--- pretty_name: Evaluation run of CohereForAI/aya-23-8B dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [CohereForAI/aya-23-8B](https://huggingface.co/CohereForAI/aya-23-8B)\nThe dataset\ \ is composed of 5 configuration(s), each one corresponding 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.\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(\n\t\"africa-intelligence/aya23-benchmarking\"\ ,\n\tname=\"CohereForAI__aya-23-8B__afrimgsm_direct_xho\",\n\tsplit=\"latest\"\n\ )\n```\n\n## Latest results\n\nThese are the [latest results from run 2024-10-01T03-01-55.801880](https://huggingface.co/datasets/africa-intelligence/aya23-benchmarking/blob/main/CohereForAI/aya-23-8B/results_2024-10-01T03-01-55.801880.json)\ \ (note that there 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 \"afrimgsm_direct_xho\"\ : {\n \"alias\": \"afrimgsm_direct_xho\",\n \"exact_match,remove_whitespace\"\ : 0.0,\n \"exact_match_stderr,remove_whitespace\": 0.0,\n \ \ \"exact_match,flexible-extract\": 0.008,\n \"exact_match_stderr,flexible-extract\"\ : 0.005645483676690173\n },\n \"afrimgsm_direct_zul\": {\n \ \ \"alias\": \"afrimgsm_direct_zul\",\n \"exact_match,remove_whitespace\"\ : 0.0,\n \"exact_match_stderr,remove_whitespace\": 0.0,\n \ \ \"exact_match,flexible-extract\": 0.02,\n \"exact_match_stderr,flexible-extract\"\ : 0.008872139507342683\n },\n \"afrimmlu_direct_xho\": {\n \ \ \"alias\": \"afrimmlu_direct_xho\",\n \"acc,none\": 0.228,\n \ \ \"acc_stderr,none\": 0.018781306529363204,\n \"f1,none\":\ \ 0.22499762903231807,\n \"f1_stderr,none\": \"N/A\"\n },\n \ \ \"afrimmlu_direct_zul\": {\n \"alias\": \"afrimmlu_direct_zul\"\ ,\n \"acc,none\": 0.25,\n \"acc_stderr,none\": 0.019384310743640384,\n\ \ \"f1,none\": 0.2522065219763795,\n \"f1_stderr,none\": \"\ N/A\"\n },\n \"afrixnli_en_direct_xho\": {\n \"alias\"\ : \"afrixnli_en_direct_xho\",\n \"acc,none\": 0.335,\n \"\ acc_stderr,none\": 0.019285007627653686,\n \"f1,none\": 0.27778903523584375,\n\ \ \"f1_stderr,none\": \"N/A\"\n },\n \"afrixnli_en_direct_zul\"\ : {\n \"alias\": \"afrixnli_en_direct_zul\",\n \"acc,none\"\ : 0.33166666666666667,\n \"acc_stderr,none\": 0.019236854622688142,\n\ \ \"f1,none\": 0.26541415513303723,\n \"f1_stderr,none\":\ \ \"N/A\"\n }\n },\n \"afrimgsm_direct_xho\": {\n \"alias\"\ : \"afrimgsm_direct_xho\",\n \"exact_match,remove_whitespace\": 0.0,\n \ \ \"exact_match_stderr,remove_whitespace\": 0.0,\n \"exact_match,flexible-extract\"\ : 0.008,\n \"exact_match_stderr,flexible-extract\": 0.005645483676690173\n\ \ },\n \"afrimgsm_direct_zul\": {\n \"alias\": \"afrimgsm_direct_zul\"\ ,\n \"exact_match,remove_whitespace\": 0.0,\n \"exact_match_stderr,remove_whitespace\"\ : 0.0,\n \"exact_match,flexible-extract\": 0.02,\n \"exact_match_stderr,flexible-extract\"\ : 0.008872139507342683\n },\n \"afrimmlu_direct_xho\": {\n \"alias\"\ : \"afrimmlu_direct_xho\",\n \"acc,none\": 0.228,\n \"acc_stderr,none\"\ : 0.018781306529363204,\n \"f1,none\": 0.22499762903231807,\n \"f1_stderr,none\"\ : \"N/A\"\n },\n \"afrimmlu_direct_zul\": {\n \"alias\": \"afrimmlu_direct_zul\"\ ,\n \"acc,none\": 0.25,\n \"acc_stderr,none\": 0.019384310743640384,\n\ \ \"f1,none\": 0.2522065219763795,\n \"f1_stderr,none\": \"N/A\"\n\ \ },\n \"afrixnli_en_direct_xho\": {\n \"alias\": \"afrixnli_en_direct_xho\"\ ,\n \"acc,none\": 0.335,\n \"acc_stderr,none\": 0.019285007627653686,\n\ \ \"f1,none\": 0.27778903523584375,\n \"f1_stderr,none\": \"N/A\"\n\ \ },\n \"afrixnli_en_direct_zul\": {\n \"alias\": \"afrixnli_en_direct_zul\"\ ,\n \"acc,none\": 0.33166666666666667,\n \"acc_stderr,none\": 0.019236854622688142,\n\ \ \"f1,none\": 0.26541415513303723,\n \"f1_stderr,none\": \"N/A\"\n\ \ }\n}\n```" repo_url: https://huggingface.co/CohereForAI/aya-23-8B leaderboard_url: '' point_of_contact: '' configs: - config_name: CohereForAI__aya-23-8B__afrimgsm_direct_xho data_files: - split: 2024_10_01T03_01_55.801880 path: - '**/samples_afrimgsm_direct_xho_2024-10-01T03-01-55.801880.jsonl' - split: latest path: - '**/samples_afrimgsm_direct_xho_2024-10-01T03-01-55.801880.jsonl' - config_name: CohereForAI__aya-23-8B__afrimgsm_direct_zul data_files: - split: 2024_10_01T03_01_55.801880 path: - '**/samples_afrimgsm_direct_zul_2024-10-01T03-01-55.801880.jsonl' - split: latest path: - '**/samples_afrimgsm_direct_zul_2024-10-01T03-01-55.801880.jsonl' - config_name: CohereForAI__aya-23-8B__afrimmlu_direct_xho