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- ### Signal and Noise: A Framework for Reducing Uncertainty in Language Model Evaluation
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  <p align="center">
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  <a href="https://github.com/allenai/signal-and-noise/blob/main/LICENSE">
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  Our work studies the ratio between signal, a benchmark's ability to separate models; and noise, a benchmark's sensitivity to random variability during training steps.
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+ ## Signal and Noise: A Framework for Reducing Uncertainty in Language Model Evaluation
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  <p align="center">
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  <a href="https://github.com/allenai/signal-and-noise/blob/main/LICENSE">
 
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  Our work studies the ratio between signal, a benchmark's ability to separate models; and noise, a benchmark's sensitivity to random variability during training steps.
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+ ### Main Data (XXX models)
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+ **TODO ADD**
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+ ### DataDecide Data (225 models with 4M to 1B params)
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+ ```python
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+ import pandas as pd
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+ from snr.download.hf import pull_predictions_from_hf
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+ local_path = pull_predictions_from_hf("allenai/signal-and-noise", split_name='datadecide_intermediate')
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+ df = pd.read_parquet(local_path)
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+ print(f'Loaded {len(df):,} model evaluations')
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+ >>> Loaded 212,047 model evaluations
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+ ```
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+
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+ ### Random Seed Data (20 models with 1B params)
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+ ```python
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+ import pandas as pd
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+ from snr.download.hf import pull_predictions_from_hf
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+ local_path = pull_predictions_from_hf("allenai/signal-and-noise", split_name='random_seeds')
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+ df = pd.read_parquet(local_path)
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+ print(f'Loaded {len(df):,} model evaluations')
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+ >>> Loaded 296,358 model evaluations
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+ ```