": 0.03896878985070417,\n \"\ acc_norm\": 0.7603305785123967,\n \"acc_norm_stderr\": 0.03896878985070417\n\ \ },\n \"harness\|hendrycksTest-jurisprudence\|5\": {\n \"acc\": 0.75,\n\ \ \"acc_stderr\": 0.04186091791394607,\n \"acc_norm\": 0.75,\n \ \ \"acc_norm_stderr\": 0.04186091791394607\n },\n \"harness\|hendrycksTest-logical_fallacies\|5\"\ : {\n \"acc\": 0.7484662576687117,\n \"acc_stderr\": 0.03408997886857529,\n\ \ \"acc_norm\": 0.7484662576687117,\n \"acc_norm_stderr\": 0.03408997886857529\n\ \ },\n \"harness\|hendrycksTest-machine_learning\|5\": {\n \"acc\": 0.49107142857142855,\n\ \ \"acc_stderr\": 0.04745033255489123,\n \"acc_norm\": 0.49107142857142855,\n\ \ \"acc_norm_stderr\": 0.04745033255489123\n },\n \"harness\|hendrycksTest-management\|5\"\ : {\n \"acc\": 0.7961165048543689,\n \"acc_stderr\": 0.039891398595317706,\n\ \ \"acc_norm\": 0.7961165048543689,\n \"acc_norm_stderr\": 0.039891398595317706\n\ \ },\n \"harness\|hendrycksTest-marketing\|5\": {\n \"acc\": 0.8760683760683761,\n\ \ \"acc_stderr\": 0.02158649400128136,\n \"acc_norm\": 0.8760683760683761,\n\ \ \"acc_norm_stderr\": 0.02158649400128136\n },\n \"harness\|hendrycksTest-medical_genetics\|5\"\ : {\n \"acc\": 0.66,\n \"acc_stderr\": 0.04760952285695237,\n \ \ \"acc_norm\": 0.66,\n \"acc_norm_stderr\": 0.04760952285695237\n \ \ },\n \"harness\|hendrycksTest-miscellaneous\|5\": {\n \"acc\": 0.80970625798212,\n\ \ \"acc_stderr\": 0.014036945850381398,\n \"acc_norm\": 0.80970625798212,\n\ \ \"acc_norm_stderr\": 0.014036945850381398\n },\n \"harness\|hendrycksTest-moral_disputes\|5\"\ : {\n \"acc\": 0.6878612716763006,\n \"acc_stderr\": 0.024946792225272314,\n\ \ \"acc_norm\": 0.6878612716763006,\n \"acc_norm_stderr\": 0.024946792225272314\n\ \ },\n \"harness\|hendrycksTest-moral_scenarios\|5\": {\n \"acc\": 0.3329608938547486,\n\ \ \"acc_stderr\": 0.015761716178397566,\n \"acc_norm\": 0.3329608938547486,\n\ \ \"acc_norm_stderr\": 0.015761716178397566\n },\n \"harness\|hendrycksTest-nutrition\|5\"\ : {\n \"acc\": 0.7189542483660131,\n \"acc_stderr\": 0.025738854797818737,\n\ \ \"acc_norm\": 0.7189542483660131,\n \"acc_norm_stderr\": 0.025738854797818737\n\ \ },\n \"harness\|hendrycksTest-philosophy\|5\": {\n \"acc\": 0.707395498392283,\n\ \ \"acc_stderr\": 0.02583989833487798,\n \"acc_norm\": 0.707395498392283,\n\ \ \"acc_norm_stderr\": 0.02583989833487798\n },\n \"harness\|hendrycksTest-prehistory\|5\"\ : {\n \"acc\": 0.7129629629629629,\n \"acc_stderr\": 0.02517104191530968,\n\ \ \"acc_norm\": 0.7129629629629629,\n \"acc_norm_stderr\": 0.02517104191530968\n\ \ },\n \"harness\|hendrycksTest-professional_accounting\|5\": {\n \"\ acc\": 0.4929078014184397,\n \"acc_stderr\": 0.02982449855912901,\n \ \ \"acc_norm\": 0.4929078014184397,\n \"acc_norm_stderr\": 0.02982449855912901\n\ \ },\n \"harness\|hendrycksTest-professional_law\|5\": {\n \"acc\": 0.4511082138200782,\n\ \ \"acc_stderr\": 0.012709037347346233,\n \"acc_norm\": 0.4511082138200782,\n\ \ \"acc_norm_stderr\": 0.012709037347346233\n },\n \"harness\|hendrycksTest-professional_medicine\|5\"\ : {\n \"acc\": 0.6323529411764706,\n \"acc_stderr\": 0.029289413409403192,\n\ \ \"acc_norm\": 0.6323529411764706,\n \"acc_norm_stderr\": 0.029289413409403192\n\ \ },\n \"harness\|hendrycksTest-professional_psychology\|5\": {\n \"\ acc\": 0.6584967320261438,\n \"acc_stderr\": 0.01918463932809249,\n \ \ \"acc_norm\": 0.6584967320261438,\n \"acc_norm_stderr\": 0.01918463932809249\n\ \ },\n \"harness\|hendrycksTest-public_relations\|5\": {\n \"acc\": 0.6454545454545455,\n\ \ \"acc_stderr\": 0.04582004841505417,\n \"acc_norm\": 0.6454545454545455,\n\ \ \"acc_norm_stderr\": 0.04582004841505417\n },\n \"harness\|hendrycksTest-security_studies\|5\"\ : {\n \"acc\": 0.6979591836734694,\n \"acc_stderr\": 0.029393609319879804,\n\ \ \"acc_norm\": 0.6979591836734694,\n \"acc_norm_stderr\": 0.029393609319879804\n\ \ },\n \"harness\|hendrycksTest-sociology\|5\": {\n \"acc\": 0.8407960199004975,\n\ \ \"acc_stderr\": 0.02587064676616913,\n \"acc_norm\": 0.8407960199004975,\n\ \ \"acc_norm_stderr\": 0.02587064676616913\n },\n \"harness\|hendrycksTest-us_foreign_policy\|5\"\ : {\n \"acc\": 0.84,\n \"acc_stderr\": 0.03684529491774709,\n \ \ \"acc_norm\": 0.84,\n \"acc_norm_stderr\": 0.03684529491774709\n \ \ },\n \"harness\|hendrycksTest-virology\|5\": {\n \"acc\": 0.536144578313253,\n\ \ \"acc_stderr\": 0.038823108508905954,\n \"acc_norm\": 0.536144578313253,\n\ \ \"acc_norm_stderr\": 0.038823108508905954\n },\n \"harness\|hendrycksTest-world_religions\|5\"\ : {\n \"acc\": 0.8128654970760234,\n \"acc_stderr\": 0.029913127232368036,\n\ \ \"acc_norm\": 0.8128654970760234,\n \"acc_norm_stderr\": 0.029913127232368036\n\ \ },\n \"harness\|truthfulqa:mc\|0\": {\n \"mc1\": 0.36964504283965727,\n\ \ \"mc1_stderr\": 0.016898180706973888,\n \"mc2\": 0.5384391963865467,\n\ \ \"mc2_stderr\": 0.015414673673859326\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.7726913970007893,\n \"acc_stderr\": 0.011778612167091087\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.4313874147081122,\n \ \ \"acc_stderr\": 0.013642195352511575\n }\n}\n```" repo_url: https://huggingface.co/Azure99/blossom-v4-mistral-7b leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2023_12_28T11_10_20.298869 path: - '/details_harness\|arc:challenge\|25_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-12-28T11-10-20.298869.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '/details_harness\|gsm8k\|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_12_28T11_10_20.298869 path: - '/details_harness\|hellaswag\|10_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-12-28T11-10-20.298869.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '/details_harness\|hendrycksTest-management\|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '/details_harness\|hendrycksTest-virology\|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_12_28T11_10_20.298869 path: - '/details_harness\|truthfulqa:mc\|0_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-12-28T11-10-20.298869.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '/details_harness\|winogrande\|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2023-12-28T11-10-20.298869.parquet' - config_name: results data_files: - split: 2023_12_28T11_10_20.298869 path: - results_2023-12-28T11-10-20.298869.parquet - split: latest path: - results_2023-12-28T11-10-20.298869.parquet --- # Dataset Card for Evaluation run of Azure99/blossom-v4-mistral-7b <!-- Provide a quick summary of the dataset. --> Dataset automatically created during the evaluation run of model [Azure99/blossom-v4-mistral-7b](https://huggingface.co/Azure99/blossom-v4-mistral-7b) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_Azure99__blossom-v4-mistral-7b", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-12-28T11:10:20.298869](https://huggingface.co/datasets/open-llm-leaderboard/details_Azure99__blossom-v4-mistral-7b/blob/main/results_2023-12-28T11-10-20.298869.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval): ```python { "all": { "acc": 0.6235420002967518, "acc_stderr": 0.03272388603364805, "acc_norm": 0.6281854377869052, "acc_norm_stderr": 0.03338061598239654, "mc1": 0.36964504283965727, "mc1_stderr": 0.016898180706973888, "mc2": 0.5384391963865467, "mc2_stderr": 0.015414673673859326 }, "harness\|arc:challenge\|25": { "acc": 0.5793515358361775, "acc_stderr": 0.014426211252508397, "acc_norm": 0.6203071672354948, "acc_norm_stderr": 0.014182119866974872 }, "harness\|hellaswag\|10": { "acc": 0.6390161322445728, "acc_stderr": 0.004793042992396035, "acc_norm": 0.8290181238797052, "acc_norm_stderr": 0.0037572368063973345 }, "harness\|hendrycksTest-abstract_algebra\|5": { "acc": 0.28, "acc_stderr": 0.04512608598542129, "acc_norm": 0.28, "acc_norm_stderr": 0.04512608598542129 }, "harness\|hendrycksTest-anatomy\|5": { "acc": 0.5851851851851851, "acc_stderr": 0.04256193767901409, "acc_norm": 0.5851851851851851, "acc_norm_stderr": 0.04256193767901409 }, "harness\|hendrycksTest-astronomy\|5": { "acc": 0.6381578947368421, "acc_stderr": 0.03910525752849724, "acc_norm": 0.6381578947368421, "acc_norm_stderr": 0.03910525752849724 }, "harness\|hendrycksTest-business_ethics\|5": { "acc": 0.62, "acc_stderr": 0.048783173121456316, "acc_norm": 0.62, "acc_norm_stderr": 0.048783173121456316 }, "harness\|hendrycksTest-clinical_knowledge\|5": { "acc": 0.6943396226415094, "acc_stderr": 0.028353298073322666, "acc_norm": 0.6943396226415094, "acc_norm_stderr": 0.028353298073322666 }, "harness\|hendrycksTest-college_biology\|5": { "acc": 0.7152777777777778, "acc_stderr": 0.03773809990686934, "acc_norm": 0.7152777777777778, "acc_norm_stderr": 0.03773809990686934 }, "harness\|hendrycksTest-college_chemistry\|5": { "acc": 0.45, "acc_stderr": 0.05, "acc_norm": 0.45, "acc_norm_stderr": 0.05 }, "harness\|hendrycksTest-college_computer_science\|5": { "acc": 0.5, "acc_stderr": 0.050251890762960605, "acc_norm": 0.5, "acc_norm_stderr": 0.050251890762960605 }, "harness\|hendrycksTest-college_mathematics\|5": { "acc": 0.36, "acc_stderr": 0.04824181513244218, "acc_norm": 0.36, "acc_norm_stderr": 0.04824181513244218 }, "harness\|hendrycksTest-college_medicine\|5": { "acc": 0.5838150289017341, "acc_stderr": 0.03758517775404947, "acc_norm": 0.5838150289017341, "acc_norm_stderr": 0.03758517775404947 }, "harness\|hendrycksTest-college_physics\|5": { "acc": 0.4019607843137255, "acc_stderr": 0.048786087144669955, "acc_norm": 0.4019607843137255, "acc_norm_stderr": 0.048786087144669955 }, "harness\|hendrycksTest-computer_security\|5": { "acc": 0.74, "acc_stderr": 0.0440844002276808, "acc_norm": 0.74, "acc_norm_stderr": 0.0440844002276808 }, "harness\|hendrycksTest-conceptual_physics\|5": { "acc": 0.5787234042553191, "acc_stderr": 0.03227834510146268, "acc_norm": 0.5787234042553191, "acc_norm_stderr": 0.03227834510146268 }, "harness\|hendrycksTest-econometrics\|5": { "acc": 0.49122807017543857, "acc_stderr": 0.04702880432049615, "acc_norm": 0.49122807017543857, "acc_norm_stderr": 0.04702880432049615 }, "harness\|hendrycksTest-electrical_engineering\|5": { "acc": 0.5724137931034483, "acc_stderr": 0.04122737111370333, "acc_norm": 0.5724137931034483, "acc_norm_stderr": 0.04122737111370333 }, "harness\|hendrycksTest-elementary_mathematics\|5": { "acc": 0.41005291005291006, "acc_stderr": 0.02533120243894443, "acc_norm": 0.41005291005291006, "acc_norm_stderr": 0.02533120243894443 }, "harness\|hendrycksTest-formal_logic\|5": { "acc": 0.3968253968253968, "acc_stderr": 0.04375888492727061, "acc_norm": 0.3968253968253968, "acc_norm_stderr": 0.04375888492727061 }, "harness\|hendrycksTest-global_facts\|5": { "acc": 0.4, "acc_stderr": 0.049236596391733084, "acc_norm": 0.4, "acc_norm_stderr": 0.049236596391733084 }, "harness\|hendrycksTest-high_school_biology\|5": { "acc": 0.7322580645161291, "acc_stderr": 0.025189006660212378, "acc_norm": 0.7322580645161291, "acc_norm_stderr": 0.025189006660212378 }, "harness\|hendrycksTest-high_school_chemistry\|5": { "acc": 0.5270935960591133, "acc_stderr": 0.03512819077876106, "acc_norm": 0.5270935960591133, "acc_norm_stderr": 0.03512819077876106 }, "harness\|hendrycksTest-high_school_computer_science\|5": { "acc": 0.68, "acc_stderr": 0.04688261722621505, "acc_norm": 0.68, "acc_norm_stderr": 0.04688261722621505 }, "harness\|hendrycksTest-high_school_european_history\|5": { "acc": 0.7696969696969697, "acc_stderr": 0.0328766675860349, "acc_norm": 0.7696969696969697, "acc_norm_stderr": 0.0328766675860349 }, "harness\|hendrycksTest-high_school_geography\|5": { "acc": 0.7828282828282829, "acc_stderr": 0.029376616484945627, "acc_norm": 0.7828282828282829, "acc_norm_stderr": 0.029376616484945627 }, "harness\|hendrycksTest-high_school_government_and_politics\|5": { "acc": 0.8549222797927462, "acc_stderr": 0.025416343096306433, "acc_norm": 0.8549222797927462, "acc_norm_stderr": 0.025416343096306433 }, "harness\|hendrycksTest-high_school_macroeconomics\|5": { "acc": 0.6153846153846154, "acc_stderr": 0.024666744915187208, "acc_norm": 0.6153846153846154, "acc_norm_stderr": 0.024666744915187208 }, "harness\|hendrycksTest-high_school_mathematics\|5": { "acc": 0.3148148148148148, "acc_stderr": 0.028317533496066468, "acc_norm": 0.3148148148148148, "acc_norm_stderr": 0.028317533496066468 }, "harness\|hendrycksTest-high_school_microeconomics\|5": { "acc": 0.6554621848739496, "acc_stderr": 0.030868682604121622, "acc_norm": 0.6554621848739496, "acc_norm_stderr": 0.030868682604121622 }, "harness\|hendrycksTest-high_school_physics\|5": { "acc": 0.32450331125827814, "acc_stderr": 0.03822746937658753, "acc_norm": 0.32450331125827814, "acc_norm_stderr": 0.03822746937658753 }, "harness\|hendrycksTest-high_school_psychology\|5": { "acc": 0.8018348623853211, "acc_stderr": 0.017090573804217902, "acc_norm": 0.8018348623853211, "acc_norm_stderr": 0.017090573804217902 }, "harness\|hendrycksTest-high_school_statistics\|5": { "acc": 0.4675925925925926, "acc_stderr": 0.03402801581358966, "acc_norm": 0.4675925925925926, "acc_norm_stderr": 0.03402801581358966 }, "harness\|hendrycksTest-high_school_us_history\|5": { "acc": 0.8235294117647058, "acc_stderr": 0.026756401538078966, "acc_norm": 0.8235294117647058, "acc_norm_stderr": 0.026756401538078966 }, "harness\|hendrycksTest-high_school_world_history\|5": { "acc": 0.7721518987341772, "acc_stderr": 0.027303484599069422, "acc_norm": 0.7721518987341772, "acc_norm_stderr": 0.027303484599069422 }, "harness\|hendrycksTest-human_aging\|5": { "acc": 0.6502242152466368, "acc_stderr": 0.03200736719484503, "acc_norm": 0.6502242152466368, "acc_norm_stderr": 0.03200736719484503 }, "harness\|hendrycksTest-human_sexuality\|5": { "acc": 0.7633587786259542, "acc_stderr": 0.03727673575596913, "acc_norm": 0.7633587786259542, "acc_norm_stderr": 0.03727673575596913 }, "harness\|hendrycksTest-international_law\|5": { "acc": 0.7603305785123967, "acc_stderr": 0.03896878985070417, "acc_norm": 0.7603305785123967, "acc_norm_stderr": 0.03896878985070417 }, "harness\|hendrycksTest-jurisprudence\|5": { "acc": 0.75, "acc_stderr": 0.04186091791394607, "acc_norm": 0.75, "acc_norm_stderr": 0.04186091791394607 }, "harness\|hendrycksTest-logical_fallacies\|5": { "acc": 0.7484662576687117, "acc_stderr": 0.03408997886857529, "acc_norm": 0.7484662576687117, "acc_norm_stderr": 0.03408997886857529 }, "harness\|hendrycksTest-machine_learning\|5": { "acc": 0.49107142857142855, "acc_stderr": 0.04745033255489123, "acc_norm": 0.49107142857142855, "acc_norm_stderr": 0.04745033255489123 }, "harness\|hendrycksTest-management\|5": { "acc": 0.7961165048543689, "acc_stderr": 0.039891398595317706, "acc_norm": 0.7961165048543689, "acc_norm_stderr": 0.039891398595317706 }, "harness\|hendrycksTest-marketing\|5": { "acc": 0.8760683760683761, "acc_stderr": 0.02158649400128136, "acc_norm": 0.8760683760683761, "acc_norm_stderr": 0.02158649400128136 }, "harness\|hendrycksTest-medical_genetics\|5": { "acc": 0.66, "acc_stderr": 0.04760952285695237, "acc_norm": 0.66, "acc_norm_stderr": 0.04760952285695237 }, "harness\|hendrycksTest-miscellaneous\|5": { "acc": 0.80970625798212, "acc_stderr": 0.014036945850381398, "acc_norm": 0.80970625798212, "acc_norm_stderr": 0.014036945850381398 }, "harness\|hendrycksTest-moral_disputes\|5": { "acc": 0.6878612716763006, "acc_stderr": 0.024946792225272314, "acc_norm": 0.6878612716763006, "acc_norm_stderr": 0.024946792225272314 }, "harness\|hendrycksTest-moral_scenarios\|5": { "acc": 0.3329608938547486, "acc_stderr": 0.015761716178397566, "acc_norm": 0.3329608938547486, "acc_norm_stderr": 0.015761716178397566 }, "harness\|hendrycksTest-nutrition\|5": { "acc": 0.7189542483660131, "acc_stderr": 0.025738854797818737, "acc_norm": 0.7189542483660131, "acc_norm_stderr": 0.025738854797818737 }, "harness\|hendrycksTest-philosophy\|5": { "acc": 0.707395498392283, "acc_stderr": 0.02583989833487798, "acc_norm": 0.707395498392283, "acc_norm_stderr": 0.02583989833487798 }, "harness\|hendrycksTest-prehistory\|5": { "acc": 0.7129629629629629, "acc_stderr": 0.02517104191530968, "acc_norm": 0.7129629629629629, "acc_norm_stderr": 0.02517104191530968 }, "harness\|hendrycksTest-professional_accounting\|5": { "acc": 0.4929078014184397, "acc_stderr": 0.02982449855912901, "acc_norm": 0.4929078014184397, "acc_norm_stderr": 0.02982449855912901 }, "harness\|hendrycksTest-professional_law\|5": { "acc": 0.4511082138200782, "acc_stderr": 0.012709037347346233, "acc_norm": 0.4511082138200782, "acc_norm_stderr": 0.012709037347346233 }, "harness\|hendrycksTest-professional_medicine\|5": { "acc": 0.6323529411764706, "acc_stderr": 0.029289413409403192, "acc_norm": 0.6323529411764706, "acc_norm_stderr": 0.029289413409403192 }, "harness\|hendrycksTest-professional_psychology\|5": { "acc": 0.6584967320261438, "acc_stderr": 0.01918463932809249, "acc_norm": 0.6584967320261438, "acc_norm_stderr": 0.01918463932809249 }, "harness\|hendrycksTest-public_relations\|5": { "acc": 0.6454545454545455, "acc_stderr": 0.04582004841505417, "acc_norm": 0.6454545454545455, "acc_norm_stderr": 0.04582004841505417 }, "harness\|hendrycksTest-security_studies\|5": { "acc": 0.6979591836734694, "acc_stderr": 0.029393609319879804, "acc_norm": 0.6979591836734694, "acc_norm_stderr": 0.029393609319879804 }, "harness\|hendrycksTest-sociology\|5": { "acc": 0.8407960199004975, "acc_stderr": 0.02587064676616913, "acc_norm": 0.8407960199004975, "acc_norm_stderr": 0.02587064676616913 }, "harness\|hendrycksTest-us_foreign_policy\|5": { "acc": 0.84, "acc_stderr": 0.03684529491774709, "acc_norm": 0.84, "acc_norm_stderr": 0.03684529491774709 }, "harness\|hendrycksTest-virology\|5": { "acc": 0.536144578313253, "acc_stderr": 0.038823108508905954, "acc_norm": 0.536144578313253, "acc_norm_stderr": 0.038823108508905954 }, "harness\|hendrycksTest-world_religions\|5": { "acc": 0.8128654970760234, "acc_stderr": 0.029913127232368036, "acc_norm": 0.8128654970760234, "acc_norm_stderr": 0.029913127232368036 }, "harness\|truthfulqa:mc\|0": { "mc1": 0.36964504283965727, "mc1_stderr": 0.016898180706973888, "mc2": 0.5384391963865467, "mc2_stderr": 0.015414673673859326 }, "harness\|winogrande\|5": { "acc": 0.7726913970007893, "acc_stderr": 0.011778612167091087 }, "harness\|gsm8k\|5": { "acc": 0.4313874147081122, "acc_stderr": 0.013642195352511575 } } ``` ## Dataset Details ### Dataset Description <!-- Provide a longer summary of what this dataset is. --> - Curated by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] ### Dataset Sources [optional] <!-- Provide the basic links for the dataset. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the dataset is intended to be used. --> ### Direct Use <!-- This section describes suitable use cases for the dataset. --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. --> [More Information Needed] ## Dataset Structure <!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. --> [More Information Needed] ## Dataset Creation ### Curation Rationale <!-- Motivation for the creation of this dataset. --> [More Information Needed] ### Source Data <!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). --> #### Data Collection and Processing <!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. --> [More Information Needed] #### Who are the source data producers? <!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. --> [More Information Needed] ### Annotations [optional] <!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. --> #### Annotation process <!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. --> [More Information Needed] #### Who are the annotators? <!-- This section describes the people or systems who created the annotations. --> [More Information Needed] #### Personal and Sensitive Information <!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations. ## Citation [optional] <!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Dataset Card Authors [optional] [More Information Needed] ## Dataset Card Contact [More Information Needed]
Zuntan/Animagine_XL_3.0-Character	--- license: unknown --- # Animagine XL 3.0 Character [EasySdxlWebUi](https://github.com/Zuntan03/EasySdxlWebUi) による [Animagine XL 3.0](https://huggingface.co/cagliostrolab/animagine-xl-3.0) の [公式 Character ワイルドカード](https://huggingface.co/spaces/Linaqruf/animagine-xl/resolve/main/wildcard/character.txt) の立ち絵データセットです。データセットのダウンロードは [こちら（2880枚、497MB）](https://huggingface.co/datasets/Zuntan/Animagine_XL_3.0-Character/resolve/main/character.zip?download=true)。 [表情(278MB)](https://huggingface.co/datasets/Zuntan/Animagine_XL_3.0-Character/resolve/main/face.zip?download=true) と [画風(115MB)](https://yyy.wpx.jp/EasySdxlWebUi/style.zip) も用意しました。 ![face](./face_grid.webp) 画像の類似度や Tagger の結果比較で正常動作するワイルドカードリストを用意できないかな？と思って始めてみました。が、衣装違いなどの不正解画像でも作品名やキャラ名の影響を大きく受けるため、他のソースなしの正否分類は難しそうです。 - 各 webp 画像を [Stable Diffusion web UI](https://github.com/AUTOMATIC1111/stable-diffusion-webui) の `PNG内の情報を表示` にドラッグ＆ドロップすると生成情報を確認できます。 - プロンプトは `__animagine/character__, solo, full body, standing, no background, simple background, masterpiece, best quality <lora:lcm-animagine-3:1>` です。 - ネガティブプロンプト Animagine XL のデフォルトネガティブの先頭に NSFW 対策付与で `nsfw, rating: sensitive, lowres, bad anatomy, bad hands, text, error, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts, signature, watermark, username, blurry, artist name` です。 - アップスケール前の生成サイズは `832` x `1216` です。 - Seed は `1234567` です。 - 他のシードで正否が変わる可能性があります。 - 他は EasySdxlWebUi のデフォルト設定です。 [grid0](https://yyy.wpx.jp/m/202401/animagine_character/grid0.webp), [grid1](https://yyy.wpx.jp/m/202401/animagine_character/grid1.webp), [grid2](https://yyy.wpx.jp/m/202401/animagine_character/grid2.webp), [grid3](https://yyy.wpx.jp/m/202401/animagine_character/grid3.webp)
ramachaitanya22/mental_health_and_fitness_data	--- dataset_info: features: - name: Human dtype: string - name: Assistant dtype: string splits: - name: train num_bytes: 4021848.8 num_examples: 3552 - name: test num_bytes: 1005462.2 num_examples: 888 download_size: 2746185 dataset_size: 5027311.0 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---
mboth/luftVersorgen-50-undersampled	--- configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* - split: valid path: data/valid-* dataset_info: features: - name: Datatype dtype: string - name: Beschreibung dtype: string - name: Name dtype: string - name: Unit dtype: string - name: text dtype: string - name: Grundfunktion dtype: string - name: label dtype: class_label: names: '0': LuftBereitstellen '1': LuftVerteilen splits: - name: train num_bytes: 19757.430602572782 num_examples: 100 - name: test num_bytes: 290707 num_examples: 1477 - name: valid num_bytes: 290707 num_examples: 1477 download_size: 227539 dataset_size: 601171.4306025729 --- # Dataset Card for "luftVersorgen-50-undersampled" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
TrainingDataPro/roads-segmentation-dataset	--- license: cc-by-nc-nd-4.0 task_categories: - image-segmentation - image-to-image language: - en tags: - code --- # Roads Segmentation Dataset This dataset comprises a collection of images captured through DVRs (Digital Video Recorders) showcasing roads. Each image is accompanied by segmentation masks demarcating different entities (road surface, cars, road signs, marking and background) within the scene. The dataset can be utilized for enhancing computer vision algorithms involved in road surveillance, navigation, and intelligent transportation systemsand and in autonomous driving systems. ![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F12421376%2Fb0789a0ec8075d9c7abdb0aa9faced59%2FFrame%2012.png?generation=1694606364403023&alt=media) # Get the dataset ### This is just an example of the data Leave a request on [https://trainingdata.pro/data-market](https://trainingdata.pro/data-market/roads-segmentation?utm_source=huggingface&utm_medium=cpc&utm_campaign=roads-segmentation-dataset) to discuss your requirements, learn about the price and buy the dataset. # Dataset structure - images - contains of original images of roads - masks - includes segmentation masks created for the original images - annotations.xml - contains coordinates of the bounding boxes and detected text, created for the original photo # Data Format Each image from `images` folder is accompanied by an XML-annotation in the `annotations.xml` file indicating the coordinates of the polygons and labels . For each point, the x and y coordinates are provided. ### Сlasses: - road_surface: surface of the road, - marking: white and yellow marking on the road, - road_sign: road signs, - car: cars on the road, - background: side of the road and surronding objects # Example of XML file structure ![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F12421376%2Fa74a4214f4dd89a35527ef008abfc151%2Fcarbon.png?generation=1694608637609153&alt=media) # Roads Segmentation might be made in accordance with your requirements. ## [TrainingData](https://trainingdata.pro/data-market/roads-segmentation?utm_source=huggingface&utm_medium=cpc&utm_campaign=roads-segmentation-dataset) provides high-quality data annotation tailored to your needs More datasets in TrainingData's Kaggle account: https://www.kaggle.com/trainingdatapro/datasets TrainingData's GitHub: https://github.com/Trainingdata-datamarket/TrainingData_All_datasets
mesolitica/rumi-jawi	--- language: ms task_categories: - text2text-generation task_ids: [] tags: - conditional-text-generation --- # rumi-jawi Notebooks to gather the dataset at https://github.com/huseinzol05/malay-dataset/tree/master/normalization/rumi-jawi
open-llm-leaderboard/details_andysalerno__rainbowfish-v6	--- pretty_name: Evaluation run of andysalerno/rainbowfish-v6 dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [andysalerno/rainbowfish-v6](https://huggingface.co/andysalerno/rainbowfish-v6)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 63 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the aggregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_andysalerno__rainbowfish-v6\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-02-09T16:40:31.289715](https://huggingface.co/datasets/open-llm-leaderboard/details_andysalerno__rainbowfish-v6/blob/main/results_2024-02-09T16-40-31.289715.json)(note\ \ that their might be results for other tasks in the repos if successive evals didn't\ \ cover the same tasks. You find each in the results and the \"latest\" split for\ \ each eval):\n\n```python\n{\n \"all\": {\n \"acc\": 0.6251300156980985,\n\ \ \"acc_stderr\": 0.03253464808226719,\n \"acc_norm\": 0.6311200052519415,\n\ \ \"acc_norm_stderr\": 0.03319319250421297,\n \"mc1\": 0.3243574051407589,\n\ \ \"mc1_stderr\": 0.01638797677964794,\n \"mc2\": 0.4837489625680555,\n\ \ \"mc2_stderr\": 0.015088896132364547\n },\n \"harness\|arc:challenge\|25\"\ : {\n \"acc\": 0.5708191126279863,\n \"acc_stderr\": 0.014464085894870655,\n\ \ \"acc_norm\": 0.6194539249146758,\n \"acc_norm_stderr\": 0.014188277712349814\n\ \ },\n \"harness\|hellaswag\|10\": {\n \"acc\": 0.628460466042621,\n\ \ \"acc_stderr\": 0.004822286556305222,\n \"acc_norm\": 0.8251344353714399,\n\ \ \"acc_norm_stderr\": 0.003790757646575897\n },\n \"harness\|hendrycksTest-abstract_algebra\|5\"\ : {\n \"acc\": 0.27,\n \"acc_stderr\": 0.0446196043338474,\n \ \ \"acc_norm\": 0.27,\n \"acc_norm_stderr\": 0.0446196043338474\n },\n\ \ \"harness\|hendrycksTest-anatomy\|5\": {\n \"acc\": 0.6222222222222222,\n\ \ \"acc_stderr\": 0.04188307537595852,\n \"acc_norm\": 0.6222222222222222,\n\ \ \"acc_norm_stderr\": 0.04188307537595852\n },\n \"harness\|hendrycksTest-astronomy\|5\"\ : {\n \"acc\": 0.6710526315789473,\n \"acc_stderr\": 0.038234289699266046,\n\ \ \"acc_norm\": 0.6710526315789473,\n \"acc_norm_stderr\": 0.038234289699266046\n\ \ },\n \"harness\|hendrycksTest-business_ethics\|5\": {\n \"acc\": 0.59,\n\ \ \"acc_stderr\": 0.049431107042371025,\n \"acc_norm\": 0.59,\n \ \ \"acc_norm_stderr\": 0.049431107042371025\n },\n \"harness\|hendrycksTest-clinical_knowledge\|5\"\ : {\n \"acc\": 0.6867924528301886,\n \"acc_stderr\": 0.028544793319055326,\n\ \ \"acc_norm\": 0.6867924528301886,\n \"acc_norm_stderr\": 0.028544793319055326\n\ \ },\n \"harness\|hendrycksTest-college_biology\|5\": {\n \"acc\": 0.7291666666666666,\n\ \ \"acc_stderr\": 0.03716177437566017,\n \"acc_norm\": 0.7291666666666666,\n\ \ \"acc_norm_stderr\": 0.03716177437566017\n },\n \"harness\|hendrycksTest-college_chemistry\|5\"\ : {\n \"acc\": 0.48,\n \"acc_stderr\": 0.050211673156867795,\n \ \ \"acc_norm\": 0.48,\n \"acc_norm_stderr\": 0.050211673156867795\n \ \ },\n \"harness\|hendrycksTest-college_computer_science\|5\": {\n \"\ acc\": 0.51,\n \"acc_stderr\": 0.05024183937956912,\n \"acc_norm\"\ : 0.51,\n \"acc_norm_stderr\": 0.05024183937956912\n },\n \"harness\|hendrycksTest-college_mathematics\|5\"\ : {\n \"acc\": 0.35,\n \"acc_stderr\": 0.047937248544110196,\n \ \ \"acc_norm\": 0.35,\n \"acc_norm_stderr\": 0.047937248544110196\n \ \ },\n \"harness\|hendrycksTest-college_medicine\|5\": {\n \"acc\": 0.6184971098265896,\n\ \ \"acc_stderr\": 0.03703851193099521,\n \"acc_norm\": 0.6184971098265896,\n\ \ \"acc_norm_stderr\": 0.03703851193099521\n },\n \"harness\|hendrycksTest-college_physics\|5\"\ : {\n \"acc\": 0.3333333333333333,\n \"acc_stderr\": 0.04690650298201942,\n\ \ \"acc_norm\": 0.3333333333333333,\n \"acc_norm_stderr\": 0.04690650298201942\n\ \ },\n \"harness\|hendrycksTest-computer_security\|5\": {\n \"acc\":\ \ 0.77,\n \"acc_stderr\": 0.04229525846816505,\n \"acc_norm\": 0.77,\n\ \ \"acc_norm_stderr\": 0.04229525846816505\n },\n \"harness\|hendrycksTest-conceptual_physics\|5\"\ : {\n \"acc\": 0.5446808510638298,\n \"acc_stderr\": 0.03255525359340355,\n\ \ \"acc_norm\": 0.5446808510638298,\n \"acc_norm_stderr\": 0.03255525359340355\n\ \ },\n \"harness\|hendrycksTest-econometrics\|5\": {\n \"acc\": 0.49122807017543857,\n\ \ \"acc_stderr\": 0.047028804320496165,\n \"acc_norm\": 0.49122807017543857,\n\ \ \"acc_norm_stderr\": 0.047028804320496165\n },\n \"harness\|hendrycksTest-electrical_engineering\|5\"\ : {\n \"acc\": 0.5655172413793104,\n \"acc_stderr\": 0.04130740879555498,\n\ \ \"acc_norm\": 0.5655172413793104,\n \"acc_norm_stderr\": 0.04130740879555498\n\ \ },\n \"harness\|hendrycksTest-elementary_mathematics\|5\": {\n \"acc\"\ : 0.3888888888888889,\n \"acc_stderr\": 0.025107425481137282,\n \"\ acc_norm\": 0.3888888888888889,\n \"acc_norm_stderr\": 0.025107425481137282\n\ \ },\n \"harness\|hendrycksTest-formal_logic\|5\": {\n \"acc\": 0.3968253968253968,\n\ \ \"acc_stderr\": 0.043758884927270605,\n \"acc_norm\": 0.3968253968253968,\n\ \ \"acc_norm_stderr\": 0.043758884927270605\n },\n \"harness\|hendrycksTest-global_facts\|5\"\ : {\n \"acc\": 0.4,\n \"acc_stderr\": 0.04923659639173309,\n \ \ \"acc_norm\": 0.4,\n \"acc_norm_stderr\": 0.04923659639173309\n },\n\ \ \"harness\|hendrycksTest-high_school_biology\|5\": {\n \"acc\": 0.7451612903225806,\n\ \ \"acc_stderr\": 0.024790118459332208,\n \"acc_norm\": 0.7451612903225806,\n\ \ \"acc_norm_stderr\": 0.024790118459332208\n },\n \"harness\|hendrycksTest-high_school_chemistry\|5\"\ : {\n \"acc\": 0.5270935960591133,\n \"acc_stderr\": 0.03512819077876106,\n\ \ \"acc_norm\": 0.5270935960591133,\n \"acc_norm_stderr\": 0.03512819077876106\n\ \ },\n \"harness\|hendrycksTest-high_school_computer_science\|5\": {\n \ \ \"acc\": 0.67,\n \"acc_stderr\": 0.047258156262526066,\n \"acc_norm\"\ : 0.67,\n \"acc_norm_stderr\": 0.047258156262526066\n },\n \"harness\|hendrycksTest-high_school_european_history\|5\"\ : {\n \"acc\": 0.7636363636363637,\n \"acc_stderr\": 0.033175059300091826,\n\ \ \"acc_norm\": 0.7636363636363637,\n \"acc_norm_stderr\": 0.033175059300091826\n\ \ },\n \"harness\|hendrycksTest-high_school_geography\|5\": {\n \"acc\"\ : 0.7777777777777778,\n \"acc_stderr\": 0.02962022787479048,\n \"\ acc_norm\": 0.7777777777777778,\n \"acc_norm_stderr\": 0.02962022787479048\n\ \ },\n \"harness\|hendrycksTest-high_school_government_and_politics\|5\": {\n\ \ \"acc\": 0.8756476683937824,\n \"acc_stderr\": 0.02381447708659355,\n\ \ \"acc_norm\": 0.8756476683937824,\n \"acc_norm_stderr\": 0.02381447708659355\n\ \ },\n \"harness\|hendrycksTest-high_school_macroeconomics\|5\": {\n \ \ \"acc\": 0.617948717948718,\n \"acc_stderr\": 0.024635549163908237,\n \ \ \"acc_norm\": 0.617948717948718,\n \"acc_norm_stderr\": 0.024635549163908237\n\ \ },\n \"harness\|hendrycksTest-high_school_mathematics\|5\": {\n \"\ acc\": 0.337037037037037,\n \"acc_stderr\": 0.028820884666253255,\n \ \ \"acc_norm\": 0.337037037037037,\n \"acc_norm_stderr\": 0.028820884666253255\n\ \ },\n \"harness\|hendrycksTest-high_school_microeconomics\|5\": {\n \ \ \"acc\": 0.6680672268907563,\n \"acc_stderr\": 0.03058869701378364,\n \ \ \"acc_norm\": 0.6680672268907563,\n \"acc_norm_stderr\": 0.03058869701378364\n\ \ },\n \"harness\|hendrycksTest-high_school_physics\|5\": {\n \"acc\"\ : 0.33774834437086093,\n \"acc_stderr\": 0.03861557546255169,\n \"\ acc_norm\": 0.33774834437086093,\n \"acc_norm_stderr\": 0.03861557546255169\n\ \ },\n \"harness\|hendrycksTest-high_school_psychology\|5\": {\n \"acc\"\ : 0.8036697247706422,\n \"acc_stderr\": 0.01703071933915435,\n \"\ acc_norm\": 0.8036697247706422,\n \"acc_norm_stderr\": 0.01703071933915435\n\ \ },\n \"harness\|hendrycksTest-high_school_statistics\|5\": {\n \"acc\"\ : 0.49537037037037035,\n \"acc_stderr\": 0.03409825519163572,\n \"\ acc_norm\": 0.49537037037037035,\n \"acc_norm_stderr\": 0.03409825519163572\n\ \ },\n \"harness\|hendrycksTest-high_school_us_history\|5\": {\n \"acc\"\ : 0.7990196078431373,\n \"acc_stderr\": 0.028125972265654373,\n \"\ acc_norm\": 0.7990196078431373,\n \"acc_norm_stderr\": 0.028125972265654373\n\ \ },\n \"harness\|hendrycksTest-high_school_world_history\|5\": {\n \"\ acc\": 0.7805907172995781,\n \"acc_stderr\": 0.026939106581553945,\n \ \ \"acc_norm\": 0.7805907172995781,\n \"acc_norm_stderr\": 0.026939106581553945\n\ \ },\n \"harness\|hendrycksTest-human_aging\|5\": {\n \"acc\": 0.6547085201793722,\n\ \ \"acc_stderr\": 0.03191100192835794,\n \"acc_norm\": 0.6547085201793722,\n\ \ \"acc_norm_stderr\": 0.03191100192835794\n },\n \"harness\|hendrycksTest-human_sexuality\|5\"\ : {\n \"acc\": 0.7709923664122137,\n \"acc_stderr\": 0.036853466317118506,\n\ \ \"acc_norm\": 0.7709923664122137,\n \"acc_norm_stderr\": 0.036853466317118506\n\ \ },\n \"harness\|hendrycksTest-international_law\|5\": {\n \"acc\":\ \ 0.8016528925619835,\n \"acc_stderr\": 0.036401182719909456,\n \"\ acc_norm\": 0.8016528925619835,\n \"acc_norm_stderr\": 0.036401182719909456\n\ \ },\n \"harness\|hendrycksTest-jurisprudence\|5\": {\n \"acc\": 0.7592592592592593,\n\ \ \"acc_stderr\": 0.04133119440243838,\n \"acc_norm\": 0.7592592592592593,\n\ \ \"acc_norm_stderr\": 0.04133119440243838\n },\n \"harness\|hendrycksTest-logical_fallacies\|5\"\ : {\n \"acc\": 0.7730061349693251,\n \"acc_stderr\": 0.032910995786157686,\n\ \ \"acc_norm\": 0.7730061349693251,\n \"acc_norm_stderr\": 0.032910995786157686\n\ \ },\n \"harness\|hendrycksTest-machine_learning\|5\": {\n \"acc\": 0.44642857142857145,\n\ \ \"acc_stderr\": 0.04718471485219588,\n \"acc_norm\": 0.44642857142857145,\n\ \ \"acc_norm_stderr\": 0.04718471485219588\n },\n \"harness\|hendrycksTest-management\|5\"\ : {\n \"acc\": 0.7572815533980582,\n \"acc_stderr\": 0.04245022486384495,\n\ \ \"acc_norm\": 0.7572815533980582,\n \"acc_norm_stderr\": 0.04245022486384495\n\ \ },\n \"harness\|hendrycksTest-marketing\|5\": {\n \"acc\": 0.8589743589743589,\n\ \ \"acc_stderr\": 0.022801382534597524,\n \"acc_norm\": 0.8589743589743589,\n\ \ \"acc_norm_stderr\": 0.022801382534597524\n },\n \"harness\|hendrycksTest-medical_genetics\|5\"\ : {\n \"acc\": 0.7,\n \"acc_stderr\": 0.046056618647183814,\n \ \ \"acc_norm\": 0.7,\n \"acc_norm_stderr\": 0.046056618647183814\n \ \ },\n \"harness\|hendrycksTest-miscellaneous\|5\": {\n \"acc\": 0.8071519795657727,\n\ \ \"acc_stderr\": 0.014108533515757431,\n \"acc_norm\": 0.8071519795657727,\n\ \ \"acc_norm_stderr\": 0.014108533515757431\n },\n \"harness\|hendrycksTest-moral_disputes\|5\"\ : {\n \"acc\": 0.6965317919075145,\n \"acc_stderr\": 0.024752411960917212,\n\ \ \"acc_norm\": 0.6965317919075145,\n \"acc_norm_stderr\": 0.024752411960917212\n\ \ },\n \"harness\|hendrycksTest-moral_scenarios\|5\": {\n \"acc\": 0.29608938547486036,\n\ \ \"acc_stderr\": 0.01526867731760228,\n \"acc_norm\": 0.29608938547486036,\n\ \ \"acc_norm_stderr\": 0.01526867731760228\n },\n \"harness\|hendrycksTest-nutrition\|5\"\ : {\n \"acc\": 0.7549019607843137,\n \"acc_stderr\": 0.024630048979824775,\n\ \ \"acc_norm\": 0.7549019607843137,\n \"acc_norm_stderr\": 0.024630048979824775\n\ \ },\n \"harness\|hendrycksTest-philosophy\|5\": {\n \"acc\": 0.7266881028938906,\n\ \ \"acc_stderr\": 0.025311765975426122,\n \"acc_norm\": 0.7266881028938906,\n\ \ \"acc_norm_stderr\": 0.025311765975426122\n },\n \"harness\|hendrycksTest-prehistory\|5\"\ : {\n \"acc\": 0.7098765432098766,\n \"acc_stderr\": 0.025251173936495036,\n\ \ \"acc_norm\": 0.7098765432098766,\n \"acc_norm_stderr\": 0.025251173936495036\n\ \ },\n \"harness\|hendrycksTest-professional_accounting\|5\": {\n \"\ acc\": 0.5,\n \"acc_stderr\": 0.029827499313594685,\n \"acc_norm\"\ : 0.5,\n \"acc_norm_stderr\": 0.029827499313594685\n },\n \"harness\|hendrycksTest-professional_law\|5\"\ : {\n \"acc\": 0.4491525423728814,\n \"acc_stderr\": 0.01270403051885149,\n\ \ \"acc_norm\": 0.4491525423728814,\n \"acc_norm_stderr\": 0.01270403051885149\n\ \ },\n \"harness\|hendrycksTest-professional_medicine\|5\": {\n \"acc\"\ : 0.6654411764705882,\n \"acc_stderr\": 0.028661996202335303,\n \"\ acc_norm\": 0.6654411764705882,\n \"acc_norm_stderr\": 0.028661996202335303\n\ \ },\n \"harness\|hendrycksTest-professional_psychology\|5\": {\n \"\ acc\": 0.6552287581699346,\n \"acc_stderr\": 0.01922832201869664,\n \ \ \"acc_norm\": 0.6552287581699346,\n \"acc_norm_stderr\": 0.01922832201869664\n\ \ },\n \"harness\|hendrycksTest-public_relations\|5\": {\n \"acc\": 0.6454545454545455,\n\ \ \"acc_stderr\": 0.045820048415054174,\n \"acc_norm\": 0.6454545454545455,\n\ \ \"acc_norm_stderr\": 0.045820048415054174\n },\n \"harness\|hendrycksTest-security_studies\|5\"\ : {\n \"acc\": 0.7346938775510204,\n \"acc_stderr\": 0.028263889943784603,\n\ \ \"acc_norm\": 0.7346938775510204,\n \"acc_norm_stderr\": 0.028263889943784603\n\ \ },\n \"harness\|hendrycksTest-sociology\|5\": {\n \"acc\": 0.8059701492537313,\n\ \ \"acc_stderr\": 0.027962677604768914,\n \"acc_norm\": 0.8059701492537313,\n\ \ \"acc_norm_stderr\": 0.027962677604768914\n },\n \"harness\|hendrycksTest-us_foreign_policy\|5\"\ : {\n \"acc\": 0.85,\n \"acc_stderr\": 0.03588702812826371,\n \ \ \"acc_norm\": 0.85,\n \"acc_norm_stderr\": 0.03588702812826371\n \ \ },\n \"harness\|hendrycksTest-virology\|5\": {\n \"acc\": 0.5421686746987951,\n\ \ \"acc_stderr\": 0.0387862677100236,\n \"acc_norm\": 0.5421686746987951,\n\ \ \"acc_norm_stderr\": 0.0387862677100236\n },\n \"harness\|hendrycksTest-world_religions\|5\"\ : {\n \"acc\": 0.8128654970760234,\n \"acc_stderr\": 0.029913127232368036,\n\ \ \"acc_norm\": 0.8128654970760234,\n \"acc_norm_stderr\": 0.029913127232368036\n\ \ },\n \"harness\|truthfulqa:mc\|0\": {\n \"mc1\": 0.3243574051407589,\n\ \ \"mc1_stderr\": 0.01638797677964794,\n \"mc2\": 0.4837489625680555,\n\ \ \"mc2_stderr\": 0.015088896132364547\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.7790055248618785,\n \"acc_stderr\": 0.01166122363764341\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.36315390447308565,\n \ \ \"acc_stderr\": 0.013246614539839868\n }\n}\n```" repo_url: https://huggingface.co/andysalerno/rainbowfish-v6 leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2024_02_09T16_40_31.289715 path: - '/details_harness\|arc:challenge\|25_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2024-02-09T16-40-31.289715.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '/details_harness\|gsm8k\|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_02_09T16_40_31.289715 path: - '/details_harness\|hellaswag\|10_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-02-09T16-40-31.289715.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '/details_harness\|hendrycksTest-international_law\|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '/details_harness\|hendrycksTest-management\|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '/details_harness\|hendrycksTest-marketing\|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '/details_harness\|hendrycksTest-sociology\|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '/details_harness\|hendrycksTest-virology\|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_02_09T16_40_31.289715 path: - '/details_harness\|truthfulqa:mc\|0_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2024-02-09T16-40-31.289715.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '/details_harness\|winogrande\|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2024-02-09T16-40-31.289715.parquet' - config_name: results data_files: - split: 2024_02_09T16_40_31.289715 path: - results_2024-02-09T16-40-31.289715.parquet - split: latest path: - results_2024-02-09T16-40-31.289715.parquet --- # Dataset Card for Evaluation run of andysalerno/rainbowfish-v6 <!-- Provide a quick summary of the dataset. --> Dataset automatically created during the evaluation run of model [andysalerno/rainbowfish-v6](https://huggingface.co/andysalerno/rainbowfish-v6) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_andysalerno__rainbowfish-v6", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-02-09T16:40:31.289715](https://huggingface.co/datasets/open-llm-leaderboard/details_andysalerno__rainbowfish-v6/blob/main/results_2024-02-09T16-40-31.289715.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval): ```python { "all": { "acc": 0.6251300156980985, "acc_stderr": 0.03253464808226719, "acc_norm": 0.6311200052519415, "acc_norm_stderr": 0.03319319250421297, "mc1": 0.3243574051407589, "mc1_stderr": 0.01638797677964794, "mc2": 0.4837489625680555, "mc2_stderr": 0.015088896132364547 }, "harness\|arc:challenge\|25": { "acc": 0.5708191126279863, "acc_stderr": 0.014464085894870655, "acc_norm": 0.6194539249146758, "acc_norm_stderr": 0.014188277712349814 }, "harness\|hellaswag\|10": { "acc": 0.628460466042621, "acc_stderr": 0.004822286556305222, "acc_norm": 0.8251344353714399, "acc_norm_stderr": 0.003790757646575897 }, "harness\|hendrycksTest-abstract_algebra\|5": { "acc": 0.27, "acc_stderr": 0.0446196043338474, "acc_norm": 0.27, "acc_norm_stderr": 0.0446196043338474 }, "harness\|hendrycksTest-anatomy\|5": { "acc": 0.6222222222222222, "acc_stderr": 0.04188307537595852, "acc_norm": 0.6222222222222222, "acc_norm_stderr": 0.04188307537595852 }, "harness\|hendrycksTest-astronomy\|5": { "acc": 0.6710526315789473, "acc_stderr": 0.038234289699266046, "acc_norm": 0.6710526315789473, "acc_norm_stderr": 0.038234289699266046 }, "harness\|hendrycksTest-business_ethics\|5": { "acc": 0.59, "acc_stderr": 0.049431107042371025, "acc_norm": 0.59, "acc_norm_stderr": 0.049431107042371025 }, "harness\|hendrycksTest-clinical_knowledge\|5": { "acc": 0.6867924528301886, "acc_stderr": 0.028544793319055326, "acc_norm": 0.6867924528301886, "acc_norm_stderr": 0.028544793319055326 }, "harness\|hendrycksTest-college_biology\|5": { "acc": 0.7291666666666666, "acc_stderr": 0.03716177437566017, "acc_norm": 0.7291666666666666, "acc_norm_stderr": 0.03716177437566017 }, "harness\|hendrycksTest-college_chemistry\|5": { "acc": 0.48, "acc_stderr": 0.050211673156867795, "acc_norm": 0.48, "acc_norm_stderr": 0.050211673156867795 }, "harness\|hendrycksTest-college_computer_science\|5": { "acc": 0.51, "acc_stderr": 0.05024183937956912, "acc_norm": 0.51, "acc_norm_stderr": 0.05024183937956912 }, "harness\|hendrycksTest-college_mathematics\|5": { "acc": 0.35, "acc_stderr": 0.047937248544110196, "acc_norm": 0.35, "acc_norm_stderr": 0.047937248544110196 }, "harness\|hendrycksTest-college_medicine\|5": { "acc": 0.6184971098265896, "acc_stderr": 0.03703851193099521, "acc_norm": 0.6184971098265896, "acc_norm_stderr": 0.03703851193099521 }, "harness\|hendrycksTest-college_physics\|5": { "acc": 0.3333333333333333, "acc_stderr": 0.04690650298201942, "acc_norm": 0.3333333333333333, "acc_norm_stderr": 0.04690650298201942 }, "harness\|hendrycksTest-computer_security\|5": { "acc": 0.77, "acc_stderr": 0.04229525846816505, "acc_norm": 0.77, "acc_norm_stderr": 0.04229525846816505 }, "harness\|hendrycksTest-conceptual_physics\|5": { "acc": 0.5446808510638298, "acc_stderr": 0.03255525359340355, "acc_norm": 0.5446808510638298, "acc_norm_stderr": 0.03255525359340355 }, "harness\|hendrycksTest-econometrics\|5": { "acc": 0.49122807017543857, "acc_stderr": 0.047028804320496165, "acc_norm": 0.49122807017543857, "acc_norm_stderr": 0.047028804320496165 }, "harness\|hendrycksTest-electrical_engineering\|5": { "acc": 0.5655172413793104, "acc_stderr": 0.04130740879555498, "acc_norm": 0.5655172413793104, "acc_norm_stderr": 0.04130740879555498 }, "harness\|hendrycksTest-elementary_mathematics\|5": { "acc": 0.3888888888888889, "acc_stderr": 0.025107425481137282, "acc_norm": 0.3888888888888889, "acc_norm_stderr": 0.025107425481137282 }, "harness\|hendrycksTest-formal_logic\|5": { "acc": 0.3968253968253968, "acc_stderr": 0.043758884927270605, "acc_norm": 0.3968253968253968, "acc_norm_stderr": 0.043758884927270605 }, "harness\|hendrycksTest-global_facts\|5": { "acc": 0.4, "acc_stderr": 0.04923659639173309, "acc_norm": 0.4, "acc_norm_stderr": 0.04923659639173309 }, "harness\|hendrycksTest-high_school_biology\|5": { "acc": 0.7451612903225806, "acc_stderr": 0.024790118459332208, "acc_norm": 0.7451612903225806, "acc_norm_stderr": 0.024790118459332208 }, "harness\|hendrycksTest-high_school_chemistry\|5": { "acc": 0.5270935960591133, "acc_stderr": 0.03512819077876106, "acc_norm": 0.5270935960591133, "acc_norm_stderr": 0.03512819077876106 }, "harness\|hendrycksTest-high_school_computer_science\|5": { "acc": 0.67, "acc_stderr": 0.047258156262526066, "acc_norm": 0.67, "acc_norm_stderr": 0.047258156262526066 }, "harness\|hendrycksTest-high_school_european_history\|5": { "acc": 0.7636363636363637, "acc_stderr": 0.033175059300091826, "acc_norm": 0.7636363636363637, "acc_norm_stderr": 0.033175059300091826 }, "harness\|hendrycksTest-high_school_geography\|5": { "acc": 0.7777777777777778, "acc_stderr": 0.02962022787479048, "acc_norm": 0.7777777777777778, "acc_norm_stderr": 0.02962022787479048 }, "harness\|hendrycksTest-high_school_government_and_politics\|5": { "acc": 0.8756476683937824, "acc_stderr": 0.02381447708659355, "acc_norm": 0.8756476683937824, "acc_norm_stderr": 0.02381447708659355 }, "harness\|hendrycksTest-high_school_macroeconomics\|5": { "acc": 0.617948717948718, "acc_stderr": 0.024635549163908237, "acc_norm": 0.617948717948718, "acc_norm_stderr": 0.024635549163908237 }, "harness\|hendrycksTest-high_school_mathematics\|5": { "acc": 0.337037037037037, "acc_stderr": 0.028820884666253255, "acc_norm": 0.337037037037037, "acc_norm_stderr": 0.028820884666253255 }, "harness\|hendrycksTest-high_school_microeconomics\|5": { "acc": 0.6680672268907563, "acc_stderr": 0.03058869701378364, "acc_norm": 0.6680672268907563, "acc_norm_stderr": 0.03058869701378364 }, "harness\|hendrycksTest-high_school_physics\|5": { "acc": 0.33774834437086093, "acc_stderr": 0.03861557546255169, "acc_norm": 0.33774834437086093, "acc_norm_stderr": 0.03861557546255169 }, "harness\|hendrycksTest-high_school_psychology\|5": { "acc": 0.8036697247706422, "acc_stderr": 0.01703071933915435, "acc_norm": 0.8036697247706422, "acc_norm_stderr": 0.01703071933915435 }, "harness\|hendrycksTest-high_school_statistics\|5": { "acc": 0.49537037037037035, "acc_stderr": 0.03409825519163572, "acc_norm": 0.49537037037037035, "acc_norm_stderr": 0.03409825519163572 }, "harness\|hendrycksTest-high_school_us_history\|5": { "acc": 0.7990196078431373, "acc_stderr": 0.028125972265654373, "acc_norm": 0.7990196078431373, "acc_norm_stderr": 0.028125972265654373 }, "harness\|hendrycksTest-high_school_world_history\|5": { "acc": 0.7805907172995781, "acc_stderr": 0.026939106581553945, "acc_norm": 0.7805907172995781, "acc_norm_stderr": 0.026939106581553945 }, "harness\|hendrycksTest-human_aging\|5": { "acc": 0.6547085201793722, "acc_stderr": 0.03191100192835794, "acc_norm": 0.6547085201793722, "acc_norm_stderr": 0.03191100192835794 }, "harness\|hendrycksTest-human_sexuality\|5": { "acc": 0.7709923664122137, "acc_stderr": 0.036853466317118506, "acc_norm": 0.7709923664122137, "acc_norm_stderr": 0.036853466317118506 }, "harness\|hendrycksTest-international_law\|5": { "acc": 0.8016528925619835, "acc_stderr": 0.036401182719909456, "acc_norm": 0.8016528925619835, "acc_norm_stderr": 0.036401182719909456 }, "harness\|hendrycksTest-jurisprudence\|5": { "acc": 0.7592592592592593, "acc_stderr": 0.04133119440243838, "acc_norm": 0.7592592592592593, "acc_norm_stderr": 0.04133119440243838 }, "harness\|hendrycksTest-logical_fallacies\|5": { "acc": 0.7730061349693251, "acc_stderr": 0.032910995786157686, "acc_norm": 0.7730061349693251, "acc_norm_stderr": 0.032910995786157686 }, "harness\|hendrycksTest-machine_learning\|5": { "acc": 0.44642857142857145, "acc_stderr": 0.04718471485219588, "acc_norm": 0.44642857142857145, "acc_norm_stderr": 0.04718471485219588 }, "harness\|hendrycksTest-management\|5": { "acc": 0.7572815533980582, "acc_stderr": 0.04245022486384495, "acc_norm": 0.7572815533980582, "acc_norm_stderr": 0.04245022486384495 }, "harness\|hendrycksTest-marketing\|5": { "acc": 0.8589743589743589, "acc_stderr": 0.022801382534597524, "acc_norm": 0.8589743589743589, "acc_norm_stderr": 0.022801382534597524 }, "harness\|hendrycksTest-medical_genetics\|5": { "acc": 0.7, "acc_stderr": 0.046056618647183814, "acc_norm": 0.7, "acc_norm_stderr": 0.046056618647183814 }, "harness\|hendrycksTest-miscellaneous\|5": { "acc": 0.8071519795657727, "acc_stderr": 0.014108533515757431, "acc_norm": 0.8071519795657727, "acc_norm_stderr": 0.014108533515757431 }, "harness\|hendrycksTest-moral_disputes\|5": { "acc": 0.6965317919075145, "acc_stderr": 0.024752411960917212, "acc_norm": 0.6965317919075145, "acc_norm_stderr": 0.024752411960917212 }, "harness\|hendrycksTest-moral_scenarios\|5": { "acc": 0.29608938547486036, "acc_stderr": 0.01526867731760228, "acc_norm": 0.29608938547486036, "acc_norm_stderr": 0.01526867731760228 }, "harness\|hendrycksTest-nutrition\|5": { "acc": 0.7549019607843137, "acc_stderr": 0.024630048979824775, "acc_norm": 0.7549019607843137, "acc_norm_stderr": 0.024630048979824775 }, "harness\|hendrycksTest-philosophy\|5": { "acc": 0.7266881028938906, "acc_stderr": 0.025311765975426122, "acc_norm": 0.7266881028938906, "acc_norm_stderr": 0.025311765975426122 }, "harness\|hendrycksTest-prehistory\|5": { "acc": 0.7098765432098766, "acc_stderr": 0.025251173936495036, "acc_norm": 0.7098765432098766, "acc_norm_stderr": 0.025251173936495036 }, "harness\|hendrycksTest-professional_accounting\|5": { "acc": 0.5, "acc_stderr": 0.029827499313594685, "acc_norm": 0.5, "acc_norm_stderr": 0.029827499313594685 }, "harness\|hendrycksTest-professional_law\|5": { "acc": 0.4491525423728814, "acc_stderr": 0.01270403051885149, "acc_norm": 0.4491525423728814, "acc_norm_stderr": 0.01270403051885149 }, "harness\|hendrycksTest-professional_medicine\|5": { "acc": 0.6654411764705882, "acc_stderr": 0.028661996202335303, "acc_norm": 0.6654411764705882, "acc_norm_stderr": 0.028661996202335303 }, "harness\|hendrycksTest-professional_psychology\|5": { "acc": 0.6552287581699346, "acc_stderr": 0.01922832201869664, "acc_norm": 0.6552287581699346, "acc_norm_stderr": 0.01922832201869664 }, "harness\|hendrycksTest-public_relations\|5": { "acc": 0.6454545454545455, "acc_stderr": 0.045820048415054174, "acc_norm": 0.6454545454545455, "acc_norm_stderr": 0.045820048415054174 }, "harness\|hendrycksTest-security_studies\|5": { "acc": 0.7346938775510204, "acc_stderr": 0.028263889943784603, "acc_norm": 0.7346938775510204, "acc_norm_stderr": 0.028263889943784603 }, "harness\|hendrycksTest-sociology\|5": { "acc": 0.8059701492537313, "acc_stderr": 0.027962677604768914, "acc_norm": 0.8059701492537313, "acc_norm_stderr": 0.027962677604768914 }, "harness\|hendrycksTest-us_foreign_policy\|5": { "acc": 0.85, "acc_stderr": 0.03588702812826371, "acc_norm": 0.85, "acc_norm_stderr": 0.03588702812826371 }, "harness\|hendrycksTest-virology\|5": { "acc": 0.5421686746987951, "acc_stderr": 0.0387862677100236, "acc_norm": 0.5421686746987951, "acc_norm_stderr": 0.0387862677100236 }, "harness\|hendrycksTest-world_religions\|5": { "acc": 0.8128654970760234, "acc_stderr": 0.029913127232368036, "acc_norm": 0.8128654970760234, "acc_norm_stderr": 0.029913127232368036 }, "harness\|truthfulqa:mc\|0": { "mc1": 0.3243574051407589, "mc1_stderr": 0.01638797677964794, "mc2": 0.4837489625680555, "mc2_stderr": 0.015088896132364547 }, "harness\|winogrande\|5": { "acc": 0.7790055248618785, "acc_stderr": 0.01166122363764341 }, "harness\|gsm8k\|5": { "acc": 0.36315390447308565, "acc_stderr": 0.013246614539839868 } } ``` ## Dataset Details ### Dataset Description <!-- Provide a longer summary of what this dataset is. --> - Curated by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] ### Dataset Sources [optional] <!-- Provide the basic links for the dataset. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the dataset is intended to be used. --> ### Direct Use <!-- This section describes suitable use cases for the dataset. --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. --> [More Information Needed] ## Dataset Structure <!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. --> [More Information Needed] ## Dataset Creation ### Curation Rationale <!-- Motivation for the creation of this dataset. --> [More Information Needed] ### Source Data <!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). --> #### Data Collection and Processing <!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. --> [More Information Needed] #### Who are the source data producers? <!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. --> [More Information Needed] ### Annotations [optional] <!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. --> #### Annotation process <!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. --> [More Information Needed] #### Who are the annotators? <!-- This section describes the people or systems who created the annotations. --> [More Information Needed] #### Personal and Sensitive Information <!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users should be made aware of the risks, biases and limitations of the dataset. 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zolak/twitter_dataset_1713023754	--- dataset_info: features: - name: id dtype: string - name: tweet_content dtype: string - name: user_name dtype: string - name: user_id dtype: string - name: created_at dtype: string - name: url dtype: string - name: favourite_count dtype: float64 - name: scraped_at dtype: string - name: image_urls dtype: string splits: - name: train num_bytes: 58501863 num_examples: 150576 download_size: 29705449 dataset_size: 58501863 configs: - config_name: default data_files: - split: train path: data/train-* ---
