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: 0.43661971830985913
+      value: 0.5633802816901409
 ---
 
 <!-- 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_pretrain_wnli
 
-This model is a fine-tuned version of [gokuls/bert_12_layer_model_v2_complete_training_new](https://huggingface.co/gokuls/bert_12_layer_model_v2_complete_training_new) on the GLUE WNLI dataset.
+This model is a fine-tuned version of [gokuls/bert_12_layer_model_v2_complete_training_new](https://huggingface.co/gokuls/bert_12_layer_model_v2_complete_training_new) on the glue dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.9151
-- Accuracy: 0.4366
+- Loss: 0.6963
+- Accuracy: 0.5634
 
 ## 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
@@ -65,13 +63,21 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 8.8479        | 1.0   | 5    | 1.9492          | 0.4366   |
-| 9.5465        | 2.0   | 10   | 0.9151          | 0.4366   |
-| 8.6319        | 3.0   | 15   | 2.4510          | 0.5634   |
-| 9.7722        | 4.0   | 20   | 4.1092          | 0.5634   |
-| 10.479        | 5.0   | 25   | 4.9877          | 0.5634   |
-| 10.4548       | 6.0   | 30   | 5.4947          | 0.5634   |
-| 10.5408       | 7.0   | 35   | 4.8345          | 0.5634   |
+| 0.8646        | 1.0   | 5    | 0.7422          | 0.4366   |
+| 0.7094        | 2.0   | 10   | 0.7290          | 0.4366   |
+| 0.7047        | 3.0   | 15   | 0.7053          | 0.5634   |
+| 0.7203        | 4.0   | 20   | 0.7022          | 0.4366   |
+| 0.7           | 5.0   | 25   | 0.6977          | 0.4366   |
+| 0.7098        | 6.0   | 30   | 0.6885          | 0.5634   |
+| 0.695         | 7.0   | 35   | 0.7045          | 0.4366   |
+| 0.7053        | 8.0   | 40   | 0.6858          | 0.5634   |
+| 0.7095        | 9.0   | 45   | 0.7070          | 0.4366   |
+| 0.7012        | 10.0  | 50   | 0.6857          | 0.5634   |
+| 0.6995        | 11.0  | 55   | 0.6969          | 0.4507   |
+| 0.6913        | 12.0  | 60   | 0.6875          | 0.5634   |
+| 0.6963        | 13.0  | 65   | 0.6959          | 0.4789   |
+| 0.6996        | 14.0  | 70   | 0.7190          | 0.4366   |
+| 0.6957        | 15.0  | 75   | 0.6963          | 0.5634   |
 
 
 ### Framework versions