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README.md

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+---
+pretty_name: Evaluation run of psmathur/model_009
+dataset_summary: "Dataset automatically created during the evaluation run of model\
+  \ [psmathur/model_009](https://huggingface.co/psmathur/model_009) on the [Open LLM\
+  \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\
+  \nThe dataset is composed of 3 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_psmathur__model_009_public\"\
+  ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\
+  These are the [latest results from run 2023-11-09T07:41:27.734814](https://huggingface.co/datasets/open-llm-leaderboard/details_psmathur__model_009_public/blob/main/results_2023-11-09T07-41-27.734814.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\": 0.3341023489932886,\n\
+  \        \"em_stderr\": 0.004830400685277283,\n        \"f1\": 0.440147860738256,\n\
+  \        \"f1_stderr\": 0.0045184970708564655,\n        \"acc\": 0.6087212395126058,\n\
+  \        \"acc_stderr\": 0.0120913878225072\n    },\n    \"harness|drop|3\": {\n\
+  \        \"em\": 0.3341023489932886,\n        \"em_stderr\": 0.004830400685277283,\n\
+  \        \"f1\": 0.440147860738256,\n        \"f1_stderr\": 0.0045184970708564655\n\
+  \    },\n    \"harness|gsm8k|5\": {\n        \"acc\": 0.39423805913570886,\n   \
+  \     \"acc_stderr\": 0.01346085235709565\n    },\n    \"harness|winogrande|5\"\
+  : {\n        \"acc\": 0.8232044198895028,\n        \"acc_stderr\": 0.010721923287918747\n\
+  \    }\n}\n```"
+repo_url: https://huggingface.co/psmathur/model_009
+leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
+point_of_contact: clementine@hf.co
+configs:
+- config_name: harness_drop_3
+  data_files:
+  - split: 2023_11_09T07_41_27.734814
+    path:
+    - '**/details_harness|drop|3_2023-11-09T07-41-27.734814.parquet'
+  - split: latest
+    path:
+    - '**/details_harness|drop|3_2023-11-09T07-41-27.734814.parquet'
+- config_name: harness_gsm8k_5
+  data_files:
+  - split: 2023_11_09T07_41_27.734814
+    path:
+    - '**/details_harness|gsm8k|5_2023-11-09T07-41-27.734814.parquet'
+  - split: latest
+    path:
+    - '**/details_harness|gsm8k|5_2023-11-09T07-41-27.734814.parquet'
+- config_name: harness_winogrande_5
+  data_files:
+  - split: 2023_11_09T07_41_27.734814
+    path:
+    - '**/details_harness|winogrande|5_2023-11-09T07-41-27.734814.parquet'
+  - split: latest
+    path:
+    - '**/details_harness|winogrande|5_2023-11-09T07-41-27.734814.parquet'
+- config_name: results
+  data_files:
+  - split: 2023_11_09T07_41_27.734814
+    path:
+    - results_2023-11-09T07-41-27.734814.parquet
+  - split: latest
+    path:
+    - results_2023-11-09T07-41-27.734814.parquet
+---
+
+# Dataset Card for Evaluation run of psmathur/model_009
+
+## Dataset Description
+
+- **Homepage:** 
+- **Repository:** https://huggingface.co/psmathur/model_009
+- **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 [psmathur/model_009](https://huggingface.co/psmathur/model_009) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).
+
+The dataset is composed of 3 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_psmathur__model_009_public",
+	"harness_winogrande_5",
+	split="train")
+```
+
+## Latest results
+
+These are the [latest results from run 2023-11-09T07:41:27.734814](https://huggingface.co/datasets/open-llm-leaderboard/details_psmathur__model_009_public/blob/main/results_2023-11-09T07-41-27.734814.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": 0.3341023489932886,
+        "em_stderr": 0.004830400685277283,
+        "f1": 0.440147860738256,
+        "f1_stderr": 0.0045184970708564655,
+        "acc": 0.6087212395126058,
+        "acc_stderr": 0.0120913878225072
+    },
+    "harness|drop|3": {
+        "em": 0.3341023489932886,
+        "em_stderr": 0.004830400685277283,
+        "f1": 0.440147860738256,
+        "f1_stderr": 0.0045184970708564655
+    },
+    "harness|gsm8k|5": {
+        "acc": 0.39423805913570886,
+        "acc_stderr": 0.01346085235709565
+    },
+    "harness|winogrande|5": {
+        "acc": 0.8232044198895028,
+        "acc_stderr": 0.010721923287918747
+    }
+}
+```
+
+### 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]