cenkersisman/viki_soru_cevap	--- dataset_info: features: - name: answer dtype: string - name: question dtype: string - name: title dtype: string splits: - name: train num_bytes: 5319410 num_examples: 34983 download_size: 2529944 dataset_size: 5319410 --- # Dataset Card for "viki_soru_cevap" ## Hakkında Bu veri seti, Türkçe Vikipedi üzerindeki içeriklerden oluşturulan bir soru ve cevap veri setidir. Oluşturulan veri seti sentetik olarak üretilmiştir. Cevaplar, context metin üzerinden alınmış olsa da doğruluğu garanti edilmemektedir. Sorular da sentetik olarak üretilmiştir ## Başlıklara göre en fazla soru cevap içeren konular aşağıdadır: * Futbol rekabetleri listesi: 313 adet * Cengiz Han: 310 adet * Triple H: 196 adet * Lüleburgaz Muharebesi: 158 adet * Zümrüdüanka Yoldaşlığı: 155 adet * Shakespeare eserleri çevirileri listesi: 145 adet * Kırkpınar Yağlı Güreşleri: 142 adet * Sovyetler Birliği'nin askerî tarihi: 136 adet * I. Baybars: 135 adet * Dumbledore'un Ordusu: 126 adet * Nicolaus Copernicus: 119 adet * Ermenistan Sovyet Sosyalist Cumhuriyeti: 111 adet * Boshin Savaşı: 99 adet * Suvorov Harekâtı: 98 adet * Gökhan Türkmen: 96 adet * Wolfgang Amadeus Mozart: 95 adet * Joachim von Ribbentrop: 95 adet * Rumyantsev Harekâtı: 94 adet * Hermann Göring: 93 adet * Nâzım Hikmet: 90 adet * Said Nursî: 90 adet * Emîn: 88 adet * Antonio Gramsci: 87 adet * Gilles Deleuze: 86 adet * Madagaskar: 86 adet * Faşizm: 85 adet * Mac OS X Snow Leopard: 85 adet * Korsun-Şevçenkovski Taarruzu: 84 adet * Soğuk Savaş: 84 adet * Adolf Eichmann: 83 adet * Niccolò Paganini: 83 adet * II. Dünya Savaşı tankları: 81 adet * Pergamon: 81 adet * IV. Mihail: 80 adet * Bolşeviklere karşı sol ayaklanmalar: 77 adet * Osman Gazi: 77 adet * V. Leon: 76 adet * Ajda Pekkan: 75 adet * Mehdi Savaşı: 75 adet * Tsushima Muharebesi: 73 adet * Mehdî (Abbâsî halifesi): 72 adet * Franck Ribéry: 72 adet * I. Basileios: 69 adet * Antimon: 68 adet * Kolomb öncesi Amerika: 68 adet * Otto Skorzeny: 68 adet * Kâzım Koyuncu: 68 adet * İmamiye (Şiilik öğretisi): 66 adet * Oscar Niemeyer: 66 adet [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
open-llm-leaderboard/details_jeonsworld__CarbonVillain-en-10.7B-v1	--- pretty_name: Evaluation run of jeonsworld/CarbonVillain-en-10.7B-v1 dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [jeonsworld/CarbonVillain-en-10.7B-v1](https://huggingface.co/jeonsworld/CarbonVillain-en-10.7B-v1)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 63 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the aggregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_jeonsworld__CarbonVillain-en-10.7B-v1\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-12-29T20:15:36.884484](https://huggingface.co/datasets/open-llm-leaderboard/details_jeonsworld__CarbonVillain-en-10.7B-v1/blob/main/results_2023-12-29T20-15-36.884484.json)(note\ \ that their might be results for other tasks in the repos if successive evals didn't\ \ cover the same tasks. You find each in the results and the \"latest\" split for\ \ each eval):\n\n```python\n{\n \"all\": {\n \"acc\": 0.6677851094474622,\n\ \ \"acc_stderr\": 0.031647346301320364,\n \"acc_norm\": 0.6687652386109932,\n\ \ \"acc_norm_stderr\": 0.032290288467975714,\n \"mc1\": 0.572827417380661,\n\ \ \"mc1_stderr\": 0.017316834410963926,\n \"mc2\": 0.7197651592692368,\n\ \ \"mc2_stderr\": 0.014984462732010536\n },\n \"harness\|arc:challenge\|25\"\ : {\n \"acc\": 0.6843003412969283,\n \"acc_stderr\": 0.013582571095815291,\n\ \ \"acc_norm\": 0.712457337883959,\n \"acc_norm_stderr\": 0.013226719056266125\n\ \ },\n \"harness\|hellaswag\|10\": {\n \"acc\": 0.7148974307906791,\n\ \ \"acc_stderr\": 0.00450540617660685,\n \"acc_norm\": 0.8845847440748855,\n\ \ \"acc_norm_stderr\": 0.0031886940284536315\n },\n \"harness\|hendrycksTest-abstract_algebra\|5\"\ : {\n \"acc\": 0.42,\n \"acc_stderr\": 0.049604496374885836,\n \ \ \"acc_norm\": 0.42,\n \"acc_norm_stderr\": 0.049604496374885836\n \ \ },\n \"harness\|hendrycksTest-anatomy\|5\": {\n \"acc\": 0.6148148148148148,\n\ \ \"acc_stderr\": 0.04203921040156279,\n \"acc_norm\": 0.6148148148148148,\n\ \ \"acc_norm_stderr\": 0.04203921040156279\n },\n \"harness\|hendrycksTest-astronomy\|5\"\ : {\n \"acc\": 0.756578947368421,\n \"acc_stderr\": 0.034923496688842384,\n\ \ \"acc_norm\": 0.756578947368421,\n \"acc_norm_stderr\": 0.034923496688842384\n\ \ },\n \"harness\|hendrycksTest-business_ethics\|5\": {\n \"acc\": 0.73,\n\ \ \"acc_stderr\": 0.04461960433384741,\n \"acc_norm\": 0.73,\n \ \ \"acc_norm_stderr\": 0.04461960433384741\n },\n \"harness\|hendrycksTest-clinical_knowledge\|5\"\ : {\n \"acc\": 0.6830188679245283,\n \"acc_stderr\": 0.02863723563980089,\n\ \ \"acc_norm\": 0.6830188679245283,\n \"acc_norm_stderr\": 0.02863723563980089\n\ \ },\n \"harness\|hendrycksTest-college_biology\|5\": {\n \"acc\": 0.7847222222222222,\n\ \ \"acc_stderr\": 0.03437079344106135,\n \"acc_norm\": 0.7847222222222222,\n\ \ \"acc_norm_stderr\": 0.03437079344106135\n },\n \"harness\|hendrycksTest-college_chemistry\|5\"\ : {\n \"acc\": 0.47,\n \"acc_stderr\": 0.050161355804659205,\n \ \ \"acc_norm\": 0.47,\n \"acc_norm_stderr\": 0.050161355804659205\n \ \ },\n \"harness\|hendrycksTest-college_computer_science\|5\": {\n \"\ acc\": 0.51,\n \"acc_stderr\": 0.05024183937956913,\n \"acc_norm\"\ : 0.51,\n \"acc_norm_stderr\": 0.05024183937956913\n },\n \"harness\|hendrycksTest-college_mathematics\|5\"\ : {\n \"acc\": 0.35,\n \"acc_stderr\": 0.0479372485441102,\n \ \ \"acc_norm\": 0.35,\n \"acc_norm_stderr\": 0.0479372485441102\n },\n\ \ \"harness\|hendrycksTest-college_medicine\|5\": {\n \"acc\": 0.6705202312138728,\n\ \ \"acc_stderr\": 0.03583901754736412,\n \"acc_norm\": 0.6705202312138728,\n\ \ \"acc_norm_stderr\": 0.03583901754736412\n },\n \"harness\|hendrycksTest-college_physics\|5\"\ : {\n \"acc\": 0.39215686274509803,\n \"acc_stderr\": 0.04858083574266346,\n\ \ \"acc_norm\": 0.39215686274509803,\n \"acc_norm_stderr\": 0.04858083574266346\n\ \ },\n \"harness\|hendrycksTest-computer_security\|5\": {\n \"acc\":\ \ 0.75,\n \"acc_stderr\": 0.04351941398892446,\n \"acc_norm\": 0.75,\n\ \ \"acc_norm_stderr\": 0.04351941398892446\n },\n \"harness\|hendrycksTest-conceptual_physics\|5\"\ : {\n \"acc\": 0.6212765957446809,\n \"acc_stderr\": 0.03170995606040655,\n\ \ \"acc_norm\": 0.6212765957446809,\n \"acc_norm_stderr\": 0.03170995606040655\n\ \ },\n \"harness\|hendrycksTest-econometrics\|5\": {\n \"acc\": 0.4824561403508772,\n\ \ \"acc_stderr\": 0.04700708033551038,\n \"acc_norm\": 0.4824561403508772,\n\ \ \"acc_norm_stderr\": 0.04700708033551038\n },\n \"harness\|hendrycksTest-electrical_engineering\|5\"\ : {\n \"acc\": 0.6344827586206897,\n \"acc_stderr\": 0.040131241954243856,\n\ \ \"acc_norm\": 0.6344827586206897,\n \"acc_norm_stderr\": 0.040131241954243856\n\ \ },\n \"harness\|hendrycksTest-elementary_mathematics\|5\": {\n \"acc\"\ : 0.5026455026455027,\n \"acc_stderr\": 0.02575094967813038,\n \"\ acc_norm\": 0.5026455026455027,\n \"acc_norm_stderr\": 0.02575094967813038\n\ \ },\n \"harness\|hendrycksTest-formal_logic\|5\": {\n \"acc\": 0.42857142857142855,\n\ \ \"acc_stderr\": 0.0442626668137991,\n \"acc_norm\": 0.42857142857142855,\n\ \ \"acc_norm_stderr\": 0.0442626668137991\n },\n \"harness\|hendrycksTest-global_facts\|5\"\ : {\n \"acc\": 0.36,\n \"acc_stderr\": 0.048241815132442176,\n \ \ \"acc_norm\": 0.36,\n \"acc_norm_stderr\": 0.048241815132442176\n \ \ },\n \"harness\|hendrycksTest-high_school_biology\|5\": {\n \"acc\"\ : 0.8258064516129032,\n \"acc_stderr\": 0.021576248184514587,\n \"\ acc_norm\": 0.8258064516129032,\n \"acc_norm_stderr\": 0.021576248184514587\n\ \ },\n \"harness\|hendrycksTest-high_school_chemistry\|5\": {\n \"acc\"\ : 0.5073891625615764,\n \"acc_stderr\": 0.035176035403610105,\n \"\ acc_norm\": 0.5073891625615764,\n \"acc_norm_stderr\": 0.035176035403610105\n\ \ },\n \"harness\|hendrycksTest-high_school_computer_science\|5\": {\n \ \ \"acc\": 0.72,\n \"acc_stderr\": 0.04512608598542128,\n \"acc_norm\"\ : 0.72,\n \"acc_norm_stderr\": 0.04512608598542128\n },\n \"harness\|hendrycksTest-high_school_european_history\|5\"\ : {\n \"acc\": 0.8181818181818182,\n \"acc_stderr\": 0.03011768892950357,\n\ \ \"acc_norm\": 0.8181818181818182,\n \"acc_norm_stderr\": 0.03011768892950357\n\ \ },\n \"harness\|hendrycksTest-high_school_geography\|5\": {\n \"acc\"\ : 0.8636363636363636,\n \"acc_stderr\": 0.024450155973189835,\n \"\ acc_norm\": 0.8636363636363636,\n \"acc_norm_stderr\": 0.024450155973189835\n\ \ },\n \"harness\|hendrycksTest-high_school_government_and_politics\|5\": {\n\ \ \"acc\": 0.8963730569948186,\n \"acc_stderr\": 0.021995311963644244,\n\ \ \"acc_norm\": 0.8963730569948186,\n \"acc_norm_stderr\": 0.021995311963644244\n\ \ },\n \"harness\|hendrycksTest-high_school_macroeconomics\|5\": {\n \ \ \"acc\": 0.6666666666666666,\n \"acc_stderr\": 0.023901157979402534,\n\ \ \"acc_norm\": 0.6666666666666666,\n \"acc_norm_stderr\": 0.023901157979402534\n\ \ },\n \"harness\|hendrycksTest-high_school_mathematics\|5\": {\n \"\ acc\": 0.36666666666666664,\n \"acc_stderr\": 0.029381620726465073,\n \ \ \"acc_norm\": 0.36666666666666664,\n \"acc_norm_stderr\": 0.029381620726465073\n\ \ },\n \"harness\|hendrycksTest-high_school_microeconomics\|5\": {\n \ \ \"acc\": 0.7142857142857143,\n \"acc_stderr\": 0.029344572500634332,\n\ \ \"acc_norm\": 0.7142857142857143,\n \"acc_norm_stderr\": 0.029344572500634332\n\ \ },\n \"harness\|hendrycksTest-high_school_physics\|5\": {\n \"acc\"\ : 0.37748344370860926,\n \"acc_stderr\": 0.03958027231121569,\n \"\ acc_norm\": 0.37748344370860926,\n \"acc_norm_stderr\": 0.03958027231121569\n\ \ },\n \"harness\|hendrycksTest-high_school_psychology\|5\": {\n \"acc\"\ : 0.8458715596330275,\n \"acc_stderr\": 0.015480826865374308,\n \"\ acc_norm\": 0.8458715596330275,\n \"acc_norm_stderr\": 0.015480826865374308\n\ \ },\n \"harness\|hendrycksTest-high_school_statistics\|5\": {\n \"acc\"\ : 0.5740740740740741,\n \"acc_stderr\": 0.03372343271653062,\n \"\ acc_norm\": 0.5740740740740741,\n \"acc_norm_stderr\": 0.03372343271653062\n\ \ },\n \"harness\|hendrycksTest-high_school_us_history\|5\": {\n \"acc\"\ : 0.8578431372549019,\n \"acc_stderr\": 0.02450980392156862,\n \"\ acc_norm\": 0.8578431372549019,\n \"acc_norm_stderr\": 0.02450980392156862\n\ \ },\n \"harness\|hendrycksTest-high_school_world_history\|5\": {\n \"\ acc\": 0.8481012658227848,\n \"acc_stderr\": 0.023363878096632446,\n \ \ \"acc_norm\": 0.8481012658227848,\n \"acc_norm_stderr\": 0.023363878096632446\n\ \ },\n \"harness\|hendrycksTest-human_aging\|5\": {\n \"acc\": 0.672645739910314,\n\ \ \"acc_stderr\": 0.03149384670994131,\n \"acc_norm\": 0.672645739910314,\n\ \ \"acc_norm_stderr\": 0.03149384670994131\n },\n \"harness\|hendrycksTest-human_sexuality\|5\"\ : {\n \"acc\": 0.7557251908396947,\n \"acc_stderr\": 0.03768335959728743,\n\ \ \"acc_norm\": 0.7557251908396947,\n \"acc_norm_stderr\": 0.03768335959728743\n\ \ },\n \"harness\|hendrycksTest-international_law\|5\": {\n \"acc\":\ \ 0.7768595041322314,\n \"acc_stderr\": 0.03800754475228733,\n \"\ acc_norm\": 0.7768595041322314,\n \"acc_norm_stderr\": 0.03800754475228733\n\ \ },\n \"harness\|hendrycksTest-jurisprudence\|5\": {\n \"acc\": 0.8055555555555556,\n\ \ \"acc_stderr\": 0.038260763248848646,\n \"acc_norm\": 0.8055555555555556,\n\ \ \"acc_norm_stderr\": 0.038260763248848646\n },\n \"harness\|hendrycksTest-logical_fallacies\|5\"\ : {\n \"acc\": 0.7607361963190185,\n \"acc_stderr\": 0.033519538795212696,\n\ \ \"acc_norm\": 0.7607361963190185,\n \"acc_norm_stderr\": 0.033519538795212696\n\ \ },\n \"harness\|hendrycksTest-machine_learning\|5\": {\n \"acc\": 0.4642857142857143,\n\ \ \"acc_stderr\": 0.04733667890053756,\n \"acc_norm\": 0.4642857142857143,\n\ \ \"acc_norm_stderr\": 0.04733667890053756\n },\n \"harness\|hendrycksTest-management\|5\"\ : {\n \"acc\": 0.8543689320388349,\n \"acc_stderr\": 0.03492606476623791,\n\ \ \"acc_norm\": 0.8543689320388349,\n \"acc_norm_stderr\": 0.03492606476623791\n\ \ },\n \"harness\|hendrycksTest-marketing\|5\": {\n \"acc\": 0.8589743589743589,\n\ \ \"acc_stderr\": 0.02280138253459753,\n \"acc_norm\": 0.8589743589743589,\n\ \ \"acc_norm_stderr\": 0.02280138253459753\n },\n \"harness\|hendrycksTest-medical_genetics\|5\"\ : {\n \"acc\": 0.7,\n \"acc_stderr\": 0.046056618647183814,\n \ \ \"acc_norm\": 0.7,\n \"acc_norm_stderr\": 0.046056618647183814\n \ \ },\n \"harness\|hendrycksTest-miscellaneous\|5\": {\n \"acc\": 0.8071519795657727,\n\ \ \"acc_stderr\": 0.014108533515757431,\n \"acc_norm\": 0.8071519795657727,\n\ \ \"acc_norm_stderr\": 0.014108533515757431\n },\n \"harness\|hendrycksTest-moral_disputes\|5\"\ : {\n \"acc\": 0.7543352601156069,\n \"acc_stderr\": 0.023176298203992005,\n\ \ \"acc_norm\": 0.7543352601156069,\n \"acc_norm_stderr\": 0.023176298203992005\n\ \ },\n \"harness\|hendrycksTest-moral_scenarios\|5\": {\n \"acc\": 0.39888268156424583,\n\ \ \"acc_stderr\": 0.016376966142610073,\n \"acc_norm\": 0.39888268156424583,\n\ \ \"acc_norm_stderr\": 0.016376966142610073\n },\n \"harness\|hendrycksTest-nutrition\|5\"\ : {\n \"acc\": 0.7581699346405228,\n \"acc_stderr\": 0.024518195641879334,\n\ \ \"acc_norm\": 0.7581699346405228,\n \"acc_norm_stderr\": 0.024518195641879334\n\ \ },\n \"harness\|hendrycksTest-philosophy\|5\": {\n \"acc\": 0.7266881028938906,\n\ \ \"acc_stderr\": 0.025311765975426122,\n \"acc_norm\": 0.7266881028938906,\n\ \ \"acc_norm_stderr\": 0.025311765975426122\n },\n \"harness\|hendrycksTest-prehistory\|5\"\ : {\n \"acc\": 0.7808641975308642,\n \"acc_stderr\": 0.02301670564026219,\n\ \ \"acc_norm\": 0.7808641975308642,\n \"acc_norm_stderr\": 0.02301670564026219\n\ \ },\n \"harness\|hendrycksTest-professional_accounting\|5\": {\n \"\ acc\": 0.49645390070921985,\n \"acc_stderr\": 0.02982674915328092,\n \ \ \"acc_norm\": 0.49645390070921985,\n \"acc_norm_stderr\": 0.02982674915328092\n\ \ },\n \"harness\|hendrycksTest-professional_law\|5\": {\n \"acc\": 0.4934810951760104,\n\ \ \"acc_stderr\": 0.012769150688867503,\n \"acc_norm\": 0.4934810951760104,\n\ \ \"acc_norm_stderr\": 0.012769150688867503\n },\n \"harness\|hendrycksTest-professional_medicine\|5\"\ : {\n \"acc\": 0.7389705882352942,\n \"acc_stderr\": 0.026679252270103128,\n\ \ \"acc_norm\": 0.7389705882352942,\n \"acc_norm_stderr\": 0.026679252270103128\n\ \ },\n \"harness\|hendrycksTest-professional_psychology\|5\": {\n \"\ acc\": 0.6797385620915033,\n \"acc_stderr\": 0.018875682938069446,\n \ \ \"acc_norm\": 0.6797385620915033,\n \"acc_norm_stderr\": 0.018875682938069446\n\ \ },\n \"harness\|hendrycksTest-public_relations\|5\": {\n \"acc\": 0.6909090909090909,\n\ \ \"acc_stderr\": 0.044262946482000985,\n \"acc_norm\": 0.6909090909090909,\n\ \ \"acc_norm_stderr\": 0.044262946482000985\n },\n \"harness\|hendrycksTest-security_studies\|5\"\ : {\n \"acc\": 0.7387755102040816,\n \"acc_stderr\": 0.02812342933514278,\n\ \ \"acc_norm\": 0.7387755102040816,\n \"acc_norm_stderr\": 0.02812342933514278\n\ \ },\n \"harness\|hendrycksTest-sociology\|5\": {\n \"acc\": 0.8407960199004975,\n\ \ \"acc_stderr\": 0.02587064676616913,\n \"acc_norm\": 0.8407960199004975,\n\ \ \"acc_norm_stderr\": 0.02587064676616913\n },\n \"harness\|hendrycksTest-us_foreign_policy\|5\"\ : {\n \"acc\": 0.9,\n \"acc_stderr\": 0.030151134457776334,\n \ \ \"acc_norm\": 0.9,\n \"acc_norm_stderr\": 0.030151134457776334\n \ \ },\n \"harness\|hendrycksTest-virology\|5\": {\n \"acc\": 0.5843373493975904,\n\ \ \"acc_stderr\": 0.03836722176598053,\n \"acc_norm\": 0.5843373493975904,\n\ \ \"acc_norm_stderr\": 0.03836722176598053\n },\n \"harness\|hendrycksTest-world_religions\|5\"\ : {\n \"acc\": 0.7777777777777778,\n \"acc_stderr\": 0.03188578017686398,\n\ \ \"acc_norm\": 0.7777777777777778,\n \"acc_norm_stderr\": 0.03188578017686398\n\ \ },\n \"harness\|truthfulqa:mc\|0\": {\n \"mc1\": 0.572827417380661,\n\ \ \"mc1_stderr\": 0.017316834410963926,\n \"mc2\": 0.7197651592692368,\n\ \ \"mc2_stderr\": 0.014984462732010536\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.8326756116811366,\n \"acc_stderr\": 0.010490608806828075\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.6429112964366944,\n \ \ \"acc_stderr\": 0.013197931775445206\n }\n}\n```" repo_url: https://huggingface.co/jeonsworld/CarbonVillain-en-10.7B-v1 leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2023_12_29T20_15_36.884484 path: - '/details_harness\|arc:challenge\|25_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-12-29T20-15-36.884484.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '/details_harness\|gsm8k\|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_12_29T20_15_36.884484 path: - '/details_harness\|hellaswag\|10_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-12-29T20-15-36.884484.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '/details_harness\|hendrycksTest-management\|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '/details_harness\|hendrycksTest-virology\|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_12_29T20_15_36.884484 path: - '/details_harness\|truthfulqa:mc\|0_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-12-29T20-15-36.884484.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '/details_harness\|winogrande\|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2023-12-29T20-15-36.884484.parquet' - config_name: results data_files: - split: 2023_12_29T20_15_36.884484 path: - results_2023-12-29T20-15-36.884484.parquet - split: latest path: - results_2023-12-29T20-15-36.884484.parquet --- # Dataset Card for Evaluation run of jeonsworld/CarbonVillain-en-10.7B-v1 <!-- Provide a quick summary of the dataset. --> Dataset automatically created during the evaluation run of model [jeonsworld/CarbonVillain-en-10.7B-v1](https://huggingface.co/jeonsworld/CarbonVillain-en-10.7B-v1) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_jeonsworld__CarbonVillain-en-10.7B-v1", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-12-29T20:15:36.884484](https://huggingface.co/datasets/open-llm-leaderboard/details_jeonsworld__CarbonVillain-en-10.7B-v1/blob/main/results_2023-12-29T20-15-36.884484.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval): ```python { "all": { "acc": 0.6677851094474622, "acc_stderr": 0.031647346301320364, "acc_norm": 0.6687652386109932, "acc_norm_stderr": 0.032290288467975714, "mc1": 0.572827417380661, "mc1_stderr": 0.017316834410963926, "mc2": 0.7197651592692368, "mc2_stderr": 0.014984462732010536 }, "harness\|arc:challenge\|25": { "acc": 0.6843003412969283, "acc_stderr": 0.013582571095815291, "acc_norm": 0.712457337883959, "acc_norm_stderr": 0.013226719056266125 }, "harness\|hellaswag\|10": { "acc": 0.7148974307906791, "acc_stderr": 0.00450540617660685, "acc_norm": 0.8845847440748855, "acc_norm_stderr": 0.0031886940284536315 }, "harness\|hendrycksTest-abstract_algebra\|5": { "acc": 0.42, "acc_stderr": 0.049604496374885836, "acc_norm": 0.42, "acc_norm_stderr": 0.049604496374885836 }, "harness\|hendrycksTest-anatomy\|5": { "acc": 0.6148148148148148, "acc_stderr": 0.04203921040156279, "acc_norm": 0.6148148148148148, "acc_norm_stderr": 0.04203921040156279 }, "harness\|hendrycksTest-astronomy\|5": { "acc": 0.756578947368421, "acc_stderr": 0.034923496688842384, "acc_norm": 0.756578947368421, "acc_norm_stderr": 0.034923496688842384 }, "harness\|hendrycksTest-business_ethics\|5": { "acc": 0.73, "acc_stderr": 0.04461960433384741, "acc_norm": 0.73, "acc_norm_stderr": 0.04461960433384741 }, "harness\|hendrycksTest-clinical_knowledge\|5": { "acc": 0.6830188679245283, "acc_stderr": 0.02863723563980089, "acc_norm": 0.6830188679245283, "acc_norm_stderr": 0.02863723563980089 }, "harness\|hendrycksTest-college_biology\|5": { "acc": 0.7847222222222222, "acc_stderr": 0.03437079344106135, "acc_norm": 0.7847222222222222, "acc_norm_stderr": 0.03437079344106135 }, "harness\|hendrycksTest-college_chemistry\|5": { "acc": 0.47, "acc_stderr": 0.050161355804659205, "acc_norm": 0.47, "acc_norm_stderr": 0.050161355804659205 }, "harness\|hendrycksTest-college_computer_science\|5": { "acc": 0.51, "acc_stderr": 0.05024183937956913, "acc_norm": 0.51, "acc_norm_stderr": 0.05024183937956913 }, "harness\|hendrycksTest-college_mathematics\|5": { "acc": 0.35, "acc_stderr": 0.0479372485441102, "acc_norm": 0.35, "acc_norm_stderr": 0.0479372485441102 }, "harness\|hendrycksTest-college_medicine\|5": { "acc": 0.6705202312138728, "acc_stderr": 0.03583901754736412, "acc_norm": 0.6705202312138728, "acc_norm_stderr": 0.03583901754736412 }, "harness\|hendrycksTest-college_physics\|5": { "acc": 0.39215686274509803, "acc_stderr": 0.04858083574266346, "acc_norm": 0.39215686274509803, "acc_norm_stderr": 0.04858083574266346 }, "harness\|hendrycksTest-computer_security\|5": { "acc": 0.75, "acc_stderr": 0.04351941398892446, "acc_norm": 0.75, "acc_norm_stderr": 0.04351941398892446 }, "harness\|hendrycksTest-conceptual_physics\|5": { "acc": 0.6212765957446809, "acc_stderr": 0.03170995606040655, "acc_norm": 0.6212765957446809, "acc_norm_stderr": 0.03170995606040655 }, "harness\|hendrycksTest-econometrics\|5": { "acc": 0.4824561403508772, "acc_stderr": 0.04700708033551038, "acc_norm": 0.4824561403508772, "acc_norm_stderr": 0.04700708033551038 }, "harness\|hendrycksTest-electrical_engineering\|5": { "acc": 0.6344827586206897, "acc_stderr": 0.040131241954243856, "acc_norm": 0.6344827586206897, "acc_norm_stderr": 0.040131241954243856 }, "harness\|hendrycksTest-elementary_mathematics\|5": { "acc": 0.5026455026455027, "acc_stderr": 0.02575094967813038, "acc_norm": 0.5026455026455027, "acc_norm_stderr": 0.02575094967813038 }, "harness\|hendrycksTest-formal_logic\|5": { "acc": 0.42857142857142855, "acc_stderr": 0.0442626668137991, "acc_norm": 0.42857142857142855, "acc_norm_stderr": 0.0442626668137991 }, "harness\|hendrycksTest-global_facts\|5": { "acc": 0.36, "acc_stderr": 0.048241815132442176, "acc_norm": 0.36, "acc_norm_stderr": 0.048241815132442176 }, "harness\|hendrycksTest-high_school_biology\|5": { "acc": 0.8258064516129032, "acc_stderr": 0.021576248184514587, "acc_norm": 0.8258064516129032, "acc_norm_stderr": 0.021576248184514587 }, "harness\|hendrycksTest-high_school_chemistry\|5": { "acc": 0.5073891625615764, "acc_stderr": 0.035176035403610105, "acc_norm": 0.5073891625615764, "acc_norm_stderr": 0.035176035403610105 }, "harness\|hendrycksTest-high_school_computer_science\|5": { "acc": 0.72, "acc_stderr": 0.04512608598542128, "acc_norm": 0.72, "acc_norm_stderr": 0.04512608598542128 }, "harness\|hendrycksTest-high_school_european_history\|5": { "acc": 0.8181818181818182, "acc_stderr": 0.03011768892950357, "acc_norm": 0.8181818181818182, "acc_norm_stderr": 0.03011768892950357 }, "harness\|hendrycksTest-high_school_geography\|5": { "acc": 0.8636363636363636, "acc_stderr": 0.024450155973189835, "acc_norm": 0.8636363636363636, "acc_norm_stderr": 0.024450155973189835 }, "harness\|hendrycksTest-high_school_government_and_politics\|5": { "acc": 0.8963730569948186, "acc_stderr": 0.021995311963644244, "acc_norm": 0.8963730569948186, "acc_norm_stderr": 0.021995311963644244 }, "harness\|hendrycksTest-high_school_macroeconomics\|5": { "acc": 0.6666666666666666, "acc_stderr": 0.023901157979402534, "acc_norm": 0.6666666666666666, "acc_norm_stderr": 0.023901157979402534 }, "harness\|hendrycksTest-high_school_mathematics\|5": { "acc": 0.36666666666666664, "acc_stderr": 0.029381620726465073, "acc_norm": 0.36666666666666664, "acc_norm_stderr": 0.029381620726465073 }, "harness\|hendrycksTest-high_school_microeconomics\|5": { "acc": 0.7142857142857143, "acc_stderr": 0.029344572500634332, "acc_norm": 0.7142857142857143, "acc_norm_stderr": 0.029344572500634332 }, "harness\|hendrycksTest-high_school_physics\|5": { "acc": 0.37748344370860926, "acc_stderr": 0.03958027231121569, "acc_norm": 0.37748344370860926, "acc_norm_stderr": 0.03958027231121569 }, "harness\|hendrycksTest-high_school_psychology\|5": { "acc": 0.8458715596330275, "acc_stderr": 0.015480826865374308, "acc_norm": 0.8458715596330275, "acc_norm_stderr": 0.015480826865374308 }, "harness\|hendrycksTest-high_school_statistics\|5": { "acc": 0.5740740740740741, "acc_stderr": 0.03372343271653062, "acc_norm": 0.5740740740740741, "acc_norm_stderr": 0.03372343271653062 }, "harness\|hendrycksTest-high_school_us_history\|5": { "acc": 0.8578431372549019, "acc_stderr": 0.02450980392156862, "acc_norm": 0.8578431372549019, "acc_norm_stderr": 0.02450980392156862 }, "harness\|hendrycksTest-high_school_world_history\|5": { "acc": 0.8481012658227848, "acc_stderr": 0.023363878096632446, "acc_norm": 0.8481012658227848, "acc_norm_stderr": 0.023363878096632446 }, "harness\|hendrycksTest-human_aging\|5": { "acc": 0.672645739910314, "acc_stderr": 0.03149384670994131, "acc_norm": 0.672645739910314, "acc_norm_stderr": 0.03149384670994131 }, "harness\|hendrycksTest-human_sexuality\|5": { "acc": 0.7557251908396947, "acc_stderr": 0.03768335959728743, "acc_norm": 0.7557251908396947, "acc_norm_stderr": 0.03768335959728743 }, "harness\|hendrycksTest-international_law\|5": { "acc": 0.7768595041322314, "acc_stderr": 0.03800754475228733, "acc_norm": 0.7768595041322314, "acc_norm_stderr": 0.03800754475228733 }, "harness\|hendrycksTest-jurisprudence\|5": { "acc": 0.8055555555555556, "acc_stderr": 0.038260763248848646, "acc_norm": 0.8055555555555556, "acc_norm_stderr": 0.038260763248848646 }, "harness\|hendrycksTest-logical_fallacies\|5": { "acc": 0.7607361963190185, "acc_stderr": 0.033519538795212696, "acc_norm": 0.7607361963190185, "acc_norm_stderr": 0.033519538795212696 }, "harness\|hendrycksTest-machine_learning\|5": { "acc": 0.4642857142857143, "acc_stderr": 0.04733667890053756, "acc_norm": 0.4642857142857143, "acc_norm_stderr": 0.04733667890053756 }, "harness\|hendrycksTest-management\|5": { "acc": 0.8543689320388349, "acc_stderr": 0.03492606476623791, "acc_norm": 0.8543689320388349, "acc_norm_stderr": 0.03492606476623791 }, "harness\|hendrycksTest-marketing\|5": { "acc": 0.8589743589743589, "acc_stderr": 0.02280138253459753, "acc_norm": 0.8589743589743589, "acc_norm_stderr": 0.02280138253459753 }, "harness\|hendrycksTest-medical_genetics\|5": { "acc": 0.7, "acc_stderr": 0.046056618647183814, "acc_norm": 0.7, "acc_norm_stderr": 0.046056618647183814 }, "harness\|hendrycksTest-miscellaneous\|5": { "acc": 0.8071519795657727, "acc_stderr": 0.014108533515757431, "acc_norm": 0.8071519795657727, "acc_norm_stderr": 0.014108533515757431 }, "harness\|hendrycksTest-moral_disputes\|5": { "acc": 0.7543352601156069, "acc_stderr": 0.023176298203992005, "acc_norm": 0.7543352601156069, "acc_norm_stderr": 0.023176298203992005 }, "harness\|hendrycksTest-moral_scenarios\|5": { "acc": 0.39888268156424583, "acc_stderr": 0.016376966142610073, "acc_norm": 0.39888268156424583, "acc_norm_stderr": 0.016376966142610073 }, "harness\|hendrycksTest-nutrition\|5": { "acc": 0.7581699346405228, "acc_stderr": 0.024518195641879334, "acc_norm": 0.7581699346405228, "acc_norm_stderr": 0.024518195641879334 }, "harness\|hendrycksTest-philosophy\|5": { "acc": 0.7266881028938906, "acc_stderr": 0.025311765975426122, "acc_norm": 0.7266881028938906, "acc_norm_stderr": 0.025311765975426122 }, "harness\|hendrycksTest-prehistory\|5": { "acc": 0.7808641975308642, "acc_stderr": 0.02301670564026219, "acc_norm": 0.7808641975308642, "acc_norm_stderr": 0.02301670564026219 }, "harness\|hendrycksTest-professional_accounting\|5": { "acc": 0.49645390070921985, "acc_stderr": 0.02982674915328092, "acc_norm": 0.49645390070921985, "acc_norm_stderr": 0.02982674915328092 }, "harness\|hendrycksTest-professional_law\|5": { "acc": 0.4934810951760104, "acc_stderr": 0.012769150688867503, "acc_norm": 0.4934810951760104, "acc_norm_stderr": 0.012769150688867503 }, "harness\|hendrycksTest-professional_medicine\|5": { "acc": 0.7389705882352942, "acc_stderr": 0.026679252270103128, "acc_norm": 0.7389705882352942, "acc_norm_stderr": 0.026679252270103128 }, "harness\|hendrycksTest-professional_psychology\|5": { "acc": 0.6797385620915033, "acc_stderr": 0.018875682938069446, "acc_norm": 0.6797385620915033, "acc_norm_stderr": 0.018875682938069446 }, "harness\|hendrycksTest-public_relations\|5": { "acc": 0.6909090909090909, "acc_stderr": 0.044262946482000985, "acc_norm": 0.6909090909090909, "acc_norm_stderr": 0.044262946482000985 }, "harness\|hendrycksTest-security_studies\|5": { "acc": 0.7387755102040816, "acc_stderr": 0.02812342933514278, "acc_norm": 0.7387755102040816, "acc_norm_stderr": 0.02812342933514278 }, "harness\|hendrycksTest-sociology\|5": { "acc": 0.8407960199004975, "acc_stderr": 0.02587064676616913, "acc_norm": 0.8407960199004975, "acc_norm_stderr": 0.02587064676616913 }, "harness\|hendrycksTest-us_foreign_policy\|5": { "acc": 0.9, "acc_stderr": 0.030151134457776334, "acc_norm": 0.9, "acc_norm_stderr": 0.030151134457776334 }, "harness\|hendrycksTest-virology\|5": { "acc": 0.5843373493975904, "acc_stderr": 0.03836722176598053, "acc_norm": 0.5843373493975904, "acc_norm_stderr": 0.03836722176598053 }, "harness\|hendrycksTest-world_religions\|5": { "acc": 0.7777777777777778, "acc_stderr": 0.03188578017686398, "acc_norm": 0.7777777777777778, "acc_norm_stderr": 0.03188578017686398 }, "harness\|truthfulqa:mc\|0": { "mc1": 0.572827417380661, "mc1_stderr": 0.017316834410963926, "mc2": 0.7197651592692368, "mc2_stderr": 0.014984462732010536 }, "harness\|winogrande\|5": { "acc": 0.8326756116811366, "acc_stderr": 0.010490608806828075 }, "harness\|gsm8k\|5": { "acc": 0.6429112964366944, "acc_stderr": 0.013197931775445206 } } ``` ## Dataset Details ### Dataset Description <!-- Provide a longer summary of what this dataset is. --> - Curated by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] ### Dataset Sources [optional] <!-- Provide the basic links for the dataset. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More 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karawalla/aqcommands	--- license: bigcode-openrail-m ---
autoevaluate/autoeval-eval-lener_br-lener_br-b36dee-1776161641	--- type: predictions tags: - autotrain - evaluation datasets: - lener_br eval_info: task: entity_extraction model: Luciano/bertimbau-large-lener_br metrics: [] dataset_name: lener_br dataset_config: lener_br dataset_split: validation col_mapping: tokens: tokens tags: ner_tags --- # Dataset Card for AutoTrain Evaluator This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset: * Task: Token Classification * Model: Luciano/bertimbau-large-lener_br * Dataset: lener_br * Config: lener_br * Split: validation To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator). ## Contributions Thanks to [@Luciano](https://huggingface.co/Luciano) for evaluating this model.
CyberHarem/python_girlsfrontline	--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of python/パイソン/蟒蛇 (Girls' Frontline) This is the dataset of python/パイソン/蟒蛇 (Girls' Frontline), containing 43 images and their tags. The core tags of this character are `black_hair, breasts, green_eyes, long_hair, mole, mole_under_eye, earrings, large_breasts, multicolored_hair`, which are pruned in this dataset. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). ## List of Packages \| Name \| Images \| Size \| Download \| Type \| Description \| \|:-----------------\|---------:\|:----------\|:-----------------------------------------------------------------------------------------------------------------------\|:-----------\|:---------------------------------------------------------------------\| \| raw \| 43 \| 54.58 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/python_girlsfrontline/resolve/main/dataset-raw.zip) \| Waifuc-Raw \| Raw data with meta information (min edge aligned to 1400 if larger). \| \| 800 \| 43 \| 31.16 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/python_girlsfrontline/resolve/main/dataset-800.zip) \| IMG+TXT \| dataset with the shorter side not exceeding 800 pixels. \| \| stage3-p480-800 \| 115 \| 66.92 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/python_girlsfrontline/resolve/main/dataset-stage3-p480-800.zip) \| IMG+TXT \| 3-stage cropped dataset with the area not less than 480x480 pixels. \| \| 1200 \| 43 \| 48.14 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/python_girlsfrontline/resolve/main/dataset-1200.zip) \| IMG+TXT \| dataset with the shorter side not exceeding 1200 pixels. \| \| stage3-p480-1200 \| 115 \| 94.53 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/python_girlsfrontline/resolve/main/dataset-stage3-p480-1200.zip) \| IMG+TXT \| 3-stage cropped dataset with the area not less than 480x480 pixels. \| ### Load Raw Dataset with Waifuc We provide raw dataset (including tagged images) for [waifuc](https://deepghs.github.io/waifuc/main/tutorials/installation/index.html) loading. If you need this, just run the following code ```python import os import zipfile from huggingface_hub import hf_hub_download from waifuc.source import LocalSource # download raw archive file zip_file = hf_hub_download( repo_id='CyberHarem/python_girlsfrontline', repo_type='dataset', filename='dataset-raw.zip', ) # extract files to your directory dataset_dir = 'dataset_dir' os.makedirs(dataset_dir, exist_ok=True) with zipfile.ZipFile(zip_file, 'r') as zf: zf.extractall(dataset_dir) # load the dataset with waifuc source = LocalSource(dataset_dir) for item in source: print(item.image, item.meta['filename'], item.meta['tags']) ``` ## List of Clusters List of tag clustering result, maybe some outfits can be mined here. ### Raw Text Version \| # \| Samples \| Img-1 \| Img-2 \| Img-3 \| Img-4 \| Img-5 \| Tags \| \|----:\|----------:\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\| \| 0 \| 31 \| ![](samples/0/clu0-sample0.png) \| ![](samples/0/clu0-sample1.png) \| ![](samples/0/clu0-sample2.png) \| ![](samples/0/clu0-sample3.png) \| ![](samples/0/clu0-sample4.png) \| 1girl, looking_at_viewer, smile, solo, jewelry, navel, black_gloves, simple_background, white_background, jacket, makeup, black_shirt, handgun, blush, holding_weapon, revolver, thighhighs, white_necktie \| ### Table Version \| # \| Samples \| Img-1 \| Img-2 \| Img-3 \| Img-4 \| Img-5 \| 1girl \| looking_at_viewer \| smile \| solo \| jewelry \| navel \| black_gloves \| simple_background \| white_background \| jacket \| makeup \| black_shirt \| handgun \| blush \| holding_weapon \| revolver \| thighhighs \| white_necktie \| \|----:\|----------:\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------\|:--------------------\|:--------\|:-------\|:----------\|:--------\|:---------------\|:--------------------\|:-------------------\|:---------\|:---------\|:--------------\|:----------\|:--------\|:-----------------\|:-----------\|:-------------\|:----------------\| \| 0 \| 31 \| ![](samples/0/clu0-sample0.png) \| ![](samples/0/clu0-sample1.png) \| ![](samples/0/clu0-sample2.png) \| ![](samples/0/clu0-sample3.png) \| ![](samples/0/clu0-sample4.png) \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \|
Torsaan/NTNU_RED	--- license: mit --- Some data collected on NTNU Campus Gjøvik with a Leica p40 then prossesed (normals, downsampled etc) and augmented Phillip Nerdum - Tor Henrik Øverby Olsen (2024) Some data collected from http://redwood-data.org/3dscan/ then prossesed (normals, downsampled etc) and augmented. @article{Choi2016, author = {Sungjoon Choi and Qian-Yi Zhou and Stephen Miller and Vladlen Koltun}, title = {A Large Dataset of Object Scans}, journal = {arXiv:1602.02481}, year = {2016}, } Contains filelist , shapelist , and test , train val split. Used for fine tuning a model trained on the modelnet40 dataset. Any part of the dataset can be used for any purpose with proper attribution. If you use any of the data, please cite - Phillip Nerdrum - Tor Henrik Øverby Olsen NTNU 2024 - Bachelor thesis: TBD @article{Choi2016, author = {Sungjoon Choi and Qian-Yi Zhou and Stephen Miller and Vladlen Koltun}, title = {A Large Dataset of Object Scans}, journal = {arXiv:1602.02481}, year = {2016}, }
CyberHarem/senzaki_ema_idolmastercinderellagirls	--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of senzaki_ema/仙崎恵磨 (THE iDOLM@STER: Cinderella Girls) This is the dataset of senzaki_ema/仙崎恵磨 (THE iDOLM@STER: Cinderella Girls), containing 59 images and their tags. The core tags of this character are `short_hair, blonde_hair, earrings, very_short_hair, red_eyes, breasts, ear_piercing`, which are pruned in this dataset. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). ## List of Packages \| Name \| Images \| Size \| Download \| Type \| Description \| \|:-----------------\|---------:\|:----------\|:---------------------------------------------------------------------------------------------------------------------------------------\|:-----------\|:---------------------------------------------------------------------\| \| raw \| 59 \| 54.11 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/senzaki_ema_idolmastercinderellagirls/resolve/main/dataset-raw.zip) \| Waifuc-Raw \| Raw data with meta information (min edge aligned to 1400 if larger). \| \| 800 \| 59 \| 37.69 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/senzaki_ema_idolmastercinderellagirls/resolve/main/dataset-800.zip) \| IMG+TXT \| dataset with the shorter side not exceeding 800 pixels. \| \| stage3-p480-800 \| 127 \| 71.11 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/senzaki_ema_idolmastercinderellagirls/resolve/main/dataset-stage3-p480-800.zip) \| IMG+TXT \| 3-stage cropped dataset with the area not less than 480x480 pixels. \| \| 1200 \| 59 \| 49.23 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/senzaki_ema_idolmastercinderellagirls/resolve/main/dataset-1200.zip) \| IMG+TXT \| dataset with the shorter side not exceeding 1200 pixels. \| \| stage3-p480-1200 \| 127 \| 89.15 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/senzaki_ema_idolmastercinderellagirls/resolve/main/dataset-stage3-p480-1200.zip) \| IMG+TXT \| 3-stage cropped dataset with the area not less than 480x480 pixels. \| ### Load Raw Dataset with Waifuc We provide raw dataset (including tagged images) for [waifuc](https://deepghs.github.io/waifuc/main/tutorials/installation/index.html) loading. If you need this, just run the following code ```python import os import zipfile from huggingface_hub import hf_hub_download from waifuc.source import LocalSource # download raw archive file zip_file = hf_hub_download( repo_id='CyberHarem/senzaki_ema_idolmastercinderellagirls', repo_type='dataset', filename='dataset-raw.zip', ) # extract files to your directory dataset_dir = 'dataset_dir' os.makedirs(dataset_dir, exist_ok=True) with zipfile.ZipFile(zip_file, 'r') as zf: zf.extractall(dataset_dir) # load the dataset with waifuc source = LocalSource(dataset_dir) for item in source: print(item.image, item.meta['filename'], item.meta['tags']) ``` ## List of Clusters List of tag clustering result, maybe some outfits can be mined here. ### Raw Text Version \| # \| Samples \| Img-1 \| Img-2 \| Img-3 \| Img-4 \| Img-5 \| Tags \| \|----:\|----------:\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:-----------------------------------------------------------------------------------------------------\| \| 0 \| 14 \| ![](samples/0/clu0-sample0.png) \| ![](samples/0/clu0-sample1.png) \| ![](samples/0/clu0-sample2.png) \| ![](samples/0/clu0-sample3.png) \| ![](samples/0/clu0-sample4.png) \| 1girl, jewelry, solo, card_(medium), character_name, sun_symbol, looking_at_viewer, open_mouth, grin \| ### Table Version \| # \| Samples \| Img-1 \| Img-2 \| Img-3 \| Img-4 \| Img-5 \| 1girl \| jewelry \| solo \| card_(medium) \| character_name \| sun_symbol \| looking_at_viewer \| open_mouth \| grin \| \|----:\|----------:\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------\|:----------\|:-------\|:----------------\|:-----------------\|:-------------\|:--------------------\|:-------------\|:-------\| \| 0 \| 14 \| ![](samples/0/clu0-sample0.png) \| ![](samples/0/clu0-sample1.png) \| ![](samples/0/clu0-sample2.png) \| ![](samples/0/clu0-sample3.png) \| ![](samples/0/clu0-sample4.png) \| X \| X \| X \| X \| X \| X \| X \| X \| X \|
Admin0805/Mytokens	--- license: other license_name: citibankdemobusiness license_link: https://citibankdemobusiness.dev ---
skrishna/SeqSense_gen_8	--- dataset_info: features: - name: input dtype: string - name: answer dtype: int64 splits: - name: train num_bytes: 25416 num_examples: 300 download_size: 8511 dataset_size: 25416 --- # Dataset Card for "SeqSense_gen_8" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
Nexdata/Cantonese_Dialect_Speech_Data_by_Mobile_Phone	--- YAML tags: - copy-paste the tags obtained with the tagging app: https://github.com/huggingface/datasets-tagging --- # Dataset Card for Nexdata/Cantonese_Dialect_Speech_Data_by_Mobile_Phone ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/54?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary It collects 4,888 speakers from Guangdong Province and is recorded in quiet indoor environment. The recorded content covers 500,000 commonly used spoken sentences, including high-frequency words in weico and daily used expressions. The average number of repetitions is 1.5 and the average sentence length is 12.5 words. Recording devices are mainstream Android phones and iPhones. For more details, please refer to the link: https://www.nexdata.ai/datasets/54?source=Huggingface ### Supported Tasks and Leaderboards automatic-speech-recognition, audio-speaker-identification: The dataset can be used to train a model for Automatic Speech Recognition (ASR). ### Languages Cantonese ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions
salma-remyx/ffmperative_refined_5.5k	--- dataset_info: features: - name: prompt dtype: string - name: response dtype: string splits: - name: train num_bytes: 3277970 num_examples: 5565 download_size: 1001170 dataset_size: 3277970 --- # Dataset Card for "ffmperative_refined_5.5k" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
codys12/PRM800K	--- license: mit ---
elvincth/durecdial-knowledge	--- license: mit ---
open-llm-leaderboard/details_Isotonic__Hermes-2-Pro-Mixtral-4x7B	--- pretty_name: Evaluation run of Isotonic/Hermes-2-Pro-Mixtral-4x7B dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [Isotonic/Hermes-2-Pro-Mixtral-4x7B](https://huggingface.co/Isotonic/Hermes-2-Pro-Mixtral-4x7B)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 63 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the aggregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_Isotonic__Hermes-2-Pro-Mixtral-4x7B\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-03-22T02:39:47.890512](https://huggingface.co/datasets/open-llm-leaderboard/details_Isotonic__Hermes-2-Pro-Mixtral-4x7B/blob/main/results_2024-03-22T02-39-47.890512.json)(note\ \ that their might be results for other tasks in the repos if successive evals didn't\ \ cover the same tasks. You find each in the results and the \"latest\" split for\ \ each eval):\n\n```python\n{\n \"all\": {\n \"acc\": 0.6247175996493741,\n\ \ \"acc_stderr\": 0.03257864192508729,\n \"acc_norm\": 0.6264034162110771,\n\ \ \"acc_norm_stderr\": 0.033228987439788436,\n \"mc1\": 0.4186046511627907,\n\ \ \"mc1_stderr\": 0.017270015284476848,\n \"mc2\": 0.5902365843525761,\n\ \ \"mc2_stderr\": 0.015835546003395855\n },\n \"harness\|arc:challenge\|25\"\ : {\n \"acc\": 0.6126279863481229,\n \"acc_stderr\": 0.014235872487909869,\n\ \ \"acc_norm\": 0.6424914675767918,\n \"acc_norm_stderr\": 0.014005494275916573\n\ \ },\n \"harness\|hellaswag\|10\": {\n \"acc\": 0.6480780720971918,\n\ \ \"acc_stderr\": 0.004765937515197187,\n \"acc_norm\": 0.8270264887472615,\n\ \ \"acc_norm_stderr\": 0.003774513882615956\n },\n \"harness\|hendrycksTest-abstract_algebra\|5\"\ : {\n \"acc\": 0.29,\n \"acc_stderr\": 0.04560480215720684,\n \ \ \"acc_norm\": 0.29,\n \"acc_norm_stderr\": 0.04560480215720684\n \ \ },\n \"harness\|hendrycksTest-anatomy\|5\": {\n \"acc\": 0.5777777777777777,\n\ \ \"acc_stderr\": 0.04266763404099582,\n \"acc_norm\": 0.5777777777777777,\n\ \ \"acc_norm_stderr\": 0.04266763404099582\n },\n \"harness\|hendrycksTest-astronomy\|5\"\ : {\n \"acc\": 0.6973684210526315,\n \"acc_stderr\": 0.03738520676119668,\n\ \ \"acc_norm\": 0.6973684210526315,\n \"acc_norm_stderr\": 0.03738520676119668\n\ \ },\n \"harness\|hendrycksTest-business_ethics\|5\": {\n \"acc\": 0.58,\n\ \ \"acc_stderr\": 0.049604496374885836,\n \"acc_norm\": 0.58,\n \ \ \"acc_norm_stderr\": 0.049604496374885836\n },\n \"harness\|hendrycksTest-clinical_knowledge\|5\"\ : {\n \"acc\": 0.6830188679245283,\n \"acc_stderr\": 0.02863723563980089,\n\ \ \"acc_norm\": 0.6830188679245283,\n \"acc_norm_stderr\": 0.02863723563980089\n\ \ },\n \"harness\|hendrycksTest-college_biology\|5\": {\n \"acc\": 0.7222222222222222,\n\ \ \"acc_stderr\": 0.037455547914624555,\n \"acc_norm\": 0.7222222222222222,\n\ \ \"acc_norm_stderr\": 0.037455547914624555\n },\n \"harness\|hendrycksTest-college_chemistry\|5\"\ : {\n \"acc\": 0.44,\n \"acc_stderr\": 0.04988876515698589,\n \ \ \"acc_norm\": 0.44,\n \"acc_norm_stderr\": 0.04988876515698589\n \ \ },\n \"harness\|hendrycksTest-college_computer_science\|5\": {\n \"acc\"\ : 0.52,\n \"acc_stderr\": 0.050211673156867795,\n \"acc_norm\": 0.52,\n\ \ \"acc_norm_stderr\": 0.050211673156867795\n },\n \"harness\|hendrycksTest-college_mathematics\|5\"\ : {\n \"acc\": 0.3,\n \"acc_stderr\": 0.046056618647183814,\n \ \ \"acc_norm\": 0.3,\n \"acc_norm_stderr\": 0.046056618647183814\n \ \ },\n \"harness\|hendrycksTest-college_medicine\|5\": {\n \"acc\": 0.5953757225433526,\n\ \ \"acc_stderr\": 0.03742461193887248,\n \"acc_norm\": 0.5953757225433526,\n\ \ \"acc_norm_stderr\": 0.03742461193887248\n },\n \"harness\|hendrycksTest-college_physics\|5\"\ : {\n \"acc\": 0.37254901960784315,\n \"acc_stderr\": 0.04810840148082636,\n\ \ \"acc_norm\": 0.37254901960784315,\n \"acc_norm_stderr\": 0.04810840148082636\n\ \ },\n \"harness\|hendrycksTest-computer_security\|5\": {\n \"acc\":\ \ 0.78,\n \"acc_stderr\": 0.04163331998932261,\n \"acc_norm\": 0.78,\n\ \ \"acc_norm_stderr\": 0.04163331998932261\n },\n \"harness\|hendrycksTest-conceptual_physics\|5\"\ : {\n \"acc\": 0.5617021276595745,\n \"acc_stderr\": 0.03243618636108102,\n\ \ \"acc_norm\": 0.5617021276595745,\n \"acc_norm_stderr\": 0.03243618636108102\n\ \ },\n \"harness\|hendrycksTest-econometrics\|5\": {\n \"acc\": 0.4824561403508772,\n\ \ \"acc_stderr\": 0.04700708033551038,\n \"acc_norm\": 0.4824561403508772,\n\ \ \"acc_norm_stderr\": 0.04700708033551038\n },\n \"harness\|hendrycksTest-electrical_engineering\|5\"\ : {\n \"acc\": 0.5103448275862069,\n \"acc_stderr\": 0.04165774775728763,\n\ \ \"acc_norm\": 0.5103448275862069,\n \"acc_norm_stderr\": 0.04165774775728763\n\ \ },\n \"harness\|hendrycksTest-elementary_mathematics\|5\": {\n \"acc\"\ : 0.42063492063492064,\n \"acc_stderr\": 0.025424835086923996,\n \"\ acc_norm\": 0.42063492063492064,\n \"acc_norm_stderr\": 0.025424835086923996\n\ \ },\n \"harness\|hendrycksTest-formal_logic\|5\": {\n \"acc\": 0.42063492063492064,\n\ \ \"acc_stderr\": 0.04415438226743744,\n \"acc_norm\": 0.42063492063492064,\n\ \ \"acc_norm_stderr\": 0.04415438226743744\n },\n \"harness\|hendrycksTest-global_facts\|5\"\ : {\n \"acc\": 0.32,\n \"acc_stderr\": 0.04688261722621504,\n \ \ \"acc_norm\": 0.32,\n \"acc_norm_stderr\": 0.04688261722621504\n \ \ },\n \"harness\|hendrycksTest-high_school_biology\|5\": {\n \"acc\": 0.7354838709677419,\n\ \ \"acc_stderr\": 0.02509189237885928,\n \"acc_norm\": 0.7354838709677419,\n\ \ \"acc_norm_stderr\": 0.02509189237885928\n },\n \"harness\|hendrycksTest-high_school_chemistry\|5\"\ : {\n \"acc\": 0.4482758620689655,\n \"acc_stderr\": 0.03499113137676744,\n\ \ \"acc_norm\": 0.4482758620689655,\n \"acc_norm_stderr\": 0.03499113137676744\n\ \ },\n \"harness\|hendrycksTest-high_school_computer_science\|5\": {\n \ \ \"acc\": 0.67,\n \"acc_stderr\": 0.04725815626252607,\n \"acc_norm\"\ : 0.67,\n \"acc_norm_stderr\": 0.04725815626252607\n },\n \"harness\|hendrycksTest-high_school_european_history\|5\"\ : {\n \"acc\": 0.7515151515151515,\n \"acc_stderr\": 0.03374402644139403,\n\ \ \"acc_norm\": 0.7515151515151515,\n \"acc_norm_stderr\": 0.03374402644139403\n\ \ },\n \"harness\|hendrycksTest-high_school_geography\|5\": {\n \"acc\"\ : 0.7777777777777778,\n \"acc_stderr\": 0.029620227874790486,\n \"\ acc_norm\": 0.7777777777777778,\n \"acc_norm_stderr\": 0.029620227874790486\n\ \ },\n \"harness\|hendrycksTest-high_school_government_and_politics\|5\": {\n\ \ \"acc\": 0.8601036269430051,\n \"acc_stderr\": 0.02503387058301518,\n\ \ \"acc_norm\": 0.8601036269430051,\n \"acc_norm_stderr\": 0.02503387058301518\n\ \ },\n \"harness\|hendrycksTest-high_school_macroeconomics\|5\": {\n \ \ \"acc\": 0.6282051282051282,\n \"acc_stderr\": 0.024503472557110932,\n\ \ \"acc_norm\": 0.6282051282051282,\n \"acc_norm_stderr\": 0.024503472557110932\n\ \ },\n \"harness\|hendrycksTest-high_school_mathematics\|5\": {\n \"\ acc\": 0.3074074074074074,\n \"acc_stderr\": 0.028133252578815642,\n \ \ \"acc_norm\": 0.3074074074074074,\n \"acc_norm_stderr\": 0.028133252578815642\n\ \ },\n \"harness\|hendrycksTest-high_school_microeconomics\|5\": {\n \ \ \"acc\": 0.6848739495798319,\n \"acc_stderr\": 0.030176808288974337,\n\ \ \"acc_norm\": 0.6848739495798319,\n \"acc_norm_stderr\": 0.030176808288974337\n\ \ },\n \"harness\|hendrycksTest-high_school_physics\|5\": {\n \"acc\"\ : 0.3708609271523179,\n \"acc_stderr\": 0.03943966699183629,\n \"\ acc_norm\": 0.3708609271523179,\n \"acc_norm_stderr\": 0.03943966699183629\n\ \ },\n \"harness\|hendrycksTest-high_school_psychology\|5\": {\n \"acc\"\ : 0.8256880733944955,\n \"acc_stderr\": 0.016265675632010344,\n \"\ acc_norm\": 0.8256880733944955,\n \"acc_norm_stderr\": 0.016265675632010344\n\ \ },\n \"harness\|hendrycksTest-high_school_statistics\|5\": {\n \"acc\"\ : 0.5138888888888888,\n \"acc_stderr\": 0.03408655867977749,\n \"\ acc_norm\": 0.5138888888888888,\n \"acc_norm_stderr\": 0.03408655867977749\n\ \ },\n \"harness\|hendrycksTest-high_school_us_history\|5\": {\n \"acc\"\ : 0.7892156862745098,\n \"acc_stderr\": 0.028626547912437416,\n \"\ acc_norm\": 0.7892156862745098,\n \"acc_norm_stderr\": 0.028626547912437416\n\ \ },\n \"harness\|hendrycksTest-high_school_world_history\|5\": {\n \"\ acc\": 0.8059071729957806,\n \"acc_stderr\": 0.025744902532290902,\n \ \ \"acc_norm\": 0.8059071729957806,\n \"acc_norm_stderr\": 0.025744902532290902\n\ \ },\n \"harness\|hendrycksTest-human_aging\|5\": {\n \"acc\": 0.6771300448430493,\n\ \ \"acc_stderr\": 0.031381476375754995,\n \"acc_norm\": 0.6771300448430493,\n\ \ \"acc_norm_stderr\": 0.031381476375754995\n },\n \"harness\|hendrycksTest-human_sexuality\|5\"\ : {\n \"acc\": 0.732824427480916,\n \"acc_stderr\": 0.038808483010823944,\n\ \ \"acc_norm\": 0.732824427480916,\n \"acc_norm_stderr\": 0.038808483010823944\n\ \ },\n \"harness\|hendrycksTest-international_law\|5\": {\n \"acc\":\ \ 0.71900826446281,\n \"acc_stderr\": 0.04103203830514512,\n \"acc_norm\"\ : 0.71900826446281,\n \"acc_norm_stderr\": 0.04103203830514512\n },\n\ \ \"harness\|hendrycksTest-jurisprudence\|5\": {\n \"acc\": 0.75,\n \ \ \"acc_stderr\": 0.04186091791394607,\n \"acc_norm\": 0.75,\n \ \ \"acc_norm_stderr\": 0.04186091791394607\n },\n \"harness\|hendrycksTest-logical_fallacies\|5\"\ : {\n \"acc\": 0.7361963190184049,\n \"acc_stderr\": 0.03462419931615623,\n\ \ \"acc_norm\": 0.7361963190184049,\n \"acc_norm_stderr\": 0.03462419931615623\n\ \ },\n \"harness\|hendrycksTest-machine_learning\|5\": {\n \"acc\": 0.48214285714285715,\n\ \ \"acc_stderr\": 0.047427623612430116,\n \"acc_norm\": 0.48214285714285715,\n\ \ \"acc_norm_stderr\": 0.047427623612430116\n },\n \"harness\|hendrycksTest-management\|5\"\ : {\n \"acc\": 0.7766990291262136,\n \"acc_stderr\": 0.04123553189891431,\n\ \ \"acc_norm\": 0.7766990291262136,\n \"acc_norm_stderr\": 0.04123553189891431\n\ \ },\n \"harness\|hendrycksTest-marketing\|5\": {\n \"acc\": 0.8803418803418803,\n\ \ \"acc_stderr\": 0.021262719400406957,\n \"acc_norm\": 0.8803418803418803,\n\ \ \"acc_norm_stderr\": 0.021262719400406957\n },\n \"harness\|hendrycksTest-medical_genetics\|5\"\ : {\n \"acc\": 0.67,\n \"acc_stderr\": 0.04725815626252609,\n \ \ \"acc_norm\": 0.67,\n \"acc_norm_stderr\": 0.04725815626252609\n \ \ },\n \"harness\|hendrycksTest-miscellaneous\|5\": {\n \"acc\": 0.8135376756066411,\n\ \ \"acc_stderr\": 0.013927751372001506,\n \"acc_norm\": 0.8135376756066411,\n\ \ \"acc_norm_stderr\": 0.013927751372001506\n },\n \"harness\|hendrycksTest-moral_disputes\|5\"\ : {\n \"acc\": 0.7138728323699421,\n \"acc_stderr\": 0.024332146779134128,\n\ \ \"acc_norm\": 0.7138728323699421,\n \"acc_norm_stderr\": 0.024332146779134128\n\ \ },\n \"harness\|hendrycksTest-moral_scenarios\|5\": {\n \"acc\": 0.24916201117318434,\n\ \ \"acc_stderr\": 0.01446589382985993,\n \"acc_norm\": 0.24916201117318434,\n\ \ \"acc_norm_stderr\": 0.01446589382985993\n },\n \"harness\|hendrycksTest-nutrition\|5\"\ : {\n \"acc\": 0.7352941176470589,\n \"acc_stderr\": 0.025261691219729487,\n\ \ \"acc_norm\": 0.7352941176470589,\n \"acc_norm_stderr\": 0.025261691219729487\n\ \ },\n \"harness\|hendrycksTest-philosophy\|5\": {\n \"acc\": 0.7041800643086816,\n\ \ \"acc_stderr\": 0.025922371788818767,\n \"acc_norm\": 0.7041800643086816,\n\ \ \"acc_norm_stderr\": 0.025922371788818767\n },\n \"harness\|hendrycksTest-prehistory\|5\"\ : {\n \"acc\": 0.7067901234567902,\n \"acc_stderr\": 0.025329888171900922,\n\ \ \"acc_norm\": 0.7067901234567902,\n \"acc_norm_stderr\": 0.025329888171900922\n\ \ },\n \"harness\|hendrycksTest-professional_accounting\|5\": {\n \"\ acc\": 0.5,\n \"acc_stderr\": 0.029827499313594685,\n \"acc_norm\"\ : 0.5,\n \"acc_norm_stderr\": 0.029827499313594685\n },\n \"harness\|hendrycksTest-professional_law\|5\"\ : {\n \"acc\": 0.4667535853976532,\n \"acc_stderr\": 0.01274197433389723,\n\ \ \"acc_norm\": 0.4667535853976532,\n \"acc_norm_stderr\": 0.01274197433389723\n\ \ },\n \"harness\|hendrycksTest-professional_medicine\|5\": {\n \"acc\"\ : 0.6764705882352942,\n \"acc_stderr\": 0.02841820861940676,\n \"\ acc_norm\": 0.6764705882352942,\n \"acc_norm_stderr\": 0.02841820861940676\n\ \ },\n \"harness\|hendrycksTest-professional_psychology\|5\": {\n \"\ acc\": 0.630718954248366,\n \"acc_stderr\": 0.01952431674486635,\n \ \ \"acc_norm\": 0.630718954248366,\n \"acc_norm_stderr\": 0.01952431674486635\n\ \ },\n \"harness\|hendrycksTest-public_relations\|5\": {\n \"acc\": 0.6636363636363637,\n\ \ \"acc_stderr\": 0.04525393596302506,\n \"acc_norm\": 0.6636363636363637,\n\ \ \"acc_norm_stderr\": 0.04525393596302506\n },\n \"harness\|hendrycksTest-security_studies\|5\"\ : {\n \"acc\": 0.726530612244898,\n \"acc_stderr\": 0.02853556033712844,\n\ \ \"acc_norm\": 0.726530612244898,\n \"acc_norm_stderr\": 0.02853556033712844\n\ \ },\n \"harness\|hendrycksTest-sociology\|5\": {\n \"acc\": 0.8208955223880597,\n\ \ \"acc_stderr\": 0.027113286753111837,\n \"acc_norm\": 0.8208955223880597,\n\ \ \"acc_norm_stderr\": 0.027113286753111837\n },\n \"harness\|hendrycksTest-us_foreign_policy\|5\"\ : {\n \"acc\": 0.87,\n \"acc_stderr\": 0.03379976689896309,\n \ \ \"acc_norm\": 0.87,\n \"acc_norm_stderr\": 0.03379976689896309\n \ \ },\n \"harness\|hendrycksTest-virology\|5\": {\n \"acc\": 0.5240963855421686,\n\ \ \"acc_stderr\": 0.03887971849597264,\n \"acc_norm\": 0.5240963855421686,\n\ \ \"acc_norm_stderr\": 0.03887971849597264\n },\n \"harness\|hendrycksTest-world_religions\|5\"\ : {\n \"acc\": 0.8187134502923976,\n \"acc_stderr\": 0.029547741687640044,\n\ \ \"acc_norm\": 0.8187134502923976,\n \"acc_norm_stderr\": 0.029547741687640044\n\ \ },\n \"harness\|truthfulqa:mc\|0\": {\n \"mc1\": 0.4186046511627907,\n\ \ \"mc1_stderr\": 0.017270015284476848,\n \"mc2\": 0.5902365843525761,\n\ \ \"mc2_stderr\": 0.015835546003395855\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.7545382794001578,\n \"acc_stderr\": 0.012095272937183633\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.604245640636846,\n \ \ \"acc_stderr\": 0.013469823701048815\n }\n}\n```" repo_url: https://huggingface.co/Isotonic/Hermes-2-Pro-Mixtral-4x7B leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2024_03_22T02_39_47.890512 path: - '/details_harness\|arc:challenge\|25_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2024-03-22T02-39-47.890512.