data_files: - split: 2024_10_01T03_01_55.801880 path: - '**/samples_afrimmlu_direct_xho_2024-10-01T03-01-55.801880.jsonl' - split: latest path: - '**/samples_afrimmlu_direct_xho_2024-10-01T03-01-55.801880.jsonl' - config_name: CohereForAI__aya-23-8B__afrimmlu_direct_zul data_files: - split: 2024_10_01T03_01_55.801880 path: - '**/samples_afrimmlu_direct_zul_2024-10-01T03-01-55.801880.jsonl' - split: latest path: - '**/samples_afrimmlu_direct_zul_2024-10-01T03-01-55.801880.jsonl' - config_name: CohereForAI__aya-23-8B__afrixnli_en_direct_xho data_files: - split: 2024_10_01T03_01_55.801880 path: - '**/samples_afrixnli_en_direct_xho_2024-10-01T03-01-55.801880.jsonl' - split: latest path: - '**/samples_afrixnli_en_direct_xho_2024-10-01T03-01-55.801880.jsonl' - config_name: CohereForAI__aya-23-8B__afrixnli_en_direct_zul data_files: - split: 2024_10_01T03_01_55.801880 path: - '**/samples_afrixnli_en_direct_zul_2024-10-01T03-01-55.801880.jsonl' - split: latest path: - '**/samples_afrixnli_en_direct_zul_2024-10-01T03-01-55.801880.jsonl' --- # Dataset Card for Evaluation run of CohereForAI/aya-23-8B Dataset automatically created during the evaluation run of model [CohereForAI/aya-23-8B](https://huggingface.co/CohereForAI/aya-23-8B) The dataset is composed of 5 configuration(s), each one corresponding 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. To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset( "africa-intelligence/aya23-benchmarking", name="CohereForAI__aya-23-8B__afrimgsm_direct_xho", split="latest" ) ``` ## Latest results These are the [latest results from run 2024-10-01T03-01-55.801880](https://huggingface.co/datasets/africa-intelligence/aya23-benchmarking/blob/main/CohereForAI/aya-23-8B/results_2024-10-01T03-01-55.801880.json) (note that there 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": { "afrimgsm_direct_xho": { "alias": "afrimgsm_direct_xho", "exact_match,remove_whitespace": 0.0, "exact_match_stderr,remove_whitespace": 0.0, "exact_match,flexible-extract": 0.008, "exact_match_stderr,flexible-extract": 0.005645483676690173 }, "afrimgsm_direct_zul": { "alias": "afrimgsm_direct_zul", "exact_match,remove_whitespace": 0.0, "exact_match_stderr,remove_whitespace": 0.0, "exact_match,flexible-extract": 0.02, "exact_match_stderr,flexible-extract": 0.008872139507342683 }, "afrimmlu_direct_xho": { "alias": "afrimmlu_direct_xho", "acc,none": 0.228, "acc_stderr,none": 0.018781306529363204, "f1,none": 0.22499762903231807, "f1_stderr,none": "N/A" }, "afrimmlu_direct_zul": { "alias": "afrimmlu_direct_zul", "acc,none": 0.25, "acc_stderr,none": 0.019384310743640384, "f1,none": 0.2522065219763795, "f1_stderr,none": "N/A" }, "afrixnli_en_direct_xho": { "alias": "afrixnli_en_direct_xho", "acc,none": 0.335, "acc_stderr,none": 0.019285007627653686, "f1,none": 0.27778903523584375, "f1_stderr,none": "N/A" }, "afrixnli_en_direct_zul": { "alias": "afrixnli_en_direct_zul", "acc,none": 0.33166666666666667, "acc_stderr,none": 0.019236854622688142, "f1,none": 0.26541415513303723, "f1_stderr,none": "N/A" } }, "afrimgsm_direct_xho": { "alias": "afrimgsm_direct_xho", "exact_match,remove_whitespace": 0.0, "exact_match_stderr,remove_whitespace": 0.0, "exact_match,flexible-extract": 0.008, "exact_match_stderr,flexible-extract": 0.005645483676690173 }, "afrimgsm_direct_zul": { "alias": "afrimgsm_direct_zul", "exact_match,remove_whitespace": 0.0, "exact_match_stderr,remove_whitespace": 0.0, "exact_match,flexible-extract": 0.02, "exact_match_stderr,flexible-extract": 0.008872139507342683 }, "afrimmlu_direct_xho": { "alias": "afrimmlu_direct_xho", "acc,none": 0.228, "acc_stderr,none": 0.018781306529363204, "f1,none": 0.22499762903231807, "f1_stderr,none": "N/A" }, "afrimmlu_direct_zul": { "alias": "afrimmlu_direct_zul", "acc,none": 0.25, "acc_stderr,none": 0.019384310743640384, "f1,none": 0.2522065219763795, "f1_stderr,none": "N/A" }, "afrixnli_en_direct_xho": { "alias": "afrixnli_en_direct_xho", "acc,none": 0.335, "acc_stderr,none": 0.019285007627653686, "f1,none": 0.27778903523584375, "f1_stderr,none": "N/A" }, "afrixnli_en_direct_zul": { "alias": "afrixnli_en_direct_zul", "acc,none": 0.33166666666666667, "acc_stderr,none": 0.019236854622688142, "f1,none": 0.26541415513303723, "f1_stderr,none": "N/A" } } ``` ## 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? 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