update model card README.md

README.md

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+---
+license: apache-2.0
+base_model: bert-base-uncased
+tags:
+- generated_from_trainer
+datasets:
+- swag
+metrics:
+- accuracy
+model-index:
+- name: bert_base_swag_model
+  results: []
+---
+
+<!-- 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_swag_model
+
+This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the swag dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.0354
+- Accuracy: 0.7900
+
+## 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: 5e-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: 3
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|
+| 0.7647        | 1.0   | 4597  | 0.5830          | 0.7740   |
+| 0.387         | 2.0   | 9194  | 0.6383          | 0.7855   |
+| 0.147         | 3.0   | 13791 | 1.0354          | 0.7900   |
+
+
+### Framework versions
+
+- Transformers 4.31.0
+- Pytorch 2.0.0
+- Datasets 2.14.4
+- Tokenizers 0.13.3