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '/details_harness\|gsm8k\|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_03_22T02_39_47.890512 path: - '/details_harness\|hellaswag\|10_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-03-22T02-39-47.890512.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '/details_harness\|hendrycksTest-international_law\|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '/details_harness\|hendrycksTest-management\|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '/details_harness\|hendrycksTest-marketing\|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '/details_harness\|hendrycksTest-sociology\|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '/details_harness\|hendrycksTest-virology\|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_03_22T02_39_47.890512 path: - '/details_harness\|truthfulqa:mc\|0_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2024-03-22T02-39-47.890512.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '/details_harness\|winogrande\|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2024-03-22T02-39-47.890512.parquet' - config_name: results data_files: - split: 2024_03_22T02_39_47.890512 path: - results_2024-03-22T02-39-47.890512.parquet - split: latest path: - results_2024-03-22T02-39-47.890512.parquet --- # Dataset Card for Evaluation run of Isotonic/Hermes-2-Pro-Mixtral-4x7B <!-- Provide a quick summary of the dataset. --> Dataset automatically created during the evaluation run of model [Isotonic/Hermes-2-Pro-Mixtral-4x7B](https://huggingface.co/Isotonic/Hermes-2-Pro-Mixtral-4x7B) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_Isotonic__Hermes-2-Pro-Mixtral-4x7B", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-03-22T02:39:47.890512](https://huggingface.co/datasets/open-llm-leaderboard/details_Isotonic__Hermes-2-Pro-Mixtral-4x7B/blob/main/results_2024-03-22T02-39-47.890512.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval): ```python { "all": { "acc": 0.6247175996493741, "acc_stderr": 0.03257864192508729, "acc_norm": 0.6264034162110771, "acc_norm_stderr": 0.033228987439788436, "mc1": 0.4186046511627907, "mc1_stderr": 0.017270015284476848, "mc2": 0.5902365843525761, "mc2_stderr": 0.015835546003395855 }, "harness\|arc:challenge\|25": { "acc": 0.6126279863481229, "acc_stderr": 0.014235872487909869, "acc_norm": 0.6424914675767918, "acc_norm_stderr": 0.014005494275916573 }, "harness\|hellaswag\|10": { "acc": 0.6480780720971918, "acc_stderr": 0.004765937515197187, "acc_norm": 0.8270264887472615, "acc_norm_stderr": 0.003774513882615956 }, "harness\|hendrycksTest-abstract_algebra\|5": { "acc": 0.29, "acc_stderr": 0.04560480215720684, "acc_norm": 0.29, "acc_norm_stderr": 0.04560480215720684 }, "harness\|hendrycksTest-anatomy\|5": { "acc": 0.5777777777777777, "acc_stderr": 0.04266763404099582, "acc_norm": 0.5777777777777777, "acc_norm_stderr": 0.04266763404099582 }, "harness\|hendrycksTest-astronomy\|5": { "acc": 0.6973684210526315, "acc_stderr": 0.03738520676119668, "acc_norm": 0.6973684210526315, "acc_norm_stderr": 0.03738520676119668 }, "harness\|hendrycksTest-business_ethics\|5": { "acc": 0.58, "acc_stderr": 0.049604496374885836, "acc_norm": 0.58, "acc_norm_stderr": 0.049604496374885836 }, "harness\|hendrycksTest-clinical_knowledge\|5": { "acc": 0.6830188679245283, "acc_stderr": 0.02863723563980089, "acc_norm": 0.6830188679245283, "acc_norm_stderr": 0.02863723563980089 }, "harness\|hendrycksTest-college_biology\|5": { "acc": 0.7222222222222222, "acc_stderr": 0.037455547914624555, "acc_norm": 0.7222222222222222, "acc_norm_stderr": 0.037455547914624555 }, "harness\|hendrycksTest-college_chemistry\|5": { "acc": 0.44, "acc_stderr": 0.04988876515698589, "acc_norm": 0.44, "acc_norm_stderr": 0.04988876515698589 }, "harness\|hendrycksTest-college_computer_science\|5": { "acc": 0.52, "acc_stderr": 0.050211673156867795, "acc_norm": 0.52, "acc_norm_stderr": 0.050211673156867795 }, "harness\|hendrycksTest-college_mathematics\|5": { "acc": 0.3, "acc_stderr": 0.046056618647183814, "acc_norm": 0.3, "acc_norm_stderr": 0.046056618647183814 }, "harness\|hendrycksTest-college_medicine\|5": { "acc": 0.5953757225433526, "acc_stderr": 0.03742461193887248, "acc_norm": 0.5953757225433526, "acc_norm_stderr": 0.03742461193887248 }, "harness\|hendrycksTest-college_physics\|5": { "acc": 0.37254901960784315, "acc_stderr": 0.04810840148082636, "acc_norm": 0.37254901960784315, "acc_norm_stderr": 0.04810840148082636 }, "harness\|hendrycksTest-computer_security\|5": { "acc": 0.78, "acc_stderr": 0.04163331998932261, "acc_norm": 0.78, "acc_norm_stderr": 0.04163331998932261 }, "harness\|hendrycksTest-conceptual_physics\|5": { "acc": 0.5617021276595745, "acc_stderr": 0.03243618636108102, "acc_norm": 0.5617021276595745, "acc_norm_stderr": 0.03243618636108102 }, "harness\|hendrycksTest-econometrics\|5": { "acc": 0.4824561403508772, "acc_stderr": 0.04700708033551038, "acc_norm": 0.4824561403508772, "acc_norm_stderr": 0.04700708033551038 }, "harness\|hendrycksTest-electrical_engineering\|5": { "acc": 0.5103448275862069, "acc_stderr": 0.04165774775728763, "acc_norm": 0.5103448275862069, "acc_norm_stderr": 0.04165774775728763 }, "harness\|hendrycksTest-elementary_mathematics\|5": { "acc": 0.42063492063492064, "acc_stderr": 0.025424835086923996, "acc_norm": 0.42063492063492064, "acc_norm_stderr": 0.025424835086923996 }, "harness\|hendrycksTest-formal_logic\|5": { "acc": 0.42063492063492064, "acc_stderr": 0.04415438226743744, "acc_norm": 0.42063492063492064, "acc_norm_stderr": 0.04415438226743744 }, "harness\|hendrycksTest-global_facts\|5": { "acc": 0.32, "acc_stderr": 0.04688261722621504, "acc_norm": 0.32, "acc_norm_stderr": 0.04688261722621504 }, "harness\|hendrycksTest-high_school_biology\|5": { "acc": 0.7354838709677419, "acc_stderr": 0.02509189237885928, "acc_norm": 0.7354838709677419, "acc_norm_stderr": 0.02509189237885928 }, "harness\|hendrycksTest-high_school_chemistry\|5": { "acc": 0.4482758620689655, "acc_stderr": 0.03499113137676744, "acc_norm": 0.4482758620689655, "acc_norm_stderr": 0.03499113137676744 }, "harness\|hendrycksTest-high_school_computer_science\|5": { "acc": 0.67, "acc_stderr": 0.04725815626252607, "acc_norm": 0.67, "acc_norm_stderr": 0.04725815626252607 }, "harness\|hendrycksTest-high_school_european_history\|5": { "acc": 0.7515151515151515, "acc_stderr": 0.03374402644139403, "acc_norm": 0.7515151515151515, "acc_norm_stderr": 0.03374402644139403 }, "harness\|hendrycksTest-high_school_geography\|5": { "acc": 0.7777777777777778, "acc_stderr": 0.029620227874790486, "acc_norm": 0.7777777777777778, "acc_norm_stderr": 0.029620227874790486 }, "harness\|hendrycksTest-high_school_government_and_politics\|5": { "acc": 0.8601036269430051, "acc_stderr": 0.02503387058301518, "acc_norm": 0.8601036269430051, "acc_norm_stderr": 0.02503387058301518 }, "harness\|hendrycksTest-high_school_macroeconomics\|5": { "acc": 0.6282051282051282, "acc_stderr": 0.024503472557110932, "acc_norm": 0.6282051282051282, "acc_norm_stderr": 0.024503472557110932 }, "harness\|hendrycksTest-high_school_mathematics\|5": { "acc": 0.3074074074074074, "acc_stderr": 0.028133252578815642, "acc_norm": 0.3074074074074074, "acc_norm_stderr": 0.028133252578815642 }, "harness\|hendrycksTest-high_school_microeconomics\|5": { "acc": 0.6848739495798319, "acc_stderr": 0.030176808288974337, "acc_norm": 0.6848739495798319, "acc_norm_stderr": 0.030176808288974337 }, "harness\|hendrycksTest-high_school_physics\|5": { "acc": 0.3708609271523179, "acc_stderr": 0.03943966699183629, "acc_norm": 0.3708609271523179, "acc_norm_stderr": 0.03943966699183629 }, "harness\|hendrycksTest-high_school_psychology\|5": { "acc": 0.8256880733944955, "acc_stderr": 0.016265675632010344, "acc_norm": 0.8256880733944955, "acc_norm_stderr": 0.016265675632010344 }, "harness\|hendrycksTest-high_school_statistics\|5": { "acc": 0.5138888888888888, "acc_stderr": 0.03408655867977749, "acc_norm": 0.5138888888888888, "acc_norm_stderr": 0.03408655867977749 }, "harness\|hendrycksTest-high_school_us_history\|5": { "acc": 0.7892156862745098, "acc_stderr": 0.028626547912437416, "acc_norm": 0.7892156862745098, "acc_norm_stderr": 0.028626547912437416 }, "harness\|hendrycksTest-high_school_world_history\|5": { "acc": 0.8059071729957806, "acc_stderr": 0.025744902532290902, "acc_norm": 0.8059071729957806, "acc_norm_stderr": 0.025744902532290902 }, "harness\|hendrycksTest-human_aging\|5": { "acc": 0.6771300448430493, "acc_stderr": 0.031381476375754995, "acc_norm": 0.6771300448430493, "acc_norm_stderr": 0.031381476375754995 }, "harness\|hendrycksTest-human_sexuality\|5": { "acc": 0.732824427480916, "acc_stderr": 0.038808483010823944, "acc_norm": 0.732824427480916, "acc_norm_stderr": 0.038808483010823944 }, "harness\|hendrycksTest-international_law\|5": { "acc": 0.71900826446281, "acc_stderr": 0.04103203830514512, "acc_norm": 0.71900826446281, "acc_norm_stderr": 0.04103203830514512 }, "harness\|hendrycksTest-jurisprudence\|5": { "acc": 0.75, "acc_stderr": 0.04186091791394607, "acc_norm": 0.75, "acc_norm_stderr": 0.04186091791394607 }, "harness\|hendrycksTest-logical_fallacies\|5": { "acc": 0.7361963190184049, "acc_stderr": 0.03462419931615623, "acc_norm": 0.7361963190184049, "acc_norm_stderr": 0.03462419931615623 }, "harness\|hendrycksTest-machine_learning\|5": { "acc": 0.48214285714285715, "acc_stderr": 0.047427623612430116, "acc_norm": 0.48214285714285715, "acc_norm_stderr": 0.047427623612430116 }, "harness\|hendrycksTest-management\|5": { "acc": 0.7766990291262136, "acc_stderr": 0.04123553189891431, "acc_norm": 0.7766990291262136, "acc_norm_stderr": 0.04123553189891431 }, "harness\|hendrycksTest-marketing\|5": { "acc": 0.8803418803418803, "acc_stderr": 0.021262719400406957, "acc_norm": 0.8803418803418803, "acc_norm_stderr": 0.021262719400406957 }, "harness\|hendrycksTest-medical_genetics\|5": { "acc": 0.67, "acc_stderr": 0.04725815626252609, "acc_norm": 0.67, "acc_norm_stderr": 0.04725815626252609 }, "harness\|hendrycksTest-miscellaneous\|5": { "acc": 0.8135376756066411, "acc_stderr": 0.013927751372001506, "acc_norm": 0.8135376756066411, "acc_norm_stderr": 0.013927751372001506 }, "harness\|hendrycksTest-moral_disputes\|5": { "acc": 0.7138728323699421, "acc_stderr": 0.024332146779134128, "acc_norm": 0.7138728323699421, "acc_norm_stderr": 0.024332146779134128 }, "harness\|hendrycksTest-moral_scenarios\|5": { "acc": 0.24916201117318434, "acc_stderr": 0.01446589382985993, "acc_norm": 0.24916201117318434, "acc_norm_stderr": 0.01446589382985993 }, "harness\|hendrycksTest-nutrition\|5": { "acc": 0.7352941176470589, "acc_stderr": 0.025261691219729487, "acc_norm": 0.7352941176470589, "acc_norm_stderr": 0.025261691219729487 }, "harness\|hendrycksTest-philosophy\|5": { "acc": 0.7041800643086816, "acc_stderr": 0.025922371788818767, "acc_norm": 0.7041800643086816, "acc_norm_stderr": 0.025922371788818767 }, "harness\|hendrycksTest-prehistory\|5": { "acc": 0.7067901234567902, "acc_stderr": 0.025329888171900922, "acc_norm": 0.7067901234567902, "acc_norm_stderr": 0.025329888171900922 }, "harness\|hendrycksTest-professional_accounting\|5": { "acc": 0.5, "acc_stderr": 0.029827499313594685, "acc_norm": 0.5, "acc_norm_stderr": 0.029827499313594685 }, "harness\|hendrycksTest-professional_law\|5": { "acc": 0.4667535853976532, "acc_stderr": 0.01274197433389723, "acc_norm": 0.4667535853976532, "acc_norm_stderr": 0.01274197433389723 }, "harness\|hendrycksTest-professional_medicine\|5": { "acc": 0.6764705882352942, "acc_stderr": 0.02841820861940676, "acc_norm": 0.6764705882352942, "acc_norm_stderr": 0.02841820861940676 }, "harness\|hendrycksTest-professional_psychology\|5": { "acc": 0.630718954248366, "acc_stderr": 0.01952431674486635, "acc_norm": 0.630718954248366, "acc_norm_stderr": 0.01952431674486635 }, "harness\|hendrycksTest-public_relations\|5": { "acc": 0.6636363636363637, "acc_stderr": 0.04525393596302506, "acc_norm": 0.6636363636363637, "acc_norm_stderr": 0.04525393596302506 }, "harness\|hendrycksTest-security_studies\|5": { "acc": 0.726530612244898, "acc_stderr": 0.02853556033712844, "acc_norm": 0.726530612244898, "acc_norm_stderr": 0.02853556033712844 }, "harness\|hendrycksTest-sociology\|5": { "acc": 0.8208955223880597, "acc_stderr": 0.027113286753111837, "acc_norm": 0.8208955223880597, "acc_norm_stderr": 0.027113286753111837 }, "harness\|hendrycksTest-us_foreign_policy\|5": { "acc": 0.87, "acc_stderr": 0.03379976689896309, "acc_norm": 0.87, "acc_norm_stderr": 0.03379976689896309 }, "harness\|hendrycksTest-virology\|5": { "acc": 0.5240963855421686, "acc_stderr": 0.03887971849597264, "acc_norm": 0.5240963855421686, "acc_norm_stderr": 0.03887971849597264 }, "harness\|hendrycksTest-world_religions\|5": { "acc": 0.8187134502923976, "acc_stderr": 0.029547741687640044, "acc_norm": 0.8187134502923976, "acc_norm_stderr": 0.029547741687640044 }, "harness\|truthfulqa:mc\|0": { "mc1": 0.4186046511627907, "mc1_stderr": 0.017270015284476848, "mc2": 0.5902365843525761, "mc2_stderr": 0.015835546003395855 }, "harness\|winogrande\|5": { "acc": 0.7545382794001578, "acc_stderr": 0.012095272937183633 }, "harness\|gsm8k\|5": { "acc": 0.604245640636846, "acc_stderr": 0.013469823701048815 } } ``` ## Dataset Details ### Dataset Description <!-- Provide a longer summary of what this dataset is. --> - Curated by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] ### Dataset Sources [optional] <!-- Provide the basic links for the dataset. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the dataset is intended to be used. --> ### Direct Use <!-- This section describes suitable use cases for the dataset. --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. --> [More Information Needed] ## Dataset Structure <!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. --> [More Information Needed] ## Dataset Creation ### Curation Rationale <!-- Motivation for the creation of this dataset. --> [More Information Needed] ### Source Data <!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). --> #### Data Collection and Processing <!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. --> [More Information Needed] #### Who are the source data producers? <!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. --> [More Information Needed] ### Annotations [optional] <!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. --> #### Annotation process <!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. --> [More Information Needed] #### Who are the annotators? <!-- This section describes the people or systems who created the annotations. --> [More Information Needed] #### Personal and Sensitive Information <!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations. ## Citation [optional] <!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Dataset Card Authors [optional] [More Information Needed] ## Dataset Card Contact [More Information Needed]
open-responsibility/frameworks	--- license: apache-2.0 configs: - config_name: default data_files: - split: train path: - "catalog.json" --- https://huggingface.co/datasets/open-responsibility/frameworks
hippocrates/qa_train_old	--- configs: - config_name: default data_files: - split: train path: data/train-* - split: valid path: data/valid-* dataset_info: features: - name: id dtype: string - name: conversations list: - name: from dtype: string - name: value dtype: string - name: text dtype: string splits: - name: train num_bytes: 485067176 num_examples: 404269 - name: valid num_bytes: 4491759 num_examples: 5505 download_size: 241040216 dataset_size: 489558935 --- # Dataset Card for "qa_train" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
one-sec-cv12/chunk_132	--- dataset_info: features: - name: audio dtype: audio: sampling_rate: 16000 splits: - name: train num_bytes: 20839438512.875 num_examples: 216969 download_size: 19299011373 dataset_size: 20839438512.875 --- # Dataset Card for "chunk_132" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
J-LAB/OpenHermes_PTBR	--- dataset_info: features: - name: instruction dtype: string - name: input dtype: string - name: output dtype: string splits: - name: train num_bytes: 1391804745 num_examples: 860176 download_size: 772872708 dataset_size: 1391804745 configs: - config_name: default data_files: - split: train path: data/train-* ---
wisenut-nlp-team/aihub_admin_generated_answers	--- dataset_info: features: - name: id dtype: string - name: title dtype: string - name: question dtype: string - name: context dtype: string - name: answer dtype: string - name: original_answer dtype: string - name: similar_contexts sequence: string splits: - name: train num_bytes: 5293612104 num_examples: 315745 download_size: 2662886163 dataset_size: 5293612104 --- # Dataset Card for "aihub_admin_generated_answers_last" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
tyzhu/squad_qa_context_v5_full_recite_ans_sent_last_permute_rerun	--- configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* dataset_info: features: - name: id dtype: string - name: title dtype: string - name: context dtype: string - name: question dtype: string - name: answers sequence: - name: text dtype: string - name: answer_start dtype: int32 - name: answer dtype: string - name: context_id dtype: string - name: inputs dtype: string - name: targets dtype: string splits: - name: train num_bytes: 4850217.0 num_examples: 2385 - name: validation num_bytes: 631113 num_examples: 300 download_size: 1204825 dataset_size: 5481330.0 --- # Dataset Card for "squad_qa_context_v5_full_recite_ans_sent_last_permute_rerun" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
GTZ22/vozmiguel	--- license: openrail ---
ODD2903/ProjetA23	--- license: apache-2.0 ---
open-llm-leaderboard/details_BFauber__lora_llama2-13b_10e5_r32_a16	--- pretty_name: Evaluation run of BFauber/lora_llama2-13b_10e5_r32_a16 dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [BFauber/lora_llama2-13b_10e5_r32_a16](https://huggingface.co/BFauber/lora_llama2-13b_10e5_r32_a16)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 63 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the aggregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_BFauber__lora_llama2-13b_10e5_r32_a16\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-02-10T00:35:29.195349](https://huggingface.co/datasets/open-llm-leaderboard/details_BFauber__lora_llama2-13b_10e5_r32_a16/blob/main/results_2024-02-10T00-35-29.195349.json)(note\ \ that their might be results for other tasks in the repos if successive evals didn't\ \ cover the same tasks. You find each in the results and the \"latest\" split for\ \ each eval):\n\n```python\n{\n \"all\": {\n \"acc\": 0.5560019624665314,\n\ \ \"acc_stderr\": 0.03364714043907589,\n \"acc_norm\": 0.5619565729235969,\n\ \ \"acc_norm_stderr\": 0.03436835615145709,\n \"mc1\": 0.26193390452876375,\n\ \ \"mc1_stderr\": 0.015392118805015025,\n \"mc2\": 0.38301200451667206,\n\ \ \"mc2_stderr\": 0.013767815310741604\n },\n \"harness\|arc:challenge\|25\"\ : {\n \"acc\": 0.560580204778157,\n \"acc_stderr\": 0.014503747823580123,\n\ \ \"acc_norm\": 0.5989761092150171,\n \"acc_norm_stderr\": 0.01432225579071987\n\ \ },\n \"harness\|hellaswag\|10\": {\n \"acc\": 0.6163114917347142,\n\ \ \"acc_stderr\": 0.004852896681736758,\n \"acc_norm\": 0.8233419637522406,\n\ \ \"acc_norm_stderr\": 0.0038059961194403754\n },\n \"harness\|hendrycksTest-abstract_algebra\|5\"\ : {\n \"acc\": 0.33,\n \"acc_stderr\": 0.04725815626252606,\n \ \ \"acc_norm\": 0.33,\n \"acc_norm_stderr\": 0.04725815626252606\n \ \ },\n \"harness\|hendrycksTest-anatomy\|5\": {\n \"acc\": 0.48148148148148145,\n\ \ \"acc_stderr\": 0.043163785995113245,\n \"acc_norm\": 0.48148148148148145,\n\ \ \"acc_norm_stderr\": 0.043163785995113245\n },\n \"harness\|hendrycksTest-astronomy\|5\"\ : {\n \"acc\": 0.5328947368421053,\n \"acc_stderr\": 0.04060127035236397,\n\ \ \"acc_norm\": 0.5328947368421053,\n \"acc_norm_stderr\": 0.04060127035236397\n\ \ },\n \"harness\|hendrycksTest-business_ethics\|5\": {\n \"acc\": 0.52,\n\ \ \"acc_stderr\": 0.05021167315686779,\n \"acc_norm\": 0.52,\n \ \ \"acc_norm_stderr\": 0.05021167315686779\n },\n \"harness\|hendrycksTest-clinical_knowledge\|5\"\ : {\n \"acc\": 0.6226415094339622,\n \"acc_stderr\": 0.029832808114796,\n\ \ \"acc_norm\": 0.6226415094339622,\n \"acc_norm_stderr\": 0.029832808114796\n\ \ },\n \"harness\|hendrycksTest-college_biology\|5\": {\n \"acc\": 0.6041666666666666,\n\ \ \"acc_stderr\": 0.04089465449325582,\n \"acc_norm\": 0.6041666666666666,\n\ \ \"acc_norm_stderr\": 0.04089465449325582\n },\n \"harness\|hendrycksTest-college_chemistry\|5\"\ : {\n \"acc\": 0.45,\n \"acc_stderr\": 0.05,\n \"acc_norm\"\ : 0.45,\n \"acc_norm_stderr\": 0.05\n },\n \"harness\|hendrycksTest-college_computer_science\|5\"\ : {\n \"acc\": 0.47,\n \"acc_stderr\": 0.05016135580465919,\n \ \ \"acc_norm\": 0.47,\n \"acc_norm_stderr\": 0.05016135580465919\n \ \ },\n \"harness\|hendrycksTest-college_mathematics\|5\": {\n \"acc\": 0.3,\n\ \ \"acc_stderr\": 0.046056618647183814,\n \"acc_norm\": 0.3,\n \ \ \"acc_norm_stderr\": 0.046056618647183814\n },\n \"harness\|hendrycksTest-college_medicine\|5\"\ : {\n \"acc\": 0.5549132947976878,\n \"acc_stderr\": 0.03789401760283647,\n\ \ \"acc_norm\": 0.5549132947976878,\n \"acc_norm_stderr\": 0.03789401760283647\n\ \ },\n \"harness\|hendrycksTest-college_physics\|5\": {\n \"acc\": 0.2647058823529412,\n\ \ \"acc_stderr\": 0.04389869956808778,\n \"acc_norm\": 0.2647058823529412,\n\ \ \"acc_norm_stderr\": 0.04389869956808778\n },\n \"harness\|hendrycksTest-computer_security\|5\"\ : {\n \"acc\": 0.69,\n \"acc_stderr\": 0.04648231987117316,\n \ \ \"acc_norm\": 0.69,\n \"acc_norm_stderr\": 0.04648231987117316\n \ \ },\n \"harness\|hendrycksTest-conceptual_physics\|5\": {\n \"acc\": 0.451063829787234,\n\ \ \"acc_stderr\": 0.032529096196131965,\n \"acc_norm\": 0.451063829787234,\n\ \ \"acc_norm_stderr\": 0.032529096196131965\n },\n \"harness\|hendrycksTest-econometrics\|5\"\ : {\n \"acc\": 0.2719298245614035,\n \"acc_stderr\": 0.04185774424022056,\n\ \ \"acc_norm\": 0.2719298245614035,\n \"acc_norm_stderr\": 0.04185774424022056\n\ \ },\n \"harness\|hendrycksTest-electrical_engineering\|5\": {\n \"acc\"\ : 0.5241379310344828,\n \"acc_stderr\": 0.0416180850350153,\n \"acc_norm\"\ : 0.5241379310344828,\n \"acc_norm_stderr\": 0.0416180850350153\n },\n\ \ \"harness\|hendrycksTest-elementary_mathematics\|5\": {\n \"acc\": 0.328042328042328,\n\ \ \"acc_stderr\": 0.02418049716437691,\n \"acc_norm\": 0.328042328042328,\n\ \ \"acc_norm_stderr\": 0.02418049716437691\n },\n \"harness\|hendrycksTest-formal_logic\|5\"\ : {\n \"acc\": 0.3333333333333333,\n \"acc_stderr\": 0.04216370213557835,\n\ \ \"acc_norm\": 0.3333333333333333,\n \"acc_norm_stderr\": 0.04216370213557835\n\ \ },\n \"harness\|hendrycksTest-global_facts\|5\": {\n \"acc\": 0.37,\n\ \ \"acc_stderr\": 0.048523658709391,\n \"acc_norm\": 0.37,\n \ \ \"acc_norm_stderr\": 0.048523658709391\n },\n \"harness\|hendrycksTest-high_school_biology\|5\"\ : {\n \"acc\": 0.6903225806451613,\n \"acc_stderr\": 0.026302774983517418,\n\ \ \"acc_norm\": 0.6903225806451613,\n \"acc_norm_stderr\": 0.026302774983517418\n\ \ },\n \"harness\|hendrycksTest-high_school_chemistry\|5\": {\n \"acc\"\ : 0.458128078817734,\n \"acc_stderr\": 0.03505630140785742,\n \"acc_norm\"\ : 0.458128078817734,\n \"acc_norm_stderr\": 0.03505630140785742\n },\n\ \ \"harness\|hendrycksTest-high_school_computer_science\|5\": {\n \"acc\"\ : 0.56,\n \"acc_stderr\": 0.04988876515698589,\n \"acc_norm\": 0.56,\n\ \ \"acc_norm_stderr\": 0.04988876515698589\n },\n \"harness\|hendrycksTest-high_school_european_history\|5\"\ : {\n \"acc\": 0.6303030303030303,\n \"acc_stderr\": 0.03769430314512566,\n\ \ \"acc_norm\": 0.6303030303030303,\n \"acc_norm_stderr\": 0.03769430314512566\n\ \ },\n \"harness\|hendrycksTest-high_school_geography\|5\": {\n \"acc\"\ : 0.6919191919191919,\n \"acc_stderr\": 0.032894773300986155,\n \"\ acc_norm\": 0.6919191919191919,\n \"acc_norm_stderr\": 0.032894773300986155\n\ \ },\n \"harness\|hendrycksTest-high_school_government_and_politics\|5\": {\n\ \ \"acc\": 0.8031088082901554,\n \"acc_stderr\": 0.028697873971860677,\n\ \ \"acc_norm\": 0.8031088082901554,\n \"acc_norm_stderr\": 0.028697873971860677\n\ \ },\n \"harness\|hendrycksTest-high_school_macroeconomics\|5\": {\n \ \ \"acc\": 0.5153846153846153,\n \"acc_stderr\": 0.025339003010106515,\n\ \ \"acc_norm\": 0.5153846153846153,\n \"acc_norm_stderr\": 0.025339003010106515\n\ \ },\n \"harness\|hendrycksTest-high_school_mathematics\|5\": {\n \"\ acc\": 0.32222222222222224,\n \"acc_stderr\": 0.028493465091028604,\n \ \ \"acc_norm\": 0.32222222222222224,\n \"acc_norm_stderr\": 0.028493465091028604\n\ \ },\n \"harness\|hendrycksTest-high_school_microeconomics\|5\": {\n \ \ \"acc\": 0.5630252100840336,\n \"acc_stderr\": 0.032219436365661956,\n\ \ \"acc_norm\": 0.5630252100840336,\n \"acc_norm_stderr\": 0.032219436365661956\n\ \ },\n \"harness\|hendrycksTest-high_school_physics\|5\": {\n \"acc\"\ : 0.32450331125827814,\n \"acc_stderr\": 0.03822746937658753,\n \"\ acc_norm\": 0.32450331125827814,\n \"acc_norm_stderr\": 0.03822746937658753\n\ \ },\n \"harness\|hendrycksTest-high_school_psychology\|5\": {\n \"acc\"\ : 0.7522935779816514,\n \"acc_stderr\": 0.01850814360254781,\n \"\ acc_norm\": 0.7522935779816514,\n \"acc_norm_stderr\": 0.01850814360254781\n\ \ },\n \"harness\|hendrycksTest-high_school_statistics\|5\": {\n \"acc\"\ : 0.4722222222222222,\n \"acc_stderr\": 0.0340470532865388,\n \"acc_norm\"\ : 0.4722222222222222,\n \"acc_norm_stderr\": 0.0340470532865388\n },\n\ \ \"harness\|hendrycksTest-high_school_us_history\|5\": {\n \"acc\": 0.7401960784313726,\n\ \ \"acc_stderr\": 0.03077855467869326,\n \"acc_norm\": 0.7401960784313726,\n\ \ \"acc_norm_stderr\": 0.03077855467869326\n },\n \"harness\|hendrycksTest-high_school_world_history\|5\"\ : {\n \"acc\": 0.7130801687763713,\n \"acc_stderr\": 0.02944377302259469,\n\ \ \"acc_norm\": 0.7130801687763713,\n \"acc_norm_stderr\": 0.02944377302259469\n\ \ },\n \"harness\|hendrycksTest-human_aging\|5\": {\n \"acc\": 0.6412556053811659,\n\ \ \"acc_stderr\": 0.03219079200419995,\n \"acc_norm\": 0.6412556053811659,\n\ \ \"acc_norm_stderr\": 0.03219079200419995\n },\n \"harness\|hendrycksTest-human_sexuality\|5\"\ : {\n \"acc\": 0.6259541984732825,\n \"acc_stderr\": 0.042438692422305246,\n\ \ \"acc_norm\": 0.6259541984732825,\n \"acc_norm_stderr\": 0.042438692422305246\n\ \ },\n \"harness\|hendrycksTest-international_law\|5\": {\n \"acc\":\ \ 0.7355371900826446,\n \"acc_stderr\": 0.04026187527591207,\n \"\ acc_norm\": 0.7355371900826446,\n \"acc_norm_stderr\": 0.04026187527591207\n\ \ },\n \"harness\|hendrycksTest-jurisprudence\|5\": {\n \"acc\": 0.7314814814814815,\n\ \ \"acc_stderr\": 0.042844679680521934,\n \"acc_norm\": 0.7314814814814815,\n\ \ \"acc_norm_stderr\": 0.042844679680521934\n },\n \"harness\|hendrycksTest-logical_fallacies\|5\"\ : {\n \"acc\": 0.6809815950920245,\n \"acc_stderr\": 0.03661997551073836,\n\ \ \"acc_norm\": 0.6809815950920245,\n \"acc_norm_stderr\": 0.03661997551073836\n\ \ },\n \"harness\|hendrycksTest-machine_learning\|5\": {\n \"acc\": 0.3125,\n\ \ \"acc_stderr\": 0.043994650575715215,\n \"acc_norm\": 0.3125,\n\ \ \"acc_norm_stderr\": 0.043994650575715215\n },\n \"harness\|hendrycksTest-management\|5\"\ : {\n \"acc\": 0.7572815533980582,\n \"acc_stderr\": 0.04245022486384495,\n\ \ \"acc_norm\": 0.7572815533980582,\n \"acc_norm_stderr\": 0.04245022486384495\n\ \ },\n \"harness\|hendrycksTest-marketing\|5\": {\n \"acc\": 0.8076923076923077,\n\ \ \"acc_stderr\": 0.02581923325648372,\n \"acc_norm\": 0.8076923076923077,\n\ \ \"acc_norm_stderr\": 0.02581923325648372\n },\n \"harness\|hendrycksTest-medical_genetics\|5\"\ : {\n \"acc\": 0.55,\n \"acc_stderr\": 0.04999999999999999,\n \ \ \"acc_norm\": 0.55,\n \"acc_norm_stderr\": 0.04999999999999999\n \ \ },\n \"harness\|hendrycksTest-miscellaneous\|5\": {\n \"acc\": 0.7458492975734355,\n\ \ \"acc_stderr\": 0.015569254692045757,\n \"acc_norm\": 0.7458492975734355,\n\ \ \"acc_norm_stderr\": 0.015569254692045757\n },\n \"harness\|hendrycksTest-moral_disputes\|5\"\ : {\n \"acc\": 0.6329479768786127,\n \"acc_stderr\": 0.025950054337654075,\n\ \ \"acc_norm\": 0.6329479768786127,\n \"acc_norm_stderr\": 0.025950054337654075\n\ \ },\n \"harness\|hendrycksTest-moral_scenarios\|5\": {\n \"acc\": 0.2782122905027933,\n\ \ \"acc_stderr\": 0.014987325439963539,\n \"acc_norm\": 0.2782122905027933,\n\ \ \"acc_norm_stderr\": 0.014987325439963539\n },\n \"harness\|hendrycksTest-nutrition\|5\"\ : {\n \"acc\": 0.6274509803921569,\n \"acc_stderr\": 0.027684181883302895,\n\ \ \"acc_norm\": 0.6274509803921569,\n \"acc_norm_stderr\": 0.027684181883302895\n\ \ },\n \"harness\|hendrycksTest-philosophy\|5\": {\n \"acc\": 0.6463022508038585,\n\ \ \"acc_stderr\": 0.027155208103200865,\n \"acc_norm\": 0.6463022508038585,\n\ \ \"acc_norm_stderr\": 0.027155208103200865\n },\n \"harness\|hendrycksTest-prehistory\|5\"\ : {\n \"acc\": 0.6419753086419753,\n \"acc_stderr\": 0.026675611926037103,\n\ \ \"acc_norm\": 0.6419753086419753,\n \"acc_norm_stderr\": 0.026675611926037103\n\ \ },\n \"harness\|hendrycksTest-professional_accounting\|5\": {\n \"\ acc\": 0.40070921985815605,\n \"acc_stderr\": 0.02923346574557308,\n \ \ \"acc_norm\": 0.40070921985815605,\n \"acc_norm_stderr\": 0.02923346574557308\n\ \ },\n \"harness\|hendrycksTest-professional_law\|5\": {\n \"acc\": 0.4198174706649283,\n\ \ \"acc_stderr\": 0.01260496081608737,\n \"acc_norm\": 0.4198174706649283,\n\ \ \"acc_norm_stderr\": 0.01260496081608737\n },\n \"harness\|hendrycksTest-professional_medicine\|5\"\ : {\n \"acc\": 0.5257352941176471,\n \"acc_stderr\": 0.030332578094555026,\n\ \ \"acc_norm\": 0.5257352941176471,\n \"acc_norm_stderr\": 0.030332578094555026\n\ \ },\n \"harness\|hendrycksTest-professional_psychology\|5\": {\n \"\ acc\": 0.5555555555555556,\n \"acc_stderr\": 0.020102583895887188,\n \ \ \"acc_norm\": 0.5555555555555556,\n \"acc_norm_stderr\": 0.020102583895887188\n\ \ },\n \"harness\|hendrycksTest-public_relations\|5\": {\n \"acc\": 0.6363636363636364,\n\ \ \"acc_stderr\": 0.046075820907199756,\n \"acc_norm\": 0.6363636363636364,\n\ \ \"acc_norm_stderr\": 0.046075820907199756\n },\n \"harness\|hendrycksTest-security_studies\|5\"\ : {\n \"acc\": 0.6285714285714286,\n \"acc_stderr\": 0.030932858792789848,\n\ \ \"acc_norm\": 0.6285714285714286,\n \"acc_norm_stderr\": 0.030932858792789848\n\ \ },\n \"harness\|hendrycksTest-sociology\|5\": {\n \"acc\": 0.7512437810945274,\n\ \ \"acc_stderr\": 0.030567675938916714,\n \"acc_norm\": 0.7512437810945274,\n\ \ \"acc_norm_stderr\": 0.030567675938916714\n },\n \"harness\|hendrycksTest-us_foreign_policy\|5\"\ : {\n \"acc\": 0.81,\n \"acc_stderr\": 0.03942772444036625,\n \ \ \"acc_norm\": 0.81,\n \"acc_norm_stderr\": 0.03942772444036625\n \ \ },\n \"harness\|hendrycksTest-virology\|5\": {\n \"acc\": 0.4759036144578313,\n\ \ \"acc_stderr\": 0.03887971849597264,\n \"acc_norm\": 0.4759036144578313,\n\ \ \"acc_norm_stderr\": 0.03887971849597264\n },\n \"harness\|hendrycksTest-world_religions\|5\"\ : {\n \"acc\": 0.7777777777777778,\n \"acc_stderr\": 0.03188578017686398,\n\ \ \"acc_norm\": 0.7777777777777778,\n \"acc_norm_stderr\": 0.03188578017686398\n\ \ },\n \"harness\|truthfulqa:mc\|0\": {\n \"mc1\": 0.26193390452876375,\n\ \ \"mc1_stderr\": 0.015392118805015025,\n \"mc2\": 0.38301200451667206,\n\ \ \"mc2_stderr\": 0.013767815310741604\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.7703235990528808,\n \"acc_stderr\": 0.011821645601838236\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.2357846853677028,\n \ \ \"acc_stderr\": 0.011692515650666792\n }\n}\n```" repo_url: https://huggingface.co/BFauber/lora_llama2-13b_10e5_r32_a16 leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2024_02_10T00_35_29.195349 path: - '/details_harness\|arc:challenge\|25_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2024-02-10T00-35-29.195349.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '/details_harness\|gsm8k\|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_02_10T00_35_29.195349 path: - '/details_harness\|hellaswag\|10_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-02-10T00-35-29.195349.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '/details_harness\|hendrycksTest-international_law\|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '/details_harness\|hendrycksTest-management\|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '/details_harness\|hendrycksTest-marketing\|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '/details_harness\|hendrycksTest-sociology\|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '/details_harness\|hendrycksTest-virology\|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_02_10T00_35_29.195349 path: - '/details_harness\|truthfulqa:mc\|0_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2024-02-10T00-35-29.195349.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '/details_harness\|winogrande\|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2024-02-10T00-35-29.195349.parquet' - config_name: results data_files: - split: 2024_02_10T00_35_29.195349 path: - results_2024-02-10T00-35-29.195349.parquet - split: latest path: - results_2024-02-10T00-35-29.195349.parquet --- # Dataset Card for Evaluation run of BFauber/lora_llama2-13b_10e5_r32_a16 <!-- Provide a quick summary of the dataset. --> Dataset automatically created during the evaluation run of model [BFauber/lora_llama2-13b_10e5_r32_a16](https://huggingface.co/BFauber/lora_llama2-13b_10e5_r32_a16) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_BFauber__lora_llama2-13b_10e5_r32_a16", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-02-10T00:35:29.195349](https://huggingface.co/datasets/open-llm-leaderboard/details_BFauber__lora_llama2-13b_10e5_r32_a16/blob/main/results_2024-02-10T00-35-29.195349.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval): ```python { "all": { "acc": 0.5560019624665314, "acc_stderr": 0.03364714043907589, "acc_norm": 0.5619565729235969, "acc_norm_stderr": 0.03436835615145709, "mc1": 0.26193390452876375, "mc1_stderr": 0.015392118805015025, "mc2": 0.38301200451667206, "mc2_stderr": 0.013767815310741604 }, "harness\|arc:challenge\|25": { "acc": 0.560580204778157, "acc_stderr": 0.014503747823580123, "acc_norm": 0.5989761092150171, "acc_norm_stderr": 0.01432225579071987 }, "harness\|hellaswag\|10": { "acc": 0.6163114917347142, "acc_stderr": 0.004852896681736758, "acc_norm": 0.8233419637522406, "acc_norm_stderr": 0.0038059961194403754 }, "harness\|hendrycksTest-abstract_algebra\|5": { "acc": 0.33, "acc_stderr": 0.04725815626252606, "acc_norm": 0.33, "acc_norm_stderr": 0.04725815626252606 }, "harness\|hendrycksTest-anatomy\|5": { "acc": 0.48148148148148145, "acc_stderr": 0.043163785995113245, "acc_norm": 0.48148148148148145, "acc_norm_stderr": 0.043163785995113245 }, "harness\|hendrycksTest-astronomy\|5": { "acc": 0.5328947368421053, "acc_stderr": 0.04060127035236397, "acc_norm": 0.5328947368421053, "acc_norm_stderr": 0.04060127035236397 }, "harness\|hendrycksTest-business_ethics\|5": { "acc": 0.52, "acc_stderr": 0.05021167315686779, "acc_norm": 0.52, "acc_norm_stderr": 0.05021167315686779 }, "harness\|hendrycksTest-clinical_knowledge\|5": { "acc": 0.6226415094339622, "acc_stderr": 0.029832808114796, "acc_norm": 0.6226415094339622, "acc_norm_stderr": 0.029832808114796 }, "harness\|hendrycksTest-college_biology\|5": { "acc": 0.6041666666666666, "acc_stderr": 0.04089465449325582, "acc_norm": 0.6041666666666666, "acc_norm_stderr": 0.04089465449325582 }, "harness\|hendrycksTest-college_chemistry\|5": { "acc": 0.45, "acc_stderr": 0.05, "acc_norm": 0.45, "acc_norm_stderr": 0.05 }, "harness\|hendrycksTest-college_computer_science\|5": { "acc": 0.47, "acc_stderr": 0.05016135580465919, "acc_norm": 0.47, "acc_norm_stderr": 0.05016135580465919 }, "harness\|hendrycksTest-college_mathematics\|5": { "acc": 0.3, "acc_stderr": 0.046056618647183814, "acc_norm": 0.3, "acc_norm_stderr": 0.046056618647183814 }, "harness\|hendrycksTest-college_medicine\|5": { "acc": 0.5549132947976878, "acc_stderr": 0.03789401760283647, "acc_norm": 0.5549132947976878, "acc_norm_stderr": 0.03789401760283647 }, "harness\|hendrycksTest-college_physics\|5": { "acc": 0.2647058823529412, "acc_stderr": 0.04389869956808778, "acc_norm": 0.2647058823529412, "acc_norm_stderr": 0.04389869956808778 }, "harness\|hendrycksTest-computer_security\|5": { "acc": 0.69, "acc_stderr": 0.04648231987117316, "acc_norm": 0.69, "acc_norm_stderr": 0.04648231987117316 }, "harness\|hendrycksTest-conceptual_physics\|5": { "acc": 0.451063829787234, "acc_stderr": 0.032529096196131965, "acc_norm": 0.451063829787234, "acc_norm_stderr": 0.032529096196131965 }, "harness\|hendrycksTest-econometrics\|5": { "acc": 0.2719298245614035, "acc_stderr": 0.04185774424022056, "acc_norm": 0.2719298245614035, "acc_norm_stderr": 0.04185774424022056 }, "harness\|hendrycksTest-electrical_engineering\|5": { "acc": 0.5241379310344828, "acc_stderr": 0.0416180850350153, "acc_norm": 0.5241379310344828, "acc_norm_stderr": 0.0416180850350153 }, "harness\|hendrycksTest-elementary_mathematics\|5": { "acc": 0.328042328042328, "acc_stderr": 0.02418049716437691, "acc_norm": 0.328042328042328, "acc_norm_stderr": 0.02418049716437691 }, "harness\|hendrycksTest-formal_logic\|5": { "acc": 0.3333333333333333, "acc_stderr": 0.04216370213557835, "acc_norm": 0.3333333333333333, "acc_norm_stderr": 0.04216370213557835 }, "harness\|hendrycksTest-global_facts\|5": { "acc": 0.37, "acc_stderr": 0.048523658709391, "acc_norm": 0.37, "acc_norm_stderr": 0.048523658709391 }, "harness\|hendrycksTest-high_school_biology\|5": { "acc": 0.6903225806451613, "acc_stderr": 0.026302774983517418, "acc_norm": 0.6903225806451613, "acc_norm_stderr": 0.026302774983517418 }, "harness\|hendrycksTest-high_school_chemistry\|5": { "acc": 0.458128078817734, "acc_stderr": 0.03505630140785742, "acc_norm": 0.458128078817734, "acc_norm_stderr": 0.03505630140785742 }, "harness\|hendrycksTest-high_school_computer_science\|5": { "acc": 0.56, "acc_stderr": 0.04988876515698589, "acc_norm": 0.56, "acc_norm_stderr": 0.04988876515698589 }, "harness\|hendrycksTest-high_school_european_history\|5": { "acc": 0.6303030303030303, "acc_stderr": 0.03769430314512566, "acc_norm": 0.6303030303030303, "acc_norm_stderr": 0.03769430314512566 }, "harness\|hendrycksTest-high_school_geography\|5": { "acc": 0.6919191919191919, "acc_stderr": 0.032894773300986155, "acc_norm": 0.6919191919191919, "acc_norm_stderr": 0.032894773300986155 }, "harness\|hendrycksTest-high_school_government_and_politics\|5": { "acc": 0.8031088082901554, "acc_stderr": 0.028697873971860677, "acc_norm": 0.8031088082901554, "acc_norm_stderr": 0.028697873971860677 }, "harness\|hendrycksTest-high_school_macroeconomics\|5": { "acc": 0.5153846153846153, "acc_stderr": 0.025339003010106515, "acc_norm": 0.5153846153846153, "acc_norm_stderr": 0.025339003010106515 }, "harness\|hendrycksTest-high_school_mathematics\|5": { "acc": 0.32222222222222224, "acc_stderr": 0.028493465091028604, "acc_norm": 0.32222222222222224, "acc_norm_stderr": 0.028493465091028604 }, "harness\|hendrycksTest-high_school_microeconomics\|5": { "acc": 0.5630252100840336, "acc_stderr": 0.032219436365661956, "acc_norm": 0.5630252100840336, "acc_norm_stderr": 0.032219436365661956 }, "harness\|hendrycksTest-high_school_physics\|5": { "acc": 0.32450331125827814, "acc_stderr": 0.03822746937658753, "acc_norm": 0.32450331125827814, "acc_norm_stderr": 0.03822746937658753 }, "harness\|hendrycksTest-high_school_psychology\|5": { "acc": 0.7522935779816514, "acc_stderr": 0.01850814360254781, "acc_norm": 0.7522935779816514, "acc_norm_stderr": 0.01850814360254781 }, "harness\|hendrycksTest-high_school_statistics\|5": { "acc": 0.4722222222222222, "acc_stderr": 0.0340470532865388, "acc_norm": 0.4722222222222222, "acc_norm_stderr": 0.0340470532865388 }, "harness\|hendrycksTest-high_school_us_history\|5": { "acc": 0.7401960784313726, "acc_stderr": 0.03077855467869326, "acc_norm": 0.7401960784313726, "acc_norm_stderr": 0.03077855467869326 }, "harness\|hendrycksTest-high_school_world_history\|5": { "acc": 0.7130801687763713, "acc_stderr": 0.02944377302259469, "acc_norm": 0.7130801687763713, "acc_norm_stderr": 0.02944377302259469 }, "harness\|hendrycksTest-human_aging\|5": { "acc": 0.6412556053811659, "acc_stderr": 0.03219079200419995, "acc_norm": 0.6412556053811659, "acc_norm_stderr": 0.03219079200419995 }, "harness\|hendrycksTest-human_sexuality\|5": { "acc": 0.6259541984732825, "acc_stderr": 0.042438692422305246, "acc_norm": 0.6259541984732825, "acc_norm_stderr": 0.042438692422305246 }, "harness\|hendrycksTest-international_law\|5": { "acc": 0.7355371900826446, "acc_stderr": 0.04026187527591207, "acc_norm": 0.7355371900826446, "acc_norm_stderr": 0.04026187527591207 }, "harness\|hendrycksTest-jurisprudence\|5": { "acc": 0.7314814814814815, "acc_stderr": 0.042844679680521934, "acc_norm": 0.7314814814814815, "acc_norm_stderr": 0.042844679680521934 }, "harness\|hendrycksTest-logical_fallacies\|5": { "acc": 0.6809815950920245, "acc_stderr": 0.03661997551073836, "acc_norm": 0.6809815950920245, "acc_norm_stderr": 0.03661997551073836 }, "harness\|hendrycksTest-machine_learning\|5": { "acc": 0.3125, "acc_stderr": 0.043994650575715215, "acc_norm": 0.3125, "acc_norm_stderr": 0.043994650575715215 }, "harness\|hendrycksTest-management\|5": { "acc": 0.7572815533980582, "acc_stderr": 0.04245022486384495, "acc_norm": 0.7572815533980582, "acc_norm_stderr": 0.04245022486384495 }, "harness\|hendrycksTest-marketing\|5": { "acc": 0.8076923076923077, "acc_stderr": 0.02581923325648372, "acc_norm": 0.8076923076923077, "acc_norm_stderr": 0.02581923325648372 }, "harness\|hendrycksTest-medical_genetics\|5": { "acc": 0.55, "acc_stderr": 0.04999999999999999, "acc_norm": 0.55, "acc_norm_stderr": 0.04999999999999999 }, "harness\|hendrycksTest-miscellaneous\|5": { "acc": 0.7458492975734355, "acc_stderr": 0.015569254692045757, "acc_norm": 0.7458492975734355, "acc_norm_stderr": 0.015569254692045757 }, "harness\|hendrycksTest-moral_disputes\|5": { "acc": 0.6329479768786127, "acc_stderr": 0.025950054337654075, "acc_norm": 0.6329479768786127, "acc_norm_stderr": 0.025950054337654075 }, "harness\|hendrycksTest-moral_scenarios\|5": { "acc": 0.2782122905027933, "acc_stderr": 0.014987325439963539, "acc_norm": 0.2782122905027933, "acc_norm_stderr": 0.014987325439963539 }, "harness\|hendrycksTest-nutrition\|5": { "acc": 0.6274509803921569, "acc_stderr": 0.027684181883302895, "acc_norm": 0.6274509803921569, "acc_norm_stderr": 0.027684181883302895 }, "harness\|hendrycksTest-philosophy\|5": { "acc": 0.6463022508038585, "acc_stderr": 0.027155208103200865, "acc_norm": 0.6463022508038585, "acc_norm_stderr": 0.027155208103200865 }, "harness\|hendrycksTest-prehistory\|5": { "acc": 0.6419753086419753, "acc_stderr": 0.026675611926037103, "acc_norm": 0.6419753086419753, "acc_norm_stderr": 0.026675611926037103 }, "harness\|hendrycksTest-professional_accounting\|5": { "acc": 0.40070921985815605, "acc_stderr": 0.02923346574557308, "acc_norm": 0.40070921985815605, "acc_norm_stderr": 0.02923346574557308 }, "harness\|hendrycksTest-professional_law\|5": { "acc": 0.4198174706649283, "acc_stderr": 0.01260496081608737, "acc_norm": 0.4198174706649283, "acc_norm_stderr": 0.01260496081608737 }, "harness\|hendrycksTest-professional_medicine\|5": { "acc": 0.5257352941176471, "acc_stderr": 0.030332578094555026, "acc_norm": 0.5257352941176471, "acc_norm_stderr": 0.030332578094555026 }, "harness\|hendrycksTest-professional_psychology\|5": { "acc": 0.5555555555555556, "acc_stderr": 0.020102583895887188, "acc_norm": 0.5555555555555556, "acc_norm_stderr": 0.020102583895887188 }, "harness\|hendrycksTest-public_relations\|5": { "acc": 0.6363636363636364, "acc_stderr": 0.046075820907199756, "acc_norm": 0.6363636363636364, "acc_norm_stderr": 0.046075820907199756 }, "harness\|hendrycksTest-security_studies\|5": { "acc": 0.6285714285714286, "acc_stderr": 0.030932858792789848, "acc_norm": 0.6285714285714286, "acc_norm_stderr": 0.030932858792789848 }, "harness\|hendrycksTest-sociology\|5": { "acc": 0.7512437810945274, "acc_stderr": 0.030567675938916714, "acc_norm": 0.7512437810945274, "acc_norm_stderr": 0.030567675938916714 }, "harness\|hendrycksTest-us_foreign_policy\|5": { "acc": 0.81, "acc_stderr": 0.03942772444036625, "acc_norm": 0.81, "acc_norm_stderr": 0.03942772444036625 }, "harness\|hendrycksTest-virology\|5": { "acc": 0.4759036144578313, "acc_stderr": 0.03887971849597264, "acc_norm": 0.4759036144578313, "acc_norm_stderr": 0.03887971849597264 }, "harness\|hendrycksTest-world_religions\|5": { "acc": 0.7777777777777778, "acc_stderr": 0.03188578017686398, "acc_norm": 0.7777777777777778, "acc_norm_stderr": 0.03188578017686398 }, "harness\|truthfulqa:mc\|0": { "mc1": 0.26193390452876375, "mc1_stderr": 0.015392118805015025, "mc2": 0.38301200451667206, "mc2_stderr": 0.013767815310741604 }, "harness\|winogrande\|5": { "acc": 0.7703235990528808, "acc_stderr": 0.011821645601838236 }, "harness\|gsm8k\|5": { "acc": 0.2357846853677028, "acc_stderr": 0.011692515650666792 } } ``` ## Dataset Details ### Dataset Description <!-- Provide a longer summary of what this dataset is. --> - Curated by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] ### Dataset Sources [optional] <!-- Provide the basic links for the dataset. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the dataset is intended to be used. --> ### Direct Use <!-- This section describes suitable use cases for the dataset. --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. --> [More Information Needed] ## Dataset Structure <!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. --> [More Information Needed] ## Dataset Creation ### Curation Rationale <!-- Motivation for the creation of this dataset. --> [More Information Needed] ### Source Data <!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). --> #### Data Collection and Processing <!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. --> [More Information Needed] #### Who are the source data producers? <!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. --> [More Information Needed] ### Annotations [optional] <!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. --> #### Annotation process <!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. --> [More Information Needed] #### Who are the annotators? <!-- This section describes the people or systems who created the annotations. --> [More Information Needed] #### Personal and Sensitive Information <!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations. ## Citation [optional] <!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Dataset Card Authors [optional] [More Information Needed] ## Dataset Card Contact [More Information Needed]
Barnie2/testDataset	--- license: apache-2.0 ---
AnuraSet/AnuraSet_v1.0.0	--- license: mit ---
distilled-one-sec-cv12-each-chunk-uniq/chunk_140	--- dataset_info: features: - name: logits sequence: float32 - name: mfcc sequence: sequence: float64 splits: - name: train num_bytes: 1147145696.0 num_examples: 223528 download_size: 1170538394 dataset_size: 1147145696.0 --- # Dataset Card for "chunk_140" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
Multimodal-Fatima/DTD_parition1_test_facebook_opt_1.3b_Visclues_ns_1880_random	--- dataset_info: features: - name: id dtype: int64 - name: image dtype: image - name: prompt dtype: string - name: true_label dtype: string - name: prediction dtype: string - name: scores sequence: float64 splits: - name: fewshot_1_bs_16 num_bytes: 92562773.0 num_examples: 1880 - name: fewshot_3_bs_16 num_bytes: 93877652.0 num_examples: 1880 download_size: 182697216 dataset_size: 186440425.0 --- # Dataset Card for "DTD_parition1_test_facebook_opt_1.3b_Visclues_ns_1880_random" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
jondurbin/airoboros-gpt4-1.4.1	--- license: cc-by-nc-4.0 --- The same as 1.4, but with coding updates: - rosettacode instructions were removed, due to a few issues found when spot-checking examples - limited the coding examples to fewer languages, to test if a more focused dataset would produce better results
carnival13/xlmr_hard_curr_uda_ep3	--- dataset_info: features: - name: domain_label dtype: int64 - name: pass_label dtype: int64 - name: input dtype: string - name: input_ids sequence: int32 - name: attention_mask sequence: int8 splits: - name: train num_bytes: 774087578 num_examples: 519240 download_size: 233619604 dataset_size: 774087578 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "xlmr_hard_curr_uda_ep3" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
benayas/massive_chatgpt_20pct_v2	--- dataset_info: features: - name: text dtype: string - name: category dtype: string splits: - name: train num_bytes: 750498 num_examples: 11514 download_size: 267643 dataset_size: 750498 configs: - config_name: default data_files: - split: train path: data/train-* ---
TrustLLM/TrustLLM-dataset	--- license: apache-2.0 language: - en configs: - config_name: safety data_files: "safety/json" - config_name: ethics data_files: "ethics/json" - config_name: fairness data_files: "fairness/json" - config_name: robustness data_files: "robustness/json" - config_name: privacy data_files: "privacy/json" - config_name: truthfulness data_files: "truthfulness/json" tags: - llm - trustworthy ai - nlp size_categories: - 10K<n<100K --- # Dataset Card for TrustLLM ## Dataset Summary This repository provides datasets from the TrustLLM benchmark, including six aspects: truthfulness, safety, fairness, robustness, privacy, and machine ethics. To find more details about TrustLLM, please visit the [project website](https://trustllmbenchmark.github.io/TrustLLM-Website/). ## Disclaimer The dataset contains harmful content such as partial pornography, violence, bloodshed, or bias. The opinions expressed in the data do not reflect the views of the TrustLLM team. This dataset is strictly intended for research purposes and should not be used for any other illegal activities. We advocate for the responsible use of large language models. ### Download Use `trustllm` toolkit to download the dataset: [link](https://howiehwong.github.io/TrustLLM/#dataset-download). Use `hugginface` to download the dataset: ```python from datasets import load_dataset # Load all sections dataset = load_dataset("TrustLLM/TrustLLM-dataset") # Load one of the sections dataset = load_dataset("TrustLLM/TrustLLM-dataset", data_dir="safety") ``` ## Contact Contact Us: [trustllm.benchmark@gmail.com](mailto:trustllm.benchmark@gmail.com)
ophycare/icliniq-dataset-1	--- license: llama2 ---
SantiagoPG/doc_qa	--- language: - en ---
moficodes/guanaco-gemma-500	--- dataset_info: features: - name: text dtype: string splits: - name: train num_bytes: 842593 num_examples: 500 download_size: 478887 dataset_size: 842593 configs: - config_name: default data_files: - split: train path: data/train-* ---
Revankumar/fingpt	--- license: mit ---
enzeberg/crowded_fishes	--- license: cc-by-4.0 ---
Kamyar-zeinalipour/ITA_CW	--- dataset_info: features: - name: Clue dtype: string - name: Answer dtype: string - name: couple_occurencies dtype: int64 splits: - name: train num_bytes: 5767721 num_examples: 125202 download_size: 3409199 dataset_size: 5767721 --- # Dataset Card for "ITA_CW" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
ibivibiv/alpaca_tasksource20	--- dataset_info: features: - name: input dtype: string - name: instruction dtype: string - name: output dtype: string splits: - name: train num_bytes: 135229939 num_examples: 253970 download_size: 76708825 dataset_size: 135229939 configs: - config_name: default data_files: - split: train path: data/train-* ---

