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 MNLI
+      name: glue
       type: glue
       config: mnli
       split: validation_matched
@@ -22,7 +20,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.3522172497965826
+      value: 0.3273560876209883
 ---
 
 <!-- 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_mnli
 
-This model is a fine-tuned version of [](https://huggingface.co/) on the GLUE MNLI 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: 1.0982
-- Accuracy: 0.3522
+- Loss: 1.0986
+- Accuracy: 0.3274
 
 ## 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 +58,24 @@ 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 |
 |:-------------:|:-----:|:-----:|:---------------:|:--------:|
-| 1.1062        | 1.0   | 3068  | 1.0982          | 0.3545   |
-| 1.0987        | 2.0   | 6136  | 1.0986          | 0.3182   |
-| 1.0987        | 3.0   | 9204  | 1.0984          | 0.3274   |
-| 1.0986        | 4.0   | 12272 | 1.0982          | 0.3545   |
-| 1.0986        | 5.0   | 15340 | 1.0985          | 0.3545   |
-| 1.0986        | 6.0   | 18408 | 1.0984          | 0.3274   |
-| 1.0991        | 7.0   | 21476 | nan             | 0.3545   |
-| 1.1004        | 8.0   | 24544 | nan             | 0.3545   |
-| 1.1004        | 9.0   | 27612 | nan             | 0.3545   |
+| 1.1024        | 1.0   | 3068  | 1.0987          | 0.3182   |
+| 1.0997        | 2.0   | 6136  | 1.0986          | 0.3274   |
+| 1.0988        | 3.0   | 9204  | 1.0984          | 0.3545   |
+| 1.0987        | 4.0   | 12272 | 1.0986          | 0.3545   |
+| 1.0986        | 5.0   | 15340 | 1.0986          | 0.3545   |
+| 1.0987        | 6.0   | 18408 | 1.0986          | 0.3274   |
+| 1.0986        | 7.0   | 21476 | 1.0986          | 0.3274   |
+| 1.0986        | 8.0   | 24544 | 1.0986          | 0.3274   |
 
 
 ### Framework versions
 
-- Transformers 4.29.2
+- Transformers 4.30.2
 - Pytorch 1.14.0a0+410ce96
 - Datasets 2.12.0
 - Tokenizers 0.13.3