anuj55
/

distilbert-base-uncased-finetuned-mrpc

@@ -17,9 +17,9 @@ should probably proofread and complete it, then remove this comment. -->
 This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 2.6836
-- Accuracy: 0.7109
-- F1: 0.3486
 ## Model description
@@ -48,24 +48,33 @@ The following hyperparameters were used during training:
 ### Training results
-| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
-|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
-| 0.0482        | 1.0   | 635  | 2.3706          | 0.6898   | 0.4369 |
-| 0.0413        | 2.0   | 1270 | 2.2979          | 0.6922   | 0.4137 |
-| 0.0689        | 3.0   | 1905 | 2.5452          | 0.6930   | 0.3483 |
-| 0.0445        | 4.0   | 2540 | 2.1120          | 0.6883   | 0.3427 |
-| 0.0657        | 5.0   | 3175 | 2.2432          | 0.7055   | 0.3256 |
-| 0.0522        | 6.0   | 3810 | 2.5130          | 0.6836   | 0.4239 |
-| 0.0355        | 7.0   | 4445 | 2.2756          | 0.7078   | 0.4101 |
-| 0.0272        | 8.0   | 5080 | 2.5587          | 0.6953   | 0.3229 |
-| 0.0272        | 9.0   | 5715 | 2.6836          | 0.7109   | 0.3486 |
-| 0.0209        | 10.0  | 6350 | 2.5399          | 0.6914   | 0.4537 |
-| 0.0221        | 11.0  | 6985 | 3.0262          | 0.6961   | 0.4254 |
 ### Framework versions
-- Transformers 4.28.0
-- Pytorch 2.0.0
-- Datasets 2.1.0
-- Tokenizers 0.13.3

 This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
 It achieves the following results on the evaluation set:
+- Loss: 0.5682
+- Accuracy: 0.7164
+- F1: 0.2022
 ## Model description
 ### Training results
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
+| 0.5789        | 1.0   | 635   | 0.5764          | 0.7055   | 0.0    |
+| 0.543         | 2.0   | 1270  | 0.5682          | 0.7164   | 0.2022 |
+| 0.4661        | 3.0   | 1905  | 0.6358          | 0.7164   | 0.2812 |
+| 0.2338        | 4.0   | 2540  | 0.9347          | 0.6844   | 0.4670 |
+| 0.1538        | 5.0   | 3175  | 1.3556          | 0.6758   | 0.4740 |
+| 0.1067        | 6.0   | 3810  | 1.6163          | 0.7016   | 0.3322 |
+| 0.0928        | 7.0   | 4445  | 2.0786          | 0.6984   | 0.3609 |
+| 0.0438        | 8.0   | 5080  | 2.1976          | 0.6945   | 0.4309 |
+| 0.0312        | 9.0   | 5715  | 2.1931          | 0.6969   | 0.4209 |
+| 0.0311        | 10.0  | 6350  | 2.4030          | 0.6883   | 0.4158 |
+| 0.0281        | 11.0  | 6985  | 2.3715          | 0.7148   | 0.3739 |
+| 0.0166        | 12.0  | 7620  | 2.6843          | 0.6984   | 0.3390 |
+| 0.0167        | 13.0  | 8255  | 2.7291          | 0.6922   | 0.3604 |
+| 0.0181        | 14.0  | 8890  | 2.7929          | 0.6906   | 0.3851 |
+| 0.0147        | 15.0  | 9525  | 2.8976          | 0.7117   | 0.3303 |
+| 0.0103        | 16.0  | 10160 | 3.0229          | 0.6859   | 0.3964 |
+| 0.0047        | 17.0  | 10795 | 3.0616          | 0.6836   | 0.3817 |
+| 0.0136        | 18.0  | 11430 | 3.0513          | 0.6875   | 0.3730 |
+| 0.005         | 19.0  | 12065 | 3.0634          | 0.6930   | 0.3732 |
+| 0.0042        | 20.0  | 12700 | 3.0611          | 0.7      | 0.3642 |
 ### Framework versions
+- Transformers 4.28.1
+- Pytorch 2.0.1+cu117
+- Datasets 1.18.4
+- Tokenizers 0.12.1