joey234/sst2_100_1

--- dataset_info: features: - name: idx dtype: int64 - name: sentence dtype: string - name: label dtype: int64 splits: - name: train num_bytes: 12846 num_examples: 100 download_size: 11262 dataset_size: 12846 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "sst2_100_1" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

Reindrob/dsc

--- license: unknown ---

autoevaluate/autoeval-staging-eval-project-29af5371-7254762

--- type: predictions tags: - autotrain - evaluation datasets: - conll2003 eval_info: task: entity_extraction model: elastic/distilbert-base-uncased-finetuned-conll03-english dataset_name: conll2003 dataset_config: conll2003 dataset_split: validation col_mapping: tokens: tokens tags: ner_tags --- # Dataset Card for AutoTrain Evaluator This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset: * Task: Token Classification * Model: elastic/distilbert-base-uncased-finetuned-conll03-english * Dataset: conll2003 To run new evaluation jobs, visit Hugging Face's [automatic evaluation service](https://huggingface.co/spaces/autoevaluate/model-evaluator). ## Contributions Thanks to [@douwekiela](https://huggingface.co/douwekiela) for evaluating this model.

sheriftawfikabbas/3oloum_corpus

--- language: - en pretty_name: "3oloum corpus for scientific abstract" tags: - science abstracts - English license: "gpl-3.0" --- # The 3oloum corpus of scientific titles and abstracts This is a corpus of titles and abstracts of 147,673 scientific articles that were scraped from the following scientific journals: - Nature: from year 1870 to 2021 - Science: from year 1960 to 2020 - Science Advances: from year 2015 to 2020 The corpus has been created for the purpose of contributing to natural language processing (NLP) projects. There are currently *21,309,015* words in the corpus, including the text of titles and abstracts, and excluding non-ASCII strings. Every non-ASCII character has been replaced by the string `<non_ascii>` to facilitate text processing. It is being continuously updated. ## Sample data |Title|Abstract| | :--- | :--- | | Velocity of Light and Measurement of Interplanetary Distances | The combined availability of atomic clocks and of instrumented planetoids traveling in their own solar orbits will offer the possibility of determining their distance from us, and hence interplanetary distances, in terms of the wavelength of the radiation of atomic frequency standards. It can be anticipated that the accuracy of these measurements will be very high and will not depend upon our less accurate knowledge of the velocity of light in terms of the standard meter, the sidereal second, and so on. | | High-Resolution Density Gradient Sedimentation Analysis | The principle of stability for a sample layered in a density-gradient liquid column is discussed, and a method for separating ribonucleoprotein particles by means of sedimentation in the ultracentrifuge is described. | | Daily Light Sensitivity Rhythm in a Rodent | Single 10-minute light periods can cause a phase shift in the rhythm of the daily locomotor activity of flying squirrels otherwise maintained in constant darkness. A daily rhythm of sensitivity to these standard light periods was found. | | Heat-Labile Serum Systems in Fresh-Water Fish | Serum specimens from 18 specimens of 12 different species of freshwater fish were examined for their ability to kill Toxoplasma nonspecifically. This ability was present in all sera except those of two of three great northern pike. The effect was destroyed by exposure to 53<non_ascii><non_ascii>C, 56<non_ascii><non_ascii>C, or zymosan. Complement was demonstrated in all sera except that from one great northern pike, when rabbit erythrocytes were used in the indicator system. | | Chemically Induced Phenocopy of a Tomato Mutant | Lanceolate, a spontaneous leaf-shape mutant which fails to produce cotyledons and plumule in the homozygous condition, shows development if supplied with either adenine or a diffusate obtained from normal seeds. Similar development occurs in a different genetic background. | | Mitotic Arrest by Deuterium Oxide | In marine invertebrate eggs, where cell divisions occur without growth, deuterium oxide produces arrest of, or serious delay in, mitosis and cytokinesis. All stages requiring assembly or operation of mechanical structures in the cytoplasm are sensitive to D.O. The block is reversible in some cells. | | Nonlogarithmic Linear Titration Curves | Titration curves can be based on linear nonlogarithmic forms of the equilibrium equation of a dissociation reaction. From such curves, in contrast to those based on logarithmic transformations, both the end point of the titration and the dissociation constant can be derived. | | On the Function of Corticothalamic Neurons | The effect of the synchronous discharge of a large population of corticothalamic neurons on activity within the somatosensory relay nuclei has been studied. Thalamic responses to peripheral nerve stimulation are depressed by activity in corticothalamic neurons. A subconvulsive dose of strychnine, given intravenously, changes this depression to enhancement. | | Occurrence of Scandium-46 and Cesium-134 in Radioactive Fallout | Two hitherto unreported induced radionuclides, scandium-46 and cesium-134, have been detected in fallout material. Identification was made by chemical separation and gamma scintillation spectrometry. While the origin of these materials is not known, possible routes of formation from stable elements are suggested. | | Degree of Obesity and Serum Cholesterol Level | No significant correlation was found between the serum cholesterol level and weight, weight corrected for frame size, or thickness of the fat shadow in medical students (mean age, 22 years). | | Neural and Hypophyseal Colloid Deposition in the Collared Lemming | Feral and captive lemmings from Churchill, Manitoba, are subject to a unique pathological process in which colloidal material is deposited in bloodvessel walls at scattered points through the central nervous system. Destruction of nervous tissue at these foci is progressive, and colloidal masses in the vascular lumina of the hypothalamus appear to become fixed in the capillaries of the hypophyseal anterior lobe. Inflammatory reactions are never associated with the lesions, and the latter are larger and more numerous in older animals in warmer environments. | | On Pleistocene Surface Temperatures of the North Atlantic and Arctic Oceans | Two additional interpretations are given for the important data of D. B. Ericson on the correlation of coiling directions of Globigerina pachyderma in late Pleistocene North Atlantic sediments with ocean surface temperatures. One interpretation relates the distribution of this species to the distribution and circulation of ocean water masses. On the basis of our ice-age theory, our second interpretation uses the data and correlations of Ericson to establish temperature limits of a thermal node, a line on which glacial and interglacial temperatures were equal, for the North Atlantic Ocean. This line crosses the strait between Greenland and Scandinavia. Further, Ericson9s interpretation of the 7.2<non_ascii><non_ascii>C isotherm implies that the glacial-stage surface waters of the Arctic Ocean were between 0<non_ascii><non_ascii> and 3.5<non_ascii><non_ascii>C. | | Genetic and Environmental Control of Flowering in Trifolium repens in the Tropics | Trifolium repens at low elevations expressed wide genetic variation in tendency to flower. Clones classified as flowering or nonflowering were subjected to temperatures associated with high elevations. Flowering in "nonflowering" clones was induced under warm-day-cool-night treatments. It is proposed that in the tropics, low temperatures associated with high elevations are an important factor in determining flowering, and therefore ability to persist, in plants which are long-day and temperature sensitive. | | Mammalian Liver <non_ascii><non_ascii>-Glucuronidase for Hydrolysis of Steroidal Conjugates | Although the rate of hydrolysis by mammalian <non_ascii><non_ascii>-glucuronidase appears to be inhibited by methylene chloride or carbon tetrachloride with the standard technique (phenolphthalein glucuronide as a substrate), the release of steroidal conjugates under conditions generally employed does not appear to be affected. | | Glucuronidase Activation: Enzyme Action at an Interface | The potentiating action of chloroform on bacterial <non_ascii><non_ascii>-glucuronidase has been shown to increase as the interface area between the two liquid phases increases. Prior extraction of the enzyme with chloroform causes a loss rather than an increase in activity. It is tentatively suggested that the correlation between activity and interface area may reflect a phenomenon of enzyme action at a liquid/liquid interface. | | Characterization of Endogenous Ethanol in the Mammal | Ethanol has been isolated from the tissues of several animal species in amounts ranging from 23 to 145 <non_ascii><non_ascii>mole/100 gm of tissue. Intestinal bacterial flora appear to be excluded as a source of this ethanol. Radioactivity from pyruvate-2-C14 appeared in ethanol after incubation with liver slices; this finding indicates an endogenous synthesis. | | Reciprocal Inhibition as Indicated by a Differential Staining Reaction | Neurohistological and neurophysiological studies have shown that the bilaterally represented Mauthner9s cells in teleosts are related both structurally and functionally. The VIIIth nerve afferents, as well as the axoaxonal collaterals, display a distribution pattern which supports the concept of polar function of the neuron. Inasmuch as it is possible to alter the staining reaction of both the Mauthner9s cells by unilateral stimulation of the entering VIIIth nerve roots, it is proposed that the synaptic endings serve principally as activators and that neuronal excitation or inhibition is determined by the chemical state of the dendrites, the cell body, and the axon hillock region. | | Orientation of Migratory Restlessness in the White-Crowned Sparrow | Individuals of two migratory races of white-crowned sparrows (Zonotrichia leucophrys) caged under an open sky showed a pronounced orientation in their night restlessness during normal periods of migration for the species. In August and September 1958 most birds showed a southerly orientation at night; daytime activity was random to somewhat northerly. In April and May 1959 most birds showed a strong northerly orientation at night; daytime activity was random to somewhat southerly (1). | | State of Dynamic Equilibrium in Protein of Mammalian Cells | Labeled strain L cells in suspension tissue culture showed no degradation of protein when maintained in logarithmic growth. Although the protein of these cells was not in dynamic equilibrium, the conclusions cannot be transferred to the intact mammalian organism. | | Mosses as Possible Sources of Antibiotics | An examination of 12 species of mosses has indicated that three produce substances capable of inhibiting the growth of various bacteria and other fungi. The method of extraction included several solvents. The extracts were not consistent in their antagonistic activity against the various species of microorganisms, nor were those that displayed antibiotic action always effective against the same organisms. Results indicate unstable products as well as physiological variation in the mosses. |

infinityofspace/python_codestyles-random-1k

--- configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* dataset_info: features: - name: code dtype: string - name: code_codestyle dtype: int64 - name: style_context dtype: string - name: style_context_codestyle dtype: int64 - name: label dtype: int64 splits: - name: train num_bytes: 3604934957 num_examples: 308000 - name: test num_bytes: 645620388 num_examples: 56400 download_size: 671035436 dataset_size: 4250555345 license: mit tags: - python - code-style - random size_categories: - 100K<n<1M --- # Dataset Card for "python_codestyles-random-1k" This dataset contains negative and positive examples with python code of compliance with a code style. A positive example represents compliance with the code style (label is 1). Each example is composed of two components, the first component consists of a code that either conforms to the code style or violates it and the second component corresponding to an example code that already conforms to a code style. In total, the dataset contains `1.000` completely different code styles. The code styles differ in at least one codestyle rule, which is called a `random` codestyle dataset variant. The dataset consists of a training and test group, with none of the code styles overlapping between groups. In addition, both groups contain completely different underlying codes. The examples contain source code from the following repositories: | repository | tag or commit | |:-----------------------------------------------------------------------:|:----------------------------------------:| | [TheAlgorithms/Python](https://github.com/TheAlgorithms/Python) | f614ed72170011d2d439f7901e1c8daa7deac8c4 | | [huggingface/transformers](https://github.com/huggingface/transformers) | v4.31.0 | | [huggingface/datasets](https://github.com/huggingface/datasets) | 2.13.1 | | [huggingface/diffusers](https://github.com/huggingface/diffusers) | v0.18.2 | | [huggingface/accelerate](https://github.com/huggingface/accelerate) | v0.21.0 | You can find the corresponding code styles of the examples in the file [additional_data.json](additional_data.json). The code styles in the file are split by training and test group and the index corresponds to the class for the columns `code_codestyle` and `style_context_codestyle` in the dataset. There are 364.400 samples in total and 182.200 positive and 182.200 negative samples.

NTA-Dev/training_pdfs

--- license: apache-2.0 ---

EdiOapsie/TheBlueTireBook

--- license: apache-2.0 ---

Hieu-Pham/cooking_squad

--- license: mit ---

jlbaker361/small_subtraction_decimal

--- configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* dataset_info: features: - name: input dtype: string - name: output dtype: float64 - name: text dtype: string splits: - name: train num_bytes: 2030.2222222222222 num_examples: 40 - name: test num_bytes: 253.77777777777777 num_examples: 5 download_size: 4553 dataset_size: 2284.0 --- # Dataset Card for "small_subtraction_decimal" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

SuperAGI/SAM_Dataset

--- dataset_info: features: - name: Question dtype: string - name: Answer dtype: string splits: - name: train num_bytes: 192091934 num_examples: 135119 download_size: 88166828 dataset_size: 192091934 configs: - config_name: default data_files: - split: train path: data/train-* ---

anan-2024/twitter_dataset_1713023266

--- dataset_info: features: - name: id dtype: string - name: tweet_content dtype: string - name: user_name dtype: string - name: user_id dtype: string - name: created_at dtype: string - name: url dtype: string - name: favourite_count dtype: int64 - name: scraped_at dtype: string - name: image_urls dtype: string splits: - name: train num_bytes: 105089 num_examples: 281 download_size: 58528 dataset_size: 105089 configs: - config_name: default data_files: - split: train path: data/train-* ---

catinthebag/Indo4B-Combined

--- language: - id license: mit dataset_info: features: - name: text dtype: string splits: - name: train num_bytes: 25012332583 num_examples: 232763064 download_size: 15176365901 dataset_size: 25012332583 configs: - config_name: default data_files: - split: train path: data/train-* --- This is the entire Indo4B dataset, combined into a single file. The original dataset can be found here: https://github.com/IndoNLP/indonlu This is a combination of all the different files in the compressed .tar.xz. The goal is so that anyone who's interested in Indonesian NLP can fairly simply load this dataset from huggingface, already combined in full. Note the original files consists of line-separated strings. This dataset just combines them while removing the available blank lines.

3lydatta/Daniel

--- license: openrail ---

joujiboi/japanese-knowledge-base

--- license: cc-by-nc-4.0 task_categories: - question-answering - text-generation language: - en tags: - language - japanese language - nihongo - 日本語 size_categories: - 1K<n<10K pretty_name: Japanese Knowledge Base --- # Japanese Knowledge Base JKB (Japanese Knowledge Base) is a work-in-progress question and answer dataset on the Japanese language. The goal of JKB is to provide training data for large language models to better answer questions about the Japanese language, particularly for learners of Japanese. ## The dataset contains topics about: * N5 to N1 grammar * Structure and word order * The writing systems * Word types * Particles and the commonly confused ones * Conjugation * Verbs and verb types * Adjectives and adjective types * Formality * Name suffixes ## The dataset will not focus on: * Translation * Definitions of words * Sentence nuance ## Sample ``` Question: What is a common usage scenario for 〜たり〜たり? Answer: The 〜たり〜たり structure is for listing actions as examples among various possibilities. It is commonly used to describe routines or plans. For example, one might use it to describe what they typically do on their days off or what they plan to do during a vacation. Question: How do you use 思う with na-adjectives? Answer: For na-adjectives, you can attach だ to the adjective in its plain form and then add と思う. For example, if you think someone is happy, you could say "幸せだと思います". Question: How do you use と思う with i-adjectives? Answer: To use 〜と思う with i-adjectives, you simply take the i-adjective in its plain form and attach と思う to it. For example, if you think something is hot (熱い), you can say "熱いと思う". Question: Is it possible to use 〜たい in a question? Answer: Yes, you can use 〜たい to ask about someone's desires or wishes, but be cautious when using it with superiors or elders as it can be considered impolite. ``` ## Citation This dataset uses the `Creative Commons Attribution Non Commercial 4.0` licence which means you may use my dataset for non-commercial purposes and you must give credit. ``` @misc{Japanese Knowledge Base, title = {Japanese Knowledge Base: A question and answer dataset on the Japanese language}, author = {JawGBoi}, year = {2023}, publisher = {HuggingFace}, journal = {HuggingFace repository}, howpublished = {\url{https://huggingface.co/datasets/joujiboi/japanese-knowledge-base}}, } ```

kpriyanshu256/MultiTabQA-multitable_pretraining-Salesforce-codet5-base_train-html-117000

--- dataset_info: features: - name: input_ids sequence: sequence: int32 - name: attention_mask sequence: sequence: int8 - name: labels sequence: sequence: int64 splits: - name: train num_bytes: 13336000 num_examples: 1000 download_size: 660107 dataset_size: 13336000 configs: - config_name: default data_files: - split: train path: data/train-* ---

TrainingDataPro/hand-gesture-recognition-dataset

--- language: - en license: cc-by-nc-nd-4.0 task_categories: - video-classification tags: - code dataset_info: features: - name: set_id dtype: int32 - name: fist dtype: string - name: four dtype: string - name: me dtype: string - name: one dtype: string - name: small dtype: string splits: - name: train num_bytes: 1736 num_examples: 28 download_size: 1510134076 dataset_size: 1736 --- # Hand Gesture Recognition Dataset The dataset consists of videos showcasing individuals demonstrating 5 different hand gestures (*"one", "four", "small", "fist", and "me"*). Each video captures a person prominently displaying a single hand gesture, allowing for accurate identification and differentiation of the gestures. The dataset offers a diverse range of individuals performing the gestures, enabling the exploration of variations in hand shapes, sizes, and movements across different individuals. The videos in the dataset are recorded in reasonable lighting conditions and with adequate resolution, to ensure that the hand gestures can be easily observed and studied. ### The dataset's possible applications: - hand gesture recognition - gesture-based control systems - virtual reality interactions - sign language analysis - human pose estimation and action analysis - security and authentication systems ![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F618942%2F02149459e1fc1f76e2575dcdba6ec406%2FMacBook%20Air%20-%201.png?generation=1689667735287012&alt=media) # Get the dataset ### This is just an example of the data Leave a request on [**https://trainingdata.pro/data-market**](https://trainingdata.pro/data-market?utm_source=huggingface&utm_medium=cpc&utm_campaign=hand-gesture-recognition-dataset) to discuss your requirements, learn about the price and buy the dataset. # Content - **files**: includes folders corresponding to people and containing videos with 5 different shown gestures, each file is named according to the captured gesture - **.csv** file: contains information about files in the dataset ### Hand gestures in the dataset: - "one" - "four" - "small" - "clenched fist" - "me" ### File with the extension .csv includes the following information: - **set_id**: id of the set of videos, - **one**: link to the video with "one" gesture, - **four**: link to the video with "four" gesture, - **small**: link to the video with "small" gesture, - **fist**: link to the video with "fist" gesture, - **me**: link to the video with "me" gesture # Videos with hand gestures might be collected in accordance with your requirements. ## [**TrainingData**](https://trainingdata.pro/data-market?utm_source=huggingface&utm_medium=cpc&utm_campaign=hand-gesture-recognition-dataset) provides high-quality data annotation tailored to your needs More datasets in TrainingData's Kaggle account: **https://www.kaggle.com/trainingdatapro/datasets** TrainingData's GitHub: **https://github.com/Trainingdata-datamarket/TrainingData_All_datasets**

thientran/autotrain-data-favs_bot

--- language: - en --- # AutoTrain Dataset for project: favs_bot ## Dataset Descritpion This dataset has been automatically processed by AutoTrain for project favs_bot. ### Languages The BCP-47 code for the dataset's language is en. ## Dataset Structure ### Data Instances A sample from this dataset looks as follows: ```json [ { "feat_id": "13104", "tokens": [ "Jackie", "Frank" ], "feat_pos_tags": [ 21, 21 ], "feat_chunk_tags": [ 5, 16 ], "tags": [ 3, 7 ] }, { "feat_id": "9297", "tokens": [ "U.S.", "lauds", "Russian-Chechen", "deal", "." ], "feat_pos_tags": [ 21, 20, 15, 20, 7 ], "feat_chunk_tags": [ 5, 16, 16, 16, 22 ], "tags": [ 0, 8, 1, 8, 8 ] } ] ``` ### Dataset Fields The dataset has the following fields (also called "features"): ```json { "feat_id": "Value(dtype='string', id=None)", "tokens": "Sequence(feature=Value(dtype='string', id=None), length=-1, id=None)", "feat_pos_tags": "Sequence(feature=ClassLabel(num_classes=47, names=['\"', '#', '$', \"''\", '(', ')', ',', '.', ':', 'CC', 'CD', 'DT', 'EX', 'FW', 'IN', 'JJ', 'JJR', 'JJS', 'LS', 'MD', 'NN', 'NNP', 'NNPS', 'NNS', 'NN|SYM', 'PDT', 'POS', 'PRP', 'PRP$', 'RB', 'RBR', 'RBS', 'RP', 'SYM', 'TO', 'UH', 'VB', 'VBD', 'VBG', 'VBN', 'VBP', 'VBZ', 'WDT', 'WP', 'WP$', 'WRB', '``'], id=None), length=-1, id=None)", "feat_chunk_tags": "Sequence(feature=ClassLabel(num_classes=23, names=['B-ADJP', 'B-ADVP', 'B-CONJP', 'B-INTJ', 'B-LST', 'B-NP', 'B-PP', 'B-PRT', 'B-SBAR', 'B-UCP', 'B-VP', 'I-ADJP', 'I-ADVP', 'I-CONJP', 'I-INTJ', 'I-LST', 'I-NP', 'I-PP', 'I-PRT', 'I-SBAR', 'I-UCP', 'I-VP', 'O'], id=None), length=-1, id=None)", "tags": "Sequence(feature=ClassLabel(num_classes=9, names=['B-LOC', 'B-MISC', 'B-ORG', 'B-PER', 'I-LOC', 'I-MISC', 'I-ORG', 'I-PER', 'O'], id=None), length=-1, id=None)" } ``` ### Dataset Splits This dataset is split into a train and validation split. The split sizes are as follow: | Split name | Num samples | | ------------ | ------------------- | | train | 10013 | | valid | 4029 |

georgeyw/TinyStoriesV2-GPT4-10k

--- license: cdla-sharing-1.0 ---

quaeast/multimodal_sarcasm_detection

--- language: - en --- copy of [data-of-multimodal-sarcasm-detection](https://github.com/headacheboy/data-of-multimodal-sarcasm-detection) ```python # usage from datasets import load_dataset from transformers import CLIPImageProcessor, CLIPTokenizer from torch.utils.data import DataLoader image_processor = CLIPImageProcessor.from_pretrained(clip_path) tokenizer = CLIPTokenizer.from_pretrained(clip_path) def tokenization(example): text_inputs = tokenizer(example["text"], truncation=True, padding=True, return_tensors="pt") image_inputs = image_processor(example["image"], return_tensors="pt") return {'pixel_values': image_inputs['pixel_values'], 'input_ids': text_inputs['input_ids'], 'attention_mask': text_inputs['attention_mask'], "label": example["label"]} dataset = load_dataset('quaeast/multimodal_sarcasm_detection') dataset.set_transform(tokenization) # get torch dataloader train_dl = DataLoader(dataset['train'], batch_size=256, shuffle=True) test_dl = DataLoader(dataset['test'], batch_size=256, shuffle=True) val_dl = DataLoader(dataset['validation'], batch_size=256, shuffle=True) ```

muhammadravi251001/tydiqaid-nli

--- annotations_creators: - machine-generated - manual-partial-validation language_creators: - expert-generated language: - id license: unknown multilinguality: - monolingual size_categories: - 1K<n<10K source_datasets: - TyDI-QA-ID task_categories: - text-classification task_ids: - natural-language-inference pretty_name: TyDI-QA-ID-NLI dataset_info: features: - name: premise dtype: string - name: hypothesis dtype: string - name: label dtype: class_label: names: '0': entailment '1': neutral '2': contradiction config_name: tydiqaid-nli splits: - name: train num_bytes: 3207000 num_examples: 9695 - name: validation num_bytes: 373750 num_examples: 1131 - name: test num_bytes: 565625 num_examples: 1171 download_size: 4146375 dataset_size: 11997 --- # Dataset Card for TyDI-QA-ID-NLI ## Table of Contents - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - **Repository:** [Hugging Face](https://huggingface.co/datasets/muhammadravi251001/tydiqaid-nli) - **Point of Contact:** [Hugging Face](https://huggingface.co/datasets/muhammadravi251001/tydiqaid-nli) - **Experiment:** [Github](https://github.com/muhammadravi251001/multilingual-qas-with-nli) ### Dataset Summary The TyDI-QA-ID-NLI dataset is derived from the TyDI-QA-ID question answering dataset, utilizing named entity recognition (NER), chunking tags, Regex, and embedding similarity techniques to determine its contradiction sets. Collected through this process, the dataset comprises various columns beyond premise, hypothesis, and label, including properties aligned with NER and chunking tags. This dataset is designed to facilitate Natural Language Inference (NLI) tasks and contains information extracted from diverse sources to provide comprehensive coverage. Each data instance encapsulates premise, hypothesis, label, and additional properties pertinent to NLI evaluation. ### Supported Tasks and Leaderboards - Natural Language Inference for Indonesian ### Languages Indonesian ## Dataset Structure ### Data Instances An example of `test` looks as follows. ``` { "premise": "Manuls sering kali terlihat di padang rumput stepa Asia Tengah wilayah Mongolia, Cina dan Dataran Tinggi Tibet, di mana rekor elevasi 5.050 m (16.570 kaki) dilaporkan.[5] Mereka secara luas tersebar di daerah dataran tinggi dan lekukan Intermountain serta padang rumput pegunungan di Kyrgyzstan dan Kazakhstan.[6] Di Rusia, mereka muncul sesekali di Transkaukasus dan daerah Transbaikal, di sepanjang perbatasan dengan utara-timur Kazakhstan, dan di sepanjang perbatasan dengan Mongolia dan Cina di Altai, Tyva Buryatia, dan Chita republik. Pada musim semi 1997, trek yang ditemukan di Timur Sayan pada ketinggian 2.470 m (8.100 kaki) dalam 4,5cm (1,8 in) lapisan salju yang tebal. Trek ini dianggap fakta pertama yang dapat dibuktikan mendiami daerah manuls. Analisis DNA dari kotoran individu ini menegaskan kehadiran spesies.[7] Populasi di barat daya, yaitu wilayah Laut Kaspia, Afghanistan dan Pakistan, berkurang, terisolasi dan jarang [8][9]. Pada tahun 2008, seekor individu terekam kamera di Iran Khojir National Park untuk pertama kalinya [10].,Dimanakah Kucing Pallas pertama kali ditemukan ?", "hypothesis": ",Dimanakah Kucing Pallas pertama kali ditemukan ? 2008", "label": 0 } ``` ### Data Fields The data fields are: - `premise`: a `string` feature - `hypothesis`: a `string` feature - `label`: a classification label, with possible values including `entailment` (0), `neutral` (1), `contradiction` (2). ### Data Splits #TODO The data is split across `train`, `valid`, and `test`. | split | # examples | |----------|-------:| |train| 9695| |valid| 1131| |test| 1171| ## Dataset Creation ### Curation Rationale Indonesian NLP is considered under-resourced. We need NLI dataset to fine-tuning the NLI model to utilizing them for QA models in order to improving the performance of the QA's. ### Source Data #### Initial Data Collection and Normalization We collect the data from the prominent QA dataset in Indonesian. The annotation fully by the original dataset's researcher. #### Who are the source language producers? This synthetic data was produced by machine, but the original data was produced by human. ### Personal and Sensitive Information There might be some personal information coming from Wikipedia and news, especially the information of famous/important people. ## Considerations for Using the Data ### Discussion of Biases The QA dataset (so the NLI-derived from them) is created using premise sentences taken from Wikipedia and news. These data sources may contain some bias. ### Other Known Limitations No other known limitations ## Additional Information ### Dataset Curators This dataset is the result of the collaborative work of Indonesian researchers from the University of Indonesia, Mohamed bin Zayed University of Artificial Intelligence, and the Korea Advanced Institute of Science & Technology. ### Licensing Information The license is Unknown. Please contact authors for any information on the dataset.

pyakymenko/test_repo

--- dataset_info: features: - name: audio dtype: audio - name: sentence dtype: string splits: - name: train num_bytes: 167117.0 num_examples: 3 download_size: 162079 dataset_size: 167117.0 --- # Dataset Card for "test_repo" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

open-llm-leaderboard/details_Muhammad2003__Myriad-7B-Slerp

--- pretty_name: Evaluation run of Muhammad2003/Myriad-7B-Slerp dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [Muhammad2003/Myriad-7B-Slerp](https://huggingface.co/Muhammad2003/Myriad-7B-Slerp)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 63 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the aggregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_Muhammad2003__Myriad-7B-Slerp\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-04-05T21:09:13.517339](https://huggingface.co/datasets/open-llm-leaderboard/details_Muhammad2003__Myriad-7B-Slerp/blob/main/results_2024-04-05T21-09-13.517339.json)(note\ \ that their might be results for other tasks in the repos if successive evals didn't\ \ cover the same tasks. You find each in the results and the \"latest\" split for\ \ each eval):\n\n```python\n{\n \"all\": {\n \"acc\": 0.6498757467364364,\n\ \ \"acc_stderr\": 0.0320415504432472,\n \"acc_norm\": 0.6488639096760553,\n\ \ \"acc_norm_stderr\": 0.032715942329960675,\n \"mc1\": 0.6328029375764994,\n\ \ \"mc1_stderr\": 0.016874805001453184,\n \"mc2\": 0.7800372751713768,\n\ \ \"mc2_stderr\": 0.013681851851800382\n },\n \"harness|arc:challenge|25\"\ : {\n \"acc\": 0.712457337883959,\n \"acc_stderr\": 0.013226719056266127,\n\ \ \"acc_norm\": 0.7320819112627986,\n \"acc_norm_stderr\": 0.012942030195136438\n\ \ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.717486556462856,\n\ \ \"acc_stderr\": 0.004493015945599716,\n \"acc_norm\": 0.891256721768572,\n\ \ \"acc_norm_stderr\": 0.0031068060075356255\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\ : {\n \"acc\": 0.31,\n \"acc_stderr\": 0.04648231987117316,\n \ \ \"acc_norm\": 0.31,\n \"acc_norm_stderr\": 0.04648231987117316\n \ \ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.6370370370370371,\n\ \ \"acc_stderr\": 0.04153948404742398,\n \"acc_norm\": 0.6370370370370371,\n\ \ \"acc_norm_stderr\": 0.04153948404742398\n },\n \"harness|hendrycksTest-astronomy|5\"\ : {\n \"acc\": 0.7105263157894737,\n \"acc_stderr\": 0.03690677986137283,\n\ \ \"acc_norm\": 0.7105263157894737,\n \"acc_norm_stderr\": 0.03690677986137283\n\ \ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.64,\n\ \ \"acc_stderr\": 0.04824181513244218,\n \"acc_norm\": 0.64,\n \ \ \"acc_norm_stderr\": 0.04824181513244218\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\ : {\n \"acc\": 0.7056603773584905,\n \"acc_stderr\": 0.028049186315695255,\n\ \ \"acc_norm\": 0.7056603773584905,\n \"acc_norm_stderr\": 0.028049186315695255\n\ \ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.7708333333333334,\n\ \ \"acc_stderr\": 0.03514697467862388,\n \"acc_norm\": 0.7708333333333334,\n\ \ \"acc_norm_stderr\": 0.03514697467862388\n },\n \"harness|hendrycksTest-college_chemistry|5\"\ : {\n \"acc\": 0.49,\n \"acc_stderr\": 0.05024183937956911,\n \ \ \"acc_norm\": 0.49,\n \"acc_norm_stderr\": 0.05024183937956911\n \ \ },\n \"harness|hendrycksTest-college_computer_science|5\": {\n \"acc\"\ : 0.56,\n \"acc_stderr\": 0.04988876515698589,\n \"acc_norm\": 0.56,\n\ \ \"acc_norm_stderr\": 0.04988876515698589\n },\n \"harness|hendrycksTest-college_mathematics|5\"\ : {\n \"acc\": 0.29,\n \"acc_stderr\": 0.04560480215720684,\n \ \ \"acc_norm\": 0.29,\n \"acc_norm_stderr\": 0.04560480215720684\n \ \ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.653179190751445,\n\ \ \"acc_stderr\": 0.036291466701596636,\n \"acc_norm\": 0.653179190751445,\n\ \ \"acc_norm_stderr\": 0.036291466701596636\n },\n \"harness|hendrycksTest-college_physics|5\"\ : {\n \"acc\": 0.37254901960784315,\n \"acc_stderr\": 0.04810840148082636,\n\ \ \"acc_norm\": 0.37254901960784315,\n \"acc_norm_stderr\": 0.04810840148082636\n\ \ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\ \ 0.76,\n \"acc_stderr\": 0.04292346959909283,\n \"acc_norm\": 0.76,\n\ \ \"acc_norm_stderr\": 0.04292346959909283\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\ : {\n \"acc\": 0.574468085106383,\n \"acc_stderr\": 0.03232146916224468,\n\ \ \"acc_norm\": 0.574468085106383,\n \"acc_norm_stderr\": 0.03232146916224468\n\ \ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.4824561403508772,\n\ \ \"acc_stderr\": 0.04700708033551038,\n \"acc_norm\": 0.4824561403508772,\n\ \ \"acc_norm_stderr\": 0.04700708033551038\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\ : {\n \"acc\": 0.5310344827586206,\n \"acc_stderr\": 0.04158632762097828,\n\ \ \"acc_norm\": 0.5310344827586206,\n \"acc_norm_stderr\": 0.04158632762097828\n\ \ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\ : 0.41534391534391535,\n \"acc_stderr\": 0.025379524910778398,\n \"\ acc_norm\": 0.41534391534391535,\n \"acc_norm_stderr\": 0.025379524910778398\n\ \ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.47619047619047616,\n\ \ \"acc_stderr\": 0.04467062628403273,\n \"acc_norm\": 0.47619047619047616,\n\ \ \"acc_norm_stderr\": 0.04467062628403273\n },\n \"harness|hendrycksTest-global_facts|5\"\ : {\n \"acc\": 0.3,\n \"acc_stderr\": 0.046056618647183814,\n \ \ \"acc_norm\": 0.3,\n \"acc_norm_stderr\": 0.046056618647183814\n \ \ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\": 0.7838709677419354,\n\ \ \"acc_stderr\": 0.02341529343356853,\n \"acc_norm\": 0.7838709677419354,\n\ \ \"acc_norm_stderr\": 0.02341529343356853\n },\n \"harness|hendrycksTest-high_school_chemistry|5\"\ : {\n \"acc\": 0.5123152709359606,\n \"acc_stderr\": 0.035169204442208966,\n\ \ \"acc_norm\": 0.5123152709359606,\n \"acc_norm_stderr\": 0.035169204442208966\n\ \ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \ \ \"acc\": 0.7,\n \"acc_stderr\": 0.046056618647183814,\n \"acc_norm\"\ : 0.7,\n \"acc_norm_stderr\": 0.046056618647183814\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\ : {\n \"acc\": 0.7757575757575758,\n \"acc_stderr\": 0.03256866661681102,\n\ \ \"acc_norm\": 0.7757575757575758,\n \"acc_norm_stderr\": 0.03256866661681102\n\ \ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\ : 0.803030303030303,\n \"acc_stderr\": 0.028335609732463362,\n \"\ acc_norm\": 0.803030303030303,\n \"acc_norm_stderr\": 0.028335609732463362\n\ \ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\ \ \"acc\": 0.9119170984455959,\n \"acc_stderr\": 0.02045374660160103,\n\ \ \"acc_norm\": 0.9119170984455959,\n \"acc_norm_stderr\": 0.02045374660160103\n\ \ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \ \ \"acc\": 0.658974358974359,\n \"acc_stderr\": 0.024035489676335082,\n \ \ \"acc_norm\": 0.658974358974359,\n \"acc_norm_stderr\": 0.024035489676335082\n\ \ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\ acc\": 0.3074074074074074,\n \"acc_stderr\": 0.028133252578815632,\n \ \ \"acc_norm\": 0.3074074074074074,\n \"acc_norm_stderr\": 0.028133252578815632\n\ \ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \ \ \"acc\": 0.6722689075630253,\n \"acc_stderr\": 0.03048991141767323,\n \ \ \"acc_norm\": 0.6722689075630253,\n \"acc_norm_stderr\": 0.03048991141767323\n\ \ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\ : 0.36423841059602646,\n \"acc_stderr\": 0.03929111781242742,\n \"\ acc_norm\": 0.36423841059602646,\n \"acc_norm_stderr\": 0.03929111781242742\n\ \ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\ : 0.8440366972477065,\n \"acc_stderr\": 0.01555580271359017,\n \"\ acc_norm\": 0.8440366972477065,\n \"acc_norm_stderr\": 0.01555580271359017\n\ \ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\ : 0.5092592592592593,\n \"acc_stderr\": 0.034093869469927006,\n \"\ acc_norm\": 0.5092592592592593,\n \"acc_norm_stderr\": 0.034093869469927006\n\ \ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\ : 0.8431372549019608,\n \"acc_stderr\": 0.02552472232455335,\n \"\ acc_norm\": 0.8431372549019608,\n \"acc_norm_stderr\": 0.02552472232455335\n\ \ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\ acc\": 0.8143459915611815,\n \"acc_stderr\": 0.025310495376944856,\n \ \ \"acc_norm\": 0.8143459915611815,\n \"acc_norm_stderr\": 0.025310495376944856\n\ \ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.6860986547085202,\n\ \ \"acc_stderr\": 0.031146796482972465,\n \"acc_norm\": 0.6860986547085202,\n\ \ \"acc_norm_stderr\": 0.031146796482972465\n },\n \"harness|hendrycksTest-human_sexuality|5\"\ : {\n \"acc\": 0.7938931297709924,\n \"acc_stderr\": 0.03547771004159465,\n\ \ \"acc_norm\": 0.7938931297709924,\n \"acc_norm_stderr\": 0.03547771004159465\n\ \ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\ \ 0.7603305785123967,\n \"acc_stderr\": 0.03896878985070416,\n \"\ acc_norm\": 0.7603305785123967,\n \"acc_norm_stderr\": 0.03896878985070416\n\ \ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.7592592592592593,\n\ \ \"acc_stderr\": 0.04133119440243839,\n \"acc_norm\": 0.7592592592592593,\n\ \ \"acc_norm_stderr\": 0.04133119440243839\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\ : {\n \"acc\": 0.7852760736196319,\n \"acc_stderr\": 0.032262193772867744,\n\ \ \"acc_norm\": 0.7852760736196319,\n \"acc_norm_stderr\": 0.032262193772867744\n\ \ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.42857142857142855,\n\ \ \"acc_stderr\": 0.04697113923010212,\n \"acc_norm\": 0.42857142857142855,\n\ \ \"acc_norm_stderr\": 0.04697113923010212\n },\n \"harness|hendrycksTest-management|5\"\ : {\n \"acc\": 0.7572815533980582,\n \"acc_stderr\": 0.04245022486384495,\n\ \ \"acc_norm\": 0.7572815533980582,\n \"acc_norm_stderr\": 0.04245022486384495\n\ \ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.8760683760683761,\n\ \ \"acc_stderr\": 0.021586494001281365,\n \"acc_norm\": 0.8760683760683761,\n\ \ \"acc_norm_stderr\": 0.021586494001281365\n },\n \"harness|hendrycksTest-medical_genetics|5\"\ : {\n \"acc\": 0.7,\n \"acc_stderr\": 0.046056618647183814,\n \ \ \"acc_norm\": 0.7,\n \"acc_norm_stderr\": 0.046056618647183814\n \ \ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.8237547892720306,\n\ \ \"acc_stderr\": 0.013625556907993464,\n \"acc_norm\": 0.8237547892720306,\n\ \ \"acc_norm_stderr\": 0.013625556907993464\n },\n \"harness|hendrycksTest-moral_disputes|5\"\ : {\n \"acc\": 0.7312138728323699,\n \"acc_stderr\": 0.023868003262500104,\n\ \ \"acc_norm\": 0.7312138728323699,\n \"acc_norm_stderr\": 0.023868003262500104\n\ \ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.4223463687150838,\n\ \ \"acc_stderr\": 0.016519594275297117,\n \"acc_norm\": 0.4223463687150838,\n\ \ \"acc_norm_stderr\": 0.016519594275297117\n },\n \"harness|hendrycksTest-nutrition|5\"\ : {\n \"acc\": 0.7156862745098039,\n \"acc_stderr\": 0.02582916327275748,\n\ \ \"acc_norm\": 0.7156862745098039,\n \"acc_norm_stderr\": 0.02582916327275748\n\ \ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.7009646302250804,\n\ \ \"acc_stderr\": 0.02600330111788514,\n \"acc_norm\": 0.7009646302250804,\n\ \ \"acc_norm_stderr\": 0.02600330111788514\n },\n \"harness|hendrycksTest-prehistory|5\"\ : {\n \"acc\": 0.7407407407407407,\n \"acc_stderr\": 0.024383665531035454,\n\ \ \"acc_norm\": 0.7407407407407407,\n \"acc_norm_stderr\": 0.024383665531035454\n\ \ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\ acc\": 0.4858156028368794,\n \"acc_stderr\": 0.02981549448368206,\n \ \ \"acc_norm\": 0.4858156028368794,\n \"acc_norm_stderr\": 0.02981549448368206\n\ \ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.4771838331160365,\n\ \ \"acc_stderr\": 0.012756933382823698,\n \"acc_norm\": 0.4771838331160365,\n\ \ \"acc_norm_stderr\": 0.012756933382823698\n },\n \"harness|hendrycksTest-professional_medicine|5\"\ : {\n \"acc\": 0.6801470588235294,\n \"acc_stderr\": 0.02833295951403121,\n\ \ \"acc_norm\": 0.6801470588235294,\n \"acc_norm_stderr\": 0.02833295951403121\n\ \ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\ acc\": 0.6764705882352942,\n \"acc_stderr\": 0.018926082916083383,\n \ \ \"acc_norm\": 0.6764705882352942,\n \"acc_norm_stderr\": 0.018926082916083383\n\ \ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.6727272727272727,\n\ \ \"acc_stderr\": 0.0449429086625209,\n \"acc_norm\": 0.6727272727272727,\n\ \ \"acc_norm_stderr\": 0.0449429086625209\n },\n \"harness|hendrycksTest-security_studies|5\"\ : {\n \"acc\": 0.7346938775510204,\n \"acc_stderr\": 0.028263889943784596,\n\ \ \"acc_norm\": 0.7346938775510204,\n \"acc_norm_stderr\": 0.028263889943784596\n\ \ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.8407960199004975,\n\ \ \"acc_stderr\": 0.025870646766169136,\n \"acc_norm\": 0.8407960199004975,\n\ \ \"acc_norm_stderr\": 0.025870646766169136\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\ : {\n \"acc\": 0.84,\n \"acc_stderr\": 0.03684529491774709,\n \ \ \"acc_norm\": 0.84,\n \"acc_norm_stderr\": 0.03684529491774709\n \ \ },\n \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.5542168674698795,\n\ \ \"acc_stderr\": 0.03869543323472101,\n \"acc_norm\": 0.5542168674698795,\n\ \ \"acc_norm_stderr\": 0.03869543323472101\n },\n \"harness|hendrycksTest-world_religions|5\"\ : {\n \"acc\": 0.8362573099415205,\n \"acc_stderr\": 0.028380919596145866,\n\ \ \"acc_norm\": 0.8362573099415205,\n \"acc_norm_stderr\": 0.028380919596145866\n\ \ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.6328029375764994,\n\ \ \"mc1_stderr\": 0.016874805001453184,\n \"mc2\": 0.7800372751713768,\n\ \ \"mc2_stderr\": 0.013681851851800382\n },\n \"harness|winogrande|5\"\ : {\n \"acc\": 0.8500394632991318,\n \"acc_stderr\": 0.010034394804580809\n\ \ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.7028051554207733,\n \ \ \"acc_stderr\": 0.012588685966624177\n }\n}\n```" repo_url: https://huggingface.co/Muhammad2003/Myriad-7B-Slerp leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2024_04_05T21_09_13.517339 path: - '**/details_harness|arc:challenge|25_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2024-04-05T21-09-13.517339.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '**/details_harness|gsm8k|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_04_05T21_09_13.517339 path: - '**/details_harness|hellaswag|10_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-management|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-management|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-04-05T21-09-13.517339.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '**/details_harness|hendrycksTest-anatomy|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '**/details_harness|hendrycksTest-astronomy|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '**/details_harness|hendrycksTest-college_biology|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '**/details_harness|hendrycksTest-college_physics|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '**/details_harness|hendrycksTest-computer_security|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '**/details_harness|hendrycksTest-econometrics|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '**/details_harness|hendrycksTest-global_facts|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '**/details_harness|hendrycksTest-human_aging|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '**/details_harness|hendrycksTest-international_law|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '**/details_harness|hendrycksTest-management|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '**/details_harness|hendrycksTest-marketing|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '**/details_harness|hendrycksTest-nutrition|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '**/details_harness|hendrycksTest-philosophy|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '**/details_harness|hendrycksTest-prehistory|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '**/details_harness|hendrycksTest-professional_law|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '**/details_harness|hendrycksTest-public_relations|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '**/details_harness|hendrycksTest-security_studies|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '**/details_harness|hendrycksTest-sociology|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '**/details_harness|hendrycksTest-virology|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '**/details_harness|hendrycksTest-world_religions|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2024-04-05T21-09-13.517339.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_04_05T21_09_13.517339 path: - '**/details_harness|truthfulqa:mc|0_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2024-04-05T21-09-13.517339.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_04_05T21_09_13.517339 path: - '**/details_harness|winogrande|5_2024-04-05T21-09-13.517339.parquet' - split: latest path: - '**/details_harness|winogrande|5_2024-04-05T21-09-13.517339.parquet' - config_name: results data_files: - split: 2024_04_05T21_09_13.517339 path: - results_2024-04-05T21-09-13.517339.parquet - split: latest path: - results_2024-04-05T21-09-13.517339.parquet --- # Dataset Card for Evaluation run of Muhammad2003/Myriad-7B-Slerp  Dataset automatically created during the evaluation run of model [Muhammad2003/Myriad-7B-Slerp](https://huggingface.co/Muhammad2003/Myriad-7B-Slerp) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_Muhammad2003__Myriad-7B-Slerp", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-04-05T21:09:13.517339](https://huggingface.co/datasets/open-llm-leaderboard/details_Muhammad2003__Myriad-7B-Slerp/blob/main/results_2024-04-05T21-09-13.517339.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval): ```python { "all": { "acc": 0.6498757467364364, "acc_stderr": 0.0320415504432472, "acc_norm": 0.6488639096760553, "acc_norm_stderr": 0.032715942329960675, "mc1": 0.6328029375764994, "mc1_stderr": 0.016874805001453184, "mc2": 0.7800372751713768, "mc2_stderr": 0.013681851851800382 }, "harness|arc:challenge|25": { "acc": 0.712457337883959, "acc_stderr": 0.013226719056266127, "acc_norm": 0.7320819112627986, "acc_norm_stderr": 0.012942030195136438 }, "harness|hellaswag|10": { "acc": 0.717486556462856, "acc_stderr": 0.004493015945599716, "acc_norm": 0.891256721768572, "acc_norm_stderr": 0.0031068060075356255 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.31, "acc_stderr": 0.04648231987117316, "acc_norm": 0.31, "acc_norm_stderr": 0.04648231987117316 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.6370370370370371, "acc_stderr": 0.04153948404742398, "acc_norm": 0.6370370370370371, "acc_norm_stderr": 0.04153948404742398 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.7105263157894737, "acc_stderr": 0.03690677986137283, "acc_norm": 0.7105263157894737, "acc_norm_stderr": 0.03690677986137283 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.64, "acc_stderr": 0.04824181513244218, "acc_norm": 0.64, "acc_norm_stderr": 0.04824181513244218 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.7056603773584905, "acc_stderr": 0.028049186315695255, "acc_norm": 0.7056603773584905, "acc_norm_stderr": 0.028049186315695255 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.7708333333333334, "acc_stderr": 0.03514697467862388, "acc_norm": 0.7708333333333334, "acc_norm_stderr": 0.03514697467862388 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.49, "acc_stderr": 0.05024183937956911, "acc_norm": 0.49, "acc_norm_stderr": 0.05024183937956911 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.56, "acc_stderr": 0.04988876515698589, "acc_norm": 0.56, "acc_norm_stderr": 0.04988876515698589 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.29, "acc_stderr": 0.04560480215720684, "acc_norm": 0.29, "acc_norm_stderr": 0.04560480215720684 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.653179190751445, "acc_stderr": 0.036291466701596636, "acc_norm": 0.653179190751445, "acc_norm_stderr": 0.036291466701596636 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.37254901960784315, "acc_stderr": 0.04810840148082636, "acc_norm": 0.37254901960784315, "acc_norm_stderr": 0.04810840148082636 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.76, "acc_stderr": 0.04292346959909283, "acc_norm": 0.76, "acc_norm_stderr": 0.04292346959909283 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.574468085106383, "acc_stderr": 0.03232146916224468, "acc_norm": 0.574468085106383, "acc_norm_stderr": 0.03232146916224468 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.4824561403508772, "acc_stderr": 0.04700708033551038, "acc_norm": 0.4824561403508772, "acc_norm_stderr": 0.04700708033551038 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.5310344827586206, "acc_stderr": 0.04158632762097828, "acc_norm": 0.5310344827586206, "acc_norm_stderr": 0.04158632762097828 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.41534391534391535, "acc_stderr": 0.025379524910778398, "acc_norm": 0.41534391534391535, "acc_norm_stderr": 0.025379524910778398 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.47619047619047616, "acc_stderr": 0.04467062628403273, "acc_norm": 0.47619047619047616, "acc_norm_stderr": 0.04467062628403273 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.3, "acc_stderr": 0.046056618647183814, "acc_norm": 0.3, "acc_norm_stderr": 0.046056618647183814 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.7838709677419354, "acc_stderr": 0.02341529343356853, "acc_norm": 0.7838709677419354, "acc_norm_stderr": 0.02341529343356853 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.5123152709359606, "acc_stderr": 0.035169204442208966, "acc_norm": 0.5123152709359606, "acc_norm_stderr": 0.035169204442208966 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.7, "acc_stderr": 0.046056618647183814, "acc_norm": 0.7, "acc_norm_stderr": 0.046056618647183814 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.7757575757575758, "acc_stderr": 0.03256866661681102, "acc_norm": 0.7757575757575758, "acc_norm_stderr": 0.03256866661681102 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.803030303030303, "acc_stderr": 0.028335609732463362, "acc_norm": 0.803030303030303, "acc_norm_stderr": 0.028335609732463362 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.9119170984455959, "acc_stderr": 0.02045374660160103, "acc_norm": 0.9119170984455959, "acc_norm_stderr": 0.02045374660160103 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.658974358974359, "acc_stderr": 0.024035489676335082, "acc_norm": 0.658974358974359, "acc_norm_stderr": 0.024035489676335082 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.3074074074074074, "acc_stderr": 0.028133252578815632, "acc_norm": 0.3074074074074074, "acc_norm_stderr": 0.028133252578815632 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.6722689075630253, "acc_stderr": 0.03048991141767323, "acc_norm": 0.6722689075630253, "acc_norm_stderr": 0.03048991141767323 }, "harness|hendrycksTest-high_school_physics|5": { "acc": 0.36423841059602646, "acc_stderr": 0.03929111781242742, "acc_norm": 0.36423841059602646, "acc_norm_stderr": 0.03929111781242742 }, "harness|hendrycksTest-high_school_psychology|5": { "acc": 0.8440366972477065, "acc_stderr": 0.01555580271359017, "acc_norm": 0.8440366972477065, "acc_norm_stderr": 0.01555580271359017 }, "harness|hendrycksTest-high_school_statistics|5": { "acc": 0.5092592592592593, "acc_stderr": 0.034093869469927006, "acc_norm": 0.5092592592592593, "acc_norm_stderr": 0.034093869469927006 }, "harness|hendrycksTest-high_school_us_history|5": { "acc": 0.8431372549019608, "acc_stderr": 0.02552472232455335, "acc_norm": 0.8431372549019608, "acc_norm_stderr": 0.02552472232455335 }, "harness|hendrycksTest-high_school_world_history|5": { "acc": 0.8143459915611815, "acc_stderr": 0.025310495376944856, "acc_norm": 0.8143459915611815, "acc_norm_stderr": 0.025310495376944856 }, "harness|hendrycksTest-human_aging|5": { "acc": 0.6860986547085202, "acc_stderr": 0.031146796482972465, "acc_norm": 0.6860986547085202, "acc_norm_stderr": 0.031146796482972465 }, "harness|hendrycksTest-human_sexuality|5": { "acc": 0.7938931297709924, "acc_stderr": 0.03547771004159465, "acc_norm": 0.7938931297709924, "acc_norm_stderr": 0.03547771004159465 }, "harness|hendrycksTest-international_law|5": { "acc": 0.7603305785123967, "acc_stderr": 0.03896878985070416, "acc_norm": 0.7603305785123967, "acc_norm_stderr": 0.03896878985070416 }, "harness|hendrycksTest-jurisprudence|5": { "acc": 0.7592592592592593, "acc_stderr": 0.04133119440243839, "acc_norm": 0.7592592592592593, "acc_norm_stderr": 0.04133119440243839 }, "harness|hendrycksTest-logical_fallacies|5": { "acc": 0.7852760736196319, "acc_stderr": 0.032262193772867744, "acc_norm": 0.7852760736196319, "acc_norm_stderr": 0.032262193772867744 }, "harness|hendrycksTest-machine_learning|5": { "acc": 0.42857142857142855, "acc_stderr": 0.04697113923010212, "acc_norm": 0.42857142857142855, "acc_norm_stderr": 0.04697113923010212 }, "harness|hendrycksTest-management|5": { "acc": 0.7572815533980582, "acc_stderr": 0.04245022486384495, "acc_norm": 0.7572815533980582, "acc_norm_stderr": 0.04245022486384495 }, "harness|hendrycksTest-marketing|5": { "acc": 0.8760683760683761, "acc_stderr": 0.021586494001281365, "acc_norm": 0.8760683760683761, "acc_norm_stderr": 0.021586494001281365 }, "harness|hendrycksTest-medical_genetics|5": { "acc": 0.7, "acc_stderr": 0.046056618647183814, "acc_norm": 0.7, "acc_norm_stderr": 0.046056618647183814 }, "harness|hendrycksTest-miscellaneous|5": { "acc": 0.8237547892720306, "acc_stderr": 0.013625556907993464, "acc_norm": 0.8237547892720306, "acc_norm_stderr": 0.013625556907993464 }, "harness|hendrycksTest-moral_disputes|5": { "acc": 0.7312138728323699, "acc_stderr": 0.023868003262500104, "acc_norm": 0.7312138728323699, "acc_norm_stderr": 0.023868003262500104 }, "harness|hendrycksTest-moral_scenarios|5": { "acc": 0.4223463687150838, "acc_stderr": 0.016519594275297117, "acc_norm": 0.4223463687150838, "acc_norm_stderr": 0.016519594275297117 }, "harness|hendrycksTest-nutrition|5": { "acc": 0.7156862745098039, "acc_stderr": 0.02582916327275748, "acc_norm": 0.7156862745098039, "acc_norm_stderr": 0.02582916327275748 }, "harness|hendrycksTest-philosophy|5": { "acc": 0.7009646302250804, "acc_stderr": 0.02600330111788514, "acc_norm": 0.7009646302250804, "acc_norm_stderr": 0.02600330111788514 }, "harness|hendrycksTest-prehistory|5": { "acc": 0.7407407407407407, "acc_stderr": 0.024383665531035454, "acc_norm": 0.7407407407407407, "acc_norm_stderr": 0.024383665531035454 }, "harness|hendrycksTest-professional_accounting|5": { "acc": 0.4858156028368794, "acc_stderr": 0.02981549448368206, "acc_norm": 0.4858156028368794, "acc_norm_stderr": 0.02981549448368206 }, "harness|hendrycksTest-professional_law|5": { "acc": 0.4771838331160365, "acc_stderr": 0.012756933382823698, "acc_norm": 0.4771838331160365, "acc_norm_stderr": 0.012756933382823698 }, "harness|hendrycksTest-professional_medicine|5": { "acc": 0.6801470588235294, "acc_stderr": 0.02833295951403121, "acc_norm": 0.6801470588235294, "acc_norm_stderr": 0.02833295951403121 }, "harness|hendrycksTest-professional_psychology|5": { "acc": 0.6764705882352942, "acc_stderr": 0.018926082916083383, "acc_norm": 0.6764705882352942, "acc_norm_stderr": 0.018926082916083383 }, "harness|hendrycksTest-public_relations|5": { "acc": 0.6727272727272727, "acc_stderr": 0.0449429086625209, "acc_norm": 0.6727272727272727, "acc_norm_stderr": 0.0449429086625209 }, "harness|hendrycksTest-security_studies|5": { "acc": 0.7346938775510204, "acc_stderr": 0.028263889943784596, "acc_norm": 0.7346938775510204, "acc_norm_stderr": 0.028263889943784596 }, "harness|hendrycksTest-sociology|5": { "acc": 0.8407960199004975, "acc_stderr": 0.025870646766169136, "acc_norm": 0.8407960199004975, "acc_norm_stderr": 0.025870646766169136 }, "harness|hendrycksTest-us_foreign_policy|5": { "acc": 0.84, "acc_stderr": 0.03684529491774709, "acc_norm": 0.84, "acc_norm_stderr": 0.03684529491774709 }, "harness|hendrycksTest-virology|5": { "acc": 0.5542168674698795, "acc_stderr": 0.03869543323472101, "acc_norm": 0.5542168674698795, "acc_norm_stderr": 0.03869543323472101 }, "harness|hendrycksTest-world_religions|5": { "acc": 0.8362573099415205, "acc_stderr": 0.028380919596145866, "acc_norm": 0.8362573099415205, "acc_norm_stderr": 0.028380919596145866 }, "harness|truthfulqa:mc|0": { "mc1": 0.6328029375764994, "mc1_stderr": 0.016874805001453184, "mc2": 0.7800372751713768, "mc2_stderr": 0.013681851851800382 }, "harness|winogrande|5": { "acc": 0.8500394632991318, "acc_stderr": 0.010034394804580809 }, "harness|gsm8k|5": { "acc": 0.7028051554207733, "acc_stderr": 0.012588685966624177 } } ``` ## Dataset Details ### Dataset Description  - **Curated by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] ### Dataset Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Dataset Structure  [More Information Needed] ## Dataset Creation ### Curation Rationale  [More Information Needed] ### Source Data  #### Data Collection and Processing  [More Information Needed] #### Who are the source data producers?  [More Information Needed] ### Annotations [optional]  #### Annotation process  [More Information Needed] #### Who are the annotators?  [More Information Needed] #### Personal and Sensitive Information  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations. ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Dataset Card Authors [optional] [More Information Needed] ## Dataset Card Contact [More Information Needed]

imone/OpenOrca_FLAN

--- license: mit --- This is the [OpenOrca](https://huggingface.co/datasets/Open-Orca/OpenOrca) GPT4 subset with the original FLAN answers. Each even row (indexed starting from 0) contains the OpenOrca GPT4 answer, while each odd row contains the corresponding FLAN answer.

