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RewardModelSmallerQuestionWithTwoLabelsLengthJustified

Text Classification
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RajuEEE/RewardModelSmallerQuestionWithTwoLabelsLengthJustified

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  1. README.md +6 -6
  2. model.safetensors +1 -1
  3. runs/Nov21_13-58-25_7e84c2bf9dec/events.out.tfevents.1700575118.7e84c2bf9dec.231.0 +3 -0
  4. runs/Nov21_13-58-25_7e84c2bf9dec/events.out.tfevents.1700575462.7e84c2bf9dec.231.1 +3 -0
  5. training_args.bin +1 -1
README.md CHANGED
@@ -18,10 +18,10 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.5225
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- - F1: 0.7620
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- - Roc Auc: 0.7617
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- - Accuracy: 0.7603
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  ## Model description
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@@ -52,8 +52,8 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
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- | 0.628 | 1.0 | 200 | 0.5919 | 0.6869 | 0.6873 | 0.6860 |
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- | 0.5205 | 2.0 | 400 | 0.5225 | 0.7620 | 0.7617 | 0.7603 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.5218
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+ - F1: 0.7503
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+ - Roc Auc: 0.7507
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+ - Accuracy: 0.7493
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
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+ | 0.6192 | 1.0 | 200 | 0.5706 | 0.7180 | 0.7176 | 0.7163 |
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+ | 0.5346 | 2.0 | 400 | 0.5218 | 0.7503 | 0.7507 | 0.7493 |
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  ### Framework versions
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