pretty_name: Evaluation run of TheBloke/WizardLM-7B-uncensored-GPTQ
dataset_summary: "Dataset automatically created during the evaluation run of model
\ TheBloke/WizardLM-7B-uncensored-GPTQ
\ on the 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 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 aggregated metrics on the Open LLM
\ Leaderboard).\n
\nTo load the details from a run, you can for instance do the following:\npython\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_TheBloke__WizardLM-7B-uncensored-GPTQ\"\ ,\n\t\"harness_gsm8k_5\",\n\tsplit=\"train\")\n\n\n## Latest results\n\nThese
\ are the latest results from run 2023-12-02T12:59:15.195874(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\npython\n{\n \"all\": {\n \"acc\": 0.0,\n \"\ acc_stderr\": 0.0\n },\n \"harness|gsm8k|5\": {\n \"acc\": 0.0,\n \ \ \"acc_stderr\": 0.0\n }\n}\n"
repo_url: https://huggingface.co/TheBloke/WizardLM-7B-uncensored-GPTQ
leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
point_of_contact: [email protected]
configs:

• config_name: harness_drop_3
  data_files:
  • split: 2023_10_21T21_04_26.590858
    path:
    • '**/details_harness|drop|3_2023-10-21T21-04-26.590858.parquet'
  • split: latest
    path:
    • '**/details_harness|drop|3_2023-10-21T21-04-26.590858.parquet'
• config_name: harness_gsm8k_5
  data_files:
  • split: 2023_10_21T21_04_26.590858
    path:
    • '**/details_harness|gsm8k|5_2023-10-21T21-04-26.590858.parquet'
  • split: 2023_12_02T12_59_15.195874
    path:
    • '**/details_harness|gsm8k|5_2023-12-02T12-59-15.195874.parquet'
  • split: latest
    path:
    • '**/details_harness|gsm8k|5_2023-12-02T12-59-15.195874.parquet'
• config_name: harness_winogrande_5
  data_files:
  • split: 2023_10_21T21_04_26.590858
    path:
    • '**/details_harness|winogrande|5_2023-10-21T21-04-26.590858.parquet'
  • split: latest
    path:
    • '**/details_harness|winogrande|5_2023-10-21T21-04-26.590858.parquet'
• config_name: results
  data_files:
  • split: 2023_10_21T21_04_26.590858
    path:
    • results_2023-10-21T21-04-26.590858.parquet
  • split: 2023_12_02T12_59_15.195874
    path:
    • results_2023-12-02T12-59-15.195874.parquet
  • split: latest
    path:
    • results_2023-12-02T12-59-15.195874.parquet

Dataset Card for Evaluation run of TheBloke/WizardLM-7B-uncensored-GPTQ

Dataset Description

• Homepage:
• Repository: https://huggingface.co/TheBloke/WizardLM-7B-uncensored-GPTQ
• Paper:
• Leaderboard: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
• Point of Contact: [email protected]

Dataset Summary

Dataset automatically created during the evaluation run of model TheBloke/WizardLM-7B-uncensored-GPTQ on the 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 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 aggregated metrics on the Open LLM Leaderboard).

To load the details from a run, you can for instance do the following:

from datasets import load_dataset
data = load_dataset("open-llm-leaderboard/details_TheBloke__WizardLM-7B-uncensored-GPTQ",
	"harness_gsm8k_5",
	split="train")

Latest results

These are the latest results from run 2023-12-02T12:59:15.195874(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):

{
    "all": {
        "acc": 0.0,
        "acc_stderr": 0.0
    },
    "harness|gsm8k|5": {
        "acc": 0.0,
        "acc_stderr": 0.0
    }
}

Supported Tasks and Leaderboards

[More Information Needed]

Languages

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Dataset Structure

Data Instances

[More Information Needed]

Data Fields

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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

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Considerations for Using the Data

Social Impact of Dataset

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Discussion of Biases

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Other Known Limitations

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Additional Information

Dataset Curators

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Licensing Information

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Citation Information

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Contributions

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