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 QNLI
+      name: glue
       type: glue
       config: qnli
       split: validation
@@ -22,7 +20,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.5053999633900788
+      value: 0.5215083287570932
 ---
 
 <!-- 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. -->
 
 # add_BERT_no_pretrain_qnli
 
-This model is a fine-tuned version of [](https://huggingface.co/) on the GLUE QNLI 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: 0.6930
-- Accuracy: 0.5054
+- Loss: 0.6922
+- Accuracy: 0.5215
 
 ## 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
@@ -60,23 +58,25 @@ 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 |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 0.7205        | 1.0   | 819  | 0.6930          | 0.5054   |
-| 0.6935        | 2.0   | 1638 | 0.6931          | 0.5054   |
-| 0.6932        | 3.0   | 2457 | 0.6931          | 0.5054   |
-| 0.6932        | 4.0   | 3276 | 0.6932          | 0.4946   |
-| 0.6932        | 5.0   | 4095 | 0.6931          | 0.5054   |
-| 0.6935        | 6.0   | 4914 | 0.6933          | 0.5054   |
+| 0.7079        | 1.0   | 819  | 0.7210          | 0.5054   |
+| 0.6952        | 2.0   | 1638 | 0.6912          | 0.4946   |
+| 0.6922        | 3.0   | 2457 | 0.6905          | 0.5279   |
+| 0.6918        | 4.0   | 3276 | 0.6899          | 0.5288   |
+| 0.6922        | 5.0   | 4095 | 0.6922          | 0.5153   |
+| 0.6933        | 6.0   | 4914 | 0.6926          | 0.5127   |
+| 0.6931        | 7.0   | 5733 | 0.6952          | 0.4946   |
+| 0.6933        | 8.0   | 6552 | 0.6928          | 0.5113   |
+| 0.693         | 9.0   | 7371 | 0.6922          | 0.5215   |
 
 
 ### Framework versions
 
-- Transformers 4.29.2
+- Transformers 4.30.2
 - Pytorch 1.14.0a0+410ce96
 - Datasets 2.12.0
 - Tokenizers 0.13.3