update model card README.md

README.md

@@ -21,7 +21,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.4528301886792453
+      value: 0.4371069182389937
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -31,8 +31,8 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [gchhablani/fnet-base-finetuned-wnli](https://huggingface.co/gchhablani/fnet-base-finetuned-wnli) on the glue dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.7032
-- Accuracy: 0.4528
+- Loss: 0.7290
+- Accuracy: 0.4371
 
 ## Model description
 
@@ -52,8 +52,8 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 2e-05
-- train_batch_size: 16
-- eval_batch_size: 16
+- train_batch_size: 80
+- eval_batch_size: 80
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
@@ -63,8 +63,8 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| No log        | 1.0   | 20   | 0.7039          | 0.4623   |
-| No log        | 2.0   | 40   | 0.7032          | 0.4528   |
+| No log        | 1.0   | 4    | 0.7182          | 0.4308   |
+| No log        | 2.0   | 8    | 0.7290          | 0.4371   |
 
 
 ### Framework versions