48xrf/prodanca

--- license: wtfpl ---

CyberHarem/lupusregina_beta_overlord

--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of lupusregina_beta_overlord This is the dataset of lupusregina_beta_overlord, containing 102 images and their tags. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)).

jmgb0127/FronxOwnerManual

--- configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* dataset_info: features: - name: context dtype: string - name: question dtype: string - name: answer dtype: string - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 1330685 num_examples: 1177 - name: test num_bytes: 332811 num_examples: 294 download_size: 990561 dataset_size: 1663496 --- # Dataset Card for "FronxOwnerManual" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

jacobbieker/gk2a-kerchunk

--- license: mit ---

liuyanchen1015/MULTI_VALUE_sst2_here_come

--- dataset_info: features: - name: sentence dtype: string - name: label dtype: int64 - name: idx dtype: int64 - name: score dtype: int64 splits: - name: dev num_bytes: 1351 num_examples: 9 - name: test num_bytes: 2306 num_examples: 18 - name: train num_bytes: 30466 num_examples: 263 download_size: 20603 dataset_size: 34123 --- # Dataset Card for "MULTI_VALUE_sst2_here_come" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

wanony/mika

--- license: gpl-3.0 ---

open-llm-leaderboard/details_Aeala__GPT4-x-AlpacaDente-30b

--- pretty_name: Evaluation run of Aeala/GPT4-x-AlpacaDente-30b dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [Aeala/GPT4-x-AlpacaDente-30b](https://huggingface.co/Aeala/GPT4-x-AlpacaDente-30b)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 64 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 2 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the agregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_Aeala__GPT4-x-AlpacaDente-30b\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-09-17T18:13:58.646455](https://huggingface.co/datasets/open-llm-leaderboard/details_Aeala__GPT4-x-AlpacaDente-30b/blob/main/results_2023-09-17T18-13-58.646455.json)(note\ \ that their might be results for other tasks in the repos if successive evals didn't\ \ cover the same tasks. You find each in the results and the \"latest\" split for\ \ each eval):\n\n```python\n{\n \"all\": {\n \"em\": 0.32120385906040266,\n\ \ \"em_stderr\": 0.004781891422636473,\n \"f1\": 0.43280620805369485,\n\ \ \"f1_stderr\": 0.0045611946956929435,\n \"acc\": 0.5439418899180396,\n\ \ \"acc_stderr\": 0.012071731077966974\n },\n \"harness|drop|3\": {\n\ \ \"em\": 0.32120385906040266,\n \"em_stderr\": 0.004781891422636473,\n\ \ \"f1\": 0.43280620805369485,\n \"f1_stderr\": 0.0045611946956929435\n\ \ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.3009855951478393,\n \ \ \"acc_stderr\": 0.012634504465211194\n },\n \"harness|winogrande|5\"\ : {\n \"acc\": 0.7868981846882399,\n \"acc_stderr\": 0.011508957690722754\n\ \ }\n}\n```" repo_url: https://huggingface.co/Aeala/GPT4-x-AlpacaDente-30b leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2023_07_19T23_04_17.245052 path: - '**/details_harness|arc:challenge|25_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2023-07-19T23:04:17.245052.parquet' - config_name: harness_drop_3 data_files: - split: 2023_09_17T18_13_58.646455 path: - '**/details_harness|drop|3_2023-09-17T18-13-58.646455.parquet' - split: latest path: - '**/details_harness|drop|3_2023-09-17T18-13-58.646455.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_09_17T18_13_58.646455 path: - '**/details_harness|gsm8k|5_2023-09-17T18-13-58.646455.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2023-09-17T18-13-58.646455.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_07_19T23_04_17.245052 path: - '**/details_harness|hellaswag|10_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-management|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-management|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-07-19T23:04:17.245052.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '**/details_harness|hendrycksTest-anatomy|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '**/details_harness|hendrycksTest-astronomy|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '**/details_harness|hendrycksTest-college_biology|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '**/details_harness|hendrycksTest-college_physics|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '**/details_harness|hendrycksTest-computer_security|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '**/details_harness|hendrycksTest-econometrics|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '**/details_harness|hendrycksTest-global_facts|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '**/details_harness|hendrycksTest-human_aging|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '**/details_harness|hendrycksTest-international_law|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '**/details_harness|hendrycksTest-management|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '**/details_harness|hendrycksTest-marketing|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '**/details_harness|hendrycksTest-nutrition|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '**/details_harness|hendrycksTest-philosophy|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '**/details_harness|hendrycksTest-prehistory|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '**/details_harness|hendrycksTest-professional_law|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '**/details_harness|hendrycksTest-public_relations|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '**/details_harness|hendrycksTest-security_studies|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '**/details_harness|hendrycksTest-sociology|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '**/details_harness|hendrycksTest-virology|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_07_19T23_04_17.245052 path: - '**/details_harness|hendrycksTest-world_religions|5_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2023-07-19T23:04:17.245052.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_07_19T23_04_17.245052 path: - '**/details_harness|truthfulqa:mc|0_2023-07-19T23:04:17.245052.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2023-07-19T23:04:17.245052.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_09_17T18_13_58.646455 path: - '**/details_harness|winogrande|5_2023-09-17T18-13-58.646455.parquet' - split: latest path: - '**/details_harness|winogrande|5_2023-09-17T18-13-58.646455.parquet' - config_name: results data_files: - split: 2023_07_19T23_04_17.245052 path: - results_2023-07-19T23:04:17.245052.parquet - split: 2023_09_17T18_13_58.646455 path: - results_2023-09-17T18-13-58.646455.parquet - split: latest path: - results_2023-09-17T18-13-58.646455.parquet --- # Dataset Card for Evaluation run of Aeala/GPT4-x-AlpacaDente-30b ## Dataset Description - **Homepage:** - **Repository:** https://huggingface.co/Aeala/GPT4-x-AlpacaDente-30b - **Paper:** - **Leaderboard:** https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard - **Point of Contact:** clementine@hf.co ### Dataset Summary Dataset automatically created during the evaluation run of model [Aeala/GPT4-x-AlpacaDente-30b](https://huggingface.co/Aeala/GPT4-x-AlpacaDente-30b) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 64 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 2 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the agregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_Aeala__GPT4-x-AlpacaDente-30b", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-09-17T18:13:58.646455](https://huggingface.co/datasets/open-llm-leaderboard/details_Aeala__GPT4-x-AlpacaDente-30b/blob/main/results_2023-09-17T18-13-58.646455.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval): ```python { "all": { "em": 0.32120385906040266, "em_stderr": 0.004781891422636473, "f1": 0.43280620805369485, "f1_stderr": 0.0045611946956929435, "acc": 0.5439418899180396, "acc_stderr": 0.012071731077966974 }, "harness|drop|3": { "em": 0.32120385906040266, "em_stderr": 0.004781891422636473, "f1": 0.43280620805369485, "f1_stderr": 0.0045611946956929435 }, "harness|gsm8k|5": { "acc": 0.3009855951478393, "acc_stderr": 0.012634504465211194 }, "harness|winogrande|5": { "acc": 0.7868981846882399, "acc_stderr": 0.011508957690722754 } } ``` ### Supported Tasks and Leaderboards [More Information Needed] ### Languages [More Information Needed] ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information [More Information Needed] ### Citation Information [More Information Needed] ### Contributions [More Information Needed]

metredo085/drod

--- license: apache-2.0 ---

as-cle-bert/scerevisiae-proteins-reduced

--- license: mit dataset_info: features: - name: label dtype: class_label: names: '0': Verified_Coding '1': Probably_Non_Coding - name: text dtype: string splits: - name: train num_bytes: 343452 num_examples: 480 - name: test num_bytes: 81480 num_examples: 120 download_size: 236731 dataset_size: 424932 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---

ar852/scraped-chatgpt-conversations

--- task_categories: - question-answering - text-generation - conversational size_categories: - 100K<n<1M --- # Dataset Card for Dataset Name ## Dataset Description - **Repository: {https://github.com/ar852/chatgpt-scraping}** ### Dataset Summary scraped-chatgpt-conversations contains ~100k conversations between a user and chatgpt that were shared online through reddit, twitter, or sharegpt. For sharegpt, the conversations were directly scraped from the website. For reddit and twitter, images were downloaded from submissions, segmented, and run through an OCR pipeline to obtain a conversation list. For information on how the each json file is structured, please see `json_guides.md` ### Languages - twitter 1, twitter 2, and sharegpt json files are multilingual - reddit and twitter 2 json files are english only ## Dataset Structure - refer to *json_guide.txt* ## Dataset Creation This dataset was created by scraping images from twitter, reddit, and sharegpt.com using the pushshift and twitter APIs, respectively. The images are run through a filter to check if they contain a chatgpt conversation, then the image is processed and run through an OCR pipeline to obtain the conversation text. More info can be found in the repository. ### Source Data - twitter.com - reddit.com - sharegpt.com ## Considerations for Using the Data A significant amount of dicts created from parsing reddit and twitter images may be parsed incorrectly for a number of reasons: cropping done by the image poster, incorrectly classifying the image as containing a chatgpt conversation, incorrect image parsing (segmentation) by the parser, incorrect OCR by pytesseract. ### Licensing Information [More Information Needed] ### Contributions [More Information Needed]

KushT/bbc_news_multiclass_train_val_test

--- license: mit configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* - split: test path: data/test-* dataset_info: features: - name: text dtype: string - name: label dtype: int64 splits: - name: train num_bytes: 3414429 num_examples: 1512 - name: validation num_bytes: 888603 num_examples: 379 - name: test num_bytes: 751863 num_examples: 334 download_size: 0 dataset_size: 5054895 --- Label Names: { 'business': 0, 'entertainment': 1, 'politics': 2, 'sport': 3, 'tech': 4 } Dataset: [Kaggle - BBC Full Text Document Classification](https://www.kaggle.com/datasets/shivamkushwaha/bbc-full-text-document-classification/code)

mespinosami/global230k

--- configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* - split: test path: data/test-* dataset_info: features: - name: image dtype: image - name: label dtype: image splits: - name: train num_bytes: 8623524876.02 num_examples: 162940 - name: validation num_bytes: 1335636495.768 num_examples: 23416 - name: test num_bytes: 2572452087.661 num_examples: 46463 download_size: 10844373816 dataset_size: 12531613459.449 --- # Dataset Card for "global230k" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

Aletos/Peixe

--- license: openrail ---

LennardZuendorf/openlegaldata-processed

--- license: mit dataset_info: features: - name: id dtype: int64 - name: court struct: - name: id dtype: int64 - name: jurisdiction dtype: string - name: level_of_appeal dtype: string - name: name dtype: string - name: state dtype: int64 - name: file_number dtype: string - name: date dtype: timestamp[s] - name: type dtype: string - name: content dtype: string - name: tenor dtype: string - name: facts dtype: string - name: reasoning dtype: string splits: - name: three num_bytes: 169494251 num_examples: 2828 - name: two num_bytes: 183816899 num_examples: 4954 download_size: 172182482 dataset_size: 353311150 task_categories: - text-classification language: - de tags: - legal pretty_name: Edited German Court case decision size_categories: - 1K<n<10K --- # Dataset Card for openlegaldata.io bulk case data ## Dataset Description This is a edit/cleanup of Bulk Data of [openlegaldata.io](https://de.openlegaldata.io/), which I also brought onto Huggingface [here](LennardZuendorf/openlegaldata-bulk-data). #### The Entire Dataset Is In German - **Github Repository:** [uniArchive-legalis]](https://github.com/LennardZuendorf/uniArchive-legalis) - **Repository:** [Bulk Data](https://static.openlegaldata.io/dumps/de/) ## Edit Summary I have done some cleaning and splitting of the data and filtered out large parts that were not (easily) usable, cutting down the number of cases to at max 4000 - from 250000. This results in two different splits. Which is because German Courts don't format their case decision the same way. ### Data Fields Independent of the split, most fields are the same, they are: | id | court | file_number | date | type | content | - | - | - | - | - | - | | numeric id | name of the court that made the decision | file number of the case ("Aktenzeichen") | decision date | type of the case decision | entire content (text) of the case decision Additionally, I added 3 more fields because of the splitting of the content: #### Two Split - Case Decision I could split into two parts: tenor and reasoning. - Which means the three fields tenor, content and facts contain the following: | tenor | reasoning | facts | - | - | - | | An abstract, legal summary of the cases decision | the entire rest of the decision, explaining in detail why the decision has been made | an empty text field | #### Three Split - Case Decision I could split into three parts: tenor, reasoning and facts - This Data I have used to create binary labels with the help of ChatGPT, see [legalis](https://huggingface.co/datasets/LennardZuendorf/legalis) for that - The three fields tenor, content and facts contain the following: | tenor | reasoning | facts | - | - | - | | An abstract, legal summary of the cases decision | the entire rest of the decision, explaining in detail why the decision has been made | the facts and details of a case | ### Languages - German ## Additional Information ### Licensing/Citation Information The [openlegaldata platform](https://github.com/openlegaldata/oldp) is licensed under the MIT license, you can access the dataset by citing the original source, [openlegaldata.io](https://de.openlegaldata.io/) and me, [Lennard Zündorf](https://github.com/LennardZuendorf) as the editor of this dataset.

7Jes6riv/multiclass

--- dataset_info: features: - name: text dtype: string splits: - name: train num_bytes: 195846200 num_examples: 59168 download_size: 32590912 dataset_size: 195846200 configs: - config_name: default data_files: - split: train path: data/train-* ---

Lucasss876/Tagizzy

--- license: openrail ---

curry99/rampage

--- license: mit ---

mteb/stsbenchmark-sts

--- language: - en ---

lshowway/wikipedia.reorder.sov.pl

--- dataset_info: features: - name: text dtype: string splits: - name: train num_bytes: 1958124685 num_examples: 1772445 download_size: 549518463 dataset_size: 1958124685 --- # Dataset Card for "wikipedia.reorder.sov.pl" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

CyberHarem/chapayev_azurlane

--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of chapayev/チャパエフ/恰巴耶夫 (Azur Lane) This is the dataset of chapayev/チャパエフ/恰巴耶夫 (Azur Lane), containing 289 images and their tags. The core tags of this character are `blue_hair, breasts, short_hair, blue_eyes, large_breasts, mole, mole_on_breast, bangs, hair_ornament, hat, white_headwear, military_hat, peaked_cap, hairclip`, which are pruned in this dataset. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). ## List of Packages | Name | Images | Size | Download | Type | Description | |:-----------------|---------:|:-----------|:-------------------------------------------------------------------------------------------------------------------|:-----------|:---------------------------------------------------------------------| | raw | 289 | 483.10 MiB | [Download](https://huggingface.co/datasets/CyberHarem/chapayev_azurlane/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). | | 800 | 289 | 250.62 MiB | [Download](https://huggingface.co/datasets/CyberHarem/chapayev_azurlane/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. | | stage3-p480-800 | 734 | 552.75 MiB | [Download](https://huggingface.co/datasets/CyberHarem/chapayev_azurlane/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. | | 1200 | 289 | 413.48 MiB | [Download](https://huggingface.co/datasets/CyberHarem/chapayev_azurlane/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. | | stage3-p480-1200 | 734 | 808.74 MiB | [Download](https://huggingface.co/datasets/CyberHarem/chapayev_azurlane/resolve/main/dataset-stage3-p480-1200.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. | ### Load Raw Dataset with Waifuc We provide raw dataset (including tagged images) for [waifuc](https://deepghs.github.io/waifuc/main/tutorials/installation/index.html) loading. If you need this, just run the following code ```python import os import zipfile from huggingface_hub import hf_hub_download from waifuc.source import LocalSource # download raw archive file zip_file = hf_hub_download( repo_id='CyberHarem/chapayev_azurlane', repo_type='dataset', filename='dataset-raw.zip', ) # extract files to your directory dataset_dir = 'dataset_dir' os.makedirs(dataset_dir, exist_ok=True) with zipfile.ZipFile(zip_file, 'r') as zf: zf.extractall(dataset_dir) # load the dataset with waifuc source = LocalSource(dataset_dir) for item in source: print(item.image, item.meta['filename'], item.meta['tags']) ``` ## List of Clusters List of tag clustering result, maybe some outfits can be mined here. ### Raw Text Version | # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | Tags | |----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| | 0 | 47 | ![](samples/0/clu0-sample0.png) | ![](samples/0/clu0-sample1.png) | ![](samples/0/clu0-sample2.png) | ![](samples/0/clu0-sample3.png) | ![](samples/0/clu0-sample4.png) | 1girl, blush, chain, looking_at_viewer, torn_shirt, solo, shackles, short_sleeves, navel, cleavage, smile, sitting, open_mouth | | 1 | 10 | ![](samples/1/clu1-sample0.png) | ![](samples/1/clu1-sample1.png) | ![](samples/1/clu1-sample2.png) | ![](samples/1/clu1-sample3.png) | ![](samples/1/clu1-sample4.png) | 1girl, black_gloves, cleavage, looking_at_viewer, pleated_skirt, smile, solo, white_jacket, blush, chain, long_sleeves, closed_mouth, white_skirt, black_pantyhose | | 2 | 7 | ![](samples/2/clu2-sample0.png) | ![](samples/2/clu2-sample1.png) | ![](samples/2/clu2-sample2.png) | ![](samples/2/clu2-sample3.png) | ![](samples/2/clu2-sample4.png) | 1girl, black_gloves, blush, cleavage, looking_at_viewer, smile, solo, upper_body, white_jacket, closed_mouth, simple_background, white_background | | 3 | 27 | ![](samples/3/clu3-sample0.png) | ![](samples/3/clu3-sample1.png) | ![](samples/3/clu3-sample2.png) | ![](samples/3/clu3-sample3.png) | ![](samples/3/clu3-sample4.png) | 1girl, official_alternate_costume, looking_at_viewer, white_hairband, earrings, solo, cleavage, white_choker, blush, lace-trimmed_dress, white_dress, lying, smile, nightgown, see-through_dress, thigh_strap | | 4 | 10 | ![](samples/4/clu4-sample0.png) | ![](samples/4/clu4-sample1.png) | ![](samples/4/clu4-sample2.png) | ![](samples/4/clu4-sample3.png) | ![](samples/4/clu4-sample4.png) | 1girl, looking_at_viewer, solo, white_dress, elbow_gloves, sitting, white_gloves, bare_shoulders, no_shoes, official_alternate_costume, thighs, toes, white_thighhighs, blush, cleavage, garter_straps, legs, smile, chair, soles, ass, choker, closed_mouth, foot_focus, collarbone, lying | ### Table Version | # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | blush | chain | looking_at_viewer | torn_shirt | solo | shackles | short_sleeves | navel | cleavage | smile | sitting | open_mouth | black_gloves | pleated_skirt | white_jacket | long_sleeves | closed_mouth | white_skirt | black_pantyhose | upper_body | simple_background | white_background | official_alternate_costume | white_hairband | earrings | white_choker | lace-trimmed_dress | white_dress | lying | nightgown | see-through_dress | thigh_strap | elbow_gloves | white_gloves | bare_shoulders | no_shoes | thighs | toes | white_thighhighs | garter_straps | legs | chair | soles | ass | choker | foot_focus | collarbone | |----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------|:--------|:--------|:--------------------|:-------------|:-------|:-----------|:----------------|:--------|:-----------|:--------|:----------|:-------------|:---------------|:----------------|:---------------|:---------------|:---------------|:--------------|:------------------|:-------------|:--------------------|:-------------------|:-----------------------------|:-----------------|:-----------|:---------------|:---------------------|:--------------|:--------|:------------|:--------------------|:--------------|:---------------|:---------------|:-----------------|:-----------|:---------|:-------|:-------------------|:----------------|:-------|:--------|:--------|:------|:---------|:-------------|:-------------| | 0 | 47 | ![](samples/0/clu0-sample0.png) | ![](samples/0/clu0-sample1.png) | ![](samples/0/clu0-sample2.png) | ![](samples/0/clu0-sample3.png) | ![](samples/0/clu0-sample4.png) | X | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 1 | 10 | ![](samples/1/clu1-sample0.png) | ![](samples/1/clu1-sample1.png) | ![](samples/1/clu1-sample2.png) | ![](samples/1/clu1-sample3.png) | ![](samples/1/clu1-sample4.png) | X | X | X | X | | X | | | | X | X | | | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 2 | 7 | ![](samples/2/clu2-sample0.png) | ![](samples/2/clu2-sample1.png) | ![](samples/2/clu2-sample2.png) | ![](samples/2/clu2-sample3.png) | ![](samples/2/clu2-sample4.png) | X | X | | X | | X | | | | X | X | | | X | | X | | X | | | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | 3 | 27 | ![](samples/3/clu3-sample0.png) | ![](samples/3/clu3-sample1.png) | ![](samples/3/clu3-sample2.png) | ![](samples/3/clu3-sample3.png) | ![](samples/3/clu3-sample4.png) | X | X | | X | | X | | | | X | X | | | | | | | | | | | | | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | 4 | 10 | ![](samples/4/clu4-sample0.png) | ![](samples/4/clu4-sample1.png) | ![](samples/4/clu4-sample2.png) | ![](samples/4/clu4-sample3.png) | ![](samples/4/clu4-sample4.png) | X | X | | X | | X | | | | X | X | X | | | | | | X | | | | | | X | | | | | X | X | | | | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X |

freshpearYoon/vr_train_free_43

--- dataset_info: features: - name: audio struct: - name: array sequence: float64 - name: path dtype: string - name: sampling_rate dtype: int64 - name: filename dtype: string - name: NumOfUtterance dtype: int64 - name: text dtype: string - name: samplingrate dtype: int64 - name: begin_time dtype: float64 - name: end_time dtype: float64 - name: speaker_id dtype: string - name: directory dtype: string splits: - name: train num_bytes: 6900570085 num_examples: 10000 download_size: 1224346103 dataset_size: 6900570085 configs: - config_name: default data_files: - split: train path: data/train-* ---

Cohere/wikipedia-22-12-fr-embeddings

--- annotations_creators: - expert-generated language: - fr multilinguality: - multilingual size_categories: [] source_datasets: [] tags: [] task_categories: - text-retrieval license: - apache-2.0 task_ids: - document-retrieval --- # Wikipedia (fr) embedded with cohere.ai `multilingual-22-12` encoder We encoded [Wikipedia (fr)](https://fr.wikipedia.org) using the [cohere.ai](https://txt.cohere.ai/multilingual/) `multilingual-22-12` embedding model. To get an overview how this dataset was created and pre-processed, have a look at [Cohere/wikipedia-22-12](https://huggingface.co/datasets/Cohere/wikipedia-22-12). ## Embeddings We compute for `title+" "+text` the embeddings using our `multilingual-22-12` embedding model, a state-of-the-art model that works for semantic search in 100 languages. If you want to learn more about this model, have a look at [cohere.ai multilingual embedding model](https://txt.cohere.ai/multilingual/). ## Further languages We provide embeddings of Wikipedia in many different languages: [ar](https://huggingface.co/datasets/Cohere/wikipedia-22-12-ar-embeddings), [de](https://huggingface.co/datasets/Cohere/wikipedia-22-12-de-embeddings), [en](https://huggingface.co/datasets/Cohere/wikipedia-22-12-en-embeddings), [es](https://huggingface.co/datasets/Cohere/wikipedia-22-12-es-embeddings), [fr](https://huggingface.co/datasets/Cohere/wikipedia-22-12-fr-embeddings), [hi](https://huggingface.co/datasets/Cohere/wikipedia-22-12-hi-embeddings), [it](https://huggingface.co/datasets/Cohere/wikipedia-22-12-it-embeddings), [ja](https://huggingface.co/datasets/Cohere/wikipedia-22-12-ja-embeddings), [ko](https://huggingface.co/datasets/Cohere/wikipedia-22-12-ko-embeddings), [simple english](https://huggingface.co/datasets/Cohere/wikipedia-22-12-simple-embeddings), [zh](https://huggingface.co/datasets/Cohere/wikipedia-22-12-zh-embeddings), You can find the Wikipedia datasets without embeddings at [Cohere/wikipedia-22-12](https://huggingface.co/datasets/Cohere/wikipedia-22-12). ## Loading the dataset You can either load the dataset like this: ```python from datasets import load_dataset docs = load_dataset(f"Cohere/wikipedia-22-12-fr-embeddings", split="train") ``` Or you can also stream it without downloading it before: ```python from datasets import load_dataset docs = load_dataset(f"Cohere/wikipedia-22-12-fr-embeddings", split="train", streaming=True) for doc in docs: docid = doc['id'] title = doc['title'] text = doc['text'] emb = doc['emb'] ``` ## Search A full search example: ```python #Run: pip install cohere datasets from datasets import load_dataset import torch import cohere co = cohere.Client(f"<<COHERE_API_KEY>>") # Add your cohere API key from www.cohere.com #Load at max 1000 documents + embeddings max_docs = 1000 docs_stream = load_dataset(f"Cohere/wikipedia-22-12-fr-embeddings", split="train", streaming=True) docs = [] doc_embeddings = [] for doc in docs_stream: docs.append(doc) doc_embeddings.append(doc['emb']) if len(docs) >= max_docs: break doc_embeddings = torch.tensor(doc_embeddings) query = 'Who founded Youtube' response = co.embed(texts=[query], model='multilingual-22-12') query_embedding = response.embeddings query_embedding = torch.tensor(query_embedding) # Compute dot score between query embedding and document embeddings dot_scores = torch.mm(query_embedding, doc_embeddings.transpose(0, 1)) top_k = torch.topk(dot_scores, k=3) # Print results print("Query:", query) for doc_id in top_k.indices[0].tolist(): print(docs[doc_id]['title']) print(docs[doc_id]['text'], "\n") ``` ## Performance You can find performance on the MIRACL dataset (a semantic search evaluation dataset) here: [miracl-en-queries-22-12#performance](https://huggingface.co/datasets/Cohere/miracl-en-queries-22-12#performance)

rbiojout/odoo_python_15

--- license: agpl-3.0 dataset_info: features: - name: size dtype: int64 - name: ext dtype: string - name: lang dtype: string - name: branch dtype: string - name: content dtype: string - name: avg_line_length dtype: float64 - name: max_line_length dtype: int64 splits: - name: train num_bytes: 40721998 num_examples: 9349 download_size: 12783255 dataset_size: 40721998 ---

one-sec-cv12/chunk_186

--- dataset_info: features: - name: audio dtype: audio: sampling_rate: 16000 splits: - name: train num_bytes: 12103776864.75 num_examples: 126018 download_size: 9851992082 dataset_size: 12103776864.75 --- # Dataset Card for "chunk_186" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

fadime3/Hayalet

--- license: openrail ---

joey234/mmlu-moral_disputes

--- dataset_info: features: - name: question dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D - name: negate_openai_prompt struct: - name: content dtype: string - name: role dtype: string - name: neg_question dtype: string - name: fewshot_context dtype: string - name: fewshot_context_neg dtype: string splits: - name: dev num_bytes: 4935 num_examples: 5 - name: test num_bytes: 1532082 num_examples: 346 download_size: 153575 dataset_size: 1537017 configs: - config_name: default data_files: - split: dev path: data/dev-* - split: test path: data/test-* --- # Dataset Card for "mmlu-moral_disputes" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

ProfEngel/spieltheorie

--- license: cc-by-nc-4.0 ---

Denilsonic/Datasets

--- license: openrail ---

DanGoldBr/PTT-20230720-WA0159

--- license: openrail ---

open-llm-leaderboard/details_CorticalStack__gemma-7b-ultrachat-sft

--- pretty_name: Evaluation run of CorticalStack/gemma-7b-ultrachat-sft dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [CorticalStack/gemma-7b-ultrachat-sft](https://huggingface.co/CorticalStack/gemma-7b-ultrachat-sft)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 63 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the aggregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_CorticalStack__gemma-7b-ultrachat-sft\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-02-23T17:43:57.046792](https://huggingface.co/datasets/open-llm-leaderboard/details_CorticalStack__gemma-7b-ultrachat-sft/blob/main/results_2024-02-23T17-43-57.046792.json)(note\ \ that their might be results for other tasks in the repos if successive evals didn't\ \ cover the same tasks. You find each in the results and the \"latest\" split for\ \ each eval):\n\n```python\n{\n \"all\": {\n \"acc\": 0.6393700582955444,\n\ \ \"acc_stderr\": 0.03219234730039111,\n \"acc_norm\": 0.6439639463015079,\n\ \ \"acc_norm_stderr\": 0.03283632439673242,\n \"mc1\": 0.3806609547123623,\n\ \ \"mc1_stderr\": 0.016997627871907922,\n \"mc2\": 0.5450293631615253,\n\ \ \"mc2_stderr\": 0.015380202565099867\n },\n \"harness|arc:challenge|25\"\ : {\n \"acc\": 0.5878839590443686,\n \"acc_stderr\": 0.014383915302225403,\n\ \ \"acc_norm\": 0.6126279863481229,\n \"acc_norm_stderr\": 0.01423587248790987\n\ \ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.6127265484963155,\n\ \ \"acc_stderr\": 0.004861314613286841,\n \"acc_norm\": 0.8082055367456682,\n\ \ \"acc_norm_stderr\": 0.003929076276473383\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\ : {\n \"acc\": 0.28,\n \"acc_stderr\": 0.045126085985421296,\n \ \ \"acc_norm\": 0.28,\n \"acc_norm_stderr\": 0.045126085985421296\n \ \ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.6222222222222222,\n\ \ \"acc_stderr\": 0.04188307537595852,\n \"acc_norm\": 0.6222222222222222,\n\ \ \"acc_norm_stderr\": 0.04188307537595852\n },\n \"harness|hendrycksTest-astronomy|5\"\ : {\n \"acc\": 0.6776315789473685,\n \"acc_stderr\": 0.03803510248351585,\n\ \ \"acc_norm\": 0.6776315789473685,\n \"acc_norm_stderr\": 0.03803510248351585\n\ \ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.57,\n\ \ \"acc_stderr\": 0.049756985195624284,\n \"acc_norm\": 0.57,\n \ \ \"acc_norm_stderr\": 0.049756985195624284\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\ : {\n \"acc\": 0.6452830188679245,\n \"acc_stderr\": 0.02944517532819959,\n\ \ \"acc_norm\": 0.6452830188679245,\n \"acc_norm_stderr\": 0.02944517532819959\n\ \ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.7569444444444444,\n\ \ \"acc_stderr\": 0.0358687928008034,\n \"acc_norm\": 0.7569444444444444,\n\ \ \"acc_norm_stderr\": 0.0358687928008034\n },\n \"harness|hendrycksTest-college_chemistry|5\"\ : {\n \"acc\": 0.54,\n \"acc_stderr\": 0.05009082659620332,\n \ \ \"acc_norm\": 0.54,\n \"acc_norm_stderr\": 0.05009082659620332\n \ \ },\n \"harness|hendrycksTest-college_computer_science|5\": {\n \"acc\"\ : 0.52,\n \"acc_stderr\": 0.050211673156867795,\n \"acc_norm\": 0.52,\n\ \ \"acc_norm_stderr\": 0.050211673156867795\n },\n \"harness|hendrycksTest-college_mathematics|5\"\ : {\n \"acc\": 0.35,\n \"acc_stderr\": 0.047937248544110196,\n \ \ \"acc_norm\": 0.35,\n \"acc_norm_stderr\": 0.047937248544110196\n \ \ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.6878612716763006,\n\ \ \"acc_stderr\": 0.03533133389323657,\n \"acc_norm\": 0.6878612716763006,\n\ \ \"acc_norm_stderr\": 0.03533133389323657\n },\n \"harness|hendrycksTest-college_physics|5\"\ : {\n \"acc\": 0.3431372549019608,\n \"acc_stderr\": 0.047240073523838876,\n\ \ \"acc_norm\": 0.3431372549019608,\n \"acc_norm_stderr\": 0.047240073523838876\n\ \ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\ \ 0.71,\n \"acc_stderr\": 0.045604802157206845,\n \"acc_norm\": 0.71,\n\ \ \"acc_norm_stderr\": 0.045604802157206845\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\ : {\n \"acc\": 0.6085106382978723,\n \"acc_stderr\": 0.03190701242326812,\n\ \ \"acc_norm\": 0.6085106382978723,\n \"acc_norm_stderr\": 0.03190701242326812\n\ \ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.40350877192982454,\n\ \ \"acc_stderr\": 0.046151869625837026,\n \"acc_norm\": 0.40350877192982454,\n\ \ \"acc_norm_stderr\": 0.046151869625837026\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\ : {\n \"acc\": 0.6413793103448275,\n \"acc_stderr\": 0.039966295748767186,\n\ \ \"acc_norm\": 0.6413793103448275,\n \"acc_norm_stderr\": 0.039966295748767186\n\ \ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\ : 0.4470899470899471,\n \"acc_stderr\": 0.025606723995777028,\n \"\ acc_norm\": 0.4470899470899471,\n \"acc_norm_stderr\": 0.025606723995777028\n\ \ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.46825396825396826,\n\ \ \"acc_stderr\": 0.04463112720677172,\n \"acc_norm\": 0.46825396825396826,\n\ \ \"acc_norm_stderr\": 0.04463112720677172\n },\n \"harness|hendrycksTest-global_facts|5\"\ : {\n \"acc\": 0.38,\n \"acc_stderr\": 0.04878317312145633,\n \ \ \"acc_norm\": 0.38,\n \"acc_norm_stderr\": 0.04878317312145633\n \ \ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\": 0.8064516129032258,\n\ \ \"acc_stderr\": 0.022475258525536057,\n \"acc_norm\": 0.8064516129032258,\n\ \ \"acc_norm_stderr\": 0.022475258525536057\n },\n \"harness|hendrycksTest-high_school_chemistry|5\"\ : {\n \"acc\": 0.5270935960591133,\n \"acc_stderr\": 0.03512819077876105,\n\ \ \"acc_norm\": 0.5270935960591133,\n \"acc_norm_stderr\": 0.03512819077876105\n\ \ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \ \ \"acc\": 0.66,\n \"acc_stderr\": 0.04760952285695237,\n \"acc_norm\"\ : 0.66,\n \"acc_norm_stderr\": 0.04760952285695237\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\ : {\n \"acc\": 0.7575757575757576,\n \"acc_stderr\": 0.03346409881055953,\n\ \ \"acc_norm\": 0.7575757575757576,\n \"acc_norm_stderr\": 0.03346409881055953\n\ \ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\ : 0.8484848484848485,\n \"acc_stderr\": 0.025545650426603617,\n \"\ acc_norm\": 0.8484848484848485,\n \"acc_norm_stderr\": 0.025545650426603617\n\ \ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\ \ \"acc\": 0.8601036269430051,\n \"acc_stderr\": 0.025033870583015184,\n\ \ \"acc_norm\": 0.8601036269430051,\n \"acc_norm_stderr\": 0.025033870583015184\n\ \ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \ \ \"acc\": 0.6692307692307692,\n \"acc_stderr\": 0.02385479568097112,\n \ \ \"acc_norm\": 0.6692307692307692,\n \"acc_norm_stderr\": 0.02385479568097112\n\ \ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\ acc\": 0.37777777777777777,\n \"acc_stderr\": 0.029560707392465708,\n \ \ \"acc_norm\": 0.37777777777777777,\n \"acc_norm_stderr\": 0.029560707392465708\n\ \ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \ \ \"acc\": 0.6932773109243697,\n \"acc_stderr\": 0.02995382389188703,\n \ \ \"acc_norm\": 0.6932773109243697,\n \"acc_norm_stderr\": 0.02995382389188703\n\ \ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\ : 0.3841059602649007,\n \"acc_stderr\": 0.03971301814719197,\n \"\ acc_norm\": 0.3841059602649007,\n \"acc_norm_stderr\": 0.03971301814719197\n\ \ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\ : 0.8256880733944955,\n \"acc_stderr\": 0.016265675632010333,\n \"\ acc_norm\": 0.8256880733944955,\n \"acc_norm_stderr\": 0.016265675632010333\n\ \ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\ : 0.5694444444444444,\n \"acc_stderr\": 0.03376922151252335,\n \"\ acc_norm\": 0.5694444444444444,\n \"acc_norm_stderr\": 0.03376922151252335\n\ \ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\ : 0.8137254901960784,\n \"acc_stderr\": 0.02732547096671632,\n \"\ acc_norm\": 0.8137254901960784,\n \"acc_norm_stderr\": 0.02732547096671632\n\ \ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\ acc\": 0.8185654008438819,\n \"acc_stderr\": 0.025085961144579647,\n \ \ \"acc_norm\": 0.8185654008438819,\n \"acc_norm_stderr\": 0.025085961144579647\n\ \ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.6995515695067265,\n\ \ \"acc_stderr\": 0.03076935200822915,\n \"acc_norm\": 0.6995515695067265,\n\ \ \"acc_norm_stderr\": 0.03076935200822915\n },\n \"harness|hendrycksTest-human_sexuality|5\"\ : {\n \"acc\": 0.7175572519083969,\n \"acc_stderr\": 0.03948406125768361,\n\ \ \"acc_norm\": 0.7175572519083969,\n \"acc_norm_stderr\": 0.03948406125768361\n\ \ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\ \ 0.8347107438016529,\n \"acc_stderr\": 0.03390780612972776,\n \"\ acc_norm\": 0.8347107438016529,\n \"acc_norm_stderr\": 0.03390780612972776\n\ \ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.7870370370370371,\n\ \ \"acc_stderr\": 0.039578354719809805,\n \"acc_norm\": 0.7870370370370371,\n\ \ \"acc_norm_stderr\": 0.039578354719809805\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\ : {\n \"acc\": 0.7668711656441718,\n \"acc_stderr\": 0.0332201579577674,\n\ \ \"acc_norm\": 0.7668711656441718,\n \"acc_norm_stderr\": 0.0332201579577674\n\ \ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.42857142857142855,\n\ \ \"acc_stderr\": 0.04697113923010212,\n \"acc_norm\": 0.42857142857142855,\n\ \ \"acc_norm_stderr\": 0.04697113923010212\n },\n \"harness|hendrycksTest-management|5\"\ : {\n \"acc\": 0.8446601941747572,\n \"acc_stderr\": 0.03586594738573974,\n\ \ \"acc_norm\": 0.8446601941747572,\n \"acc_norm_stderr\": 0.03586594738573974\n\ \ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.8846153846153846,\n\ \ \"acc_stderr\": 0.02093019318517933,\n \"acc_norm\": 0.8846153846153846,\n\ \ \"acc_norm_stderr\": 0.02093019318517933\n },\n \"harness|hendrycksTest-medical_genetics|5\"\ : {\n \"acc\": 0.7,\n \"acc_stderr\": 0.046056618647183814,\n \ \ \"acc_norm\": 0.7,\n \"acc_norm_stderr\": 0.046056618647183814\n \ \ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.8314176245210728,\n\ \ \"acc_stderr\": 0.013387895731543604,\n \"acc_norm\": 0.8314176245210728,\n\ \ \"acc_norm_stderr\": 0.013387895731543604\n },\n \"harness|hendrycksTest-moral_disputes|5\"\ : {\n \"acc\": 0.7023121387283237,\n \"acc_stderr\": 0.024617055388676992,\n\ \ \"acc_norm\": 0.7023121387283237,\n \"acc_norm_stderr\": 0.024617055388676992\n\ \ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.29720670391061454,\n\ \ \"acc_stderr\": 0.015285313353641597,\n \"acc_norm\": 0.29720670391061454,\n\ \ \"acc_norm_stderr\": 0.015285313353641597\n },\n \"harness|hendrycksTest-nutrition|5\"\ : {\n \"acc\": 0.7189542483660131,\n \"acc_stderr\": 0.025738854797818723,\n\ \ \"acc_norm\": 0.7189542483660131,\n \"acc_norm_stderr\": 0.025738854797818723\n\ \ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.6752411575562701,\n\ \ \"acc_stderr\": 0.026596782287697043,\n \"acc_norm\": 0.6752411575562701,\n\ \ \"acc_norm_stderr\": 0.026596782287697043\n },\n \"harness|hendrycksTest-prehistory|5\"\ : {\n \"acc\": 0.75,\n \"acc_stderr\": 0.02409347123262133,\n \ \ \"acc_norm\": 0.75,\n \"acc_norm_stderr\": 0.02409347123262133\n \ \ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"acc\"\ : 0.4787234042553192,\n \"acc_stderr\": 0.029800481645628693,\n \"\ acc_norm\": 0.4787234042553192,\n \"acc_norm_stderr\": 0.029800481645628693\n\ \ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.46936114732724904,\n\ \ \"acc_stderr\": 0.012746237711716634,\n \"acc_norm\": 0.46936114732724904,\n\ \ \"acc_norm_stderr\": 0.012746237711716634\n },\n \"harness|hendrycksTest-professional_medicine|5\"\ : {\n \"acc\": 0.6507352941176471,\n \"acc_stderr\": 0.02895975519682487,\n\ \ \"acc_norm\": 0.6507352941176471,\n \"acc_norm_stderr\": 0.02895975519682487\n\ \ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\ acc\": 0.6454248366013072,\n \"acc_stderr\": 0.0193533605475537,\n \ \ \"acc_norm\": 0.6454248366013072,\n \"acc_norm_stderr\": 0.0193533605475537\n\ \ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.6727272727272727,\n\ \ \"acc_stderr\": 0.04494290866252092,\n \"acc_norm\": 0.6727272727272727,\n\ \ \"acc_norm_stderr\": 0.04494290866252092\n },\n \"harness|hendrycksTest-security_studies|5\"\ : {\n \"acc\": 0.7020408163265306,\n \"acc_stderr\": 0.029279567411065677,\n\ \ \"acc_norm\": 0.7020408163265306,\n \"acc_norm_stderr\": 0.029279567411065677\n\ \ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.845771144278607,\n\ \ \"acc_stderr\": 0.025538433368578337,\n \"acc_norm\": 0.845771144278607,\n\ \ \"acc_norm_stderr\": 0.025538433368578337\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\ : {\n \"acc\": 0.84,\n \"acc_stderr\": 0.03684529491774708,\n \ \ \"acc_norm\": 0.84,\n \"acc_norm_stderr\": 0.03684529491774708\n \ \ },\n \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.5240963855421686,\n\ \ \"acc_stderr\": 0.03887971849597264,\n \"acc_norm\": 0.5240963855421686,\n\ \ \"acc_norm_stderr\": 0.03887971849597264\n },\n \"harness|hendrycksTest-world_religions|5\"\ : {\n \"acc\": 0.8421052631578947,\n \"acc_stderr\": 0.02796678585916089,\n\ \ \"acc_norm\": 0.8421052631578947,\n \"acc_norm_stderr\": 0.02796678585916089\n\ \ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.3806609547123623,\n\ \ \"mc1_stderr\": 0.016997627871907922,\n \"mc2\": 0.5450293631615253,\n\ \ \"mc2_stderr\": 0.015380202565099867\n },\n \"harness|winogrande|5\"\ : {\n \"acc\": 0.7813733228097869,\n \"acc_stderr\": 0.011616198215773225\n\ \ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.44655041698256254,\n \ \ \"acc_stderr\": 0.01369356654974314\n }\n}\n```" repo_url: https://huggingface.co/CorticalStack/gemma-7b-ultrachat-sft leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2024_02_23T17_43_57.046792 path: - '**/details_harness|arc:challenge|25_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2024-02-23T17-43-57.046792.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '**/details_harness|gsm8k|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_02_23T17_43_57.046792 path: - '**/details_harness|hellaswag|10_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-management|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-management|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-02-23T17-43-57.046792.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '**/details_harness|hendrycksTest-anatomy|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '**/details_harness|hendrycksTest-astronomy|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '**/details_harness|hendrycksTest-college_biology|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '**/details_harness|hendrycksTest-college_physics|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '**/details_harness|hendrycksTest-computer_security|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '**/details_harness|hendrycksTest-econometrics|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '**/details_harness|hendrycksTest-global_facts|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '**/details_harness|hendrycksTest-human_aging|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '**/details_harness|hendrycksTest-international_law|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '**/details_harness|hendrycksTest-management|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '**/details_harness|hendrycksTest-marketing|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '**/details_harness|hendrycksTest-nutrition|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '**/details_harness|hendrycksTest-philosophy|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '**/details_harness|hendrycksTest-prehistory|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '**/details_harness|hendrycksTest-professional_law|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '**/details_harness|hendrycksTest-public_relations|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '**/details_harness|hendrycksTest-security_studies|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '**/details_harness|hendrycksTest-sociology|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '**/details_harness|hendrycksTest-virology|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '**/details_harness|hendrycksTest-world_religions|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2024-02-23T17-43-57.046792.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_02_23T17_43_57.046792 path: - '**/details_harness|truthfulqa:mc|0_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2024-02-23T17-43-57.046792.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_02_23T17_43_57.046792 path: - '**/details_harness|winogrande|5_2024-02-23T17-43-57.046792.parquet' - split: latest path: - '**/details_harness|winogrande|5_2024-02-23T17-43-57.046792.parquet' - config_name: results data_files: - split: 2024_02_23T17_43_57.046792 path: - results_2024-02-23T17-43-57.046792.parquet - split: latest path: - results_2024-02-23T17-43-57.046792.parquet --- # Dataset Card for Evaluation run of CorticalStack/gemma-7b-ultrachat-sft  Dataset automatically created during the evaluation run of model [CorticalStack/gemma-7b-ultrachat-sft](https://huggingface.co/CorticalStack/gemma-7b-ultrachat-sft) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_CorticalStack__gemma-7b-ultrachat-sft", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-02-23T17:43:57.046792](https://huggingface.co/datasets/open-llm-leaderboard/details_CorticalStack__gemma-7b-ultrachat-sft/blob/main/results_2024-02-23T17-43-57.046792.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval): ```python { "all": { "acc": 0.6393700582955444, "acc_stderr": 0.03219234730039111, "acc_norm": 0.6439639463015079, "acc_norm_stderr": 0.03283632439673242, "mc1": 0.3806609547123623, "mc1_stderr": 0.016997627871907922, "mc2": 0.5450293631615253, "mc2_stderr": 0.015380202565099867 }, "harness|arc:challenge|25": { "acc": 0.5878839590443686, "acc_stderr": 0.014383915302225403, "acc_norm": 0.6126279863481229, "acc_norm_stderr": 0.01423587248790987 }, "harness|hellaswag|10": { "acc": 0.6127265484963155, "acc_stderr": 0.004861314613286841, "acc_norm": 0.8082055367456682, "acc_norm_stderr": 0.003929076276473383 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.28, "acc_stderr": 0.045126085985421296, "acc_norm": 0.28, "acc_norm_stderr": 0.045126085985421296 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.6222222222222222, "acc_stderr": 0.04188307537595852, "acc_norm": 0.6222222222222222, "acc_norm_stderr": 0.04188307537595852 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.6776315789473685, "acc_stderr": 0.03803510248351585, "acc_norm": 0.6776315789473685, "acc_norm_stderr": 0.03803510248351585 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.57, "acc_stderr": 0.049756985195624284, "acc_norm": 0.57, "acc_norm_stderr": 0.049756985195624284 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.6452830188679245, "acc_stderr": 0.02944517532819959, "acc_norm": 0.6452830188679245, "acc_norm_stderr": 0.02944517532819959 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.7569444444444444, "acc_stderr": 0.0358687928008034, "acc_norm": 0.7569444444444444, "acc_norm_stderr": 0.0358687928008034 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.54, "acc_stderr": 0.05009082659620332, "acc_norm": 0.54, "acc_norm_stderr": 0.05009082659620332 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.52, "acc_stderr": 0.050211673156867795, "acc_norm": 0.52, "acc_norm_stderr": 0.050211673156867795 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.35, "acc_stderr": 0.047937248544110196, "acc_norm": 0.35, "acc_norm_stderr": 0.047937248544110196 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.6878612716763006, "acc_stderr": 0.03533133389323657, "acc_norm": 0.6878612716763006, "acc_norm_stderr": 0.03533133389323657 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.3431372549019608, "acc_stderr": 0.047240073523838876, "acc_norm": 0.3431372549019608, "acc_norm_stderr": 0.047240073523838876 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.71, "acc_stderr": 0.045604802157206845, "acc_norm": 0.71, "acc_norm_stderr": 0.045604802157206845 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.6085106382978723, "acc_stderr": 0.03190701242326812, "acc_norm": 0.6085106382978723, "acc_norm_stderr": 0.03190701242326812 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.40350877192982454, "acc_stderr": 0.046151869625837026, "acc_norm": 0.40350877192982454, "acc_norm_stderr": 0.046151869625837026 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.6413793103448275, "acc_stderr": 0.039966295748767186, "acc_norm": 0.6413793103448275, "acc_norm_stderr": 0.039966295748767186 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.4470899470899471, "acc_stderr": 0.025606723995777028, "acc_norm": 0.4470899470899471, "acc_norm_stderr": 0.025606723995777028 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.46825396825396826, "acc_stderr": 0.04463112720677172, "acc_norm": 0.46825396825396826, "acc_norm_stderr": 0.04463112720677172 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.38, "acc_stderr": 0.04878317312145633, "acc_norm": 0.38, "acc_norm_stderr": 0.04878317312145633 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.8064516129032258, "acc_stderr": 0.022475258525536057, "acc_norm": 0.8064516129032258, "acc_norm_stderr": 0.022475258525536057 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.5270935960591133, "acc_stderr": 0.03512819077876105, "acc_norm": 0.5270935960591133, "acc_norm_stderr": 0.03512819077876105 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.66, "acc_stderr": 0.04760952285695237, "acc_norm": 0.66, "acc_norm_stderr": 0.04760952285695237 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.7575757575757576, "acc_stderr": 0.03346409881055953, "acc_norm": 0.7575757575757576, "acc_norm_stderr": 0.03346409881055953 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.8484848484848485, "acc_stderr": 0.025545650426603617, "acc_norm": 0.8484848484848485, "acc_norm_stderr": 0.025545650426603617 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.8601036269430051, "acc_stderr": 0.025033870583015184, "acc_norm": 0.8601036269430051, "acc_norm_stderr": 0.025033870583015184 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.6692307692307692, "acc_stderr": 0.02385479568097112, "acc_norm": 0.6692307692307692, "acc_norm_stderr": 0.02385479568097112 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.37777777777777777, "acc_stderr": 0.029560707392465708, "acc_norm": 0.37777777777777777, "acc_norm_stderr": 0.029560707392465708 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.6932773109243697, "acc_stderr": 0.02995382389188703, "acc_norm": 0.6932773109243697, "acc_norm_stderr": 0.02995382389188703 }, "harness|hendrycksTest-high_school_physics|5": { "acc": 0.3841059602649007, "acc_stderr": 0.03971301814719197, "acc_norm": 0.3841059602649007, "acc_norm_stderr": 0.03971301814719197 }, "harness|hendrycksTest-high_school_psychology|5": { "acc": 0.8256880733944955, "acc_stderr": 0.016265675632010333, "acc_norm": 0.8256880733944955, "acc_norm_stderr": 0.016265675632010333 }, "harness|hendrycksTest-high_school_statistics|5": { "acc": 0.5694444444444444, "acc_stderr": 0.03376922151252335, "acc_norm": 0.5694444444444444, "acc_norm_stderr": 0.03376922151252335 }, "harness|hendrycksTest-high_school_us_history|5": { "acc": 0.8137254901960784, "acc_stderr": 0.02732547096671632, "acc_norm": 0.8137254901960784, "acc_norm_stderr": 0.02732547096671632 }, "harness|hendrycksTest-high_school_world_history|5": { "acc": 0.8185654008438819, "acc_stderr": 0.025085961144579647, "acc_norm": 0.8185654008438819, "acc_norm_stderr": 0.025085961144579647 }, "harness|hendrycksTest-human_aging|5": { "acc": 0.6995515695067265, "acc_stderr": 0.03076935200822915, "acc_norm": 0.6995515695067265, "acc_norm_stderr": 0.03076935200822915 }, "harness|hendrycksTest-human_sexuality|5": { "acc": 0.7175572519083969, "acc_stderr": 0.03948406125768361, "acc_norm": 0.7175572519083969, "acc_norm_stderr": 0.03948406125768361 }, "harness|hendrycksTest-international_law|5": { "acc": 0.8347107438016529, "acc_stderr": 0.03390780612972776, "acc_norm": 0.8347107438016529, "acc_norm_stderr": 0.03390780612972776 }, "harness|hendrycksTest-jurisprudence|5": { "acc": 0.7870370370370371, "acc_stderr": 0.039578354719809805, "acc_norm": 0.7870370370370371, "acc_norm_stderr": 0.039578354719809805 }, "harness|hendrycksTest-logical_fallacies|5": { "acc": 0.7668711656441718, "acc_stderr": 0.0332201579577674, "acc_norm": 0.7668711656441718, "acc_norm_stderr": 0.0332201579577674 }, "harness|hendrycksTest-machine_learning|5": { "acc": 0.42857142857142855, "acc_stderr": 0.04697113923010212, "acc_norm": 0.42857142857142855, "acc_norm_stderr": 0.04697113923010212 }, "harness|hendrycksTest-management|5": { "acc": 0.8446601941747572, "acc_stderr": 0.03586594738573974, "acc_norm": 0.8446601941747572, "acc_norm_stderr": 0.03586594738573974 }, "harness|hendrycksTest-marketing|5": { "acc": 0.8846153846153846, "acc_stderr": 0.02093019318517933, "acc_norm": 0.8846153846153846, "acc_norm_stderr": 0.02093019318517933 }, "harness|hendrycksTest-medical_genetics|5": { "acc": 0.7, "acc_stderr": 0.046056618647183814, "acc_norm": 0.7, "acc_norm_stderr": 0.046056618647183814 }, "harness|hendrycksTest-miscellaneous|5": { "acc": 0.8314176245210728, "acc_stderr": 0.013387895731543604, "acc_norm": 0.8314176245210728, "acc_norm_stderr": 0.013387895731543604 }, "harness|hendrycksTest-moral_disputes|5": { "acc": 0.7023121387283237, "acc_stderr": 0.024617055388676992, "acc_norm": 0.7023121387283237, "acc_norm_stderr": 0.024617055388676992 }, "harness|hendrycksTest-moral_scenarios|5": { "acc": 0.29720670391061454, "acc_stderr": 0.015285313353641597, "acc_norm": 0.29720670391061454, "acc_norm_stderr": 0.015285313353641597 }, "harness|hendrycksTest-nutrition|5": { "acc": 0.7189542483660131, "acc_stderr": 0.025738854797818723, "acc_norm": 0.7189542483660131, "acc_norm_stderr": 0.025738854797818723 }, "harness|hendrycksTest-philosophy|5": { "acc": 0.6752411575562701, "acc_stderr": 0.026596782287697043, "acc_norm": 0.6752411575562701, "acc_norm_stderr": 0.026596782287697043 }, "harness|hendrycksTest-prehistory|5": { "acc": 0.75, "acc_stderr": 0.02409347123262133, "acc_norm": 0.75, "acc_norm_stderr": 0.02409347123262133 }, "harness|hendrycksTest-professional_accounting|5": { "acc": 0.4787234042553192, "acc_stderr": 0.029800481645628693, "acc_norm": 0.4787234042553192, "acc_norm_stderr": 0.029800481645628693 }, "harness|hendrycksTest-professional_law|5": { "acc": 0.46936114732724904, "acc_stderr": 0.012746237711716634, "acc_norm": 0.46936114732724904, "acc_norm_stderr": 0.012746237711716634 }, "harness|hendrycksTest-professional_medicine|5": { "acc": 0.6507352941176471, "acc_stderr": 0.02895975519682487, "acc_norm": 0.6507352941176471, "acc_norm_stderr": 0.02895975519682487 }, "harness|hendrycksTest-professional_psychology|5": { "acc": 0.6454248366013072, "acc_stderr": 0.0193533605475537, "acc_norm": 0.6454248366013072, "acc_norm_stderr": 0.0193533605475537 }, "harness|hendrycksTest-public_relations|5": { "acc": 0.6727272727272727, "acc_stderr": 0.04494290866252092, "acc_norm": 0.6727272727272727, "acc_norm_stderr": 0.04494290866252092 }, "harness|hendrycksTest-security_studies|5": { "acc": 0.7020408163265306, "acc_stderr": 0.029279567411065677, "acc_norm": 0.7020408163265306, "acc_norm_stderr": 0.029279567411065677 }, "harness|hendrycksTest-sociology|5": { "acc": 0.845771144278607, "acc_stderr": 0.025538433368578337, "acc_norm": 0.845771144278607, "acc_norm_stderr": 0.025538433368578337 }, "harness|hendrycksTest-us_foreign_policy|5": { "acc": 0.84, "acc_stderr": 0.03684529491774708, "acc_norm": 0.84, "acc_norm_stderr": 0.03684529491774708 }, "harness|hendrycksTest-virology|5": { "acc": 0.5240963855421686, "acc_stderr": 0.03887971849597264, "acc_norm": 0.5240963855421686, "acc_norm_stderr": 0.03887971849597264 }, "harness|hendrycksTest-world_religions|5": { "acc": 0.8421052631578947, "acc_stderr": 0.02796678585916089, "acc_norm": 0.8421052631578947, "acc_norm_stderr": 0.02796678585916089 }, "harness|truthfulqa:mc|0": { "mc1": 0.3806609547123623, "mc1_stderr": 0.016997627871907922, "mc2": 0.5450293631615253, "mc2_stderr": 0.015380202565099867 }, "harness|winogrande|5": { "acc": 0.7813733228097869, "acc_stderr": 0.011616198215773225 }, "harness|gsm8k|5": { "acc": 0.44655041698256254, "acc_stderr": 0.01369356654974314 } } ``` ## Dataset Details ### Dataset Description  - **Curated by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] ### Dataset Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Dataset Structure  [More Information Needed] ## Dataset Creation ### Curation Rationale  [More Information Needed] ### Source Data  #### Data Collection and Processing  [More Information Needed] #### Who are the source data producers?  [More Information Needed] ### Annotations [optional]  #### Annotation process  [More Information Needed] #### Who are the annotators?  [More Information Needed] #### Personal and Sensitive Information  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations. ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Dataset Card Authors [optional] [More Information Needed] ## Dataset Card Contact [More Information Needed]

