update model card README.md

README.md

@@ -22,7 +22,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.6526104417670683
+      value: 0.6514056224899598
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -32,8 +32,8 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the xnli dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.8165
-- Accuracy: 0.6526
+- Loss: 0.8516
+- Accuracy: 0.6514
 
 ## Model description
 
@@ -53,8 +53,8 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 1.5e-05
-- train_batch_size: 192
-- eval_batch_size: 192
+- train_batch_size: 128
+- eval_batch_size: 128
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
@@ -65,16 +65,16 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step  | Validation Loss | Accuracy |
 |:-------------:|:-----:|:-----:|:---------------:|:--------:|
-| 1.0253        | 1.0   | 2046  | 0.8330          | 0.6382   |
-| 0.9659        | 2.0   | 4092  | 0.8105          | 0.6530   |
-| 0.9445        | 3.0   | 6138  | 0.7978          | 0.6558   |
-| 0.9254        | 4.0   | 8184  | 0.7791          | 0.6594   |
-| 0.9075        | 5.0   | 10230 | 0.7792          | 0.6614   |
-| 0.8892        | 6.0   | 12276 | 0.7812          | 0.6554   |
-| 0.8728        | 7.0   | 14322 | 0.7762          | 0.6538   |
-| 0.8565        | 8.0   | 16368 | 0.8019          | 0.6494   |
-| 0.8427        | 9.0   | 18414 | 0.8067          | 0.6558   |
-| 0.8332        | 10.0  | 20460 | 0.8165          | 0.6526   |
+| 1.0129        | 1.0   | 3068  | 0.8285          | 0.6357   |
+| 0.9628        | 2.0   | 6136  | 0.8120          | 0.6470   |
+| 0.9407        | 3.0   | 9204  | 0.7934          | 0.6643   |
+| 0.9205        | 4.0   | 12272 | 0.7802          | 0.6546   |
+| 0.9001        | 5.0   | 15340 | 0.7820          | 0.6594   |
+| 0.8791        | 6.0   | 18408 | 0.8046          | 0.6502   |
+| 0.8593        | 7.0   | 21476 | 0.7950          | 0.6627   |
+| 0.8404        | 8.0   | 24544 | 0.8231          | 0.6514   |
+| 0.8242        | 9.0   | 27612 | 0.8376          | 0.6558   |
+| 0.8118        | 10.0  | 30680 | 0.8516          | 0.6514   |
 
 
 ### Framework versions