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 RTE
+      name: glue
       type: glue
       config: rte
       split: validation
@@ -22,7 +20,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.5270758122743683
+      value: 0.4729241877256318
 ---
 
 <!-- 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_rte
 
-This model is a fine-tuned version of [](https://huggingface.co/) on the GLUE RTE 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: 0.6917
-- Accuracy: 0.5271
+- Loss: 0.7269
+- Accuracy: 0.4729
 
 ## 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
@@ -60,29 +58,22 @@ 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 |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 1.9285        | 1.0   | 20   | 0.7302          | 0.5271   |
-| 0.7216        | 2.0   | 40   | 0.6919          | 0.5271   |
-| 0.7641        | 3.0   | 60   | 0.7044          | 0.4729   |
-| 0.7002        | 4.0   | 80   | 0.7476          | 0.4729   |
-| 0.7253        | 5.0   | 100  | 0.7224          | 0.5271   |
-| 0.7081        | 6.0   | 120  | 0.7066          | 0.4729   |
-| 0.6975        | 7.0   | 140  | 0.6917          | 0.5271   |
-| 0.698         | 8.0   | 160  | 0.6933          | 0.4729   |
-| 0.6967        | 9.0   | 180  | 0.6917          | 0.5271   |
-| 0.6926        | 10.0  | 200  | 0.7154          | 0.4729   |
-| 0.696         | 11.0  | 220  | 0.6964          | 0.4729   |
-| 0.694         | 12.0  | 240  | 0.6917          | 0.5271   |
+| 0.7731        | 1.0   | 20   | 0.6942          | 0.5271   |
+| 0.709         | 2.0   | 40   | 0.7189          | 0.4729   |
+| 0.7188        | 3.0   | 60   | 0.6948          | 0.4729   |
+| 0.7007        | 4.0   | 80   | 0.6980          | 0.4729   |
+| 0.7048        | 5.0   | 100  | 0.7018          | 0.5271   |
+| 0.7065        | 6.0   | 120  | 0.7269          | 0.4729   |
 
 
 ### Framework versions
 
-- Transformers 4.29.2
+- Transformers 4.30.2
 - Pytorch 1.14.0a0+410ce96
 - Datasets 2.12.0
 - Tokenizers 0.13.3