Eduardovco/Edu

--- license: openrail ---

open-llm-leaderboard/details_Azure99__blossom-v4-mistral-7b

--- pretty_name: Evaluation run of Azure99/blossom-v4-mistral-7b dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [Azure99/blossom-v4-mistral-7b](https://huggingface.co/Azure99/blossom-v4-mistral-7b)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 63 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the aggregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_Azure99__blossom-v4-mistral-7b\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-12-28T11:10:20.298869](https://huggingface.co/datasets/open-llm-leaderboard/details_Azure99__blossom-v4-mistral-7b/blob/main/results_2023-12-28T11-10-20.298869.json)(note\ \ that their might be results for other tasks in the repos if successive evals didn't\ \ cover the same tasks. You find each in the results and the \"latest\" split for\ \ each eval):\n\n```python\n{\n \"all\": {\n \"acc\": 0.6235420002967518,\n\ \ \"acc_stderr\": 0.03272388603364805,\n \"acc_norm\": 0.6281854377869052,\n\ \ \"acc_norm_stderr\": 0.03338061598239654,\n \"mc1\": 0.36964504283965727,\n\ \ \"mc1_stderr\": 0.016898180706973888,\n \"mc2\": 0.5384391963865467,\n\ \ \"mc2_stderr\": 0.015414673673859326\n },\n \"harness|arc:challenge|25\"\ : {\n \"acc\": 0.5793515358361775,\n \"acc_stderr\": 0.014426211252508397,\n\ \ \"acc_norm\": 0.6203071672354948,\n \"acc_norm_stderr\": 0.014182119866974872\n\ \ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.6390161322445728,\n\ \ \"acc_stderr\": 0.004793042992396035,\n \"acc_norm\": 0.8290181238797052,\n\ \ \"acc_norm_stderr\": 0.0037572368063973345\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\ : {\n \"acc\": 0.28,\n \"acc_stderr\": 0.04512608598542129,\n \ \ \"acc_norm\": 0.28,\n \"acc_norm_stderr\": 0.04512608598542129\n \ \ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.5851851851851851,\n\ \ \"acc_stderr\": 0.04256193767901409,\n \"acc_norm\": 0.5851851851851851,\n\ \ \"acc_norm_stderr\": 0.04256193767901409\n },\n \"harness|hendrycksTest-astronomy|5\"\ : {\n \"acc\": 0.6381578947368421,\n \"acc_stderr\": 0.03910525752849724,\n\ \ \"acc_norm\": 0.6381578947368421,\n \"acc_norm_stderr\": 0.03910525752849724\n\ \ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.62,\n\ \ \"acc_stderr\": 0.048783173121456316,\n \"acc_norm\": 0.62,\n \ \ \"acc_norm_stderr\": 0.048783173121456316\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\ : {\n \"acc\": 0.6943396226415094,\n \"acc_stderr\": 0.028353298073322666,\n\ \ \"acc_norm\": 0.6943396226415094,\n \"acc_norm_stderr\": 0.028353298073322666\n\ \ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.7152777777777778,\n\ \ \"acc_stderr\": 0.03773809990686934,\n \"acc_norm\": 0.7152777777777778,\n\ \ \"acc_norm_stderr\": 0.03773809990686934\n },\n \"harness|hendrycksTest-college_chemistry|5\"\ : {\n \"acc\": 0.45,\n \"acc_stderr\": 0.05,\n \"acc_norm\"\ : 0.45,\n \"acc_norm_stderr\": 0.05\n },\n \"harness|hendrycksTest-college_computer_science|5\"\ : {\n \"acc\": 0.5,\n \"acc_stderr\": 0.050251890762960605,\n \ \ \"acc_norm\": 0.5,\n \"acc_norm_stderr\": 0.050251890762960605\n \ \ },\n \"harness|hendrycksTest-college_mathematics|5\": {\n \"acc\": 0.36,\n\ \ \"acc_stderr\": 0.04824181513244218,\n \"acc_norm\": 0.36,\n \ \ \"acc_norm_stderr\": 0.04824181513244218\n },\n \"harness|hendrycksTest-college_medicine|5\"\ : {\n \"acc\": 0.5838150289017341,\n \"acc_stderr\": 0.03758517775404947,\n\ \ \"acc_norm\": 0.5838150289017341,\n \"acc_norm_stderr\": 0.03758517775404947\n\ \ },\n \"harness|hendrycksTest-college_physics|5\": {\n \"acc\": 0.4019607843137255,\n\ \ \"acc_stderr\": 0.048786087144669955,\n \"acc_norm\": 0.4019607843137255,\n\ \ \"acc_norm_stderr\": 0.048786087144669955\n },\n \"harness|hendrycksTest-computer_security|5\"\ : {\n \"acc\": 0.74,\n \"acc_stderr\": 0.0440844002276808,\n \ \ \"acc_norm\": 0.74,\n \"acc_norm_stderr\": 0.0440844002276808\n },\n\ \ \"harness|hendrycksTest-conceptual_physics|5\": {\n \"acc\": 0.5787234042553191,\n\ \ \"acc_stderr\": 0.03227834510146268,\n \"acc_norm\": 0.5787234042553191,\n\ \ \"acc_norm_stderr\": 0.03227834510146268\n },\n \"harness|hendrycksTest-econometrics|5\"\ : {\n \"acc\": 0.49122807017543857,\n \"acc_stderr\": 0.04702880432049615,\n\ \ \"acc_norm\": 0.49122807017543857,\n \"acc_norm_stderr\": 0.04702880432049615\n\ \ },\n \"harness|hendrycksTest-electrical_engineering|5\": {\n \"acc\"\ : 0.5724137931034483,\n \"acc_stderr\": 0.04122737111370333,\n \"\ acc_norm\": 0.5724137931034483,\n \"acc_norm_stderr\": 0.04122737111370333\n\ \ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\ : 0.41005291005291006,\n \"acc_stderr\": 0.02533120243894443,\n \"\ acc_norm\": 0.41005291005291006,\n \"acc_norm_stderr\": 0.02533120243894443\n\ \ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.3968253968253968,\n\ \ \"acc_stderr\": 0.04375888492727061,\n \"acc_norm\": 0.3968253968253968,\n\ \ \"acc_norm_stderr\": 0.04375888492727061\n },\n \"harness|hendrycksTest-global_facts|5\"\ : {\n \"acc\": 0.4,\n \"acc_stderr\": 0.049236596391733084,\n \ \ \"acc_norm\": 0.4,\n \"acc_norm_stderr\": 0.049236596391733084\n \ \ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\": 0.7322580645161291,\n\ \ \"acc_stderr\": 0.025189006660212378,\n \"acc_norm\": 0.7322580645161291,\n\ \ \"acc_norm_stderr\": 0.025189006660212378\n },\n \"harness|hendrycksTest-high_school_chemistry|5\"\ : {\n \"acc\": 0.5270935960591133,\n \"acc_stderr\": 0.03512819077876106,\n\ \ \"acc_norm\": 0.5270935960591133,\n \"acc_norm_stderr\": 0.03512819077876106\n\ \ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \ \ \"acc\": 0.68,\n \"acc_stderr\": 0.04688261722621505,\n \"acc_norm\"\ : 0.68,\n \"acc_norm_stderr\": 0.04688261722621505\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\ : {\n \"acc\": 0.7696969696969697,\n \"acc_stderr\": 0.0328766675860349,\n\ \ \"acc_norm\": 0.7696969696969697,\n \"acc_norm_stderr\": 0.0328766675860349\n\ \ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\ : 0.7828282828282829,\n \"acc_stderr\": 0.029376616484945627,\n \"\ acc_norm\": 0.7828282828282829,\n \"acc_norm_stderr\": 0.029376616484945627\n\ \ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\ \ \"acc\": 0.8549222797927462,\n \"acc_stderr\": 0.025416343096306433,\n\ \ \"acc_norm\": 0.8549222797927462,\n \"acc_norm_stderr\": 0.025416343096306433\n\ \ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \ \ \"acc\": 0.6153846153846154,\n \"acc_stderr\": 0.024666744915187208,\n\ \ \"acc_norm\": 0.6153846153846154,\n \"acc_norm_stderr\": 0.024666744915187208\n\ \ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\ acc\": 0.3148148148148148,\n \"acc_stderr\": 0.028317533496066468,\n \ \ \"acc_norm\": 0.3148148148148148,\n \"acc_norm_stderr\": 0.028317533496066468\n\ \ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \ \ \"acc\": 0.6554621848739496,\n \"acc_stderr\": 0.030868682604121622,\n\ \ \"acc_norm\": 0.6554621848739496,\n \"acc_norm_stderr\": 0.030868682604121622\n\ \ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\ : 0.32450331125827814,\n \"acc_stderr\": 0.03822746937658753,\n \"\ acc_norm\": 0.32450331125827814,\n \"acc_norm_stderr\": 0.03822746937658753\n\ \ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\ : 0.8018348623853211,\n \"acc_stderr\": 0.017090573804217902,\n \"\ acc_norm\": 0.8018348623853211,\n \"acc_norm_stderr\": 0.017090573804217902\n\ \ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\ : 0.4675925925925926,\n \"acc_stderr\": 0.03402801581358966,\n \"\ acc_norm\": 0.4675925925925926,\n \"acc_norm_stderr\": 0.03402801581358966\n\ \ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\ : 0.8235294117647058,\n \"acc_stderr\": 0.026756401538078966,\n \"\ acc_norm\": 0.8235294117647058,\n \"acc_norm_stderr\": 0.026756401538078966\n\ \ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\ acc\": 0.7721518987341772,\n \"acc_stderr\": 0.027303484599069422,\n \ \ \"acc_norm\": 0.7721518987341772,\n \"acc_norm_stderr\": 0.027303484599069422\n\ \ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.6502242152466368,\n\ \ \"acc_stderr\": 0.03200736719484503,\n \"acc_norm\": 0.6502242152466368,\n\ \ \"acc_norm_stderr\": 0.03200736719484503\n },\n \"harness|hendrycksTest-human_sexuality|5\"\ : {\n \"acc\": 0.7633587786259542,\n \"acc_stderr\": 0.03727673575596913,\n\ \ \"acc_norm\": 0.7633587786259542,\n \"acc_norm_stderr\": 0.03727673575596913\n\ \ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\ \ 0.7603305785123967,\n \"acc_stderr\": 0.03896878985070417,\n \"\ acc_norm\": 0.7603305785123967,\n \"acc_norm_stderr\": 0.03896878985070417\n\ \ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.75,\n\ \ \"acc_stderr\": 0.04186091791394607,\n \"acc_norm\": 0.75,\n \ \ \"acc_norm_stderr\": 0.04186091791394607\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\ : {\n \"acc\": 0.7484662576687117,\n \"acc_stderr\": 0.03408997886857529,\n\ \ \"acc_norm\": 0.7484662576687117,\n \"acc_norm_stderr\": 0.03408997886857529\n\ \ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.49107142857142855,\n\ \ \"acc_stderr\": 0.04745033255489123,\n \"acc_norm\": 0.49107142857142855,\n\ \ \"acc_norm_stderr\": 0.04745033255489123\n },\n \"harness|hendrycksTest-management|5\"\ : {\n \"acc\": 0.7961165048543689,\n \"acc_stderr\": 0.039891398595317706,\n\ \ \"acc_norm\": 0.7961165048543689,\n \"acc_norm_stderr\": 0.039891398595317706\n\ \ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.8760683760683761,\n\ \ \"acc_stderr\": 0.02158649400128136,\n \"acc_norm\": 0.8760683760683761,\n\ \ \"acc_norm_stderr\": 0.02158649400128136\n },\n \"harness|hendrycksTest-medical_genetics|5\"\ : {\n \"acc\": 0.66,\n \"acc_stderr\": 0.04760952285695237,\n \ \ \"acc_norm\": 0.66,\n \"acc_norm_stderr\": 0.04760952285695237\n \ \ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.80970625798212,\n\ \ \"acc_stderr\": 0.014036945850381398,\n \"acc_norm\": 0.80970625798212,\n\ \ \"acc_norm_stderr\": 0.014036945850381398\n },\n \"harness|hendrycksTest-moral_disputes|5\"\ : {\n \"acc\": 0.6878612716763006,\n \"acc_stderr\": 0.024946792225272314,\n\ \ \"acc_norm\": 0.6878612716763006,\n \"acc_norm_stderr\": 0.024946792225272314\n\ \ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.3329608938547486,\n\ \ \"acc_stderr\": 0.015761716178397566,\n \"acc_norm\": 0.3329608938547486,\n\ \ \"acc_norm_stderr\": 0.015761716178397566\n },\n \"harness|hendrycksTest-nutrition|5\"\ : {\n \"acc\": 0.7189542483660131,\n \"acc_stderr\": 0.025738854797818737,\n\ \ \"acc_norm\": 0.7189542483660131,\n \"acc_norm_stderr\": 0.025738854797818737\n\ \ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.707395498392283,\n\ \ \"acc_stderr\": 0.02583989833487798,\n \"acc_norm\": 0.707395498392283,\n\ \ \"acc_norm_stderr\": 0.02583989833487798\n },\n \"harness|hendrycksTest-prehistory|5\"\ : {\n \"acc\": 0.7129629629629629,\n \"acc_stderr\": 0.02517104191530968,\n\ \ \"acc_norm\": 0.7129629629629629,\n \"acc_norm_stderr\": 0.02517104191530968\n\ \ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\ acc\": 0.4929078014184397,\n \"acc_stderr\": 0.02982449855912901,\n \ \ \"acc_norm\": 0.4929078014184397,\n \"acc_norm_stderr\": 0.02982449855912901\n\ \ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.4511082138200782,\n\ \ \"acc_stderr\": 0.012709037347346233,\n \"acc_norm\": 0.4511082138200782,\n\ \ \"acc_norm_stderr\": 0.012709037347346233\n },\n \"harness|hendrycksTest-professional_medicine|5\"\ : {\n \"acc\": 0.6323529411764706,\n \"acc_stderr\": 0.029289413409403192,\n\ \ \"acc_norm\": 0.6323529411764706,\n \"acc_norm_stderr\": 0.029289413409403192\n\ \ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\ acc\": 0.6584967320261438,\n \"acc_stderr\": 0.01918463932809249,\n \ \ \"acc_norm\": 0.6584967320261438,\n \"acc_norm_stderr\": 0.01918463932809249\n\ \ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.6454545454545455,\n\ \ \"acc_stderr\": 0.04582004841505417,\n \"acc_norm\": 0.6454545454545455,\n\ \ \"acc_norm_stderr\": 0.04582004841505417\n },\n \"harness|hendrycksTest-security_studies|5\"\ : {\n \"acc\": 0.6979591836734694,\n \"acc_stderr\": 0.029393609319879804,\n\ \ \"acc_norm\": 0.6979591836734694,\n \"acc_norm_stderr\": 0.029393609319879804\n\ \ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.8407960199004975,\n\ \ \"acc_stderr\": 0.02587064676616913,\n \"acc_norm\": 0.8407960199004975,\n\ \ \"acc_norm_stderr\": 0.02587064676616913\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\ : {\n \"acc\": 0.84,\n \"acc_stderr\": 0.03684529491774709,\n \ \ \"acc_norm\": 0.84,\n \"acc_norm_stderr\": 0.03684529491774709\n \ \ },\n \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.536144578313253,\n\ \ \"acc_stderr\": 0.038823108508905954,\n \"acc_norm\": 0.536144578313253,\n\ \ \"acc_norm_stderr\": 0.038823108508905954\n },\n \"harness|hendrycksTest-world_religions|5\"\ : {\n \"acc\": 0.8128654970760234,\n \"acc_stderr\": 0.029913127232368036,\n\ \ \"acc_norm\": 0.8128654970760234,\n \"acc_norm_stderr\": 0.029913127232368036\n\ \ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.36964504283965727,\n\ \ \"mc1_stderr\": 0.016898180706973888,\n \"mc2\": 0.5384391963865467,\n\ \ \"mc2_stderr\": 0.015414673673859326\n },\n \"harness|winogrande|5\"\ : {\n \"acc\": 0.7726913970007893,\n \"acc_stderr\": 0.011778612167091087\n\ \ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.4313874147081122,\n \ \ \"acc_stderr\": 0.013642195352511575\n }\n}\n```" repo_url: https://huggingface.co/Azure99/blossom-v4-mistral-7b leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2023_12_28T11_10_20.298869 path: - '**/details_harness|arc:challenge|25_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2023-12-28T11-10-20.298869.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '**/details_harness|gsm8k|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_12_28T11_10_20.298869 path: - '**/details_harness|hellaswag|10_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-management|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-management|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-12-28T11-10-20.298869.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '**/details_harness|hendrycksTest-anatomy|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '**/details_harness|hendrycksTest-astronomy|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '**/details_harness|hendrycksTest-college_biology|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '**/details_harness|hendrycksTest-college_physics|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '**/details_harness|hendrycksTest-computer_security|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '**/details_harness|hendrycksTest-econometrics|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '**/details_harness|hendrycksTest-global_facts|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '**/details_harness|hendrycksTest-human_aging|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '**/details_harness|hendrycksTest-international_law|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '**/details_harness|hendrycksTest-management|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '**/details_harness|hendrycksTest-marketing|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '**/details_harness|hendrycksTest-nutrition|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '**/details_harness|hendrycksTest-philosophy|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '**/details_harness|hendrycksTest-prehistory|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '**/details_harness|hendrycksTest-professional_law|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '**/details_harness|hendrycksTest-public_relations|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '**/details_harness|hendrycksTest-security_studies|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '**/details_harness|hendrycksTest-sociology|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '**/details_harness|hendrycksTest-virology|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '**/details_harness|hendrycksTest-world_religions|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2023-12-28T11-10-20.298869.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_12_28T11_10_20.298869 path: - '**/details_harness|truthfulqa:mc|0_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2023-12-28T11-10-20.298869.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_12_28T11_10_20.298869 path: - '**/details_harness|winogrande|5_2023-12-28T11-10-20.298869.parquet' - split: latest path: - '**/details_harness|winogrande|5_2023-12-28T11-10-20.298869.parquet' - config_name: results data_files: - split: 2023_12_28T11_10_20.298869 path: - results_2023-12-28T11-10-20.298869.parquet - split: latest path: - results_2023-12-28T11-10-20.298869.parquet --- # Dataset Card for Evaluation run of Azure99/blossom-v4-mistral-7b  Dataset automatically created during the evaluation run of model [Azure99/blossom-v4-mistral-7b](https://huggingface.co/Azure99/blossom-v4-mistral-7b) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_Azure99__blossom-v4-mistral-7b", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-12-28T11:10:20.298869](https://huggingface.co/datasets/open-llm-leaderboard/details_Azure99__blossom-v4-mistral-7b/blob/main/results_2023-12-28T11-10-20.298869.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval): ```python { "all": { "acc": 0.6235420002967518, "acc_stderr": 0.03272388603364805, "acc_norm": 0.6281854377869052, "acc_norm_stderr": 0.03338061598239654, "mc1": 0.36964504283965727, "mc1_stderr": 0.016898180706973888, "mc2": 0.5384391963865467, "mc2_stderr": 0.015414673673859326 }, "harness|arc:challenge|25": { "acc": 0.5793515358361775, "acc_stderr": 0.014426211252508397, "acc_norm": 0.6203071672354948, "acc_norm_stderr": 0.014182119866974872 }, "harness|hellaswag|10": { "acc": 0.6390161322445728, "acc_stderr": 0.004793042992396035, "acc_norm": 0.8290181238797052, "acc_norm_stderr": 0.0037572368063973345 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.28, "acc_stderr": 0.04512608598542129, "acc_norm": 0.28, "acc_norm_stderr": 0.04512608598542129 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.5851851851851851, "acc_stderr": 0.04256193767901409, "acc_norm": 0.5851851851851851, "acc_norm_stderr": 0.04256193767901409 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.6381578947368421, "acc_stderr": 0.03910525752849724, "acc_norm": 0.6381578947368421, "acc_norm_stderr": 0.03910525752849724 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.62, "acc_stderr": 0.048783173121456316, "acc_norm": 0.62, "acc_norm_stderr": 0.048783173121456316 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.6943396226415094, "acc_stderr": 0.028353298073322666, "acc_norm": 0.6943396226415094, "acc_norm_stderr": 0.028353298073322666 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.7152777777777778, "acc_stderr": 0.03773809990686934, "acc_norm": 0.7152777777777778, "acc_norm_stderr": 0.03773809990686934 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.45, "acc_stderr": 0.05, "acc_norm": 0.45, "acc_norm_stderr": 0.05 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.5, "acc_stderr": 0.050251890762960605, "acc_norm": 0.5, "acc_norm_stderr": 0.050251890762960605 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.36, "acc_stderr": 0.04824181513244218, "acc_norm": 0.36, "acc_norm_stderr": 0.04824181513244218 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.5838150289017341, "acc_stderr": 0.03758517775404947, "acc_norm": 0.5838150289017341, "acc_norm_stderr": 0.03758517775404947 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.4019607843137255, "acc_stderr": 0.048786087144669955, "acc_norm": 0.4019607843137255, "acc_norm_stderr": 0.048786087144669955 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.74, "acc_stderr": 0.0440844002276808, "acc_norm": 0.74, "acc_norm_stderr": 0.0440844002276808 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.5787234042553191, "acc_stderr": 0.03227834510146268, "acc_norm": 0.5787234042553191, "acc_norm_stderr": 0.03227834510146268 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.49122807017543857, "acc_stderr": 0.04702880432049615, "acc_norm": 0.49122807017543857, "acc_norm_stderr": 0.04702880432049615 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.5724137931034483, "acc_stderr": 0.04122737111370333, "acc_norm": 0.5724137931034483, "acc_norm_stderr": 0.04122737111370333 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.41005291005291006, "acc_stderr": 0.02533120243894443, "acc_norm": 0.41005291005291006, "acc_norm_stderr": 0.02533120243894443 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.3968253968253968, "acc_stderr": 0.04375888492727061, "acc_norm": 0.3968253968253968, "acc_norm_stderr": 0.04375888492727061 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.4, "acc_stderr": 0.049236596391733084, "acc_norm": 0.4, "acc_norm_stderr": 0.049236596391733084 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.7322580645161291, "acc_stderr": 0.025189006660212378, "acc_norm": 0.7322580645161291, "acc_norm_stderr": 0.025189006660212378 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.5270935960591133, "acc_stderr": 0.03512819077876106, "acc_norm": 0.5270935960591133, "acc_norm_stderr": 0.03512819077876106 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.68, "acc_stderr": 0.04688261722621505, "acc_norm": 0.68, "acc_norm_stderr": 0.04688261722621505 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.7696969696969697, "acc_stderr": 0.0328766675860349, "acc_norm": 0.7696969696969697, "acc_norm_stderr": 0.0328766675860349 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.7828282828282829, "acc_stderr": 0.029376616484945627, "acc_norm": 0.7828282828282829, "acc_norm_stderr": 0.029376616484945627 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.8549222797927462, "acc_stderr": 0.025416343096306433, "acc_norm": 0.8549222797927462, "acc_norm_stderr": 0.025416343096306433 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.6153846153846154, "acc_stderr": 0.024666744915187208, "acc_norm": 0.6153846153846154, "acc_norm_stderr": 0.024666744915187208 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.3148148148148148, "acc_stderr": 0.028317533496066468, "acc_norm": 0.3148148148148148, "acc_norm_stderr": 0.028317533496066468 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.6554621848739496, "acc_stderr": 0.030868682604121622, "acc_norm": 0.6554621848739496, "acc_norm_stderr": 0.030868682604121622 }, "harness|hendrycksTest-high_school_physics|5": { "acc": 0.32450331125827814, "acc_stderr": 0.03822746937658753, "acc_norm": 0.32450331125827814, "acc_norm_stderr": 0.03822746937658753 }, "harness|hendrycksTest-high_school_psychology|5": { "acc": 0.8018348623853211, "acc_stderr": 0.017090573804217902, "acc_norm": 0.8018348623853211, "acc_norm_stderr": 0.017090573804217902 }, "harness|hendrycksTest-high_school_statistics|5": { "acc": 0.4675925925925926, "acc_stderr": 0.03402801581358966, "acc_norm": 0.4675925925925926, "acc_norm_stderr": 0.03402801581358966 }, "harness|hendrycksTest-high_school_us_history|5": { "acc": 0.8235294117647058, "acc_stderr": 0.026756401538078966, "acc_norm": 0.8235294117647058, "acc_norm_stderr": 0.026756401538078966 }, "harness|hendrycksTest-high_school_world_history|5": { "acc": 0.7721518987341772, "acc_stderr": 0.027303484599069422, "acc_norm": 0.7721518987341772, "acc_norm_stderr": 0.027303484599069422 }, "harness|hendrycksTest-human_aging|5": { "acc": 0.6502242152466368, "acc_stderr": 0.03200736719484503, "acc_norm": 0.6502242152466368, "acc_norm_stderr": 0.03200736719484503 }, "harness|hendrycksTest-human_sexuality|5": { "acc": 0.7633587786259542, "acc_stderr": 0.03727673575596913, "acc_norm": 0.7633587786259542, "acc_norm_stderr": 0.03727673575596913 }, "harness|hendrycksTest-international_law|5": { "acc": 0.7603305785123967, "acc_stderr": 0.03896878985070417, "acc_norm": 0.7603305785123967, "acc_norm_stderr": 0.03896878985070417 }, "harness|hendrycksTest-jurisprudence|5": { "acc": 0.75, "acc_stderr": 0.04186091791394607, "acc_norm": 0.75, "acc_norm_stderr": 0.04186091791394607 }, "harness|hendrycksTest-logical_fallacies|5": { "acc": 0.7484662576687117, "acc_stderr": 0.03408997886857529, "acc_norm": 0.7484662576687117, "acc_norm_stderr": 0.03408997886857529 }, "harness|hendrycksTest-machine_learning|5": { "acc": 0.49107142857142855, "acc_stderr": 0.04745033255489123, "acc_norm": 0.49107142857142855, "acc_norm_stderr": 0.04745033255489123 }, "harness|hendrycksTest-management|5": { "acc": 0.7961165048543689, "acc_stderr": 0.039891398595317706, "acc_norm": 0.7961165048543689, "acc_norm_stderr": 0.039891398595317706 }, "harness|hendrycksTest-marketing|5": { "acc": 0.8760683760683761, "acc_stderr": 0.02158649400128136, "acc_norm": 0.8760683760683761, "acc_norm_stderr": 0.02158649400128136 }, "harness|hendrycksTest-medical_genetics|5": { "acc": 0.66, "acc_stderr": 0.04760952285695237, "acc_norm": 0.66, "acc_norm_stderr": 0.04760952285695237 }, "harness|hendrycksTest-miscellaneous|5": { "acc": 0.80970625798212, "acc_stderr": 0.014036945850381398, "acc_norm": 0.80970625798212, "acc_norm_stderr": 0.014036945850381398 }, "harness|hendrycksTest-moral_disputes|5": { "acc": 0.6878612716763006, "acc_stderr": 0.024946792225272314, "acc_norm": 0.6878612716763006, "acc_norm_stderr": 0.024946792225272314 }, "harness|hendrycksTest-moral_scenarios|5": { "acc": 0.3329608938547486, "acc_stderr": 0.015761716178397566, "acc_norm": 0.3329608938547486, "acc_norm_stderr": 0.015761716178397566 }, "harness|hendrycksTest-nutrition|5": { "acc": 0.7189542483660131, "acc_stderr": 0.025738854797818737, "acc_norm": 0.7189542483660131, "acc_norm_stderr": 0.025738854797818737 }, "harness|hendrycksTest-philosophy|5": { "acc": 0.707395498392283, "acc_stderr": 0.02583989833487798, "acc_norm": 0.707395498392283, "acc_norm_stderr": 0.02583989833487798 }, "harness|hendrycksTest-prehistory|5": { "acc": 0.7129629629629629, "acc_stderr": 0.02517104191530968, "acc_norm": 0.7129629629629629, "acc_norm_stderr": 0.02517104191530968 }, "harness|hendrycksTest-professional_accounting|5": { "acc": 0.4929078014184397, "acc_stderr": 0.02982449855912901, "acc_norm": 0.4929078014184397, "acc_norm_stderr": 0.02982449855912901 }, "harness|hendrycksTest-professional_law|5": { "acc": 0.4511082138200782, "acc_stderr": 0.012709037347346233, "acc_norm": 0.4511082138200782, "acc_norm_stderr": 0.012709037347346233 }, "harness|hendrycksTest-professional_medicine|5": { "acc": 0.6323529411764706, "acc_stderr": 0.029289413409403192, "acc_norm": 0.6323529411764706, "acc_norm_stderr": 0.029289413409403192 }, "harness|hendrycksTest-professional_psychology|5": { "acc": 0.6584967320261438, "acc_stderr": 0.01918463932809249, "acc_norm": 0.6584967320261438, "acc_norm_stderr": 0.01918463932809249 }, "harness|hendrycksTest-public_relations|5": { "acc": 0.6454545454545455, "acc_stderr": 0.04582004841505417, "acc_norm": 0.6454545454545455, "acc_norm_stderr": 0.04582004841505417 }, "harness|hendrycksTest-security_studies|5": { "acc": 0.6979591836734694, "acc_stderr": 0.029393609319879804, "acc_norm": 0.6979591836734694, "acc_norm_stderr": 0.029393609319879804 }, "harness|hendrycksTest-sociology|5": { "acc": 0.8407960199004975, "acc_stderr": 0.02587064676616913, "acc_norm": 0.8407960199004975, "acc_norm_stderr": 0.02587064676616913 }, "harness|hendrycksTest-us_foreign_policy|5": { "acc": 0.84, "acc_stderr": 0.03684529491774709, "acc_norm": 0.84, "acc_norm_stderr": 0.03684529491774709 }, "harness|hendrycksTest-virology|5": { "acc": 0.536144578313253, "acc_stderr": 0.038823108508905954, "acc_norm": 0.536144578313253, "acc_norm_stderr": 0.038823108508905954 }, "harness|hendrycksTest-world_religions|5": { "acc": 0.8128654970760234, "acc_stderr": 0.029913127232368036, "acc_norm": 0.8128654970760234, "acc_norm_stderr": 0.029913127232368036 }, "harness|truthfulqa:mc|0": { "mc1": 0.36964504283965727, "mc1_stderr": 0.016898180706973888, "mc2": 0.5384391963865467, "mc2_stderr": 0.015414673673859326 }, "harness|winogrande|5": { "acc": 0.7726913970007893, "acc_stderr": 0.011778612167091087 }, "harness|gsm8k|5": { "acc": 0.4313874147081122, "acc_stderr": 0.013642195352511575 } } ``` ## Dataset Details ### Dataset Description  - **Curated by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] ### Dataset Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Dataset Structure  [More Information Needed] ## Dataset Creation ### Curation Rationale  [More Information Needed] ### Source Data  #### Data Collection and Processing  [More Information Needed] #### Who are the source data producers?  [More Information Needed] ### Annotations [optional]  #### Annotation process  [More Information Needed] #### Who are the annotators?  [More Information Needed] #### Personal and Sensitive Information  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations. ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Dataset Card Authors [optional] [More Information Needed] ## Dataset Card Contact [More Information Needed]

Zuntan/Animagine_XL_3.0-Character

--- license: unknown --- # Animagine XL 3.0 Character [EasySdxlWebUi](https://github.com/Zuntan03/EasySdxlWebUi) による [Animagine XL 3.0](https://huggingface.co/cagliostrolab/animagine-xl-3.0) の [公式 Character ワイルドカード](https://huggingface.co/spaces/Linaqruf/animagine-xl/resolve/main/wildcard/character.txt) の立ち絵データセットです。データセットのダウンロードは [こちら（2880枚、497MB）](https://huggingface.co/datasets/Zuntan/Animagine_XL_3.0-Character/resolve/main/character.zip?download=true)。 **[表情(278MB)](https://huggingface.co/datasets/Zuntan/Animagine_XL_3.0-Character/resolve/main/face.zip?download=true) と [画風(115MB)](https://yyy.wpx.jp/EasySdxlWebUi/style.zip) も用意しました。** ![face](./face_grid.webp) 画像の類似度や Tagger の結果比較で正常動作するワイルドカードリストを用意できないかな？と思って始めてみました。が、衣装違いなどの不正解画像でも作品名やキャラ名の影響を大きく受けるため、他のソースなしの正否分類は難しそうです。 - 各 webp 画像を [Stable Diffusion web UI](https://github.com/AUTOMATIC1111/stable-diffusion-webui) の `PNG内の情報を表示` にドラッグ＆ドロップすると生成情報を確認できます。 - プロンプトは `__animagine/character__, solo, full body, standing, no background, simple background, masterpiece, best quality <lora:lcm-animagine-3:1>` です。 - ネガティブプロンプト Animagine XL のデフォルトネガティブの先頭に NSFW 対策付与で `nsfw, rating: sensitive, lowres, bad anatomy, bad hands, text, error, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts, signature, watermark, username, blurry, artist name` です。 - アップスケール前の生成サイズは `832` x `1216` です。 - Seed は `1234567` です。 - 他のシードで正否が変わる可能性があります。 - 他は EasySdxlWebUi のデフォルト設定です。 [grid0](https://yyy.wpx.jp/m/202401/animagine_character/grid0.webp), [grid1](https://yyy.wpx.jp/m/202401/animagine_character/grid1.webp), [grid2](https://yyy.wpx.jp/m/202401/animagine_character/grid2.webp), [grid3](https://yyy.wpx.jp/m/202401/animagine_character/grid3.webp)

ramachaitanya22/mental_health_and_fitness_data

--- dataset_info: features: - name: Human dtype: string - name: Assistant dtype: string splits: - name: train num_bytes: 4021848.8 num_examples: 3552 - name: test num_bytes: 1005462.2 num_examples: 888 download_size: 2746185 dataset_size: 5027311.0 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---

mboth/luftVersorgen-50-undersampled

--- configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* - split: valid path: data/valid-* dataset_info: features: - name: Datatype dtype: string - name: Beschreibung dtype: string - name: Name dtype: string - name: Unit dtype: string - name: text dtype: string - name: Grundfunktion dtype: string - name: label dtype: class_label: names: '0': LuftBereitstellen '1': LuftVerteilen splits: - name: train num_bytes: 19757.430602572782 num_examples: 100 - name: test num_bytes: 290707 num_examples: 1477 - name: valid num_bytes: 290707 num_examples: 1477 download_size: 227539 dataset_size: 601171.4306025729 --- # Dataset Card for "luftVersorgen-50-undersampled" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

TrainingDataPro/roads-segmentation-dataset

--- license: cc-by-nc-nd-4.0 task_categories: - image-segmentation - image-to-image language: - en tags: - code --- # Roads Segmentation Dataset This dataset comprises a collection of images captured through **DVRs** (Digital Video Recorders) showcasing roads. Each image is accompanied by segmentation masks demarcating different entities (**road surface, cars, road signs, marking and background**) within the scene. The dataset can be utilized for enhancing computer vision algorithms involved in road surveillance, navigation, and intelligent transportation systemsand and in autonomous driving systems. ![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F12421376%2Fb0789a0ec8075d9c7abdb0aa9faced59%2FFrame%2012.png?generation=1694606364403023&alt=media) # Get the dataset ### This is just an example of the data Leave a request on [**https://trainingdata.pro/data-market**](https://trainingdata.pro/data-market/roads-segmentation?utm_source=huggingface&utm_medium=cpc&utm_campaign=roads-segmentation-dataset) to discuss your requirements, learn about the price and buy the dataset. # Dataset structure - **images** - contains of original images of roads - **masks** - includes segmentation masks created for the original images - **annotations.xml** - contains coordinates of the bounding boxes and detected text, created for the original photo # Data Format Each image from `images` folder is accompanied by an XML-annotation in the `annotations.xml` file indicating the coordinates of the polygons and labels . For each point, the x and y coordinates are provided. ### Сlasses: - **road_surface**: surface of the road, - **marking**: white and yellow marking on the road, - **road_sign**: road signs, - **car**: cars on the road, - **background**: side of the road and surronding objects # Example of XML file structure ![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F12421376%2Fa74a4214f4dd89a35527ef008abfc151%2Fcarbon.png?generation=1694608637609153&alt=media) # Roads Segmentation might be made in accordance with your requirements. ## [**TrainingData**](https://trainingdata.pro/data-market/roads-segmentation?utm_source=huggingface&utm_medium=cpc&utm_campaign=roads-segmentation-dataset) provides high-quality data annotation tailored to your needs More datasets in TrainingData's Kaggle account: **https://www.kaggle.com/trainingdatapro/datasets** TrainingData's GitHub: **https://github.com/Trainingdata-datamarket/TrainingData_All_datasets**

mesolitica/rumi-jawi

--- language: ms task_categories: - text2text-generation task_ids: [] tags: - conditional-text-generation --- # rumi-jawi Notebooks to gather the dataset at https://github.com/huseinzol05/malay-dataset/tree/master/normalization/rumi-jawi

open-llm-leaderboard/details_andysalerno__rainbowfish-v6

--- pretty_name: Evaluation run of andysalerno/rainbowfish-v6 dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [andysalerno/rainbowfish-v6](https://huggingface.co/andysalerno/rainbowfish-v6)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 63 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the aggregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_andysalerno__rainbowfish-v6\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-02-09T16:40:31.289715](https://huggingface.co/datasets/open-llm-leaderboard/details_andysalerno__rainbowfish-v6/blob/main/results_2024-02-09T16-40-31.289715.json)(note\ \ that their might be results for other tasks in the repos if successive evals didn't\ \ cover the same tasks. You find each in the results and the \"latest\" split for\ \ each eval):\n\n```python\n{\n \"all\": {\n \"acc\": 0.6251300156980985,\n\ \ \"acc_stderr\": 0.03253464808226719,\n \"acc_norm\": 0.6311200052519415,\n\ \ \"acc_norm_stderr\": 0.03319319250421297,\n \"mc1\": 0.3243574051407589,\n\ \ \"mc1_stderr\": 0.01638797677964794,\n \"mc2\": 0.4837489625680555,\n\ \ \"mc2_stderr\": 0.015088896132364547\n },\n \"harness|arc:challenge|25\"\ : {\n \"acc\": 0.5708191126279863,\n \"acc_stderr\": 0.014464085894870655,\n\ \ \"acc_norm\": 0.6194539249146758,\n \"acc_norm_stderr\": 0.014188277712349814\n\ \ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.628460466042621,\n\ \ \"acc_stderr\": 0.004822286556305222,\n \"acc_norm\": 0.8251344353714399,\n\ \ \"acc_norm_stderr\": 0.003790757646575897\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\ : {\n \"acc\": 0.27,\n \"acc_stderr\": 0.0446196043338474,\n \ \ \"acc_norm\": 0.27,\n \"acc_norm_stderr\": 0.0446196043338474\n },\n\ \ \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.6222222222222222,\n\ \ \"acc_stderr\": 0.04188307537595852,\n \"acc_norm\": 0.6222222222222222,\n\ \ \"acc_norm_stderr\": 0.04188307537595852\n },\n \"harness|hendrycksTest-astronomy|5\"\ : {\n \"acc\": 0.6710526315789473,\n \"acc_stderr\": 0.038234289699266046,\n\ \ \"acc_norm\": 0.6710526315789473,\n \"acc_norm_stderr\": 0.038234289699266046\n\ \ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.59,\n\ \ \"acc_stderr\": 0.049431107042371025,\n \"acc_norm\": 0.59,\n \ \ \"acc_norm_stderr\": 0.049431107042371025\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\ : {\n \"acc\": 0.6867924528301886,\n \"acc_stderr\": 0.028544793319055326,\n\ \ \"acc_norm\": 0.6867924528301886,\n \"acc_norm_stderr\": 0.028544793319055326\n\ \ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.7291666666666666,\n\ \ \"acc_stderr\": 0.03716177437566017,\n \"acc_norm\": 0.7291666666666666,\n\ \ \"acc_norm_stderr\": 0.03716177437566017\n },\n \"harness|hendrycksTest-college_chemistry|5\"\ : {\n \"acc\": 0.48,\n \"acc_stderr\": 0.050211673156867795,\n \ \ \"acc_norm\": 0.48,\n \"acc_norm_stderr\": 0.050211673156867795\n \ \ },\n \"harness|hendrycksTest-college_computer_science|5\": {\n \"\ acc\": 0.51,\n \"acc_stderr\": 0.05024183937956912,\n \"acc_norm\"\ : 0.51,\n \"acc_norm_stderr\": 0.05024183937956912\n },\n \"harness|hendrycksTest-college_mathematics|5\"\ : {\n \"acc\": 0.35,\n \"acc_stderr\": 0.047937248544110196,\n \ \ \"acc_norm\": 0.35,\n \"acc_norm_stderr\": 0.047937248544110196\n \ \ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.6184971098265896,\n\ \ \"acc_stderr\": 0.03703851193099521,\n \"acc_norm\": 0.6184971098265896,\n\ \ \"acc_norm_stderr\": 0.03703851193099521\n },\n \"harness|hendrycksTest-college_physics|5\"\ : {\n \"acc\": 0.3333333333333333,\n \"acc_stderr\": 0.04690650298201942,\n\ \ \"acc_norm\": 0.3333333333333333,\n \"acc_norm_stderr\": 0.04690650298201942\n\ \ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\ \ 0.77,\n \"acc_stderr\": 0.04229525846816505,\n \"acc_norm\": 0.77,\n\ \ \"acc_norm_stderr\": 0.04229525846816505\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\ : {\n \"acc\": 0.5446808510638298,\n \"acc_stderr\": 0.03255525359340355,\n\ \ \"acc_norm\": 0.5446808510638298,\n \"acc_norm_stderr\": 0.03255525359340355\n\ \ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.49122807017543857,\n\ \ \"acc_stderr\": 0.047028804320496165,\n \"acc_norm\": 0.49122807017543857,\n\ \ \"acc_norm_stderr\": 0.047028804320496165\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\ : {\n \"acc\": 0.5655172413793104,\n \"acc_stderr\": 0.04130740879555498,\n\ \ \"acc_norm\": 0.5655172413793104,\n \"acc_norm_stderr\": 0.04130740879555498\n\ \ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\ : 0.3888888888888889,\n \"acc_stderr\": 0.025107425481137282,\n \"\ acc_norm\": 0.3888888888888889,\n \"acc_norm_stderr\": 0.025107425481137282\n\ \ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.3968253968253968,\n\ \ \"acc_stderr\": 0.043758884927270605,\n \"acc_norm\": 0.3968253968253968,\n\ \ \"acc_norm_stderr\": 0.043758884927270605\n },\n \"harness|hendrycksTest-global_facts|5\"\ : {\n \"acc\": 0.4,\n \"acc_stderr\": 0.04923659639173309,\n \ \ \"acc_norm\": 0.4,\n \"acc_norm_stderr\": 0.04923659639173309\n },\n\ \ \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\": 0.7451612903225806,\n\ \ \"acc_stderr\": 0.024790118459332208,\n \"acc_norm\": 0.7451612903225806,\n\ \ \"acc_norm_stderr\": 0.024790118459332208\n },\n \"harness|hendrycksTest-high_school_chemistry|5\"\ : {\n \"acc\": 0.5270935960591133,\n \"acc_stderr\": 0.03512819077876106,\n\ \ \"acc_norm\": 0.5270935960591133,\n \"acc_norm_stderr\": 0.03512819077876106\n\ \ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \ \ \"acc\": 0.67,\n \"acc_stderr\": 0.047258156262526066,\n \"acc_norm\"\ : 0.67,\n \"acc_norm_stderr\": 0.047258156262526066\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\ : {\n \"acc\": 0.7636363636363637,\n \"acc_stderr\": 0.033175059300091826,\n\ \ \"acc_norm\": 0.7636363636363637,\n \"acc_norm_stderr\": 0.033175059300091826\n\ \ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\ : 0.7777777777777778,\n \"acc_stderr\": 0.02962022787479048,\n \"\ acc_norm\": 0.7777777777777778,\n \"acc_norm_stderr\": 0.02962022787479048\n\ \ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\ \ \"acc\": 0.8756476683937824,\n \"acc_stderr\": 0.02381447708659355,\n\ \ \"acc_norm\": 0.8756476683937824,\n \"acc_norm_stderr\": 0.02381447708659355\n\ \ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \ \ \"acc\": 0.617948717948718,\n \"acc_stderr\": 0.024635549163908237,\n \ \ \"acc_norm\": 0.617948717948718,\n \"acc_norm_stderr\": 0.024635549163908237\n\ \ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\ acc\": 0.337037037037037,\n \"acc_stderr\": 0.028820884666253255,\n \ \ \"acc_norm\": 0.337037037037037,\n \"acc_norm_stderr\": 0.028820884666253255\n\ \ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \ \ \"acc\": 0.6680672268907563,\n \"acc_stderr\": 0.03058869701378364,\n \ \ \"acc_norm\": 0.6680672268907563,\n \"acc_norm_stderr\": 0.03058869701378364\n\ \ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\ : 0.33774834437086093,\n \"acc_stderr\": 0.03861557546255169,\n \"\ acc_norm\": 0.33774834437086093,\n \"acc_norm_stderr\": 0.03861557546255169\n\ \ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\ : 0.8036697247706422,\n \"acc_stderr\": 0.01703071933915435,\n \"\ acc_norm\": 0.8036697247706422,\n \"acc_norm_stderr\": 0.01703071933915435\n\ \ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\ : 0.49537037037037035,\n \"acc_stderr\": 0.03409825519163572,\n \"\ acc_norm\": 0.49537037037037035,\n \"acc_norm_stderr\": 0.03409825519163572\n\ \ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\ : 0.7990196078431373,\n \"acc_stderr\": 0.028125972265654373,\n \"\ acc_norm\": 0.7990196078431373,\n \"acc_norm_stderr\": 0.028125972265654373\n\ \ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\ acc\": 0.7805907172995781,\n \"acc_stderr\": 0.026939106581553945,\n \ \ \"acc_norm\": 0.7805907172995781,\n \"acc_norm_stderr\": 0.026939106581553945\n\ \ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.6547085201793722,\n\ \ \"acc_stderr\": 0.03191100192835794,\n \"acc_norm\": 0.6547085201793722,\n\ \ \"acc_norm_stderr\": 0.03191100192835794\n },\n \"harness|hendrycksTest-human_sexuality|5\"\ : {\n \"acc\": 0.7709923664122137,\n \"acc_stderr\": 0.036853466317118506,\n\ \ \"acc_norm\": 0.7709923664122137,\n \"acc_norm_stderr\": 0.036853466317118506\n\ \ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\ \ 0.8016528925619835,\n \"acc_stderr\": 0.036401182719909456,\n \"\ acc_norm\": 0.8016528925619835,\n \"acc_norm_stderr\": 0.036401182719909456\n\ \ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.7592592592592593,\n\ \ \"acc_stderr\": 0.04133119440243838,\n \"acc_norm\": 0.7592592592592593,\n\ \ \"acc_norm_stderr\": 0.04133119440243838\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\ : {\n \"acc\": 0.7730061349693251,\n \"acc_stderr\": 0.032910995786157686,\n\ \ \"acc_norm\": 0.7730061349693251,\n \"acc_norm_stderr\": 0.032910995786157686\n\ \ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.44642857142857145,\n\ \ \"acc_stderr\": 0.04718471485219588,\n \"acc_norm\": 0.44642857142857145,\n\ \ \"acc_norm_stderr\": 0.04718471485219588\n },\n \"harness|hendrycksTest-management|5\"\ : {\n \"acc\": 0.7572815533980582,\n \"acc_stderr\": 0.04245022486384495,\n\ \ \"acc_norm\": 0.7572815533980582,\n \"acc_norm_stderr\": 0.04245022486384495\n\ \ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.8589743589743589,\n\ \ \"acc_stderr\": 0.022801382534597524,\n \"acc_norm\": 0.8589743589743589,\n\ \ \"acc_norm_stderr\": 0.022801382534597524\n },\n \"harness|hendrycksTest-medical_genetics|5\"\ : {\n \"acc\": 0.7,\n \"acc_stderr\": 0.046056618647183814,\n \ \ \"acc_norm\": 0.7,\n \"acc_norm_stderr\": 0.046056618647183814\n \ \ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.8071519795657727,\n\ \ \"acc_stderr\": 0.014108533515757431,\n \"acc_norm\": 0.8071519795657727,\n\ \ \"acc_norm_stderr\": 0.014108533515757431\n },\n \"harness|hendrycksTest-moral_disputes|5\"\ : {\n \"acc\": 0.6965317919075145,\n \"acc_stderr\": 0.024752411960917212,\n\ \ \"acc_norm\": 0.6965317919075145,\n \"acc_norm_stderr\": 0.024752411960917212\n\ \ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.29608938547486036,\n\ \ \"acc_stderr\": 0.01526867731760228,\n \"acc_norm\": 0.29608938547486036,\n\ \ \"acc_norm_stderr\": 0.01526867731760228\n },\n \"harness|hendrycksTest-nutrition|5\"\ : {\n \"acc\": 0.7549019607843137,\n \"acc_stderr\": 0.024630048979824775,\n\ \ \"acc_norm\": 0.7549019607843137,\n \"acc_norm_stderr\": 0.024630048979824775\n\ \ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.7266881028938906,\n\ \ \"acc_stderr\": 0.025311765975426122,\n \"acc_norm\": 0.7266881028938906,\n\ \ \"acc_norm_stderr\": 0.025311765975426122\n },\n \"harness|hendrycksTest-prehistory|5\"\ : {\n \"acc\": 0.7098765432098766,\n \"acc_stderr\": 0.025251173936495036,\n\ \ \"acc_norm\": 0.7098765432098766,\n \"acc_norm_stderr\": 0.025251173936495036\n\ \ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\ acc\": 0.5,\n \"acc_stderr\": 0.029827499313594685,\n \"acc_norm\"\ : 0.5,\n \"acc_norm_stderr\": 0.029827499313594685\n },\n \"harness|hendrycksTest-professional_law|5\"\ : {\n \"acc\": 0.4491525423728814,\n \"acc_stderr\": 0.01270403051885149,\n\ \ \"acc_norm\": 0.4491525423728814,\n \"acc_norm_stderr\": 0.01270403051885149\n\ \ },\n \"harness|hendrycksTest-professional_medicine|5\": {\n \"acc\"\ : 0.6654411764705882,\n \"acc_stderr\": 0.028661996202335303,\n \"\ acc_norm\": 0.6654411764705882,\n \"acc_norm_stderr\": 0.028661996202335303\n\ \ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\ acc\": 0.6552287581699346,\n \"acc_stderr\": 0.01922832201869664,\n \ \ \"acc_norm\": 0.6552287581699346,\n \"acc_norm_stderr\": 0.01922832201869664\n\ \ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.6454545454545455,\n\ \ \"acc_stderr\": 0.045820048415054174,\n \"acc_norm\": 0.6454545454545455,\n\ \ \"acc_norm_stderr\": 0.045820048415054174\n },\n \"harness|hendrycksTest-security_studies|5\"\ : {\n \"acc\": 0.7346938775510204,\n \"acc_stderr\": 0.028263889943784603,\n\ \ \"acc_norm\": 0.7346938775510204,\n \"acc_norm_stderr\": 0.028263889943784603\n\ \ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.8059701492537313,\n\ \ \"acc_stderr\": 0.027962677604768914,\n \"acc_norm\": 0.8059701492537313,\n\ \ \"acc_norm_stderr\": 0.027962677604768914\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\ : {\n \"acc\": 0.85,\n \"acc_stderr\": 0.03588702812826371,\n \ \ \"acc_norm\": 0.85,\n \"acc_norm_stderr\": 0.03588702812826371\n \ \ },\n \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.5421686746987951,\n\ \ \"acc_stderr\": 0.0387862677100236,\n \"acc_norm\": 0.5421686746987951,\n\ \ \"acc_norm_stderr\": 0.0387862677100236\n },\n \"harness|hendrycksTest-world_religions|5\"\ : {\n \"acc\": 0.8128654970760234,\n \"acc_stderr\": 0.029913127232368036,\n\ \ \"acc_norm\": 0.8128654970760234,\n \"acc_norm_stderr\": 0.029913127232368036\n\ \ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.3243574051407589,\n\ \ \"mc1_stderr\": 0.01638797677964794,\n \"mc2\": 0.4837489625680555,\n\ \ \"mc2_stderr\": 0.015088896132364547\n },\n \"harness|winogrande|5\"\ : {\n \"acc\": 0.7790055248618785,\n \"acc_stderr\": 0.01166122363764341\n\ \ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.36315390447308565,\n \ \ \"acc_stderr\": 0.013246614539839868\n }\n}\n```" repo_url: https://huggingface.co/andysalerno/rainbowfish-v6 leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2024_02_09T16_40_31.289715 path: - '**/details_harness|arc:challenge|25_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2024-02-09T16-40-31.289715.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '**/details_harness|gsm8k|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_02_09T16_40_31.289715 path: - '**/details_harness|hellaswag|10_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-management|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-management|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-02-09T16-40-31.289715.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '**/details_harness|hendrycksTest-anatomy|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '**/details_harness|hendrycksTest-astronomy|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '**/details_harness|hendrycksTest-college_biology|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '**/details_harness|hendrycksTest-college_physics|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '**/details_harness|hendrycksTest-computer_security|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '**/details_harness|hendrycksTest-econometrics|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '**/details_harness|hendrycksTest-global_facts|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '**/details_harness|hendrycksTest-human_aging|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '**/details_harness|hendrycksTest-international_law|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '**/details_harness|hendrycksTest-management|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '**/details_harness|hendrycksTest-marketing|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '**/details_harness|hendrycksTest-nutrition|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '**/details_harness|hendrycksTest-philosophy|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '**/details_harness|hendrycksTest-prehistory|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '**/details_harness|hendrycksTest-professional_law|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '**/details_harness|hendrycksTest-public_relations|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '**/details_harness|hendrycksTest-security_studies|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '**/details_harness|hendrycksTest-sociology|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '**/details_harness|hendrycksTest-virology|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '**/details_harness|hendrycksTest-world_religions|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2024-02-09T16-40-31.289715.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_02_09T16_40_31.289715 path: - '**/details_harness|truthfulqa:mc|0_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2024-02-09T16-40-31.289715.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_02_09T16_40_31.289715 path: - '**/details_harness|winogrande|5_2024-02-09T16-40-31.289715.parquet' - split: latest path: - '**/details_harness|winogrande|5_2024-02-09T16-40-31.289715.parquet' - config_name: results data_files: - split: 2024_02_09T16_40_31.289715 path: - results_2024-02-09T16-40-31.289715.parquet - split: latest path: - results_2024-02-09T16-40-31.289715.parquet --- # Dataset Card for Evaluation run of andysalerno/rainbowfish-v6  Dataset automatically created during the evaluation run of model [andysalerno/rainbowfish-v6](https://huggingface.co/andysalerno/rainbowfish-v6) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_andysalerno__rainbowfish-v6", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-02-09T16:40:31.289715](https://huggingface.co/datasets/open-llm-leaderboard/details_andysalerno__rainbowfish-v6/blob/main/results_2024-02-09T16-40-31.289715.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval): ```python { "all": { "acc": 0.6251300156980985, "acc_stderr": 0.03253464808226719, "acc_norm": 0.6311200052519415, "acc_norm_stderr": 0.03319319250421297, "mc1": 0.3243574051407589, "mc1_stderr": 0.01638797677964794, "mc2": 0.4837489625680555, "mc2_stderr": 0.015088896132364547 }, "harness|arc:challenge|25": { "acc": 0.5708191126279863, "acc_stderr": 0.014464085894870655, "acc_norm": 0.6194539249146758, "acc_norm_stderr": 0.014188277712349814 }, "harness|hellaswag|10": { "acc": 0.628460466042621, "acc_stderr": 0.004822286556305222, "acc_norm": 0.8251344353714399, "acc_norm_stderr": 0.003790757646575897 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.27, "acc_stderr": 0.0446196043338474, "acc_norm": 0.27, "acc_norm_stderr": 0.0446196043338474 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.6222222222222222, "acc_stderr": 0.04188307537595852, "acc_norm": 0.6222222222222222, "acc_norm_stderr": 0.04188307537595852 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.6710526315789473, "acc_stderr": 0.038234289699266046, "acc_norm": 0.6710526315789473, "acc_norm_stderr": 0.038234289699266046 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.59, "acc_stderr": 0.049431107042371025, "acc_norm": 0.59, "acc_norm_stderr": 0.049431107042371025 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.6867924528301886, "acc_stderr": 0.028544793319055326, "acc_norm": 0.6867924528301886, "acc_norm_stderr": 0.028544793319055326 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.7291666666666666, "acc_stderr": 0.03716177437566017, "acc_norm": 0.7291666666666666, "acc_norm_stderr": 0.03716177437566017 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.48, "acc_stderr": 0.050211673156867795, "acc_norm": 0.48, "acc_norm_stderr": 0.050211673156867795 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.51, "acc_stderr": 0.05024183937956912, "acc_norm": 0.51, "acc_norm_stderr": 0.05024183937956912 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.35, "acc_stderr": 0.047937248544110196, "acc_norm": 0.35, "acc_norm_stderr": 0.047937248544110196 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.6184971098265896, "acc_stderr": 0.03703851193099521, "acc_norm": 0.6184971098265896, "acc_norm_stderr": 0.03703851193099521 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.3333333333333333, "acc_stderr": 0.04690650298201942, "acc_norm": 0.3333333333333333, "acc_norm_stderr": 0.04690650298201942 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.77, "acc_stderr": 0.04229525846816505, "acc_norm": 0.77, "acc_norm_stderr": 0.04229525846816505 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.5446808510638298, "acc_stderr": 0.03255525359340355, "acc_norm": 0.5446808510638298, "acc_norm_stderr": 0.03255525359340355 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.49122807017543857, "acc_stderr": 0.047028804320496165, "acc_norm": 0.49122807017543857, "acc_norm_stderr": 0.047028804320496165 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.5655172413793104, "acc_stderr": 0.04130740879555498, "acc_norm": 0.5655172413793104, "acc_norm_stderr": 0.04130740879555498 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.3888888888888889, "acc_stderr": 0.025107425481137282, "acc_norm": 0.3888888888888889, "acc_norm_stderr": 0.025107425481137282 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.3968253968253968, "acc_stderr": 0.043758884927270605, "acc_norm": 0.3968253968253968, "acc_norm_stderr": 0.043758884927270605 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.4, "acc_stderr": 0.04923659639173309, "acc_norm": 0.4, "acc_norm_stderr": 0.04923659639173309 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.7451612903225806, "acc_stderr": 0.024790118459332208, "acc_norm": 0.7451612903225806, "acc_norm_stderr": 0.024790118459332208 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.5270935960591133, "acc_stderr": 0.03512819077876106, "acc_norm": 0.5270935960591133, "acc_norm_stderr": 0.03512819077876106 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.67, "acc_stderr": 0.047258156262526066, "acc_norm": 0.67, "acc_norm_stderr": 0.047258156262526066 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.7636363636363637, "acc_stderr": 0.033175059300091826, "acc_norm": 0.7636363636363637, "acc_norm_stderr": 0.033175059300091826 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.7777777777777778, "acc_stderr": 0.02962022787479048, "acc_norm": 0.7777777777777778, "acc_norm_stderr": 0.02962022787479048 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.8756476683937824, "acc_stderr": 0.02381447708659355, "acc_norm": 0.8756476683937824, "acc_norm_stderr": 0.02381447708659355 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.617948717948718, "acc_stderr": 0.024635549163908237, "acc_norm": 0.617948717948718, "acc_norm_stderr": 0.024635549163908237 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.337037037037037, "acc_stderr": 0.028820884666253255, "acc_norm": 0.337037037037037, "acc_norm_stderr": 0.028820884666253255 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.6680672268907563, "acc_stderr": 0.03058869701378364, "acc_norm": 0.6680672268907563, "acc_norm_stderr": 0.03058869701378364 }, "harness|hendrycksTest-high_school_physics|5": { "acc": 0.33774834437086093, "acc_stderr": 0.03861557546255169, "acc_norm": 0.33774834437086093, "acc_norm_stderr": 0.03861557546255169 }, "harness|hendrycksTest-high_school_psychology|5": { "acc": 0.8036697247706422, "acc_stderr": 0.01703071933915435, "acc_norm": 0.8036697247706422, "acc_norm_stderr": 0.01703071933915435 }, "harness|hendrycksTest-high_school_statistics|5": { "acc": 0.49537037037037035, "acc_stderr": 0.03409825519163572, "acc_norm": 0.49537037037037035, "acc_norm_stderr": 0.03409825519163572 }, "harness|hendrycksTest-high_school_us_history|5": { "acc": 0.7990196078431373, "acc_stderr": 0.028125972265654373, "acc_norm": 0.7990196078431373, "acc_norm_stderr": 0.028125972265654373 }, "harness|hendrycksTest-high_school_world_history|5": { "acc": 0.7805907172995781, "acc_stderr": 0.026939106581553945, "acc_norm": 0.7805907172995781, "acc_norm_stderr": 0.026939106581553945 }, "harness|hendrycksTest-human_aging|5": { "acc": 0.6547085201793722, "acc_stderr": 0.03191100192835794, "acc_norm": 0.6547085201793722, "acc_norm_stderr": 0.03191100192835794 }, "harness|hendrycksTest-human_sexuality|5": { "acc": 0.7709923664122137, "acc_stderr": 0.036853466317118506, "acc_norm": 0.7709923664122137, "acc_norm_stderr": 0.036853466317118506 }, "harness|hendrycksTest-international_law|5": { "acc": 0.8016528925619835, "acc_stderr": 0.036401182719909456, "acc_norm": 0.8016528925619835, "acc_norm_stderr": 0.036401182719909456 }, "harness|hendrycksTest-jurisprudence|5": { "acc": 0.7592592592592593, "acc_stderr": 0.04133119440243838, "acc_norm": 0.7592592592592593, "acc_norm_stderr": 0.04133119440243838 }, "harness|hendrycksTest-logical_fallacies|5": { "acc": 0.7730061349693251, "acc_stderr": 0.032910995786157686, "acc_norm": 0.7730061349693251, "acc_norm_stderr": 0.032910995786157686 }, "harness|hendrycksTest-machine_learning|5": { "acc": 0.44642857142857145, "acc_stderr": 0.04718471485219588, "acc_norm": 0.44642857142857145, "acc_norm_stderr": 0.04718471485219588 }, "harness|hendrycksTest-management|5": { "acc": 0.7572815533980582, "acc_stderr": 0.04245022486384495, "acc_norm": 0.7572815533980582, "acc_norm_stderr": 0.04245022486384495 }, "harness|hendrycksTest-marketing|5": { "acc": 0.8589743589743589, "acc_stderr": 0.022801382534597524, "acc_norm": 0.8589743589743589, "acc_norm_stderr": 0.022801382534597524 }, "harness|hendrycksTest-medical_genetics|5": { "acc": 0.7, "acc_stderr": 0.046056618647183814, "acc_norm": 0.7, "acc_norm_stderr": 0.046056618647183814 }, "harness|hendrycksTest-miscellaneous|5": { "acc": 0.8071519795657727, "acc_stderr": 0.014108533515757431, "acc_norm": 0.8071519795657727, "acc_norm_stderr": 0.014108533515757431 }, "harness|hendrycksTest-moral_disputes|5": { "acc": 0.6965317919075145, "acc_stderr": 0.024752411960917212, "acc_norm": 0.6965317919075145, "acc_norm_stderr": 0.024752411960917212 }, "harness|hendrycksTest-moral_scenarios|5": { "acc": 0.29608938547486036, "acc_stderr": 0.01526867731760228, "acc_norm": 0.29608938547486036, "acc_norm_stderr": 0.01526867731760228 }, "harness|hendrycksTest-nutrition|5": { "acc": 0.7549019607843137, "acc_stderr": 0.024630048979824775, "acc_norm": 0.7549019607843137, "acc_norm_stderr": 0.024630048979824775 }, "harness|hendrycksTest-philosophy|5": { "acc": 0.7266881028938906, "acc_stderr": 0.025311765975426122, "acc_norm": 0.7266881028938906, "acc_norm_stderr": 0.025311765975426122 }, "harness|hendrycksTest-prehistory|5": { "acc": 0.7098765432098766, "acc_stderr": 0.025251173936495036, "acc_norm": 0.7098765432098766, "acc_norm_stderr": 0.025251173936495036 }, "harness|hendrycksTest-professional_accounting|5": { "acc": 0.5, "acc_stderr": 0.029827499313594685, "acc_norm": 0.5, "acc_norm_stderr": 0.029827499313594685 }, "harness|hendrycksTest-professional_law|5": { "acc": 0.4491525423728814, "acc_stderr": 0.01270403051885149, "acc_norm": 0.4491525423728814, "acc_norm_stderr": 0.01270403051885149 }, "harness|hendrycksTest-professional_medicine|5": { "acc": 0.6654411764705882, "acc_stderr": 0.028661996202335303, "acc_norm": 0.6654411764705882, "acc_norm_stderr": 0.028661996202335303 }, "harness|hendrycksTest-professional_psychology|5": { "acc": 0.6552287581699346, "acc_stderr": 0.01922832201869664, "acc_norm": 0.6552287581699346, "acc_norm_stderr": 0.01922832201869664 }, "harness|hendrycksTest-public_relations|5": { "acc": 0.6454545454545455, "acc_stderr": 0.045820048415054174, "acc_norm": 0.6454545454545455, "acc_norm_stderr": 0.045820048415054174 }, "harness|hendrycksTest-security_studies|5": { "acc": 0.7346938775510204, "acc_stderr": 0.028263889943784603, "acc_norm": 0.7346938775510204, "acc_norm_stderr": 0.028263889943784603 }, "harness|hendrycksTest-sociology|5": { "acc": 0.8059701492537313, "acc_stderr": 0.027962677604768914, "acc_norm": 0.8059701492537313, "acc_norm_stderr": 0.027962677604768914 }, "harness|hendrycksTest-us_foreign_policy|5": { "acc": 0.85, "acc_stderr": 0.03588702812826371, "acc_norm": 0.85, "acc_norm_stderr": 0.03588702812826371 }, "harness|hendrycksTest-virology|5": { "acc": 0.5421686746987951, "acc_stderr": 0.0387862677100236, "acc_norm": 0.5421686746987951, "acc_norm_stderr": 0.0387862677100236 }, "harness|hendrycksTest-world_religions|5": { "acc": 0.8128654970760234, "acc_stderr": 0.029913127232368036, "acc_norm": 0.8128654970760234, "acc_norm_stderr": 0.029913127232368036 }, "harness|truthfulqa:mc|0": { "mc1": 0.3243574051407589, "mc1_stderr": 0.01638797677964794, "mc2": 0.4837489625680555, "mc2_stderr": 0.015088896132364547 }, "harness|winogrande|5": { "acc": 0.7790055248618785, "acc_stderr": 0.01166122363764341 }, "harness|gsm8k|5": { "acc": 0.36315390447308565, "acc_stderr": 0.013246614539839868 } } ``` ## Dataset Details ### Dataset Description  - **Curated by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] ### Dataset Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Dataset Structure  [More Information Needed] ## Dataset Creation ### Curation Rationale  [More Information Needed] ### Source Data  #### Data Collection and Processing  [More Information Needed] #### Who are the source data producers?  [More Information Needed] ### Annotations [optional]  #### Annotation process  [More Information Needed] #### Who are the annotators?  [More Information Needed] #### Personal and Sensitive Information  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations. ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Dataset Card Authors [optional] [More Information Needed] ## Dataset Card Contact [More Information Needed]

