update model card README.md

README.md

@@ -20,7 +20,7 @@ model-index:
     metrics:
     - name: Rouge1
       type: rouge
-      value: 34.4566
+      value: 34.3503
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -30,11 +30,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [domenicrosati/t5-small-finetuned-contradiction](https://huggingface.co/domenicrosati/t5-small-finetuned-contradiction) on the snli dataset.
 It achieves the following results on the evaluation set:
-- Loss: 2.0953
-- Rouge1: 34.4566
-- Rouge2: 14.7585
-- Rougel: 32.7187
-- Rougelsum: 32.7372
+- Loss: 2.0662
+- Rouge1: 34.3503
+- Rouge2: 14.671
+- Rougel: 32.5398
+- Rougelsum: 32.5331
 
 ## Model description
 
@@ -59,17 +59,21 @@ The following hyperparameters were used during training:
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 4
+- num_epochs: 8
 - mixed_precision_training: Native AMP
 
 ### Training results
 
 | Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum |
 |:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
-| 2.0722        | 1.0   | 2863  | 2.1159          | 34.4508 | 14.7296 | 32.684  | 32.6938   |
-| 2.1261        | 2.0   | 5726  | 2.1038          | 34.4131 | 14.7231 | 32.6427 | 32.6554   |
-| 2.1192        | 3.0   | 8589  | 2.0975          | 34.491  | 14.6856 | 32.7155 | 32.7326   |
-| 2.1186        | 4.0   | 11452 | 2.0953          | 34.5066 | 14.7893 | 32.772  | 32.7931   |
+| 2.0071        | 1.0   | 2863  | 2.1018          | 34.4519 | 14.6277 | 32.6441 | 32.6415   |
+| 2.0704        | 2.0   | 5726  | 2.0897          | 34.4688 | 14.7508 | 32.6253 | 32.6227   |
+| 2.0738        | 3.0   | 8589  | 2.0808          | 34.4291 | 14.5548 | 32.6263 | 32.6384   |
+| 2.0788        | 4.0   | 11452 | 2.0744          | 34.6759 | 14.842  | 32.8169 | 32.823    |
+| 2.0781        | 5.0   | 14315 | 2.0714          | 34.4961 | 14.7307 | 32.6362 | 32.6378   |
+| 2.0687        | 6.0   | 17178 | 2.0674          | 34.6406 | 14.8359 | 32.8403 | 32.8423   |
+| 2.0627        | 7.0   | 20041 | 2.0671          | 34.526  | 14.6943 | 32.6919 | 32.694    |
+| 2.0585        | 8.0   | 22904 | 2.0662          | 34.4196 | 14.7107 | 32.607  | 32.6035   |
 
 
 ### Framework versions