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 QQP
+      name: glue
       type: glue
       config: qqp
       split: validation
@@ -23,10 +21,10 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.6318327974276527
+      value: 0.8216423447934702
     - name: F1
       type: f1
-      value: 0.0
+      value: 0.7376005239983989
 ---
 
 <!-- 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_qqp
 
-This model is a fine-tuned version of [](https://huggingface.co/) on the GLUE QQP 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: 0.6579
-- Accuracy: 0.6318
-- F1: 0.0
-- Combined Score: 0.3159
+- Loss: 0.5113
+- Accuracy: 0.8216
+- F1: 0.7376
+- Combined Score: 0.7796
 
 ## 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
@@ -66,27 +64,22 @@ 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 |
-|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---:|:--------------:|
-| 0.6669        | 1.0   | 2843  | 0.6595          | 0.6318   | 0.0 | 0.3159         |
-| 0.6591        | 2.0   | 5686  | 0.6587          | 0.6318   | 0.0 | 0.3159         |
-| 0.6589        | 3.0   | 8529  | 0.6582          | 0.6318   | 0.0 | 0.3159         |
-| 0.6587        | 4.0   | 11372 | 0.6580          | 0.6318   | 0.0 | 0.3159         |
-| 0.6586        | 5.0   | 14215 | 0.6579          | 0.6318   | 0.0 | 0.3159         |
-| 0.6586        | 6.0   | 17058 | 0.6580          | 0.6318   | 0.0 | 0.3159         |
-| 0.6586        | 7.0   | 19901 | 0.6580          | 0.6318   | 0.0 | 0.3159         |
-| 0.6586        | 8.0   | 22744 | 0.6579          | 0.6318   | 0.0 | 0.3159         |
-| 0.6586        | 9.0   | 25587 | 0.6580          | 0.6318   | 0.0 | 0.3159         |
-| 0.6586        | 10.0  | 28430 | 0.6580          | 0.6318   | 0.0 | 0.3159         |
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     | Combined Score |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:--------------:|
+| 0.5037        | 1.0   | 2843  | 0.4537          | 0.7856   | 0.6931 | 0.7393         |
+| 0.4066        | 2.0   | 5686  | 0.4549          | 0.7946   | 0.6758 | 0.7352         |
+| 0.3367        | 3.0   | 8529  | 0.4630          | 0.7950   | 0.6650 | 0.7300         |
+| 0.2876        | 4.0   | 11372 | 0.5279          | 0.8180   | 0.7598 | 0.7889         |
+| 0.2498        | 5.0   | 14215 | 0.4857          | 0.8217   | 0.7650 | 0.7933         |
+| 0.2371        | 6.0   | 17058 | 0.5113          | 0.8216   | 0.7376 | 0.7796         |
 
 
 ### Framework versions
 
-- Transformers 4.29.2
+- Transformers 4.30.2
 - Pytorch 1.14.0a0+410ce96
 - Datasets 2.12.0
 - Tokenizers 0.13.3