HuggingFaceBR4/thomwolf-small-llama

Dataset Card for Evaluation run of 3050

Dataset Summary

Dataset automatically created during the evaluation run of model 3050 on the Open LLM Leaderboard.

The dataset is composed of 406 configuration, each one coresponding to one of the evaluated task.

The dataset has been created from 116 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).

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

from datasets import load_dataset
data = load_dataset("HuggingFaceBR4/thomwolf-small-llama",
    "harness_winogrande_0_small_llama_1p82G_the_pile_eval_3050_parquet",
    split="train")

Latest results

These are the latest results from run (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": 0.3484644210447005,
        "acc_stderr": 0.011027112856079687,
        "acc_norm": 0.31556595066284593,
        "acc_norm_stderr": 0.0116539643464742
    },
    "harness|arc:challenge|0": {
        "acc": 0.2167235494880546,
        "acc_stderr": 0.012040156713481189,
        "acc_norm": 0.2645051194539249,
        "acc_norm_stderr": 0.01288927294931337
    },
    "harness|arc:easy|0": {
        "acc": 0.25126262626262624,
        "acc_stderr": 0.008900141191221627,
        "acc_norm": 0.24621212121212122,
        "acc_norm_stderr": 0.008839902656771871
    },
    "harness|hellaswag|0": {
        "acc": 0.25343557060346544,
        "acc_stderr": 0.0043408916733205065,
        "acc_norm": 0.25731925911173076,
        "acc_norm_stderr": 0.00436263363737448
    },
    "harness|openbookqa|0": {
        "acc": 0.188,
        "acc_stderr": 0.017490678880346222,
        "acc_norm": 0.3,
        "acc_norm_stderr": 0.02051442622562805
    },
    "harness|piqa|0": {
        "acc": 0.5380848748639826,
        "acc_stderr": 0.011631933367846709,
        "acc_norm": 0.5097932535364527,
        "acc_norm_stderr": 0.011663586263283223
    },
    "harness|super_glue:boolq|0": {
        "acc": 0.4795107033639144,
        "acc_stderr": 0.008737709345935943
    },
    "harness|winogrande|0": {
        "acc": 0.5122336227308603,
        "acc_stderr": 0.014048278820405621
    }
}

Supported Tasks and Leaderboards

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Languages

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Dataset Structure

Data Instances

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Data Fields

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Data Splits

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Dataset Creation

Curation Rationale

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Source Data

Initial Data Collection and Normalization

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Who are the source language producers?

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Annotations

Annotation process

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Who are the annotators?

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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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