add model

README.md

@@ -16,7 +16,7 @@ model_index:
     metric:
       name: Accuracy
       type: accuracy
-      value: 0.9277522935779816
+      value: 0.930045871559633
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -26,8 +26,8 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the glue dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.3194
-- Accuracy: 0.9278
+- Loss: 0.2485
+- Accuracy: 0.9300
 
 ## Model description
 
@@ -47,8 +47,8 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 2e-05
-- train_batch_size: 16
-- eval_batch_size: 16
+- train_batch_size: 32
+- eval_batch_size: 32
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
@@ -58,16 +58,16 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step  | Validation Loss | Accuracy |
 |:-------------:|:-----:|:-----:|:---------------:|:--------:|
-| 0.1803        | 1.0   | 4210  | 0.3157          | 0.9117   |
-| 0.1249        | 2.0   | 8420  | 0.3171          | 0.9209   |
-| 0.0803        | 3.0   | 12630 | 0.3355          | 0.9232   |
-| 0.0699        | 4.0   | 16840 | 0.3194          | 0.9278   |
-| 0.0371        | 5.0   | 21050 | 0.3965          | 0.9266   |
+| 0.1662        | 1.0   | 2105  | 0.2485          | 0.9300   |
+| 0.1102        | 2.0   | 4210  | 0.2777          | 0.9266   |
+| 0.0835        | 3.0   | 6315  | 0.3368          | 0.9232   |
+| 0.0529        | 4.0   | 8420  | 0.3310          | 0.9255   |
+| 0.035         | 5.0   | 10525 | 0.3855          | 0.9278   |
 
 
 ### Framework versions
 
-- Transformers 4.9.2
-- Pytorch 1.9.0+cu102
+- Transformers 4.9.1
+- Pytorch 1.8.1
 - Datasets 1.11.0
-- Tokenizers 0.10.3
+- Tokenizers 0.10.1

config.json

@@ -20,7 +20,7 @@
   "pretrained_model_name_or_path": "bert-base-uncased",
   "problem_type": "single_label_classification",
   "torch_dtype": "float32",
-  "transformers_version": "4.9.2",
+  "transformers_version": "4.9.1",
   "type_vocab_size": 2,
   "use_cache": true,
   "vocab_size": 30522

pytorch_model.bin

@@ -1,3 +1,3 @@
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+size 438024457

training_args.bin

@@ -1,3 +1,3 @@
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 size 2671