update model card README.md

README.md

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+---
+language:
+- en
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- glue
+metrics:
+- accuracy
+model-index:
+- name: bert-base-cased-finetuned-wnli
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: GLUE WNLI
+      type: glue
+      args: wnli
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.4647887323943662
+---
+
+<!-- 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. -->
+
+# bert-base-cased-finetuned-wnli
+
+This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the GLUE WNLI dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6996
+- Accuracy: 0.4648
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 2e-05
+- train_batch_size: 16
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 5.0
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.7299        | 1.0   | 40   | 0.6923          | 0.5634   |
+| 0.6982        | 2.0   | 80   | 0.7027          | 0.3803   |
+| 0.6972        | 3.0   | 120  | 0.7005          | 0.4507   |
+| 0.6992        | 4.0   | 160  | 0.6977          | 0.5352   |
+| 0.699         | 5.0   | 200  | 0.6996          | 0.4648   |
+
+
+### Framework versions
+
+- Transformers 4.11.0.dev0
+- Pytorch 1.9.0
+- Datasets 1.12.1
+- Tokenizers 0.10.3