update model card README.md

README.md

@@ -1,23 +1,38 @@
 ---
 license: apache-2.0
 tags:
-- generated_from_keras_callback
+- generated_from_trainer
+datasets:
+- glue
+metrics:
+- accuracy
 model-index:
-- name: rwang5688/distilbert-base-uncased-finetuned-sst2
-  results: []
+- name: distilbert-base-uncased-finetuned-sst2
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: glue
+      type: glue
+      config: sst2
+      split: validation
+      args: sst2
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.911697247706422
 ---
 
-<!-- This model card has been generated automatically according to the information Keras had access to. You should
-probably proofread and complete it, then remove this comment. -->
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
 
-# rwang5688/distilbert-base-uncased-finetuned-sst2
+# distilbert-base-uncased-finetuned-sst2
 
-This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
+This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the glue dataset.
 It achieves the following results on the evaluation set:
-- Train Loss: 0.1064
-- Validation Loss: 0.2699
-- Train Accuracy: 0.8968
-- Epoch: 1
+- Loss: 0.3574
+- Accuracy: 0.9117
 
 ## Model description
 
@@ -36,20 +51,28 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- optimizer: {'name': 'Adam', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 21045, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
-- training_precision: float32
+- learning_rate: 2e-05
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 5
 
 ### Training results
 
-| Train Loss | Validation Loss | Train Accuracy | Epoch |
-|:----------:|:---------------:|:--------------:|:-----:|
-| 0.2119     | 0.2385          | 0.9037         | 0     |
-| 0.1064     | 0.2699          | 0.8968         | 1     |
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|
+| 0.1867        | 1.0   | 4210  | 0.3226          | 0.9071   |
+| 0.1277        | 2.0   | 8420  | 0.3630          | 0.9037   |
+| 0.1027        | 3.0   | 12630 | 0.3574          | 0.9117   |
+| 0.0659        | 4.0   | 16840 | 0.4427          | 0.9048   |
+| 0.0334        | 5.0   | 21050 | 0.4979          | 0.9083   |
 
 
 ### Framework versions
 
-- Transformers 4.21.1
-- TensorFlow 2.9.1
-- Datasets 2.4.0
-- Tokenizers 0.12.1
+- Transformers 4.27.1
+- Pytorch 2.0.0+cu117
+- Datasets 2.10.1
+- Tokenizers 0.13.2