zolak/twitter_dataset_1713023754

--- dataset_info: features: - name: id dtype: string - name: tweet_content dtype: string - name: user_name dtype: string - name: user_id dtype: string - name: created_at dtype: string - name: url dtype: string - name: favourite_count dtype: float64 - name: scraped_at dtype: string - name: image_urls dtype: string splits: - name: train num_bytes: 58501863 num_examples: 150576 download_size: 29705449 dataset_size: 58501863 configs: - config_name: default data_files: - split: train path: data/train-* ---

cenkersisman/viki_soru_cevap

--- dataset_info: features: - name: answer dtype: string - name: question dtype: string - name: title dtype: string splits: - name: train num_bytes: 5319410 num_examples: 34983 download_size: 2529944 dataset_size: 5319410 --- # Dataset Card for "viki_soru_cevap" ## Hakkında Bu veri seti, Türkçe Vikipedi üzerindeki içeriklerden oluşturulan bir soru ve cevap veri setidir. Oluşturulan veri seti sentetik olarak üretilmiştir. Cevaplar, context metin üzerinden alınmış olsa da doğruluğu garanti edilmemektedir. Sorular da sentetik olarak üretilmiştir ## Başlıklara göre en fazla soru cevap içeren konular aşağıdadır: * Futbol rekabetleri listesi: 313 adet * Cengiz Han: 310 adet * Triple H: 196 adet * Lüleburgaz Muharebesi: 158 adet * Zümrüdüanka Yoldaşlığı: 155 adet * Shakespeare eserleri çevirileri listesi: 145 adet * Kırkpınar Yağlı Güreşleri: 142 adet * Sovyetler Birliği'nin askerî tarihi: 136 adet * I. Baybars: 135 adet * Dumbledore'un Ordusu: 126 adet * Nicolaus Copernicus: 119 adet * Ermenistan Sovyet Sosyalist Cumhuriyeti: 111 adet * Boshin Savaşı: 99 adet * Suvorov Harekâtı: 98 adet * Gökhan Türkmen: 96 adet * Wolfgang Amadeus Mozart: 95 adet * Joachim von Ribbentrop: 95 adet * Rumyantsev Harekâtı: 94 adet * Hermann Göring: 93 adet * Nâzım Hikmet: 90 adet * Said Nursî: 90 adet * Emîn: 88 adet * Antonio Gramsci: 87 adet * Gilles Deleuze: 86 adet * Madagaskar: 86 adet * Faşizm: 85 adet * Mac OS X Snow Leopard: 85 adet * Korsun-Şevçenkovski Taarruzu: 84 adet * Soğuk Savaş: 84 adet * Adolf Eichmann: 83 adet * Niccolò Paganini: 83 adet * II. Dünya Savaşı tankları: 81 adet * Pergamon: 81 adet * IV. Mihail: 80 adet * Bolşeviklere karşı sol ayaklanmalar: 77 adet * Osman Gazi: 77 adet * V. Leon: 76 adet * Ajda Pekkan: 75 adet * Mehdi Savaşı: 75 adet * Tsushima Muharebesi: 73 adet * Mehdî (Abbâsî halifesi): 72 adet * Franck Ribéry: 72 adet * I. Basileios: 69 adet * Antimon: 68 adet * Kolomb öncesi Amerika: 68 adet * Otto Skorzeny: 68 adet * Kâzım Koyuncu: 68 adet * İmamiye (Şiilik öğretisi): 66 adet * Oscar Niemeyer: 66 adet [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

open-llm-leaderboard/details_jeonsworld__CarbonVillain-en-10.7B-v1

--- pretty_name: Evaluation run of jeonsworld/CarbonVillain-en-10.7B-v1 dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [jeonsworld/CarbonVillain-en-10.7B-v1](https://huggingface.co/jeonsworld/CarbonVillain-en-10.7B-v1)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 63 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the aggregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_jeonsworld__CarbonVillain-en-10.7B-v1\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-12-29T20:15:36.884484](https://huggingface.co/datasets/open-llm-leaderboard/details_jeonsworld__CarbonVillain-en-10.7B-v1/blob/main/results_2023-12-29T20-15-36.884484.json)(note\ \ that their might be results for other tasks in the repos if successive evals didn't\ \ cover the same tasks. You find each in the results and the \"latest\" split for\ \ each eval):\n\n```python\n{\n \"all\": {\n \"acc\": 0.6677851094474622,\n\ \ \"acc_stderr\": 0.031647346301320364,\n \"acc_norm\": 0.6687652386109932,\n\ \ \"acc_norm_stderr\": 0.032290288467975714,\n \"mc1\": 0.572827417380661,\n\ \ \"mc1_stderr\": 0.017316834410963926,\n \"mc2\": 0.7197651592692368,\n\ \ \"mc2_stderr\": 0.014984462732010536\n },\n \"harness|arc:challenge|25\"\ : {\n \"acc\": 0.6843003412969283,\n \"acc_stderr\": 0.013582571095815291,\n\ \ \"acc_norm\": 0.712457337883959,\n \"acc_norm_stderr\": 0.013226719056266125\n\ \ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.7148974307906791,\n\ \ \"acc_stderr\": 0.00450540617660685,\n \"acc_norm\": 0.8845847440748855,\n\ \ \"acc_norm_stderr\": 0.0031886940284536315\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\ : {\n \"acc\": 0.42,\n \"acc_stderr\": 0.049604496374885836,\n \ \ \"acc_norm\": 0.42,\n \"acc_norm_stderr\": 0.049604496374885836\n \ \ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.6148148148148148,\n\ \ \"acc_stderr\": 0.04203921040156279,\n \"acc_norm\": 0.6148148148148148,\n\ \ \"acc_norm_stderr\": 0.04203921040156279\n },\n \"harness|hendrycksTest-astronomy|5\"\ : {\n \"acc\": 0.756578947368421,\n \"acc_stderr\": 0.034923496688842384,\n\ \ \"acc_norm\": 0.756578947368421,\n \"acc_norm_stderr\": 0.034923496688842384\n\ \ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.73,\n\ \ \"acc_stderr\": 0.04461960433384741,\n \"acc_norm\": 0.73,\n \ \ \"acc_norm_stderr\": 0.04461960433384741\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\ : {\n \"acc\": 0.6830188679245283,\n \"acc_stderr\": 0.02863723563980089,\n\ \ \"acc_norm\": 0.6830188679245283,\n \"acc_norm_stderr\": 0.02863723563980089\n\ \ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.7847222222222222,\n\ \ \"acc_stderr\": 0.03437079344106135,\n \"acc_norm\": 0.7847222222222222,\n\ \ \"acc_norm_stderr\": 0.03437079344106135\n },\n \"harness|hendrycksTest-college_chemistry|5\"\ : {\n \"acc\": 0.47,\n \"acc_stderr\": 0.050161355804659205,\n \ \ \"acc_norm\": 0.47,\n \"acc_norm_stderr\": 0.050161355804659205\n \ \ },\n \"harness|hendrycksTest-college_computer_science|5\": {\n \"\ acc\": 0.51,\n \"acc_stderr\": 0.05024183937956913,\n \"acc_norm\"\ : 0.51,\n \"acc_norm_stderr\": 0.05024183937956913\n },\n \"harness|hendrycksTest-college_mathematics|5\"\ : {\n \"acc\": 0.35,\n \"acc_stderr\": 0.0479372485441102,\n \ \ \"acc_norm\": 0.35,\n \"acc_norm_stderr\": 0.0479372485441102\n },\n\ \ \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.6705202312138728,\n\ \ \"acc_stderr\": 0.03583901754736412,\n \"acc_norm\": 0.6705202312138728,\n\ \ \"acc_norm_stderr\": 0.03583901754736412\n },\n \"harness|hendrycksTest-college_physics|5\"\ : {\n \"acc\": 0.39215686274509803,\n \"acc_stderr\": 0.04858083574266346,\n\ \ \"acc_norm\": 0.39215686274509803,\n \"acc_norm_stderr\": 0.04858083574266346\n\ \ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\ \ 0.75,\n \"acc_stderr\": 0.04351941398892446,\n \"acc_norm\": 0.75,\n\ \ \"acc_norm_stderr\": 0.04351941398892446\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\ : {\n \"acc\": 0.6212765957446809,\n \"acc_stderr\": 0.03170995606040655,\n\ \ \"acc_norm\": 0.6212765957446809,\n \"acc_norm_stderr\": 0.03170995606040655\n\ \ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.4824561403508772,\n\ \ \"acc_stderr\": 0.04700708033551038,\n \"acc_norm\": 0.4824561403508772,\n\ \ \"acc_norm_stderr\": 0.04700708033551038\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\ : {\n \"acc\": 0.6344827586206897,\n \"acc_stderr\": 0.040131241954243856,\n\ \ \"acc_norm\": 0.6344827586206897,\n \"acc_norm_stderr\": 0.040131241954243856\n\ \ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\ : 0.5026455026455027,\n \"acc_stderr\": 0.02575094967813038,\n \"\ acc_norm\": 0.5026455026455027,\n \"acc_norm_stderr\": 0.02575094967813038\n\ \ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.42857142857142855,\n\ \ \"acc_stderr\": 0.0442626668137991,\n \"acc_norm\": 0.42857142857142855,\n\ \ \"acc_norm_stderr\": 0.0442626668137991\n },\n \"harness|hendrycksTest-global_facts|5\"\ : {\n \"acc\": 0.36,\n \"acc_stderr\": 0.048241815132442176,\n \ \ \"acc_norm\": 0.36,\n \"acc_norm_stderr\": 0.048241815132442176\n \ \ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\"\ : 0.8258064516129032,\n \"acc_stderr\": 0.021576248184514587,\n \"\ acc_norm\": 0.8258064516129032,\n \"acc_norm_stderr\": 0.021576248184514587\n\ \ },\n \"harness|hendrycksTest-high_school_chemistry|5\": {\n \"acc\"\ : 0.5073891625615764,\n \"acc_stderr\": 0.035176035403610105,\n \"\ acc_norm\": 0.5073891625615764,\n \"acc_norm_stderr\": 0.035176035403610105\n\ \ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \ \ \"acc\": 0.72,\n \"acc_stderr\": 0.04512608598542128,\n \"acc_norm\"\ : 0.72,\n \"acc_norm_stderr\": 0.04512608598542128\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\ : {\n \"acc\": 0.8181818181818182,\n \"acc_stderr\": 0.03011768892950357,\n\ \ \"acc_norm\": 0.8181818181818182,\n \"acc_norm_stderr\": 0.03011768892950357\n\ \ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\ : 0.8636363636363636,\n \"acc_stderr\": 0.024450155973189835,\n \"\ acc_norm\": 0.8636363636363636,\n \"acc_norm_stderr\": 0.024450155973189835\n\ \ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\ \ \"acc\": 0.8963730569948186,\n \"acc_stderr\": 0.021995311963644244,\n\ \ \"acc_norm\": 0.8963730569948186,\n \"acc_norm_stderr\": 0.021995311963644244\n\ \ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \ \ \"acc\": 0.6666666666666666,\n \"acc_stderr\": 0.023901157979402534,\n\ \ \"acc_norm\": 0.6666666666666666,\n \"acc_norm_stderr\": 0.023901157979402534\n\ \ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\ acc\": 0.36666666666666664,\n \"acc_stderr\": 0.029381620726465073,\n \ \ \"acc_norm\": 0.36666666666666664,\n \"acc_norm_stderr\": 0.029381620726465073\n\ \ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \ \ \"acc\": 0.7142857142857143,\n \"acc_stderr\": 0.029344572500634332,\n\ \ \"acc_norm\": 0.7142857142857143,\n \"acc_norm_stderr\": 0.029344572500634332\n\ \ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\ : 0.37748344370860926,\n \"acc_stderr\": 0.03958027231121569,\n \"\ acc_norm\": 0.37748344370860926,\n \"acc_norm_stderr\": 0.03958027231121569\n\ \ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\ : 0.8458715596330275,\n \"acc_stderr\": 0.015480826865374308,\n \"\ acc_norm\": 0.8458715596330275,\n \"acc_norm_stderr\": 0.015480826865374308\n\ \ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\ : 0.5740740740740741,\n \"acc_stderr\": 0.03372343271653062,\n \"\ acc_norm\": 0.5740740740740741,\n \"acc_norm_stderr\": 0.03372343271653062\n\ \ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\ : 0.8578431372549019,\n \"acc_stderr\": 0.02450980392156862,\n \"\ acc_norm\": 0.8578431372549019,\n \"acc_norm_stderr\": 0.02450980392156862\n\ \ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\ acc\": 0.8481012658227848,\n \"acc_stderr\": 0.023363878096632446,\n \ \ \"acc_norm\": 0.8481012658227848,\n \"acc_norm_stderr\": 0.023363878096632446\n\ \ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.672645739910314,\n\ \ \"acc_stderr\": 0.03149384670994131,\n \"acc_norm\": 0.672645739910314,\n\ \ \"acc_norm_stderr\": 0.03149384670994131\n },\n \"harness|hendrycksTest-human_sexuality|5\"\ : {\n \"acc\": 0.7557251908396947,\n \"acc_stderr\": 0.03768335959728743,\n\ \ \"acc_norm\": 0.7557251908396947,\n \"acc_norm_stderr\": 0.03768335959728743\n\ \ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\ \ 0.7768595041322314,\n \"acc_stderr\": 0.03800754475228733,\n \"\ acc_norm\": 0.7768595041322314,\n \"acc_norm_stderr\": 0.03800754475228733\n\ \ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.8055555555555556,\n\ \ \"acc_stderr\": 0.038260763248848646,\n \"acc_norm\": 0.8055555555555556,\n\ \ \"acc_norm_stderr\": 0.038260763248848646\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\ : {\n \"acc\": 0.7607361963190185,\n \"acc_stderr\": 0.033519538795212696,\n\ \ \"acc_norm\": 0.7607361963190185,\n \"acc_norm_stderr\": 0.033519538795212696\n\ \ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.4642857142857143,\n\ \ \"acc_stderr\": 0.04733667890053756,\n \"acc_norm\": 0.4642857142857143,\n\ \ \"acc_norm_stderr\": 0.04733667890053756\n },\n \"harness|hendrycksTest-management|5\"\ : {\n \"acc\": 0.8543689320388349,\n \"acc_stderr\": 0.03492606476623791,\n\ \ \"acc_norm\": 0.8543689320388349,\n \"acc_norm_stderr\": 0.03492606476623791\n\ \ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.8589743589743589,\n\ \ \"acc_stderr\": 0.02280138253459753,\n \"acc_norm\": 0.8589743589743589,\n\ \ \"acc_norm_stderr\": 0.02280138253459753\n },\n \"harness|hendrycksTest-medical_genetics|5\"\ : {\n \"acc\": 0.7,\n \"acc_stderr\": 0.046056618647183814,\n \ \ \"acc_norm\": 0.7,\n \"acc_norm_stderr\": 0.046056618647183814\n \ \ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.8071519795657727,\n\ \ \"acc_stderr\": 0.014108533515757431,\n \"acc_norm\": 0.8071519795657727,\n\ \ \"acc_norm_stderr\": 0.014108533515757431\n },\n \"harness|hendrycksTest-moral_disputes|5\"\ : {\n \"acc\": 0.7543352601156069,\n \"acc_stderr\": 0.023176298203992005,\n\ \ \"acc_norm\": 0.7543352601156069,\n \"acc_norm_stderr\": 0.023176298203992005\n\ \ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.39888268156424583,\n\ \ \"acc_stderr\": 0.016376966142610073,\n \"acc_norm\": 0.39888268156424583,\n\ \ \"acc_norm_stderr\": 0.016376966142610073\n },\n \"harness|hendrycksTest-nutrition|5\"\ : {\n \"acc\": 0.7581699346405228,\n \"acc_stderr\": 0.024518195641879334,\n\ \ \"acc_norm\": 0.7581699346405228,\n \"acc_norm_stderr\": 0.024518195641879334\n\ \ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.7266881028938906,\n\ \ \"acc_stderr\": 0.025311765975426122,\n \"acc_norm\": 0.7266881028938906,\n\ \ \"acc_norm_stderr\": 0.025311765975426122\n },\n \"harness|hendrycksTest-prehistory|5\"\ : {\n \"acc\": 0.7808641975308642,\n \"acc_stderr\": 0.02301670564026219,\n\ \ \"acc_norm\": 0.7808641975308642,\n \"acc_norm_stderr\": 0.02301670564026219\n\ \ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\ acc\": 0.49645390070921985,\n \"acc_stderr\": 0.02982674915328092,\n \ \ \"acc_norm\": 0.49645390070921985,\n \"acc_norm_stderr\": 0.02982674915328092\n\ \ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.4934810951760104,\n\ \ \"acc_stderr\": 0.012769150688867503,\n \"acc_norm\": 0.4934810951760104,\n\ \ \"acc_norm_stderr\": 0.012769150688867503\n },\n \"harness|hendrycksTest-professional_medicine|5\"\ : {\n \"acc\": 0.7389705882352942,\n \"acc_stderr\": 0.026679252270103128,\n\ \ \"acc_norm\": 0.7389705882352942,\n \"acc_norm_stderr\": 0.026679252270103128\n\ \ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\ acc\": 0.6797385620915033,\n \"acc_stderr\": 0.018875682938069446,\n \ \ \"acc_norm\": 0.6797385620915033,\n \"acc_norm_stderr\": 0.018875682938069446\n\ \ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.6909090909090909,\n\ \ \"acc_stderr\": 0.044262946482000985,\n \"acc_norm\": 0.6909090909090909,\n\ \ \"acc_norm_stderr\": 0.044262946482000985\n },\n \"harness|hendrycksTest-security_studies|5\"\ : {\n \"acc\": 0.7387755102040816,\n \"acc_stderr\": 0.02812342933514278,\n\ \ \"acc_norm\": 0.7387755102040816,\n \"acc_norm_stderr\": 0.02812342933514278\n\ \ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.8407960199004975,\n\ \ \"acc_stderr\": 0.02587064676616913,\n \"acc_norm\": 0.8407960199004975,\n\ \ \"acc_norm_stderr\": 0.02587064676616913\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\ : {\n \"acc\": 0.9,\n \"acc_stderr\": 0.030151134457776334,\n \ \ \"acc_norm\": 0.9,\n \"acc_norm_stderr\": 0.030151134457776334\n \ \ },\n \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.5843373493975904,\n\ \ \"acc_stderr\": 0.03836722176598053,\n \"acc_norm\": 0.5843373493975904,\n\ \ \"acc_norm_stderr\": 0.03836722176598053\n },\n \"harness|hendrycksTest-world_religions|5\"\ : {\n \"acc\": 0.7777777777777778,\n \"acc_stderr\": 0.03188578017686398,\n\ \ \"acc_norm\": 0.7777777777777778,\n \"acc_norm_stderr\": 0.03188578017686398\n\ \ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.572827417380661,\n\ \ \"mc1_stderr\": 0.017316834410963926,\n \"mc2\": 0.7197651592692368,\n\ \ \"mc2_stderr\": 0.014984462732010536\n },\n \"harness|winogrande|5\"\ : {\n \"acc\": 0.8326756116811366,\n \"acc_stderr\": 0.010490608806828075\n\ \ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.6429112964366944,\n \ \ \"acc_stderr\": 0.013197931775445206\n }\n}\n```" repo_url: https://huggingface.co/jeonsworld/CarbonVillain-en-10.7B-v1 leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2023_12_29T20_15_36.884484 path: - '**/details_harness|arc:challenge|25_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2023-12-29T20-15-36.884484.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '**/details_harness|gsm8k|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_12_29T20_15_36.884484 path: - '**/details_harness|hellaswag|10_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-management|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-management|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-12-29T20-15-36.884484.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '**/details_harness|hendrycksTest-anatomy|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '**/details_harness|hendrycksTest-astronomy|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '**/details_harness|hendrycksTest-college_biology|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '**/details_harness|hendrycksTest-college_physics|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '**/details_harness|hendrycksTest-computer_security|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '**/details_harness|hendrycksTest-econometrics|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '**/details_harness|hendrycksTest-global_facts|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '**/details_harness|hendrycksTest-human_aging|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '**/details_harness|hendrycksTest-international_law|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '**/details_harness|hendrycksTest-management|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '**/details_harness|hendrycksTest-marketing|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '**/details_harness|hendrycksTest-nutrition|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '**/details_harness|hendrycksTest-philosophy|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '**/details_harness|hendrycksTest-prehistory|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '**/details_harness|hendrycksTest-professional_law|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '**/details_harness|hendrycksTest-public_relations|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '**/details_harness|hendrycksTest-security_studies|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '**/details_harness|hendrycksTest-sociology|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '**/details_harness|hendrycksTest-virology|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '**/details_harness|hendrycksTest-world_religions|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2023-12-29T20-15-36.884484.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_12_29T20_15_36.884484 path: - '**/details_harness|truthfulqa:mc|0_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2023-12-29T20-15-36.884484.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_12_29T20_15_36.884484 path: - '**/details_harness|winogrande|5_2023-12-29T20-15-36.884484.parquet' - split: latest path: - '**/details_harness|winogrande|5_2023-12-29T20-15-36.884484.parquet' - config_name: results data_files: - split: 2023_12_29T20_15_36.884484 path: - results_2023-12-29T20-15-36.884484.parquet - split: latest path: - results_2023-12-29T20-15-36.884484.parquet --- # Dataset Card for Evaluation run of jeonsworld/CarbonVillain-en-10.7B-v1  Dataset automatically created during the evaluation run of model [jeonsworld/CarbonVillain-en-10.7B-v1](https://huggingface.co/jeonsworld/CarbonVillain-en-10.7B-v1) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_jeonsworld__CarbonVillain-en-10.7B-v1", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-12-29T20:15:36.884484](https://huggingface.co/datasets/open-llm-leaderboard/details_jeonsworld__CarbonVillain-en-10.7B-v1/blob/main/results_2023-12-29T20-15-36.884484.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval): ```python { "all": { "acc": 0.6677851094474622, "acc_stderr": 0.031647346301320364, "acc_norm": 0.6687652386109932, "acc_norm_stderr": 0.032290288467975714, "mc1": 0.572827417380661, "mc1_stderr": 0.017316834410963926, "mc2": 0.7197651592692368, "mc2_stderr": 0.014984462732010536 }, "harness|arc:challenge|25": { "acc": 0.6843003412969283, "acc_stderr": 0.013582571095815291, "acc_norm": 0.712457337883959, "acc_norm_stderr": 0.013226719056266125 }, "harness|hellaswag|10": { "acc": 0.7148974307906791, "acc_stderr": 0.00450540617660685, "acc_norm": 0.8845847440748855, "acc_norm_stderr": 0.0031886940284536315 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.42, "acc_stderr": 0.049604496374885836, "acc_norm": 0.42, "acc_norm_stderr": 0.049604496374885836 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.6148148148148148, "acc_stderr": 0.04203921040156279, "acc_norm": 0.6148148148148148, "acc_norm_stderr": 0.04203921040156279 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.756578947368421, "acc_stderr": 0.034923496688842384, "acc_norm": 0.756578947368421, "acc_norm_stderr": 0.034923496688842384 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.73, "acc_stderr": 0.04461960433384741, "acc_norm": 0.73, "acc_norm_stderr": 0.04461960433384741 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.6830188679245283, "acc_stderr": 0.02863723563980089, "acc_norm": 0.6830188679245283, "acc_norm_stderr": 0.02863723563980089 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.7847222222222222, "acc_stderr": 0.03437079344106135, "acc_norm": 0.7847222222222222, "acc_norm_stderr": 0.03437079344106135 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.47, "acc_stderr": 0.050161355804659205, "acc_norm": 0.47, "acc_norm_stderr": 0.050161355804659205 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.51, "acc_stderr": 0.05024183937956913, "acc_norm": 0.51, "acc_norm_stderr": 0.05024183937956913 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.35, "acc_stderr": 0.0479372485441102, "acc_norm": 0.35, "acc_norm_stderr": 0.0479372485441102 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.6705202312138728, "acc_stderr": 0.03583901754736412, "acc_norm": 0.6705202312138728, "acc_norm_stderr": 0.03583901754736412 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.39215686274509803, "acc_stderr": 0.04858083574266346, "acc_norm": 0.39215686274509803, "acc_norm_stderr": 0.04858083574266346 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.75, "acc_stderr": 0.04351941398892446, "acc_norm": 0.75, "acc_norm_stderr": 0.04351941398892446 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.6212765957446809, "acc_stderr": 0.03170995606040655, "acc_norm": 0.6212765957446809, "acc_norm_stderr": 0.03170995606040655 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.4824561403508772, "acc_stderr": 0.04700708033551038, "acc_norm": 0.4824561403508772, "acc_norm_stderr": 0.04700708033551038 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.6344827586206897, "acc_stderr": 0.040131241954243856, "acc_norm": 0.6344827586206897, "acc_norm_stderr": 0.040131241954243856 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.5026455026455027, "acc_stderr": 0.02575094967813038, "acc_norm": 0.5026455026455027, "acc_norm_stderr": 0.02575094967813038 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.42857142857142855, "acc_stderr": 0.0442626668137991, "acc_norm": 0.42857142857142855, "acc_norm_stderr": 0.0442626668137991 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.36, "acc_stderr": 0.048241815132442176, "acc_norm": 0.36, "acc_norm_stderr": 0.048241815132442176 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.8258064516129032, "acc_stderr": 0.021576248184514587, "acc_norm": 0.8258064516129032, "acc_norm_stderr": 0.021576248184514587 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.5073891625615764, "acc_stderr": 0.035176035403610105, "acc_norm": 0.5073891625615764, "acc_norm_stderr": 0.035176035403610105 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.72, "acc_stderr": 0.04512608598542128, "acc_norm": 0.72, "acc_norm_stderr": 0.04512608598542128 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.8181818181818182, "acc_stderr": 0.03011768892950357, "acc_norm": 0.8181818181818182, "acc_norm_stderr": 0.03011768892950357 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.8636363636363636, "acc_stderr": 0.024450155973189835, "acc_norm": 0.8636363636363636, "acc_norm_stderr": 0.024450155973189835 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.8963730569948186, "acc_stderr": 0.021995311963644244, "acc_norm": 0.8963730569948186, "acc_norm_stderr": 0.021995311963644244 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.6666666666666666, "acc_stderr": 0.023901157979402534, "acc_norm": 0.6666666666666666, "acc_norm_stderr": 0.023901157979402534 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.36666666666666664, "acc_stderr": 0.029381620726465073, "acc_norm": 0.36666666666666664, "acc_norm_stderr": 0.029381620726465073 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.7142857142857143, "acc_stderr": 0.029344572500634332, "acc_norm": 0.7142857142857143, "acc_norm_stderr": 0.029344572500634332 }, "harness|hendrycksTest-high_school_physics|5": { "acc": 0.37748344370860926, "acc_stderr": 0.03958027231121569, "acc_norm": 0.37748344370860926, "acc_norm_stderr": 0.03958027231121569 }, "harness|hendrycksTest-high_school_psychology|5": { "acc": 0.8458715596330275, "acc_stderr": 0.015480826865374308, "acc_norm": 0.8458715596330275, "acc_norm_stderr": 0.015480826865374308 }, "harness|hendrycksTest-high_school_statistics|5": { "acc": 0.5740740740740741, "acc_stderr": 0.03372343271653062, "acc_norm": 0.5740740740740741, "acc_norm_stderr": 0.03372343271653062 }, "harness|hendrycksTest-high_school_us_history|5": { "acc": 0.8578431372549019, "acc_stderr": 0.02450980392156862, "acc_norm": 0.8578431372549019, "acc_norm_stderr": 0.02450980392156862 }, "harness|hendrycksTest-high_school_world_history|5": { "acc": 0.8481012658227848, "acc_stderr": 0.023363878096632446, "acc_norm": 0.8481012658227848, "acc_norm_stderr": 0.023363878096632446 }, "harness|hendrycksTest-human_aging|5": { "acc": 0.672645739910314, "acc_stderr": 0.03149384670994131, "acc_norm": 0.672645739910314, "acc_norm_stderr": 0.03149384670994131 }, "harness|hendrycksTest-human_sexuality|5": { "acc": 0.7557251908396947, "acc_stderr": 0.03768335959728743, "acc_norm": 0.7557251908396947, "acc_norm_stderr": 0.03768335959728743 }, "harness|hendrycksTest-international_law|5": { "acc": 0.7768595041322314, "acc_stderr": 0.03800754475228733, "acc_norm": 0.7768595041322314, "acc_norm_stderr": 0.03800754475228733 }, "harness|hendrycksTest-jurisprudence|5": { "acc": 0.8055555555555556, "acc_stderr": 0.038260763248848646, "acc_norm": 0.8055555555555556, "acc_norm_stderr": 0.038260763248848646 }, "harness|hendrycksTest-logical_fallacies|5": { "acc": 0.7607361963190185, "acc_stderr": 0.033519538795212696, "acc_norm": 0.7607361963190185, "acc_norm_stderr": 0.033519538795212696 }, "harness|hendrycksTest-machine_learning|5": { "acc": 0.4642857142857143, "acc_stderr": 0.04733667890053756, "acc_norm": 0.4642857142857143, "acc_norm_stderr": 0.04733667890053756 }, "harness|hendrycksTest-management|5": { "acc": 0.8543689320388349, "acc_stderr": 0.03492606476623791, "acc_norm": 0.8543689320388349, "acc_norm_stderr": 0.03492606476623791 }, "harness|hendrycksTest-marketing|5": { "acc": 0.8589743589743589, "acc_stderr": 0.02280138253459753, "acc_norm": 0.8589743589743589, "acc_norm_stderr": 0.02280138253459753 }, "harness|hendrycksTest-medical_genetics|5": { "acc": 0.7, "acc_stderr": 0.046056618647183814, "acc_norm": 0.7, "acc_norm_stderr": 0.046056618647183814 }, "harness|hendrycksTest-miscellaneous|5": { "acc": 0.8071519795657727, "acc_stderr": 0.014108533515757431, "acc_norm": 0.8071519795657727, "acc_norm_stderr": 0.014108533515757431 }, "harness|hendrycksTest-moral_disputes|5": { "acc": 0.7543352601156069, "acc_stderr": 0.023176298203992005, "acc_norm": 0.7543352601156069, "acc_norm_stderr": 0.023176298203992005 }, "harness|hendrycksTest-moral_scenarios|5": { "acc": 0.39888268156424583, "acc_stderr": 0.016376966142610073, "acc_norm": 0.39888268156424583, "acc_norm_stderr": 0.016376966142610073 }, "harness|hendrycksTest-nutrition|5": { "acc": 0.7581699346405228, "acc_stderr": 0.024518195641879334, "acc_norm": 0.7581699346405228, "acc_norm_stderr": 0.024518195641879334 }, "harness|hendrycksTest-philosophy|5": { "acc": 0.7266881028938906, "acc_stderr": 0.025311765975426122, "acc_norm": 0.7266881028938906, "acc_norm_stderr": 0.025311765975426122 }, "harness|hendrycksTest-prehistory|5": { "acc": 0.7808641975308642, "acc_stderr": 0.02301670564026219, "acc_norm": 0.7808641975308642, "acc_norm_stderr": 0.02301670564026219 }, "harness|hendrycksTest-professional_accounting|5": { "acc": 0.49645390070921985, "acc_stderr": 0.02982674915328092, "acc_norm": 0.49645390070921985, "acc_norm_stderr": 0.02982674915328092 }, "harness|hendrycksTest-professional_law|5": { "acc": 0.4934810951760104, "acc_stderr": 0.012769150688867503, "acc_norm": 0.4934810951760104, "acc_norm_stderr": 0.012769150688867503 }, "harness|hendrycksTest-professional_medicine|5": { "acc": 0.7389705882352942, "acc_stderr": 0.026679252270103128, "acc_norm": 0.7389705882352942, "acc_norm_stderr": 0.026679252270103128 }, "harness|hendrycksTest-professional_psychology|5": { "acc": 0.6797385620915033, "acc_stderr": 0.018875682938069446, "acc_norm": 0.6797385620915033, "acc_norm_stderr": 0.018875682938069446 }, "harness|hendrycksTest-public_relations|5": { "acc": 0.6909090909090909, "acc_stderr": 0.044262946482000985, "acc_norm": 0.6909090909090909, "acc_norm_stderr": 0.044262946482000985 }, "harness|hendrycksTest-security_studies|5": { "acc": 0.7387755102040816, "acc_stderr": 0.02812342933514278, "acc_norm": 0.7387755102040816, "acc_norm_stderr": 0.02812342933514278 }, "harness|hendrycksTest-sociology|5": { "acc": 0.8407960199004975, "acc_stderr": 0.02587064676616913, "acc_norm": 0.8407960199004975, "acc_norm_stderr": 0.02587064676616913 }, "harness|hendrycksTest-us_foreign_policy|5": { "acc": 0.9, "acc_stderr": 0.030151134457776334, "acc_norm": 0.9, "acc_norm_stderr": 0.030151134457776334 }, "harness|hendrycksTest-virology|5": { "acc": 0.5843373493975904, "acc_stderr": 0.03836722176598053, "acc_norm": 0.5843373493975904, "acc_norm_stderr": 0.03836722176598053 }, "harness|hendrycksTest-world_religions|5": { "acc": 0.7777777777777778, "acc_stderr": 0.03188578017686398, "acc_norm": 0.7777777777777778, "acc_norm_stderr": 0.03188578017686398 }, "harness|truthfulqa:mc|0": { "mc1": 0.572827417380661, "mc1_stderr": 0.017316834410963926, "mc2": 0.7197651592692368, "mc2_stderr": 0.014984462732010536 }, "harness|winogrande|5": { "acc": 0.8326756116811366, "acc_stderr": 0.010490608806828075 }, "harness|gsm8k|5": { "acc": 0.6429112964366944, "acc_stderr": 0.013197931775445206 } } ``` ## Dataset Details ### Dataset Description  - **Curated by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] ### Dataset Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Dataset Structure  [More Information Needed] ## Dataset Creation ### Curation Rationale  [More Information Needed] ### Source Data  #### Data Collection and Processing  [More Information Needed] #### Who are the source data producers?  [More Information Needed] ### Annotations [optional]  #### Annotation process  [More Information Needed] #### Who are the annotators?  [More Information Needed] #### Personal and Sensitive Information  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations. ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Dataset Card Authors [optional] [More Information Needed] ## Dataset Card Contact [More Information Needed]

karawalla/aqcommands

--- license: bigcode-openrail-m ---

autoevaluate/autoeval-eval-lener_br-lener_br-b36dee-1776161641

--- type: predictions tags: - autotrain - evaluation datasets: - lener_br eval_info: task: entity_extraction model: Luciano/bertimbau-large-lener_br metrics: [] dataset_name: lener_br dataset_config: lener_br dataset_split: validation col_mapping: tokens: tokens tags: ner_tags --- # Dataset Card for AutoTrain Evaluator This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset: * Task: Token Classification * Model: Luciano/bertimbau-large-lener_br * Dataset: lener_br * Config: lener_br * Split: validation To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator). ## Contributions Thanks to [@Luciano](https://huggingface.co/Luciano) for evaluating this model.

CyberHarem/python_girlsfrontline

--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of python/パイソン/蟒蛇 (Girls' Frontline) This is the dataset of python/パイソン/蟒蛇 (Girls' Frontline), containing 43 images and their tags. The core tags of this character are `black_hair, breasts, green_eyes, long_hair, mole, mole_under_eye, earrings, large_breasts, multicolored_hair`, which are pruned in this dataset. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). ## List of Packages | Name | Images | Size | Download | Type | Description | |:-----------------|---------:|:----------|:-----------------------------------------------------------------------------------------------------------------------|:-----------|:---------------------------------------------------------------------| | raw | 43 | 54.58 MiB | [Download](https://huggingface.co/datasets/CyberHarem/python_girlsfrontline/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). | | 800 | 43 | 31.16 MiB | [Download](https://huggingface.co/datasets/CyberHarem/python_girlsfrontline/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. | | stage3-p480-800 | 115 | 66.92 MiB | [Download](https://huggingface.co/datasets/CyberHarem/python_girlsfrontline/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. | | 1200 | 43 | 48.14 MiB | [Download](https://huggingface.co/datasets/CyberHarem/python_girlsfrontline/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. | | stage3-p480-1200 | 115 | 94.53 MiB | [Download](https://huggingface.co/datasets/CyberHarem/python_girlsfrontline/resolve/main/dataset-stage3-p480-1200.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. | ### Load Raw Dataset with Waifuc We provide raw dataset (including tagged images) for [waifuc](https://deepghs.github.io/waifuc/main/tutorials/installation/index.html) loading. If you need this, just run the following code ```python import os import zipfile from huggingface_hub import hf_hub_download from waifuc.source import LocalSource # download raw archive file zip_file = hf_hub_download( repo_id='CyberHarem/python_girlsfrontline', repo_type='dataset', filename='dataset-raw.zip', ) # extract files to your directory dataset_dir = 'dataset_dir' os.makedirs(dataset_dir, exist_ok=True) with zipfile.ZipFile(zip_file, 'r') as zf: zf.extractall(dataset_dir) # load the dataset with waifuc source = LocalSource(dataset_dir) for item in source: print(item.image, item.meta['filename'], item.meta['tags']) ``` ## List of Clusters List of tag clustering result, maybe some outfits can be mined here. ### Raw Text Version | # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | Tags | |----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| | 0 | 31 | ![](samples/0/clu0-sample0.png) | ![](samples/0/clu0-sample1.png) | ![](samples/0/clu0-sample2.png) | ![](samples/0/clu0-sample3.png) | ![](samples/0/clu0-sample4.png) | 1girl, looking_at_viewer, smile, solo, jewelry, navel, black_gloves, simple_background, white_background, jacket, makeup, black_shirt, handgun, blush, holding_weapon, revolver, thighhighs, white_necktie | ### Table Version | # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | looking_at_viewer | smile | solo | jewelry | navel | black_gloves | simple_background | white_background | jacket | makeup | black_shirt | handgun | blush | holding_weapon | revolver | thighhighs | white_necktie | |----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------|:--------------------|:--------|:-------|:----------|:--------|:---------------|:--------------------|:-------------------|:---------|:---------|:--------------|:----------|:--------|:-----------------|:-----------|:-------------|:----------------| | 0 | 31 | ![](samples/0/clu0-sample0.png) | ![](samples/0/clu0-sample1.png) | ![](samples/0/clu0-sample2.png) | ![](samples/0/clu0-sample3.png) | ![](samples/0/clu0-sample4.png) | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X |

Torsaan/NTNU_RED

--- license: mit --- Some data collected on NTNU Campus Gjøvik with a Leica p40 then prossesed (normals, downsampled etc) and augmented Phillip Nerdum - Tor Henrik Øverby Olsen (2024) Some data collected from http://redwood-data.org/3dscan/ then prossesed (normals, downsampled etc) and augmented. @article{Choi2016, author = {Sungjoon Choi and Qian-Yi Zhou and Stephen Miller and Vladlen Koltun}, title = {A Large Dataset of Object Scans}, journal = {arXiv:1602.02481}, year = {2016}, } Contains filelist , shapelist , and test , train val split. Used for fine tuning a model trained on the modelnet40 dataset. Any part of the dataset can be used for any purpose with proper attribution. If you use any of the data, please cite - Phillip Nerdrum - Tor Henrik Øverby Olsen NTNU 2024 - Bachelor thesis: TBD @article{Choi2016, author = {Sungjoon Choi and Qian-Yi Zhou and Stephen Miller and Vladlen Koltun}, title = {A Large Dataset of Object Scans}, journal = {arXiv:1602.02481}, year = {2016}, }

CyberHarem/senzaki_ema_idolmastercinderellagirls

--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of senzaki_ema/仙崎恵磨 (THE iDOLM@STER: Cinderella Girls) This is the dataset of senzaki_ema/仙崎恵磨 (THE iDOLM@STER: Cinderella Girls), containing 59 images and their tags. The core tags of this character are `short_hair, blonde_hair, earrings, very_short_hair, red_eyes, breasts, ear_piercing`, which are pruned in this dataset. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). ## List of Packages | Name | Images | Size | Download | Type | Description | |:-----------------|---------:|:----------|:---------------------------------------------------------------------------------------------------------------------------------------|:-----------|:---------------------------------------------------------------------| | raw | 59 | 54.11 MiB | [Download](https://huggingface.co/datasets/CyberHarem/senzaki_ema_idolmastercinderellagirls/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). | | 800 | 59 | 37.69 MiB | [Download](https://huggingface.co/datasets/CyberHarem/senzaki_ema_idolmastercinderellagirls/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. | | stage3-p480-800 | 127 | 71.11 MiB | [Download](https://huggingface.co/datasets/CyberHarem/senzaki_ema_idolmastercinderellagirls/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. | | 1200 | 59 | 49.23 MiB | [Download](https://huggingface.co/datasets/CyberHarem/senzaki_ema_idolmastercinderellagirls/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. | | stage3-p480-1200 | 127 | 89.15 MiB | [Download](https://huggingface.co/datasets/CyberHarem/senzaki_ema_idolmastercinderellagirls/resolve/main/dataset-stage3-p480-1200.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. | ### Load Raw Dataset with Waifuc We provide raw dataset (including tagged images) for [waifuc](https://deepghs.github.io/waifuc/main/tutorials/installation/index.html) loading. If you need this, just run the following code ```python import os import zipfile from huggingface_hub import hf_hub_download from waifuc.source import LocalSource # download raw archive file zip_file = hf_hub_download( repo_id='CyberHarem/senzaki_ema_idolmastercinderellagirls', repo_type='dataset', filename='dataset-raw.zip', ) # extract files to your directory dataset_dir = 'dataset_dir' os.makedirs(dataset_dir, exist_ok=True) with zipfile.ZipFile(zip_file, 'r') as zf: zf.extractall(dataset_dir) # load the dataset with waifuc source = LocalSource(dataset_dir) for item in source: print(item.image, item.meta['filename'], item.meta['tags']) ``` ## List of Clusters List of tag clustering result, maybe some outfits can be mined here. ### Raw Text Version | # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | Tags | |----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:-----------------------------------------------------------------------------------------------------| | 0 | 14 | ![](samples/0/clu0-sample0.png) | ![](samples/0/clu0-sample1.png) | ![](samples/0/clu0-sample2.png) | ![](samples/0/clu0-sample3.png) | ![](samples/0/clu0-sample4.png) | 1girl, jewelry, solo, card_(medium), character_name, sun_symbol, looking_at_viewer, open_mouth, grin | ### Table Version | # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | jewelry | solo | card_(medium) | character_name | sun_symbol | looking_at_viewer | open_mouth | grin | |----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------|:----------|:-------|:----------------|:-----------------|:-------------|:--------------------|:-------------|:-------| | 0 | 14 | ![](samples/0/clu0-sample0.png) | ![](samples/0/clu0-sample1.png) | ![](samples/0/clu0-sample2.png) | ![](samples/0/clu0-sample3.png) | ![](samples/0/clu0-sample4.png) | X | X | X | X | X | X | X | X | X |

Admin0805/Mytokens

--- license: other license_name: citibankdemobusiness license_link: https://citibankdemobusiness.dev ---

skrishna/SeqSense_gen_8

--- dataset_info: features: - name: input dtype: string - name: answer dtype: int64 splits: - name: train num_bytes: 25416 num_examples: 300 download_size: 8511 dataset_size: 25416 --- # Dataset Card for "SeqSense_gen_8" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

Nexdata/Cantonese_Dialect_Speech_Data_by_Mobile_Phone

--- YAML tags: - copy-paste the tags obtained with the tagging app: https://github.com/huggingface/datasets-tagging --- # Dataset Card for Nexdata/Cantonese_Dialect_Speech_Data_by_Mobile_Phone ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - **Homepage:** https://www.nexdata.ai/datasets/54?source=Huggingface - **Repository:** - **Paper:** - **Leaderboard:** - **Point of Contact:** ### Dataset Summary It collects 4,888 speakers from Guangdong Province and is recorded in quiet indoor environment. The recorded content covers 500,000 commonly used spoken sentences, including high-frequency words in weico and daily used expressions. The average number of repetitions is 1.5 and the average sentence length is 12.5 words. Recording devices are mainstream Android phones and iPhones. For more details, please refer to the link: https://www.nexdata.ai/datasets/54?source=Huggingface ### Supported Tasks and Leaderboards automatic-speech-recognition, audio-speaker-identification: The dataset can be used to train a model for Automatic Speech Recognition (ASR). ### Languages Cantonese ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions

salma-remyx/ffmperative_refined_5.5k

--- dataset_info: features: - name: prompt dtype: string - name: response dtype: string splits: - name: train num_bytes: 3277970 num_examples: 5565 download_size: 1001170 dataset_size: 3277970 --- # Dataset Card for "ffmperative_refined_5.5k" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

