update model card README.md

README.md

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+---
+license: mit
+tags:
+- generated_from_trainer
+datasets:
+- glue
+metrics:
+- accuracy
+model-index:
+- name: roberta-base-qnli
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: glue
+      type: glue
+      args: qnli
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.9229361156873512
+---
+
+<!-- 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. -->
+
+# roberta-base-qnli
+
+This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the glue dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4277
+- Accuracy: 0.9229
+
+## 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
+- lr_scheduler_warmup_ratio: 0.06
+- num_epochs: 10.0
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|
+| 0.2986        | 1.0   | 6547  | 0.2215          | 0.9171   |
+| 0.243         | 2.0   | 13094 | 0.2321          | 0.9173   |
+| 0.2048        | 3.0   | 19641 | 0.2992          | 0.9246   |
+| 0.1629        | 4.0   | 26188 | 0.3538          | 0.9220   |
+| 0.1308        | 5.0   | 32735 | 0.3533          | 0.9209   |
+| 0.0846        | 6.0   | 39282 | 0.4277          | 0.9229   |
+
+
+### Framework versions
+
+- Transformers 4.20.0.dev0
+- Pytorch 1.11.0+cu113
+- Datasets 2.1.0
+- Tokenizers 0.12.1