update model card README.md

README.md

@@ -3,6 +3,9 @@ license: apache-2.0
 tags:
 - generated_from_trainer
 metrics:
+- precision
+- recall
+- f1
 - accuracy
 model-index:
 - name: distilroberta-base
@@ -16,8 +19,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 2.2660
-- Accuracy: 0.7504
+- Loss: 1.6935
+- Precision: 0.7556
+- Recall: 0.7556
+- F1: 0.7556
+- Accuracy: 0.7556
 
 ## Model description
 
@@ -43,32 +49,16 @@ The following hyperparameters were used during training:
 - distributed_type: multi-GPU
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 20
+- num_epochs: 4
 
 ### Training results
 
-| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
-|:-------------:|:-----:|:-----:|:---------------:|:--------:|
-| 1.2373        | 1.0   | 2355  | 1.1927          | 0.6802   |
-| 0.9192        | 2.0   | 4710  | 1.0538          | 0.7118   |
-| 0.6782        | 3.0   | 7065  | 0.9921          | 0.7288   |
-| 0.5687        | 4.0   | 9420  | 1.0542          | 0.7421   |
-| 0.4598        | 5.0   | 11775 | 1.2043          | 0.7384   |
-| 0.3557        | 6.0   | 14130 | 1.2833          | 0.7459   |
-| 0.3126        | 7.0   | 16485 | 1.4286          | 0.7459   |
-| 0.2541        | 8.0   | 18840 | 1.5076          | 0.7419   |
-| 0.1948        | 9.0   | 21195 | 1.6771          | 0.7371   |
-| 0.1576        | 10.0  | 23550 | 1.8419          | 0.7429   |
-| 0.1071        | 11.0  | 25905 | 1.9164          | 0.7467   |
-| 0.0977        | 12.0  | 28260 | 1.9773          | 0.7466   |
-| 0.0652        | 13.0  | 30615 | 2.0582          | 0.7486   |
-| 0.0752        | 14.0  | 32970 | 2.1108          | 0.7482   |
-| 0.0594        | 15.0  | 35325 | 2.1406          | 0.7492   |
-| 0.049         | 16.0  | 37680 | 2.1958          | 0.7485   |
-| 0.0267        | 17.0  | 40035 | 2.1858          | 0.7499   |
-| 0.0339        | 18.0  | 42390 | 2.2162          | 0.7503   |
-| 0.0137        | 19.0  | 44745 | 2.2699          | 0.7503   |
-| 0.0083        | 20.0  | 47100 | 2.2660          | 0.7504   |
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.2481        | 1.0   | 2355 | 1.5506          | 0.7409    | 0.7409 | 0.7409 | 0.7409   |
+| 0.3473        | 2.0   | 4710 | 1.5572          | 0.7428    | 0.7428 | 0.7428 | 0.7428   |
+| 0.2614        | 3.0   | 7065 | 1.6423          | 0.7539    | 0.7539 | 0.7539 | 0.7539   |
+| 0.1337        | 4.0   | 9420 | 1.6935          | 0.7556    | 0.7556 | 0.7556 | 0.7556   |
 
 
 ### Framework versions