codys12/PRM800K

--- license: mit ---

elvincth/durecdial-knowledge

--- license: mit ---

open-llm-leaderboard/details_Isotonic__Hermes-2-Pro-Mixtral-4x7B

--- pretty_name: Evaluation run of Isotonic/Hermes-2-Pro-Mixtral-4x7B dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [Isotonic/Hermes-2-Pro-Mixtral-4x7B](https://huggingface.co/Isotonic/Hermes-2-Pro-Mixtral-4x7B)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 63 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the aggregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_Isotonic__Hermes-2-Pro-Mixtral-4x7B\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-03-22T02:39:47.890512](https://huggingface.co/datasets/open-llm-leaderboard/details_Isotonic__Hermes-2-Pro-Mixtral-4x7B/blob/main/results_2024-03-22T02-39-47.890512.json)(note\ \ that their might be results for other tasks in the repos if successive evals didn't\ \ cover the same tasks. You find each in the results and the \"latest\" split for\ \ each eval):\n\n```python\n{\n \"all\": {\n \"acc\": 0.6247175996493741,\n\ \ \"acc_stderr\": 0.03257864192508729,\n \"acc_norm\": 0.6264034162110771,\n\ \ \"acc_norm_stderr\": 0.033228987439788436,\n \"mc1\": 0.4186046511627907,\n\ \ \"mc1_stderr\": 0.017270015284476848,\n \"mc2\": 0.5902365843525761,\n\ \ \"mc2_stderr\": 0.015835546003395855\n },\n \"harness|arc:challenge|25\"\ : {\n \"acc\": 0.6126279863481229,\n \"acc_stderr\": 0.014235872487909869,\n\ \ \"acc_norm\": 0.6424914675767918,\n \"acc_norm_stderr\": 0.014005494275916573\n\ \ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.6480780720971918,\n\ \ \"acc_stderr\": 0.004765937515197187,\n \"acc_norm\": 0.8270264887472615,\n\ \ \"acc_norm_stderr\": 0.003774513882615956\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\ : {\n \"acc\": 0.29,\n \"acc_stderr\": 0.04560480215720684,\n \ \ \"acc_norm\": 0.29,\n \"acc_norm_stderr\": 0.04560480215720684\n \ \ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.5777777777777777,\n\ \ \"acc_stderr\": 0.04266763404099582,\n \"acc_norm\": 0.5777777777777777,\n\ \ \"acc_norm_stderr\": 0.04266763404099582\n },\n \"harness|hendrycksTest-astronomy|5\"\ : {\n \"acc\": 0.6973684210526315,\n \"acc_stderr\": 0.03738520676119668,\n\ \ \"acc_norm\": 0.6973684210526315,\n \"acc_norm_stderr\": 0.03738520676119668\n\ \ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.58,\n\ \ \"acc_stderr\": 0.049604496374885836,\n \"acc_norm\": 0.58,\n \ \ \"acc_norm_stderr\": 0.049604496374885836\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\ : {\n \"acc\": 0.6830188679245283,\n \"acc_stderr\": 0.02863723563980089,\n\ \ \"acc_norm\": 0.6830188679245283,\n \"acc_norm_stderr\": 0.02863723563980089\n\ \ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.7222222222222222,\n\ \ \"acc_stderr\": 0.037455547914624555,\n \"acc_norm\": 0.7222222222222222,\n\ \ \"acc_norm_stderr\": 0.037455547914624555\n },\n \"harness|hendrycksTest-college_chemistry|5\"\ : {\n \"acc\": 0.44,\n \"acc_stderr\": 0.04988876515698589,\n \ \ \"acc_norm\": 0.44,\n \"acc_norm_stderr\": 0.04988876515698589\n \ \ },\n \"harness|hendrycksTest-college_computer_science|5\": {\n \"acc\"\ : 0.52,\n \"acc_stderr\": 0.050211673156867795,\n \"acc_norm\": 0.52,\n\ \ \"acc_norm_stderr\": 0.050211673156867795\n },\n \"harness|hendrycksTest-college_mathematics|5\"\ : {\n \"acc\": 0.3,\n \"acc_stderr\": 0.046056618647183814,\n \ \ \"acc_norm\": 0.3,\n \"acc_norm_stderr\": 0.046056618647183814\n \ \ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.5953757225433526,\n\ \ \"acc_stderr\": 0.03742461193887248,\n \"acc_norm\": 0.5953757225433526,\n\ \ \"acc_norm_stderr\": 0.03742461193887248\n },\n \"harness|hendrycksTest-college_physics|5\"\ : {\n \"acc\": 0.37254901960784315,\n \"acc_stderr\": 0.04810840148082636,\n\ \ \"acc_norm\": 0.37254901960784315,\n \"acc_norm_stderr\": 0.04810840148082636\n\ \ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\ \ 0.78,\n \"acc_stderr\": 0.04163331998932261,\n \"acc_norm\": 0.78,\n\ \ \"acc_norm_stderr\": 0.04163331998932261\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\ : {\n \"acc\": 0.5617021276595745,\n \"acc_stderr\": 0.03243618636108102,\n\ \ \"acc_norm\": 0.5617021276595745,\n \"acc_norm_stderr\": 0.03243618636108102\n\ \ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.4824561403508772,\n\ \ \"acc_stderr\": 0.04700708033551038,\n \"acc_norm\": 0.4824561403508772,\n\ \ \"acc_norm_stderr\": 0.04700708033551038\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\ : {\n \"acc\": 0.5103448275862069,\n \"acc_stderr\": 0.04165774775728763,\n\ \ \"acc_norm\": 0.5103448275862069,\n \"acc_norm_stderr\": 0.04165774775728763\n\ \ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\ : 0.42063492063492064,\n \"acc_stderr\": 0.025424835086923996,\n \"\ acc_norm\": 0.42063492063492064,\n \"acc_norm_stderr\": 0.025424835086923996\n\ \ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.42063492063492064,\n\ \ \"acc_stderr\": 0.04415438226743744,\n \"acc_norm\": 0.42063492063492064,\n\ \ \"acc_norm_stderr\": 0.04415438226743744\n },\n \"harness|hendrycksTest-global_facts|5\"\ : {\n \"acc\": 0.32,\n \"acc_stderr\": 0.04688261722621504,\n \ \ \"acc_norm\": 0.32,\n \"acc_norm_stderr\": 0.04688261722621504\n \ \ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\": 0.7354838709677419,\n\ \ \"acc_stderr\": 0.02509189237885928,\n \"acc_norm\": 0.7354838709677419,\n\ \ \"acc_norm_stderr\": 0.02509189237885928\n },\n \"harness|hendrycksTest-high_school_chemistry|5\"\ : {\n \"acc\": 0.4482758620689655,\n \"acc_stderr\": 0.03499113137676744,\n\ \ \"acc_norm\": 0.4482758620689655,\n \"acc_norm_stderr\": 0.03499113137676744\n\ \ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \ \ \"acc\": 0.67,\n \"acc_stderr\": 0.04725815626252607,\n \"acc_norm\"\ : 0.67,\n \"acc_norm_stderr\": 0.04725815626252607\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\ : {\n \"acc\": 0.7515151515151515,\n \"acc_stderr\": 0.03374402644139403,\n\ \ \"acc_norm\": 0.7515151515151515,\n \"acc_norm_stderr\": 0.03374402644139403\n\ \ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\ : 0.7777777777777778,\n \"acc_stderr\": 0.029620227874790486,\n \"\ acc_norm\": 0.7777777777777778,\n \"acc_norm_stderr\": 0.029620227874790486\n\ \ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\ \ \"acc\": 0.8601036269430051,\n \"acc_stderr\": 0.02503387058301518,\n\ \ \"acc_norm\": 0.8601036269430051,\n \"acc_norm_stderr\": 0.02503387058301518\n\ \ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \ \ \"acc\": 0.6282051282051282,\n \"acc_stderr\": 0.024503472557110932,\n\ \ \"acc_norm\": 0.6282051282051282,\n \"acc_norm_stderr\": 0.024503472557110932\n\ \ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\ acc\": 0.3074074074074074,\n \"acc_stderr\": 0.028133252578815642,\n \ \ \"acc_norm\": 0.3074074074074074,\n \"acc_norm_stderr\": 0.028133252578815642\n\ \ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \ \ \"acc\": 0.6848739495798319,\n \"acc_stderr\": 0.030176808288974337,\n\ \ \"acc_norm\": 0.6848739495798319,\n \"acc_norm_stderr\": 0.030176808288974337\n\ \ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\ : 0.3708609271523179,\n \"acc_stderr\": 0.03943966699183629,\n \"\ acc_norm\": 0.3708609271523179,\n \"acc_norm_stderr\": 0.03943966699183629\n\ \ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\ : 0.8256880733944955,\n \"acc_stderr\": 0.016265675632010344,\n \"\ acc_norm\": 0.8256880733944955,\n \"acc_norm_stderr\": 0.016265675632010344\n\ \ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\ : 0.5138888888888888,\n \"acc_stderr\": 0.03408655867977749,\n \"\ acc_norm\": 0.5138888888888888,\n \"acc_norm_stderr\": 0.03408655867977749\n\ \ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\ : 0.7892156862745098,\n \"acc_stderr\": 0.028626547912437416,\n \"\ acc_norm\": 0.7892156862745098,\n \"acc_norm_stderr\": 0.028626547912437416\n\ \ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\ acc\": 0.8059071729957806,\n \"acc_stderr\": 0.025744902532290902,\n \ \ \"acc_norm\": 0.8059071729957806,\n \"acc_norm_stderr\": 0.025744902532290902\n\ \ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.6771300448430493,\n\ \ \"acc_stderr\": 0.031381476375754995,\n \"acc_norm\": 0.6771300448430493,\n\ \ \"acc_norm_stderr\": 0.031381476375754995\n },\n \"harness|hendrycksTest-human_sexuality|5\"\ : {\n \"acc\": 0.732824427480916,\n \"acc_stderr\": 0.038808483010823944,\n\ \ \"acc_norm\": 0.732824427480916,\n \"acc_norm_stderr\": 0.038808483010823944\n\ \ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\ \ 0.71900826446281,\n \"acc_stderr\": 0.04103203830514512,\n \"acc_norm\"\ : 0.71900826446281,\n \"acc_norm_stderr\": 0.04103203830514512\n },\n\ \ \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.75,\n \ \ \"acc_stderr\": 0.04186091791394607,\n \"acc_norm\": 0.75,\n \ \ \"acc_norm_stderr\": 0.04186091791394607\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\ : {\n \"acc\": 0.7361963190184049,\n \"acc_stderr\": 0.03462419931615623,\n\ \ \"acc_norm\": 0.7361963190184049,\n \"acc_norm_stderr\": 0.03462419931615623\n\ \ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.48214285714285715,\n\ \ \"acc_stderr\": 0.047427623612430116,\n \"acc_norm\": 0.48214285714285715,\n\ \ \"acc_norm_stderr\": 0.047427623612430116\n },\n \"harness|hendrycksTest-management|5\"\ : {\n \"acc\": 0.7766990291262136,\n \"acc_stderr\": 0.04123553189891431,\n\ \ \"acc_norm\": 0.7766990291262136,\n \"acc_norm_stderr\": 0.04123553189891431\n\ \ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.8803418803418803,\n\ \ \"acc_stderr\": 0.021262719400406957,\n \"acc_norm\": 0.8803418803418803,\n\ \ \"acc_norm_stderr\": 0.021262719400406957\n },\n \"harness|hendrycksTest-medical_genetics|5\"\ : {\n \"acc\": 0.67,\n \"acc_stderr\": 0.04725815626252609,\n \ \ \"acc_norm\": 0.67,\n \"acc_norm_stderr\": 0.04725815626252609\n \ \ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.8135376756066411,\n\ \ \"acc_stderr\": 0.013927751372001506,\n \"acc_norm\": 0.8135376756066411,\n\ \ \"acc_norm_stderr\": 0.013927751372001506\n },\n \"harness|hendrycksTest-moral_disputes|5\"\ : {\n \"acc\": 0.7138728323699421,\n \"acc_stderr\": 0.024332146779134128,\n\ \ \"acc_norm\": 0.7138728323699421,\n \"acc_norm_stderr\": 0.024332146779134128\n\ \ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.24916201117318434,\n\ \ \"acc_stderr\": 0.01446589382985993,\n \"acc_norm\": 0.24916201117318434,\n\ \ \"acc_norm_stderr\": 0.01446589382985993\n },\n \"harness|hendrycksTest-nutrition|5\"\ : {\n \"acc\": 0.7352941176470589,\n \"acc_stderr\": 0.025261691219729487,\n\ \ \"acc_norm\": 0.7352941176470589,\n \"acc_norm_stderr\": 0.025261691219729487\n\ \ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.7041800643086816,\n\ \ \"acc_stderr\": 0.025922371788818767,\n \"acc_norm\": 0.7041800643086816,\n\ \ \"acc_norm_stderr\": 0.025922371788818767\n },\n \"harness|hendrycksTest-prehistory|5\"\ : {\n \"acc\": 0.7067901234567902,\n \"acc_stderr\": 0.025329888171900922,\n\ \ \"acc_norm\": 0.7067901234567902,\n \"acc_norm_stderr\": 0.025329888171900922\n\ \ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\ acc\": 0.5,\n \"acc_stderr\": 0.029827499313594685,\n \"acc_norm\"\ : 0.5,\n \"acc_norm_stderr\": 0.029827499313594685\n },\n \"harness|hendrycksTest-professional_law|5\"\ : {\n \"acc\": 0.4667535853976532,\n \"acc_stderr\": 0.01274197433389723,\n\ \ \"acc_norm\": 0.4667535853976532,\n \"acc_norm_stderr\": 0.01274197433389723\n\ \ },\n \"harness|hendrycksTest-professional_medicine|5\": {\n \"acc\"\ : 0.6764705882352942,\n \"acc_stderr\": 0.02841820861940676,\n \"\ acc_norm\": 0.6764705882352942,\n \"acc_norm_stderr\": 0.02841820861940676\n\ \ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\ acc\": 0.630718954248366,\n \"acc_stderr\": 0.01952431674486635,\n \ \ \"acc_norm\": 0.630718954248366,\n \"acc_norm_stderr\": 0.01952431674486635\n\ \ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.6636363636363637,\n\ \ \"acc_stderr\": 0.04525393596302506,\n \"acc_norm\": 0.6636363636363637,\n\ \ \"acc_norm_stderr\": 0.04525393596302506\n },\n \"harness|hendrycksTest-security_studies|5\"\ : {\n \"acc\": 0.726530612244898,\n \"acc_stderr\": 0.02853556033712844,\n\ \ \"acc_norm\": 0.726530612244898,\n \"acc_norm_stderr\": 0.02853556033712844\n\ \ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.8208955223880597,\n\ \ \"acc_stderr\": 0.027113286753111837,\n \"acc_norm\": 0.8208955223880597,\n\ \ \"acc_norm_stderr\": 0.027113286753111837\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\ : {\n \"acc\": 0.87,\n \"acc_stderr\": 0.03379976689896309,\n \ \ \"acc_norm\": 0.87,\n \"acc_norm_stderr\": 0.03379976689896309\n \ \ },\n \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.5240963855421686,\n\ \ \"acc_stderr\": 0.03887971849597264,\n \"acc_norm\": 0.5240963855421686,\n\ \ \"acc_norm_stderr\": 0.03887971849597264\n },\n \"harness|hendrycksTest-world_religions|5\"\ : {\n \"acc\": 0.8187134502923976,\n \"acc_stderr\": 0.029547741687640044,\n\ \ \"acc_norm\": 0.8187134502923976,\n \"acc_norm_stderr\": 0.029547741687640044\n\ \ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.4186046511627907,\n\ \ \"mc1_stderr\": 0.017270015284476848,\n \"mc2\": 0.5902365843525761,\n\ \ \"mc2_stderr\": 0.015835546003395855\n },\n \"harness|winogrande|5\"\ : {\n \"acc\": 0.7545382794001578,\n \"acc_stderr\": 0.012095272937183633\n\ \ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.604245640636846,\n \ \ \"acc_stderr\": 0.013469823701048815\n }\n}\n```" repo_url: https://huggingface.co/Isotonic/Hermes-2-Pro-Mixtral-4x7B leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2024_03_22T02_39_47.890512 path: - '**/details_harness|arc:challenge|25_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2024-03-22T02-39-47.890512.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '**/details_harness|gsm8k|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_03_22T02_39_47.890512 path: - '**/details_harness|hellaswag|10_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-management|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-management|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-03-22T02-39-47.890512.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '**/details_harness|hendrycksTest-anatomy|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '**/details_harness|hendrycksTest-astronomy|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '**/details_harness|hendrycksTest-college_biology|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '**/details_harness|hendrycksTest-college_physics|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '**/details_harness|hendrycksTest-computer_security|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '**/details_harness|hendrycksTest-econometrics|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '**/details_harness|hendrycksTest-global_facts|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '**/details_harness|hendrycksTest-human_aging|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '**/details_harness|hendrycksTest-international_law|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '**/details_harness|hendrycksTest-management|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '**/details_harness|hendrycksTest-marketing|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '**/details_harness|hendrycksTest-nutrition|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '**/details_harness|hendrycksTest-philosophy|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '**/details_harness|hendrycksTest-prehistory|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '**/details_harness|hendrycksTest-professional_law|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '**/details_harness|hendrycksTest-public_relations|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '**/details_harness|hendrycksTest-security_studies|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '**/details_harness|hendrycksTest-sociology|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '**/details_harness|hendrycksTest-virology|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '**/details_harness|hendrycksTest-world_religions|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2024-03-22T02-39-47.890512.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_03_22T02_39_47.890512 path: - '**/details_harness|truthfulqa:mc|0_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2024-03-22T02-39-47.890512.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_03_22T02_39_47.890512 path: - '**/details_harness|winogrande|5_2024-03-22T02-39-47.890512.parquet' - split: latest path: - '**/details_harness|winogrande|5_2024-03-22T02-39-47.890512.parquet' - config_name: results data_files: - split: 2024_03_22T02_39_47.890512 path: - results_2024-03-22T02-39-47.890512.parquet - split: latest path: - results_2024-03-22T02-39-47.890512.parquet --- # Dataset Card for Evaluation run of Isotonic/Hermes-2-Pro-Mixtral-4x7B  Dataset automatically created during the evaluation run of model [Isotonic/Hermes-2-Pro-Mixtral-4x7B](https://huggingface.co/Isotonic/Hermes-2-Pro-Mixtral-4x7B) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_Isotonic__Hermes-2-Pro-Mixtral-4x7B", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-03-22T02:39:47.890512](https://huggingface.co/datasets/open-llm-leaderboard/details_Isotonic__Hermes-2-Pro-Mixtral-4x7B/blob/main/results_2024-03-22T02-39-47.890512.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval): ```python { "all": { "acc": 0.6247175996493741, "acc_stderr": 0.03257864192508729, "acc_norm": 0.6264034162110771, "acc_norm_stderr": 0.033228987439788436, "mc1": 0.4186046511627907, "mc1_stderr": 0.017270015284476848, "mc2": 0.5902365843525761, "mc2_stderr": 0.015835546003395855 }, "harness|arc:challenge|25": { "acc": 0.6126279863481229, "acc_stderr": 0.014235872487909869, "acc_norm": 0.6424914675767918, "acc_norm_stderr": 0.014005494275916573 }, "harness|hellaswag|10": { "acc": 0.6480780720971918, "acc_stderr": 0.004765937515197187, "acc_norm": 0.8270264887472615, "acc_norm_stderr": 0.003774513882615956 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.29, "acc_stderr": 0.04560480215720684, "acc_norm": 0.29, "acc_norm_stderr": 0.04560480215720684 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.5777777777777777, "acc_stderr": 0.04266763404099582, "acc_norm": 0.5777777777777777, "acc_norm_stderr": 0.04266763404099582 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.6973684210526315, "acc_stderr": 0.03738520676119668, "acc_norm": 0.6973684210526315, "acc_norm_stderr": 0.03738520676119668 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.58, "acc_stderr": 0.049604496374885836, "acc_norm": 0.58, "acc_norm_stderr": 0.049604496374885836 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.6830188679245283, "acc_stderr": 0.02863723563980089, "acc_norm": 0.6830188679245283, "acc_norm_stderr": 0.02863723563980089 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.7222222222222222, "acc_stderr": 0.037455547914624555, "acc_norm": 0.7222222222222222, "acc_norm_stderr": 0.037455547914624555 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.44, "acc_stderr": 0.04988876515698589, "acc_norm": 0.44, "acc_norm_stderr": 0.04988876515698589 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.52, "acc_stderr": 0.050211673156867795, "acc_norm": 0.52, "acc_norm_stderr": 0.050211673156867795 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.3, "acc_stderr": 0.046056618647183814, "acc_norm": 0.3, "acc_norm_stderr": 0.046056618647183814 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.5953757225433526, "acc_stderr": 0.03742461193887248, "acc_norm": 0.5953757225433526, "acc_norm_stderr": 0.03742461193887248 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.37254901960784315, "acc_stderr": 0.04810840148082636, "acc_norm": 0.37254901960784315, "acc_norm_stderr": 0.04810840148082636 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.78, "acc_stderr": 0.04163331998932261, "acc_norm": 0.78, "acc_norm_stderr": 0.04163331998932261 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.5617021276595745, "acc_stderr": 0.03243618636108102, "acc_norm": 0.5617021276595745, "acc_norm_stderr": 0.03243618636108102 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.4824561403508772, "acc_stderr": 0.04700708033551038, "acc_norm": 0.4824561403508772, "acc_norm_stderr": 0.04700708033551038 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.5103448275862069, "acc_stderr": 0.04165774775728763, "acc_norm": 0.5103448275862069, "acc_norm_stderr": 0.04165774775728763 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.42063492063492064, "acc_stderr": 0.025424835086923996, "acc_norm": 0.42063492063492064, "acc_norm_stderr": 0.025424835086923996 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.42063492063492064, "acc_stderr": 0.04415438226743744, "acc_norm": 0.42063492063492064, "acc_norm_stderr": 0.04415438226743744 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.32, "acc_stderr": 0.04688261722621504, "acc_norm": 0.32, "acc_norm_stderr": 0.04688261722621504 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.7354838709677419, "acc_stderr": 0.02509189237885928, "acc_norm": 0.7354838709677419, "acc_norm_stderr": 0.02509189237885928 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.4482758620689655, "acc_stderr": 0.03499113137676744, "acc_norm": 0.4482758620689655, "acc_norm_stderr": 0.03499113137676744 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.67, "acc_stderr": 0.04725815626252607, "acc_norm": 0.67, "acc_norm_stderr": 0.04725815626252607 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.7515151515151515, "acc_stderr": 0.03374402644139403, "acc_norm": 0.7515151515151515, "acc_norm_stderr": 0.03374402644139403 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.7777777777777778, "acc_stderr": 0.029620227874790486, "acc_norm": 0.7777777777777778, "acc_norm_stderr": 0.029620227874790486 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.8601036269430051, "acc_stderr": 0.02503387058301518, "acc_norm": 0.8601036269430051, "acc_norm_stderr": 0.02503387058301518 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.6282051282051282, "acc_stderr": 0.024503472557110932, "acc_norm": 0.6282051282051282, "acc_norm_stderr": 0.024503472557110932 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.3074074074074074, "acc_stderr": 0.028133252578815642, "acc_norm": 0.3074074074074074, "acc_norm_stderr": 0.028133252578815642 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.6848739495798319, "acc_stderr": 0.030176808288974337, "acc_norm": 0.6848739495798319, "acc_norm_stderr": 0.030176808288974337 }, "harness|hendrycksTest-high_school_physics|5": { "acc": 0.3708609271523179, "acc_stderr": 0.03943966699183629, "acc_norm": 0.3708609271523179, "acc_norm_stderr": 0.03943966699183629 }, "harness|hendrycksTest-high_school_psychology|5": { "acc": 0.8256880733944955, "acc_stderr": 0.016265675632010344, "acc_norm": 0.8256880733944955, "acc_norm_stderr": 0.016265675632010344 }, "harness|hendrycksTest-high_school_statistics|5": { "acc": 0.5138888888888888, "acc_stderr": 0.03408655867977749, "acc_norm": 0.5138888888888888, "acc_norm_stderr": 0.03408655867977749 }, "harness|hendrycksTest-high_school_us_history|5": { "acc": 0.7892156862745098, "acc_stderr": 0.028626547912437416, "acc_norm": 0.7892156862745098, "acc_norm_stderr": 0.028626547912437416 }, "harness|hendrycksTest-high_school_world_history|5": { "acc": 0.8059071729957806, "acc_stderr": 0.025744902532290902, "acc_norm": 0.8059071729957806, "acc_norm_stderr": 0.025744902532290902 }, "harness|hendrycksTest-human_aging|5": { "acc": 0.6771300448430493, "acc_stderr": 0.031381476375754995, "acc_norm": 0.6771300448430493, "acc_norm_stderr": 0.031381476375754995 }, "harness|hendrycksTest-human_sexuality|5": { "acc": 0.732824427480916, "acc_stderr": 0.038808483010823944, "acc_norm": 0.732824427480916, "acc_norm_stderr": 0.038808483010823944 }, "harness|hendrycksTest-international_law|5": { "acc": 0.71900826446281, "acc_stderr": 0.04103203830514512, "acc_norm": 0.71900826446281, "acc_norm_stderr": 0.04103203830514512 }, "harness|hendrycksTest-jurisprudence|5": { "acc": 0.75, "acc_stderr": 0.04186091791394607, "acc_norm": 0.75, "acc_norm_stderr": 0.04186091791394607 }, "harness|hendrycksTest-logical_fallacies|5": { "acc": 0.7361963190184049, "acc_stderr": 0.03462419931615623, "acc_norm": 0.7361963190184049, "acc_norm_stderr": 0.03462419931615623 }, "harness|hendrycksTest-machine_learning|5": { "acc": 0.48214285714285715, "acc_stderr": 0.047427623612430116, "acc_norm": 0.48214285714285715, "acc_norm_stderr": 0.047427623612430116 }, "harness|hendrycksTest-management|5": { "acc": 0.7766990291262136, "acc_stderr": 0.04123553189891431, "acc_norm": 0.7766990291262136, "acc_norm_stderr": 0.04123553189891431 }, "harness|hendrycksTest-marketing|5": { "acc": 0.8803418803418803, "acc_stderr": 0.021262719400406957, "acc_norm": 0.8803418803418803, "acc_norm_stderr": 0.021262719400406957 }, "harness|hendrycksTest-medical_genetics|5": { "acc": 0.67, "acc_stderr": 0.04725815626252609, "acc_norm": 0.67, "acc_norm_stderr": 0.04725815626252609 }, "harness|hendrycksTest-miscellaneous|5": { "acc": 0.8135376756066411, "acc_stderr": 0.013927751372001506, "acc_norm": 0.8135376756066411, "acc_norm_stderr": 0.013927751372001506 }, "harness|hendrycksTest-moral_disputes|5": { "acc": 0.7138728323699421, "acc_stderr": 0.024332146779134128, "acc_norm": 0.7138728323699421, "acc_norm_stderr": 0.024332146779134128 }, "harness|hendrycksTest-moral_scenarios|5": { "acc": 0.24916201117318434, "acc_stderr": 0.01446589382985993, "acc_norm": 0.24916201117318434, "acc_norm_stderr": 0.01446589382985993 }, "harness|hendrycksTest-nutrition|5": { "acc": 0.7352941176470589, "acc_stderr": 0.025261691219729487, "acc_norm": 0.7352941176470589, "acc_norm_stderr": 0.025261691219729487 }, "harness|hendrycksTest-philosophy|5": { "acc": 0.7041800643086816, "acc_stderr": 0.025922371788818767, "acc_norm": 0.7041800643086816, "acc_norm_stderr": 0.025922371788818767 }, "harness|hendrycksTest-prehistory|5": { "acc": 0.7067901234567902, "acc_stderr": 0.025329888171900922, "acc_norm": 0.7067901234567902, "acc_norm_stderr": 0.025329888171900922 }, "harness|hendrycksTest-professional_accounting|5": { "acc": 0.5, "acc_stderr": 0.029827499313594685, "acc_norm": 0.5, "acc_norm_stderr": 0.029827499313594685 }, "harness|hendrycksTest-professional_law|5": { "acc": 0.4667535853976532, "acc_stderr": 0.01274197433389723, "acc_norm": 0.4667535853976532, "acc_norm_stderr": 0.01274197433389723 }, "harness|hendrycksTest-professional_medicine|5": { "acc": 0.6764705882352942, "acc_stderr": 0.02841820861940676, "acc_norm": 0.6764705882352942, "acc_norm_stderr": 0.02841820861940676 }, "harness|hendrycksTest-professional_psychology|5": { "acc": 0.630718954248366, "acc_stderr": 0.01952431674486635, "acc_norm": 0.630718954248366, "acc_norm_stderr": 0.01952431674486635 }, "harness|hendrycksTest-public_relations|5": { "acc": 0.6636363636363637, "acc_stderr": 0.04525393596302506, "acc_norm": 0.6636363636363637, "acc_norm_stderr": 0.04525393596302506 }, "harness|hendrycksTest-security_studies|5": { "acc": 0.726530612244898, "acc_stderr": 0.02853556033712844, "acc_norm": 0.726530612244898, "acc_norm_stderr": 0.02853556033712844 }, "harness|hendrycksTest-sociology|5": { "acc": 0.8208955223880597, "acc_stderr": 0.027113286753111837, "acc_norm": 0.8208955223880597, "acc_norm_stderr": 0.027113286753111837 }, "harness|hendrycksTest-us_foreign_policy|5": { "acc": 0.87, "acc_stderr": 0.03379976689896309, "acc_norm": 0.87, "acc_norm_stderr": 0.03379976689896309 }, "harness|hendrycksTest-virology|5": { "acc": 0.5240963855421686, "acc_stderr": 0.03887971849597264, "acc_norm": 0.5240963855421686, "acc_norm_stderr": 0.03887971849597264 }, "harness|hendrycksTest-world_religions|5": { "acc": 0.8187134502923976, "acc_stderr": 0.029547741687640044, "acc_norm": 0.8187134502923976, "acc_norm_stderr": 0.029547741687640044 }, "harness|truthfulqa:mc|0": { "mc1": 0.4186046511627907, "mc1_stderr": 0.017270015284476848, "mc2": 0.5902365843525761, "mc2_stderr": 0.015835546003395855 }, "harness|winogrande|5": { "acc": 0.7545382794001578, "acc_stderr": 0.012095272937183633 }, "harness|gsm8k|5": { "acc": 0.604245640636846, "acc_stderr": 0.013469823701048815 } } ``` ## Dataset Details ### Dataset Description  - **Curated by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] ### Dataset Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Dataset Structure  [More Information Needed] ## Dataset Creation ### Curation Rationale  [More Information Needed] ### Source Data  #### Data Collection and Processing  [More Information Needed] #### Who are the source data producers?  [More Information Needed] ### Annotations [optional]  #### Annotation process  [More Information Needed] #### Who are the annotators?  [More Information Needed] #### Personal and Sensitive Information  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations. ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Dataset Card Authors [optional] [More Information Needed] ## Dataset Card Contact [More Information Needed]

open-responsibility/frameworks

--- license: apache-2.0 configs: - config_name: default data_files: - split: train path: - "catalog.json" --- https://huggingface.co/datasets/open-responsibility/frameworks

hippocrates/qa_train_old

--- configs: - config_name: default data_files: - split: train path: data/train-* - split: valid path: data/valid-* dataset_info: features: - name: id dtype: string - name: conversations list: - name: from dtype: string - name: value dtype: string - name: text dtype: string splits: - name: train num_bytes: 485067176 num_examples: 404269 - name: valid num_bytes: 4491759 num_examples: 5505 download_size: 241040216 dataset_size: 489558935 --- # Dataset Card for "qa_train" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

one-sec-cv12/chunk_132

--- dataset_info: features: - name: audio dtype: audio: sampling_rate: 16000 splits: - name: train num_bytes: 20839438512.875 num_examples: 216969 download_size: 19299011373 dataset_size: 20839438512.875 --- # Dataset Card for "chunk_132" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

J-LAB/OpenHermes_PTBR

--- dataset_info: features: - name: instruction dtype: string - name: input dtype: string - name: output dtype: string splits: - name: train num_bytes: 1391804745 num_examples: 860176 download_size: 772872708 dataset_size: 1391804745 configs: - config_name: default data_files: - split: train path: data/train-* ---

wisenut-nlp-team/aihub_admin_generated_answers

--- dataset_info: features: - name: id dtype: string - name: title dtype: string - name: question dtype: string - name: context dtype: string - name: answer dtype: string - name: original_answer dtype: string - name: similar_contexts sequence: string splits: - name: train num_bytes: 5293612104 num_examples: 315745 download_size: 2662886163 dataset_size: 5293612104 --- # Dataset Card for "aihub_admin_generated_answers_last" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

tyzhu/squad_qa_context_v5_full_recite_ans_sent_last_permute_rerun

--- configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* dataset_info: features: - name: id dtype: string - name: title dtype: string - name: context dtype: string - name: question dtype: string - name: answers sequence: - name: text dtype: string - name: answer_start dtype: int32 - name: answer dtype: string - name: context_id dtype: string - name: inputs dtype: string - name: targets dtype: string splits: - name: train num_bytes: 4850217.0 num_examples: 2385 - name: validation num_bytes: 631113 num_examples: 300 download_size: 1204825 dataset_size: 5481330.0 --- # Dataset Card for "squad_qa_context_v5_full_recite_ans_sent_last_permute_rerun" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

GTZ22/vozmiguel

--- license: openrail ---

ODD2903/ProjetA23

--- license: apache-2.0 ---

open-llm-leaderboard/details_BFauber__lora_llama2-13b_10e5_r32_a16

--- pretty_name: Evaluation run of BFauber/lora_llama2-13b_10e5_r32_a16 dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [BFauber/lora_llama2-13b_10e5_r32_a16](https://huggingface.co/BFauber/lora_llama2-13b_10e5_r32_a16)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 63 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the aggregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_BFauber__lora_llama2-13b_10e5_r32_a16\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-02-10T00:35:29.195349](https://huggingface.co/datasets/open-llm-leaderboard/details_BFauber__lora_llama2-13b_10e5_r32_a16/blob/main/results_2024-02-10T00-35-29.195349.json)(note\ \ that their might be results for other tasks in the repos if successive evals didn't\ \ cover the same tasks. You find each in the results and the \"latest\" split for\ \ each eval):\n\n```python\n{\n \"all\": {\n \"acc\": 0.5560019624665314,\n\ \ \"acc_stderr\": 0.03364714043907589,\n \"acc_norm\": 0.5619565729235969,\n\ \ \"acc_norm_stderr\": 0.03436835615145709,\n \"mc1\": 0.26193390452876375,\n\ \ \"mc1_stderr\": 0.015392118805015025,\n \"mc2\": 0.38301200451667206,\n\ \ \"mc2_stderr\": 0.013767815310741604\n },\n \"harness|arc:challenge|25\"\ : {\n \"acc\": 0.560580204778157,\n \"acc_stderr\": 0.014503747823580123,\n\ \ \"acc_norm\": 0.5989761092150171,\n \"acc_norm_stderr\": 0.01432225579071987\n\ \ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.6163114917347142,\n\ \ \"acc_stderr\": 0.004852896681736758,\n \"acc_norm\": 0.8233419637522406,\n\ \ \"acc_norm_stderr\": 0.0038059961194403754\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\ : {\n \"acc\": 0.33,\n \"acc_stderr\": 0.04725815626252606,\n \ \ \"acc_norm\": 0.33,\n \"acc_norm_stderr\": 0.04725815626252606\n \ \ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.48148148148148145,\n\ \ \"acc_stderr\": 0.043163785995113245,\n \"acc_norm\": 0.48148148148148145,\n\ \ \"acc_norm_stderr\": 0.043163785995113245\n },\n \"harness|hendrycksTest-astronomy|5\"\ : {\n \"acc\": 0.5328947368421053,\n \"acc_stderr\": 0.04060127035236397,\n\ \ \"acc_norm\": 0.5328947368421053,\n \"acc_norm_stderr\": 0.04060127035236397\n\ \ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.52,\n\ \ \"acc_stderr\": 0.05021167315686779,\n \"acc_norm\": 0.52,\n \ \ \"acc_norm_stderr\": 0.05021167315686779\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\ : {\n \"acc\": 0.6226415094339622,\n \"acc_stderr\": 0.029832808114796,\n\ \ \"acc_norm\": 0.6226415094339622,\n \"acc_norm_stderr\": 0.029832808114796\n\ \ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.6041666666666666,\n\ \ \"acc_stderr\": 0.04089465449325582,\n \"acc_norm\": 0.6041666666666666,\n\ \ \"acc_norm_stderr\": 0.04089465449325582\n },\n \"harness|hendrycksTest-college_chemistry|5\"\ : {\n \"acc\": 0.45,\n \"acc_stderr\": 0.05,\n \"acc_norm\"\ : 0.45,\n \"acc_norm_stderr\": 0.05\n },\n \"harness|hendrycksTest-college_computer_science|5\"\ : {\n \"acc\": 0.47,\n \"acc_stderr\": 0.05016135580465919,\n \ \ \"acc_norm\": 0.47,\n \"acc_norm_stderr\": 0.05016135580465919\n \ \ },\n \"harness|hendrycksTest-college_mathematics|5\": {\n \"acc\": 0.3,\n\ \ \"acc_stderr\": 0.046056618647183814,\n \"acc_norm\": 0.3,\n \ \ \"acc_norm_stderr\": 0.046056618647183814\n },\n \"harness|hendrycksTest-college_medicine|5\"\ : {\n \"acc\": 0.5549132947976878,\n \"acc_stderr\": 0.03789401760283647,\n\ \ \"acc_norm\": 0.5549132947976878,\n \"acc_norm_stderr\": 0.03789401760283647\n\ \ },\n \"harness|hendrycksTest-college_physics|5\": {\n \"acc\": 0.2647058823529412,\n\ \ \"acc_stderr\": 0.04389869956808778,\n \"acc_norm\": 0.2647058823529412,\n\ \ \"acc_norm_stderr\": 0.04389869956808778\n },\n \"harness|hendrycksTest-computer_security|5\"\ : {\n \"acc\": 0.69,\n \"acc_stderr\": 0.04648231987117316,\n \ \ \"acc_norm\": 0.69,\n \"acc_norm_stderr\": 0.04648231987117316\n \ \ },\n \"harness|hendrycksTest-conceptual_physics|5\": {\n \"acc\": 0.451063829787234,\n\ \ \"acc_stderr\": 0.032529096196131965,\n \"acc_norm\": 0.451063829787234,\n\ \ \"acc_norm_stderr\": 0.032529096196131965\n },\n \"harness|hendrycksTest-econometrics|5\"\ : {\n \"acc\": 0.2719298245614035,\n \"acc_stderr\": 0.04185774424022056,\n\ \ \"acc_norm\": 0.2719298245614035,\n \"acc_norm_stderr\": 0.04185774424022056\n\ \ },\n \"harness|hendrycksTest-electrical_engineering|5\": {\n \"acc\"\ : 0.5241379310344828,\n \"acc_stderr\": 0.0416180850350153,\n \"acc_norm\"\ : 0.5241379310344828,\n \"acc_norm_stderr\": 0.0416180850350153\n },\n\ \ \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\": 0.328042328042328,\n\ \ \"acc_stderr\": 0.02418049716437691,\n \"acc_norm\": 0.328042328042328,\n\ \ \"acc_norm_stderr\": 0.02418049716437691\n },\n \"harness|hendrycksTest-formal_logic|5\"\ : {\n \"acc\": 0.3333333333333333,\n \"acc_stderr\": 0.04216370213557835,\n\ \ \"acc_norm\": 0.3333333333333333,\n \"acc_norm_stderr\": 0.04216370213557835\n\ \ },\n \"harness|hendrycksTest-global_facts|5\": {\n \"acc\": 0.37,\n\ \ \"acc_stderr\": 0.048523658709391,\n \"acc_norm\": 0.37,\n \ \ \"acc_norm_stderr\": 0.048523658709391\n },\n \"harness|hendrycksTest-high_school_biology|5\"\ : {\n \"acc\": 0.6903225806451613,\n \"acc_stderr\": 0.026302774983517418,\n\ \ \"acc_norm\": 0.6903225806451613,\n \"acc_norm_stderr\": 0.026302774983517418\n\ \ },\n \"harness|hendrycksTest-high_school_chemistry|5\": {\n \"acc\"\ : 0.458128078817734,\n \"acc_stderr\": 0.03505630140785742,\n \"acc_norm\"\ : 0.458128078817734,\n \"acc_norm_stderr\": 0.03505630140785742\n },\n\ \ \"harness|hendrycksTest-high_school_computer_science|5\": {\n \"acc\"\ : 0.56,\n \"acc_stderr\": 0.04988876515698589,\n \"acc_norm\": 0.56,\n\ \ \"acc_norm_stderr\": 0.04988876515698589\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\ : {\n \"acc\": 0.6303030303030303,\n \"acc_stderr\": 0.03769430314512566,\n\ \ \"acc_norm\": 0.6303030303030303,\n \"acc_norm_stderr\": 0.03769430314512566\n\ \ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\ : 0.6919191919191919,\n \"acc_stderr\": 0.032894773300986155,\n \"\ acc_norm\": 0.6919191919191919,\n \"acc_norm_stderr\": 0.032894773300986155\n\ \ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\ \ \"acc\": 0.8031088082901554,\n \"acc_stderr\": 0.028697873971860677,\n\ \ \"acc_norm\": 0.8031088082901554,\n \"acc_norm_stderr\": 0.028697873971860677\n\ \ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \ \ \"acc\": 0.5153846153846153,\n \"acc_stderr\": 0.025339003010106515,\n\ \ \"acc_norm\": 0.5153846153846153,\n \"acc_norm_stderr\": 0.025339003010106515\n\ \ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\ acc\": 0.32222222222222224,\n \"acc_stderr\": 0.028493465091028604,\n \ \ \"acc_norm\": 0.32222222222222224,\n \"acc_norm_stderr\": 0.028493465091028604\n\ \ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \ \ \"acc\": 0.5630252100840336,\n \"acc_stderr\": 0.032219436365661956,\n\ \ \"acc_norm\": 0.5630252100840336,\n \"acc_norm_stderr\": 0.032219436365661956\n\ \ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\ : 0.32450331125827814,\n \"acc_stderr\": 0.03822746937658753,\n \"\ acc_norm\": 0.32450331125827814,\n \"acc_norm_stderr\": 0.03822746937658753\n\ \ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\ : 0.7522935779816514,\n \"acc_stderr\": 0.01850814360254781,\n \"\ acc_norm\": 0.7522935779816514,\n \"acc_norm_stderr\": 0.01850814360254781\n\ \ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\ : 0.4722222222222222,\n \"acc_stderr\": 0.0340470532865388,\n \"acc_norm\"\ : 0.4722222222222222,\n \"acc_norm_stderr\": 0.0340470532865388\n },\n\ \ \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\": 0.7401960784313726,\n\ \ \"acc_stderr\": 0.03077855467869326,\n \"acc_norm\": 0.7401960784313726,\n\ \ \"acc_norm_stderr\": 0.03077855467869326\n },\n \"harness|hendrycksTest-high_school_world_history|5\"\ : {\n \"acc\": 0.7130801687763713,\n \"acc_stderr\": 0.02944377302259469,\n\ \ \"acc_norm\": 0.7130801687763713,\n \"acc_norm_stderr\": 0.02944377302259469\n\ \ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.6412556053811659,\n\ \ \"acc_stderr\": 0.03219079200419995,\n \"acc_norm\": 0.6412556053811659,\n\ \ \"acc_norm_stderr\": 0.03219079200419995\n },\n \"harness|hendrycksTest-human_sexuality|5\"\ : {\n \"acc\": 0.6259541984732825,\n \"acc_stderr\": 0.042438692422305246,\n\ \ \"acc_norm\": 0.6259541984732825,\n \"acc_norm_stderr\": 0.042438692422305246\n\ \ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\ \ 0.7355371900826446,\n \"acc_stderr\": 0.04026187527591207,\n \"\ acc_norm\": 0.7355371900826446,\n \"acc_norm_stderr\": 0.04026187527591207\n\ \ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.7314814814814815,\n\ \ \"acc_stderr\": 0.042844679680521934,\n \"acc_norm\": 0.7314814814814815,\n\ \ \"acc_norm_stderr\": 0.042844679680521934\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\ : {\n \"acc\": 0.6809815950920245,\n \"acc_stderr\": 0.03661997551073836,\n\ \ \"acc_norm\": 0.6809815950920245,\n \"acc_norm_stderr\": 0.03661997551073836\n\ \ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.3125,\n\ \ \"acc_stderr\": 0.043994650575715215,\n \"acc_norm\": 0.3125,\n\ \ \"acc_norm_stderr\": 0.043994650575715215\n },\n \"harness|hendrycksTest-management|5\"\ : {\n \"acc\": 0.7572815533980582,\n \"acc_stderr\": 0.04245022486384495,\n\ \ \"acc_norm\": 0.7572815533980582,\n \"acc_norm_stderr\": 0.04245022486384495\n\ \ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.8076923076923077,\n\ \ \"acc_stderr\": 0.02581923325648372,\n \"acc_norm\": 0.8076923076923077,\n\ \ \"acc_norm_stderr\": 0.02581923325648372\n },\n \"harness|hendrycksTest-medical_genetics|5\"\ : {\n \"acc\": 0.55,\n \"acc_stderr\": 0.04999999999999999,\n \ \ \"acc_norm\": 0.55,\n \"acc_norm_stderr\": 0.04999999999999999\n \ \ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.7458492975734355,\n\ \ \"acc_stderr\": 0.015569254692045757,\n \"acc_norm\": 0.7458492975734355,\n\ \ \"acc_norm_stderr\": 0.015569254692045757\n },\n \"harness|hendrycksTest-moral_disputes|5\"\ : {\n \"acc\": 0.6329479768786127,\n \"acc_stderr\": 0.025950054337654075,\n\ \ \"acc_norm\": 0.6329479768786127,\n \"acc_norm_stderr\": 0.025950054337654075\n\ \ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.2782122905027933,\n\ \ \"acc_stderr\": 0.014987325439963539,\n \"acc_norm\": 0.2782122905027933,\n\ \ \"acc_norm_stderr\": 0.014987325439963539\n },\n \"harness|hendrycksTest-nutrition|5\"\ : {\n \"acc\": 0.6274509803921569,\n \"acc_stderr\": 0.027684181883302895,\n\ \ \"acc_norm\": 0.6274509803921569,\n \"acc_norm_stderr\": 0.027684181883302895\n\ \ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.6463022508038585,\n\ \ \"acc_stderr\": 0.027155208103200865,\n \"acc_norm\": 0.6463022508038585,\n\ \ \"acc_norm_stderr\": 0.027155208103200865\n },\n \"harness|hendrycksTest-prehistory|5\"\ : {\n \"acc\": 0.6419753086419753,\n \"acc_stderr\": 0.026675611926037103,\n\ \ \"acc_norm\": 0.6419753086419753,\n \"acc_norm_stderr\": 0.026675611926037103\n\ \ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\ acc\": 0.40070921985815605,\n \"acc_stderr\": 0.02923346574557308,\n \ \ \"acc_norm\": 0.40070921985815605,\n \"acc_norm_stderr\": 0.02923346574557308\n\ \ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.4198174706649283,\n\ \ \"acc_stderr\": 0.01260496081608737,\n \"acc_norm\": 0.4198174706649283,\n\ \ \"acc_norm_stderr\": 0.01260496081608737\n },\n \"harness|hendrycksTest-professional_medicine|5\"\ : {\n \"acc\": 0.5257352941176471,\n \"acc_stderr\": 0.030332578094555026,\n\ \ \"acc_norm\": 0.5257352941176471,\n \"acc_norm_stderr\": 0.030332578094555026\n\ \ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\ acc\": 0.5555555555555556,\n \"acc_stderr\": 0.020102583895887188,\n \ \ \"acc_norm\": 0.5555555555555556,\n \"acc_norm_stderr\": 0.020102583895887188\n\ \ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.6363636363636364,\n\ \ \"acc_stderr\": 0.046075820907199756,\n \"acc_norm\": 0.6363636363636364,\n\ \ \"acc_norm_stderr\": 0.046075820907199756\n },\n \"harness|hendrycksTest-security_studies|5\"\ : {\n \"acc\": 0.6285714285714286,\n \"acc_stderr\": 0.030932858792789848,\n\ \ \"acc_norm\": 0.6285714285714286,\n \"acc_norm_stderr\": 0.030932858792789848\n\ \ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.7512437810945274,\n\ \ \"acc_stderr\": 0.030567675938916714,\n \"acc_norm\": 0.7512437810945274,\n\ \ \"acc_norm_stderr\": 0.030567675938916714\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\ : {\n \"acc\": 0.81,\n \"acc_stderr\": 0.03942772444036625,\n \ \ \"acc_norm\": 0.81,\n \"acc_norm_stderr\": 0.03942772444036625\n \ \ },\n \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.4759036144578313,\n\ \ \"acc_stderr\": 0.03887971849597264,\n \"acc_norm\": 0.4759036144578313,\n\ \ \"acc_norm_stderr\": 0.03887971849597264\n },\n \"harness|hendrycksTest-world_religions|5\"\ : {\n \"acc\": 0.7777777777777778,\n \"acc_stderr\": 0.03188578017686398,\n\ \ \"acc_norm\": 0.7777777777777778,\n \"acc_norm_stderr\": 0.03188578017686398\n\ \ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.26193390452876375,\n\ \ \"mc1_stderr\": 0.015392118805015025,\n \"mc2\": 0.38301200451667206,\n\ \ \"mc2_stderr\": 0.013767815310741604\n },\n \"harness|winogrande|5\"\ : {\n \"acc\": 0.7703235990528808,\n \"acc_stderr\": 0.011821645601838236\n\ \ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.2357846853677028,\n \ \ \"acc_stderr\": 0.011692515650666792\n }\n}\n```" repo_url: https://huggingface.co/BFauber/lora_llama2-13b_10e5_r32_a16 leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2024_02_10T00_35_29.195349 path: - '**/details_harness|arc:challenge|25_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2024-02-10T00-35-29.195349.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '**/details_harness|gsm8k|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_02_10T00_35_29.195349 path: - '**/details_harness|hellaswag|10_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-management|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-management|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-02-10T00-35-29.195349.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '**/details_harness|hendrycksTest-anatomy|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '**/details_harness|hendrycksTest-astronomy|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '**/details_harness|hendrycksTest-college_biology|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '**/details_harness|hendrycksTest-college_physics|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '**/details_harness|hendrycksTest-computer_security|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '**/details_harness|hendrycksTest-econometrics|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '**/details_harness|hendrycksTest-global_facts|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '**/details_harness|hendrycksTest-human_aging|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '**/details_harness|hendrycksTest-international_law|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '**/details_harness|hendrycksTest-management|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '**/details_harness|hendrycksTest-marketing|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '**/details_harness|hendrycksTest-nutrition|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '**/details_harness|hendrycksTest-philosophy|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '**/details_harness|hendrycksTest-prehistory|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '**/details_harness|hendrycksTest-professional_law|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '**/details_harness|hendrycksTest-public_relations|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '**/details_harness|hendrycksTest-security_studies|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '**/details_harness|hendrycksTest-sociology|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '**/details_harness|hendrycksTest-virology|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '**/details_harness|hendrycksTest-world_religions|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2024-02-10T00-35-29.195349.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_02_10T00_35_29.195349 path: - '**/details_harness|truthfulqa:mc|0_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2024-02-10T00-35-29.195349.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_02_10T00_35_29.195349 path: - '**/details_harness|winogrande|5_2024-02-10T00-35-29.195349.parquet' - split: latest path: - '**/details_harness|winogrande|5_2024-02-10T00-35-29.195349.parquet' - config_name: results data_files: - split: 2024_02_10T00_35_29.195349 path: - results_2024-02-10T00-35-29.195349.parquet - split: latest path: - results_2024-02-10T00-35-29.195349.parquet --- # Dataset Card for Evaluation run of BFauber/lora_llama2-13b_10e5_r32_a16  Dataset automatically created during the evaluation run of model [BFauber/lora_llama2-13b_10e5_r32_a16](https://huggingface.co/BFauber/lora_llama2-13b_10e5_r32_a16) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_BFauber__lora_llama2-13b_10e5_r32_a16", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-02-10T00:35:29.195349](https://huggingface.co/datasets/open-llm-leaderboard/details_BFauber__lora_llama2-13b_10e5_r32_a16/blob/main/results_2024-02-10T00-35-29.195349.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval): ```python { "all": { "acc": 0.5560019624665314, "acc_stderr": 0.03364714043907589, "acc_norm": 0.5619565729235969, "acc_norm_stderr": 0.03436835615145709, "mc1": 0.26193390452876375, "mc1_stderr": 0.015392118805015025, "mc2": 0.38301200451667206, "mc2_stderr": 0.013767815310741604 }, "harness|arc:challenge|25": { "acc": 0.560580204778157, "acc_stderr": 0.014503747823580123, "acc_norm": 0.5989761092150171, "acc_norm_stderr": 0.01432225579071987 }, "harness|hellaswag|10": { "acc": 0.6163114917347142, "acc_stderr": 0.004852896681736758, "acc_norm": 0.8233419637522406, "acc_norm_stderr": 0.0038059961194403754 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.33, "acc_stderr": 0.04725815626252606, "acc_norm": 0.33, "acc_norm_stderr": 0.04725815626252606 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.48148148148148145, "acc_stderr": 0.043163785995113245, "acc_norm": 0.48148148148148145, "acc_norm_stderr": 0.043163785995113245 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.5328947368421053, "acc_stderr": 0.04060127035236397, "acc_norm": 0.5328947368421053, "acc_norm_stderr": 0.04060127035236397 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.52, "acc_stderr": 0.05021167315686779, "acc_norm": 0.52, "acc_norm_stderr": 0.05021167315686779 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.6226415094339622, "acc_stderr": 0.029832808114796, "acc_norm": 0.6226415094339622, "acc_norm_stderr": 0.029832808114796 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.6041666666666666, "acc_stderr": 0.04089465449325582, "acc_norm": 0.6041666666666666, "acc_norm_stderr": 0.04089465449325582 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.45, "acc_stderr": 0.05, "acc_norm": 0.45, "acc_norm_stderr": 0.05 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.47, "acc_stderr": 0.05016135580465919, "acc_norm": 0.47, "acc_norm_stderr": 0.05016135580465919 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.3, "acc_stderr": 0.046056618647183814, "acc_norm": 0.3, "acc_norm_stderr": 0.046056618647183814 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.5549132947976878, "acc_stderr": 0.03789401760283647, "acc_norm": 0.5549132947976878, "acc_norm_stderr": 0.03789401760283647 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.2647058823529412, "acc_stderr": 0.04389869956808778, "acc_norm": 0.2647058823529412, "acc_norm_stderr": 0.04389869956808778 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.69, "acc_stderr": 0.04648231987117316, "acc_norm": 0.69, "acc_norm_stderr": 0.04648231987117316 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.451063829787234, "acc_stderr": 0.032529096196131965, "acc_norm": 0.451063829787234, "acc_norm_stderr": 0.032529096196131965 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.2719298245614035, "acc_stderr": 0.04185774424022056, "acc_norm": 0.2719298245614035, "acc_norm_stderr": 0.04185774424022056 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.5241379310344828, "acc_stderr": 0.0416180850350153, "acc_norm": 0.5241379310344828, "acc_norm_stderr": 0.0416180850350153 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.328042328042328, "acc_stderr": 0.02418049716437691, "acc_norm": 0.328042328042328, "acc_norm_stderr": 0.02418049716437691 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.3333333333333333, "acc_stderr": 0.04216370213557835, "acc_norm": 0.3333333333333333, "acc_norm_stderr": 0.04216370213557835 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.37, "acc_stderr": 0.048523658709391, "acc_norm": 0.37, "acc_norm_stderr": 0.048523658709391 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.6903225806451613, "acc_stderr": 0.026302774983517418, "acc_norm": 0.6903225806451613, "acc_norm_stderr": 0.026302774983517418 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.458128078817734, "acc_stderr": 0.03505630140785742, "acc_norm": 0.458128078817734, "acc_norm_stderr": 0.03505630140785742 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.56, "acc_stderr": 0.04988876515698589, "acc_norm": 0.56, "acc_norm_stderr": 0.04988876515698589 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.6303030303030303, "acc_stderr": 0.03769430314512566, "acc_norm": 0.6303030303030303, "acc_norm_stderr": 0.03769430314512566 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.6919191919191919, "acc_stderr": 0.032894773300986155, "acc_norm": 0.6919191919191919, "acc_norm_stderr": 0.032894773300986155 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.8031088082901554, "acc_stderr": 0.028697873971860677, "acc_norm": 0.8031088082901554, "acc_norm_stderr": 0.028697873971860677 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.5153846153846153, "acc_stderr": 0.025339003010106515, "acc_norm": 0.5153846153846153, "acc_norm_stderr": 0.025339003010106515 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.32222222222222224, "acc_stderr": 0.028493465091028604, "acc_norm": 0.32222222222222224, "acc_norm_stderr": 0.028493465091028604 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.5630252100840336, "acc_stderr": 0.032219436365661956, "acc_norm": 0.5630252100840336, "acc_norm_stderr": 0.032219436365661956 }, "harness|hendrycksTest-high_school_physics|5": { "acc": 0.32450331125827814, "acc_stderr": 0.03822746937658753, "acc_norm": 0.32450331125827814, "acc_norm_stderr": 0.03822746937658753 }, "harness|hendrycksTest-high_school_psychology|5": { "acc": 0.7522935779816514, "acc_stderr": 0.01850814360254781, "acc_norm": 0.7522935779816514, "acc_norm_stderr": 0.01850814360254781 }, "harness|hendrycksTest-high_school_statistics|5": { "acc": 0.4722222222222222, "acc_stderr": 0.0340470532865388, "acc_norm": 0.4722222222222222, "acc_norm_stderr": 0.0340470532865388 }, "harness|hendrycksTest-high_school_us_history|5": { "acc": 0.7401960784313726, "acc_stderr": 0.03077855467869326, "acc_norm": 0.7401960784313726, "acc_norm_stderr": 0.03077855467869326 }, "harness|hendrycksTest-high_school_world_history|5": { "acc": 0.7130801687763713, "acc_stderr": 0.02944377302259469, "acc_norm": 0.7130801687763713, "acc_norm_stderr": 0.02944377302259469 }, "harness|hendrycksTest-human_aging|5": { "acc": 0.6412556053811659, "acc_stderr": 0.03219079200419995, "acc_norm": 0.6412556053811659, "acc_norm_stderr": 0.03219079200419995 }, "harness|hendrycksTest-human_sexuality|5": { "acc": 0.6259541984732825, "acc_stderr": 0.042438692422305246, "acc_norm": 0.6259541984732825, "acc_norm_stderr": 0.042438692422305246 }, "harness|hendrycksTest-international_law|5": { "acc": 0.7355371900826446, "acc_stderr": 0.04026187527591207, "acc_norm": 0.7355371900826446, "acc_norm_stderr": 0.04026187527591207 }, "harness|hendrycksTest-jurisprudence|5": { "acc": 0.7314814814814815, "acc_stderr": 0.042844679680521934, "acc_norm": 0.7314814814814815, "acc_norm_stderr": 0.042844679680521934 }, "harness|hendrycksTest-logical_fallacies|5": { "acc": 0.6809815950920245, "acc_stderr": 0.03661997551073836, "acc_norm": 0.6809815950920245, "acc_norm_stderr": 0.03661997551073836 }, "harness|hendrycksTest-machine_learning|5": { "acc": 0.3125, "acc_stderr": 0.043994650575715215, "acc_norm": 0.3125, "acc_norm_stderr": 0.043994650575715215 }, "harness|hendrycksTest-management|5": { "acc": 0.7572815533980582, "acc_stderr": 0.04245022486384495, "acc_norm": 0.7572815533980582, "acc_norm_stderr": 0.04245022486384495 }, "harness|hendrycksTest-marketing|5": { "acc": 0.8076923076923077, "acc_stderr": 0.02581923325648372, "acc_norm": 0.8076923076923077, "acc_norm_stderr": 0.02581923325648372 }, "harness|hendrycksTest-medical_genetics|5": { "acc": 0.55, "acc_stderr": 0.04999999999999999, "acc_norm": 0.55, "acc_norm_stderr": 0.04999999999999999 }, "harness|hendrycksTest-miscellaneous|5": { "acc": 0.7458492975734355, "acc_stderr": 0.015569254692045757, "acc_norm": 0.7458492975734355, "acc_norm_stderr": 0.015569254692045757 }, "harness|hendrycksTest-moral_disputes|5": { "acc": 0.6329479768786127, "acc_stderr": 0.025950054337654075, "acc_norm": 0.6329479768786127, "acc_norm_stderr": 0.025950054337654075 }, "harness|hendrycksTest-moral_scenarios|5": { "acc": 0.2782122905027933, "acc_stderr": 0.014987325439963539, "acc_norm": 0.2782122905027933, "acc_norm_stderr": 0.014987325439963539 }, "harness|hendrycksTest-nutrition|5": { "acc": 0.6274509803921569, "acc_stderr": 0.027684181883302895, "acc_norm": 0.6274509803921569, "acc_norm_stderr": 0.027684181883302895 }, "harness|hendrycksTest-philosophy|5": { "acc": 0.6463022508038585, "acc_stderr": 0.027155208103200865, "acc_norm": 0.6463022508038585, "acc_norm_stderr": 0.027155208103200865 }, "harness|hendrycksTest-prehistory|5": { "acc": 0.6419753086419753, "acc_stderr": 0.026675611926037103, "acc_norm": 0.6419753086419753, "acc_norm_stderr": 0.026675611926037103 }, "harness|hendrycksTest-professional_accounting|5": { "acc": 0.40070921985815605, "acc_stderr": 0.02923346574557308, "acc_norm": 0.40070921985815605, "acc_norm_stderr": 0.02923346574557308 }, "harness|hendrycksTest-professional_law|5": { "acc": 0.4198174706649283, "acc_stderr": 0.01260496081608737, "acc_norm": 0.4198174706649283, "acc_norm_stderr": 0.01260496081608737 }, "harness|hendrycksTest-professional_medicine|5": { "acc": 0.5257352941176471, "acc_stderr": 0.030332578094555026, "acc_norm": 0.5257352941176471, "acc_norm_stderr": 0.030332578094555026 }, "harness|hendrycksTest-professional_psychology|5": { "acc": 0.5555555555555556, "acc_stderr": 0.020102583895887188, "acc_norm": 0.5555555555555556, "acc_norm_stderr": 0.020102583895887188 }, "harness|hendrycksTest-public_relations|5": { "acc": 0.6363636363636364, "acc_stderr": 0.046075820907199756, "acc_norm": 0.6363636363636364, "acc_norm_stderr": 0.046075820907199756 }, "harness|hendrycksTest-security_studies|5": { "acc": 0.6285714285714286, "acc_stderr": 0.030932858792789848, "acc_norm": 0.6285714285714286, "acc_norm_stderr": 0.030932858792789848 }, "harness|hendrycksTest-sociology|5": { "acc": 0.7512437810945274, "acc_stderr": 0.030567675938916714, "acc_norm": 0.7512437810945274, "acc_norm_stderr": 0.030567675938916714 }, "harness|hendrycksTest-us_foreign_policy|5": { "acc": 0.81, "acc_stderr": 0.03942772444036625, "acc_norm": 0.81, "acc_norm_stderr": 0.03942772444036625 }, "harness|hendrycksTest-virology|5": { "acc": 0.4759036144578313, "acc_stderr": 0.03887971849597264, "acc_norm": 0.4759036144578313, "acc_norm_stderr": 0.03887971849597264 }, "harness|hendrycksTest-world_religions|5": { "acc": 0.7777777777777778, "acc_stderr": 0.03188578017686398, "acc_norm": 0.7777777777777778, "acc_norm_stderr": 0.03188578017686398 }, "harness|truthfulqa:mc|0": { "mc1": 0.26193390452876375, "mc1_stderr": 0.015392118805015025, "mc2": 0.38301200451667206, "mc2_stderr": 0.013767815310741604 }, "harness|winogrande|5": { "acc": 0.7703235990528808, "acc_stderr": 0.011821645601838236 }, "harness|gsm8k|5": { "acc": 0.2357846853677028, "acc_stderr": 0.011692515650666792 } } ``` ## Dataset Details ### Dataset Description  - **Curated by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] ### Dataset Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Dataset Structure  [More Information Needed] ## Dataset Creation ### Curation Rationale  [More Information Needed] ### Source Data  #### Data Collection and Processing  [More Information Needed] #### Who are the source data producers?  [More Information Needed] ### Annotations [optional]  #### Annotation process  [More Information Needed] #### Who are the annotators?  [More Information Needed] #### Personal and Sensitive Information  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations. ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Dataset Card Authors [optional] [More Information Needed] ## Dataset Card Contact [More Information Needed]

Barnie2/testDataset

--- license: apache-2.0 ---

AnuraSet/AnuraSet_v1.0.0

--- license: mit ---

distilled-one-sec-cv12-each-chunk-uniq/chunk_140

--- dataset_info: features: - name: logits sequence: float32 - name: mfcc sequence: sequence: float64 splits: - name: train num_bytes: 1147145696.0 num_examples: 223528 download_size: 1170538394 dataset_size: 1147145696.0 --- # Dataset Card for "chunk_140" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

Multimodal-Fatima/DTD_parition1_test_facebook_opt_1.3b_Visclues_ns_1880_random

--- dataset_info: features: - name: id dtype: int64 - name: image dtype: image - name: prompt dtype: string - name: true_label dtype: string - name: prediction dtype: string - name: scores sequence: float64 splits: - name: fewshot_1_bs_16 num_bytes: 92562773.0 num_examples: 1880 - name: fewshot_3_bs_16 num_bytes: 93877652.0 num_examples: 1880 download_size: 182697216 dataset_size: 186440425.0 --- # Dataset Card for "DTD_parition1_test_facebook_opt_1.3b_Visclues_ns_1880_random" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

jondurbin/airoboros-gpt4-1.4.1

--- license: cc-by-nc-4.0 --- The same as 1.4, but with coding updates: - rosettacode instructions were removed, due to a few issues found when spot-checking examples - limited the coding examples to fewer languages, to test if a more focused dataset would produce better results

carnival13/xlmr_hard_curr_uda_ep3

--- dataset_info: features: - name: domain_label dtype: int64 - name: pass_label dtype: int64 - name: input dtype: string - name: input_ids sequence: int32 - name: attention_mask sequence: int8 splits: - name: train num_bytes: 774087578 num_examples: 519240 download_size: 233619604 dataset_size: 774087578 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "xlmr_hard_curr_uda_ep3" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

benayas/massive_chatgpt_20pct_v2

--- dataset_info: features: - name: text dtype: string - name: category dtype: string splits: - name: train num_bytes: 750498 num_examples: 11514 download_size: 267643 dataset_size: 750498 configs: - config_name: default data_files: - split: train path: data/train-* ---

TrustLLM/TrustLLM-dataset

--- license: apache-2.0 language: - en configs: - config_name: safety data_files: "safety/*json" - config_name: ethics data_files: "ethics/*json" - config_name: fairness data_files: "fairness/*json" - config_name: robustness data_files: "robustness/*json" - config_name: privacy data_files: "privacy/*json" - config_name: truthfulness data_files: "truthfulness/*json" tags: - llm - trustworthy ai - nlp size_categories: - 10K<n<100K --- # Dataset Card for TrustLLM ## Dataset Summary This repository provides datasets from the TrustLLM benchmark, including six aspects: truthfulness, safety, fairness, robustness, privacy, and machine ethics. To find more details about TrustLLM, please visit the [project website](https://trustllmbenchmark.github.io/TrustLLM-Website/). ## Disclaimer The dataset contains harmful content such as partial pornography, violence, bloodshed, or bias. The opinions expressed in the data do not reflect the views of the TrustLLM team. This dataset is strictly intended for research purposes and should not be used for any other illegal activities. We advocate for the responsible use of large language models. ### Download Use `trustllm` toolkit to download the dataset: [link](https://howiehwong.github.io/TrustLLM/#dataset-download). Use `hugginface` to download the dataset: ```python from datasets import load_dataset # Load all sections dataset = load_dataset("TrustLLM/TrustLLM-dataset") # Load one of the sections dataset = load_dataset("TrustLLM/TrustLLM-dataset", data_dir="safety") ``` ## Contact Contact Us: [trustllm.benchmark@gmail.com](mailto:trustllm.benchmark@gmail.com)

ophycare/icliniq-dataset-1

--- license: llama2 ---

SantiagoPG/doc_qa

--- language: - en ---

moficodes/guanaco-gemma-500

--- dataset_info: features: - name: text dtype: string splits: - name: train num_bytes: 842593 num_examples: 500 download_size: 478887 dataset_size: 842593 configs: - config_name: default data_files: - split: train path: data/train-* ---

Revankumar/fingpt

--- license: mit ---

enzeberg/crowded_fishes

--- license: cc-by-4.0 ---

Kamyar-zeinalipour/ITA_CW

--- dataset_info: features: - name: Clue dtype: string - name: Answer dtype: string - name: couple_occurencies dtype: int64 splits: - name: train num_bytes: 5767721 num_examples: 125202 download_size: 3409199 dataset_size: 5767721 --- # Dataset Card for "ITA_CW" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

ibivibiv/alpaca_tasksource20

--- dataset_info: features: - name: input dtype: string - name: instruction dtype: string - name: output dtype: string splits: - name: train num_bytes: 135229939 num_examples: 253970 download_size: 76708825 dataset_size: 135229939 configs: - config_name: default data_files: - split: train path: data/train-* ---