update model card README.md

README.md

@@ -1,6 +1,4 @@
 ---
-language:
-- en
 tags:
 - generated_from_trainer
 datasets:
@@ -14,7 +12,7 @@ model-index:
       name: Text Classification
       type: text-classification
     dataset:
-      name: GLUE WNLI
+      name: glue
       type: glue
       config: wnli
       split: validation
@@ -22,7 +20,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.5633802816901409
+      value: 0.352112676056338
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -30,10 +28,10 @@ should probably proofread and complete it, then remove this comment. -->
 
 # hBERTv2_new_no_pretrain_wnli
 
-This model is a fine-tuned version of [](https://huggingface.co/) on the GLUE WNLI dataset.
+This model is a fine-tuned version of [](https://huggingface.co/) on the glue dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.6916
-- Accuracy: 0.5634
+- Loss: 0.6976
+- Accuracy: 0.3521
 
 ## Model description
 
@@ -52,7 +50,7 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 0.0005
+- learning_rate: 4e-05
 - train_batch_size: 128
 - eval_batch_size: 128
 - seed: 10
@@ -60,26 +58,31 @@ The following hyperparameters were used during training:
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - num_epochs: 50
-- mixed_precision_training: Native AMP
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 2.018         | 1.0   | 5    | 7.0853          | 0.4366   |
-| 2.2331        | 2.0   | 10   | 0.8570          | 0.4366   |
-| 0.7865        | 3.0   | 15   | 0.6971          | 0.4366   |
-| 0.7062        | 4.0   | 20   | 0.6916          | 0.5634   |
-| 0.7223        | 5.0   | 25   | 0.7215          | 0.4366   |
-| 0.7916        | 6.0   | 30   | 0.8004          | 0.5634   |
-| 0.7638        | 7.0   | 35   | 0.7273          | 0.4366   |
-| 0.7096        | 8.0   | 40   | 0.7280          | 0.4366   |
-| 0.7084        | 9.0   | 45   | 0.7077          | 0.4366   |
+| 0.9765        | 1.0   | 5    | 0.6952          | 0.4366   |
+| 0.723         | 2.0   | 10   | 0.6938          | 0.4648   |
+| 0.7209        | 3.0   | 15   | 0.6902          | 0.5634   |
+| 0.7183        | 4.0   | 20   | 0.7155          | 0.5634   |
+| 0.7155        | 5.0   | 25   | 0.6875          | 0.5634   |
+| 0.7027        | 6.0   | 30   | 0.6978          | 0.4366   |
+| 0.6966        | 7.0   | 35   | 0.7161          | 0.4366   |
+| 0.7077        | 8.0   | 40   | 0.6926          | 0.5634   |
+| 0.7048        | 9.0   | 45   | 0.7409          | 0.4366   |
+| 0.7386        | 10.0  | 50   | 0.6874          | 0.5634   |
+| 0.7104        | 11.0  | 55   | 0.6875          | 0.5634   |
+| 0.7061        | 12.0  | 60   | 0.7088          | 0.4366   |
+| 0.6951        | 13.0  | 65   | 0.7009          | 0.4507   |
+| 0.6995        | 14.0  | 70   | 0.7050          | 0.4366   |
+| 0.692         | 15.0  | 75   | 0.6976          | 0.3521   |
 
 
 ### Framework versions
 
-- Transformers 4.29.2
+- Transformers 4.30.2
 - Pytorch 1.14.0a0+410ce96
 - Datasets 2.12.0
 - Tokenizers 0.13.3