SudiptoPramanik/Mail_RewardModel_RobertaBase

README.md

@@ -19,10 +19,10 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.0064
-- F1: 1.0
-- Roc Auc: 1.0
-- Accuracy: 1.0
+- Loss: 0.1713
+- F1: 0.9670
+- Roc Auc: 0.9670
+- Accuracy: 0.9670
 
 ## Model description
 
@@ -45,24 +45,24 @@ The following hyperparameters were used during training:
 - train_batch_size: 16
 - eval_batch_size: 16
 - seed: 42
-- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
 - lr_scheduler_type: linear
 - num_epochs: 5
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | F1  | Roc Auc | Accuracy |
-|:-------------:|:-----:|:----:|:---------------:|:---:|:-------:|:--------:|
-| No log        | 1.0   | 63   | 0.0064          | 1.0 | 1.0     | 1.0      |
-| 0.1495        | 2.0   | 126  | 0.0028          | 1.0 | 1.0     | 1.0      |
-| 0.1495        | 3.0   | 189  | 0.0020          | 1.0 | 1.0     | 1.0      |
-| 0.0035        | 4.0   | 252  | 0.0016          | 1.0 | 1.0     | 1.0      |
-| 0.0024        | 5.0   | 315  | 0.0015          | 1.0 | 1.0     | 1.0      |
+| Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
+| No log        | 1.0   | 63   | 0.1713          | 0.9670 | 0.9670  | 0.9670   |
+| 0.1703        | 2.0   | 126  | 0.1866          | 0.9670 | 0.9670  | 0.9670   |
+| 0.1703        | 3.0   | 189  | 0.1876          | 0.9670 | 0.9670  | 0.9670   |
+| 0.0284        | 4.0   | 252  | 0.1917          | 0.9670 | 0.9670  | 0.9670   |
+| 0.0283        | 5.0   | 315  | 0.1924          | 0.9670 | 0.9670  | 0.9670   |
 
 
 ### Framework versions
 
 - Transformers 4.47.1
-- Pytorch 2.5.1+cu121
+- Pytorch 2.5.1+cu124
 - Datasets 3.2.0
 - Tokenizers 0.21.0

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training_args.bin

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