update model card README.md

README.md

@@ -1,6 +1,4 @@
 ---
-language:
-- en
 tags:
 - generated_from_trainer
 datasets:
@@ -15,7 +13,7 @@ model-index:
       name: Text Classification
       type: text-classification
     dataset:
-      name: GLUE MRPC
+      name: glue
       type: glue
       config: mrpc
       split: validation
@@ -26,7 +24,7 @@ model-index:
       value: 0.6838235294117647
     - name: F1
       type: f1
-      value: 0.8122270742358079
+      value: 0.7867768595041322
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -34,12 +32,12 @@ should probably proofread and complete it, then remove this comment. -->
 
 # hBERTv2_new_no_pretrain_mrpc
 
-This model is a fine-tuned version of [](https://huggingface.co/) on the GLUE MRPC 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: 0.6242
+- Loss: 1.1249
 - Accuracy: 0.6838
-- F1: 0.8122
-- Combined Score: 0.7480
+- F1: 0.7868
+- Combined Score: 0.7353
 
 ## Model description
 
@@ -58,7 +56,7 @@ 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
@@ -66,23 +64,23 @@ 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 | F1     | Combined Score |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
-| 1.2542        | 1.0   | 29   | 0.6242          | 0.6838   | 0.8122 | 0.7480         |
-| 0.6656        | 2.0   | 58   | 0.6247          | 0.6838   | 0.8122 | 0.7480         |
-| 0.648         | 3.0   | 87   | 0.6309          | 0.6838   | 0.8122 | 0.7480         |
-| 0.6448        | 4.0   | 116  | 0.6373          | 0.6838   | 0.8122 | 0.7480         |
-| 0.6423        | 5.0   | 145  | 0.6279          | 0.6838   | 0.8122 | 0.7480         |
-| 0.6323        | 6.0   | 174  | 0.6351          | 0.6838   | 0.8122 | 0.7480         |
+| 0.6685        | 1.0   | 29   | 0.6107          | 0.6838   | 0.8122 | 0.7480         |
+| 0.6337        | 2.0   | 58   | 0.5914          | 0.6838   | 0.7896 | 0.7367         |
+| 0.529         | 3.0   | 87   | 0.6385          | 0.6642   | 0.7705 | 0.7174         |
+| 0.4182        | 4.0   | 116  | 0.6619          | 0.6985   | 0.8051 | 0.7518         |
+| 0.3095        | 5.0   | 145  | 1.0040          | 0.6471   | 0.7568 | 0.7019         |
+| 0.2219        | 6.0   | 174  | 0.9458          | 0.6225   | 0.7094 | 0.6660         |
+| 0.1813        | 7.0   | 203  | 1.1249          | 0.6838   | 0.7868 | 0.7353         |
 
 
 ### Framework versions
 
-- Transformers 4.29.2
+- Transformers 4.30.2
 - Pytorch 1.14.0a0+410ce96
 - Datasets 2.12.0
 - Tokenizers 0.13.3