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RewardModelSmallerQuestionWithTwoLabelsLengthJustified

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RajuEEE/RewardModelSmallerQuestionWithTwoLabelsLengthJustified

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  1. README.md +9 -8
  2. model.safetensors +1 -1
  3. runs/Dec06_22-23-37_6bd7a536c428/events.out.tfevents.1701901434.6bd7a536c428.1395.0 +3 -0
  4. runs/Dec06_22-23-37_6bd7a536c428/events.out.tfevents.1701902121.6bd7a536c428.1395.1 +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: 0.5248
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- - F1: 0.7695
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- - Roc Auc: 0.7695
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- - Accuracy: 0.7658
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  ## Model description
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@@ -46,15 +46,16 @@ The following hyperparameters were used during training:
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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- - num_epochs: 3
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
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- | 0.686 | 1.0 | 198 | 0.5967 | 0.6865 | 0.6859 | 0.6840 |
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- | 0.5425 | 2.0 | 396 | 0.5038 | 0.7681 | 0.7677 | 0.7658 |
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- | 0.4951 | 3.0 | 594 | 0.5248 | 0.7695 | 0.7695 | 0.7658 |
 
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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: 0.4883
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+ - F1: 0.7873
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+ - Roc Auc: 0.7877
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+ - Accuracy: 0.7857
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  ## Model description
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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+ - num_epochs: 4
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
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+ | 0.6771 | 1.0 | 185 | 0.6633 | 0.5913 | 0.5913 | 0.5913 |
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+ | 0.6024 | 2.0 | 370 | 0.5766 | 0.7276 | 0.7282 | 0.7262 |
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+ | 0.5358 | 3.0 | 555 | 0.4883 | 0.7873 | 0.7877 | 0.7857 |
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+ | 0.4456 | 4.0 | 740 | 0.5200 | 0.7778 | 0.7778 | 0.7738 |
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  ### Framework versions
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