update model card README.md

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: medqa_fine_tuned_generic_bert
+  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. -->
+
+# medqa_fine_tuned_generic_bert
+
+This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.4239
+- Accuracy: 0.2869
+
+## 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: 1e-05
+- train_batch_size: 4
+- eval_batch_size: 4
+- seed: 42
+- gradient_accumulation_steps: 8
+- total_train_batch_size: 32
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 100
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| No log        | 1.0   | 318  | 1.3851          | 0.2594   |
+| 1.3896        | 2.0   | 636  | 1.3805          | 0.2807   |
+| 1.3896        | 3.0   | 954  | 1.3852          | 0.2948   |
+| 1.3629        | 4.0   | 1272 | 1.3996          | 0.2980   |
+| 1.3068        | 5.0   | 1590 | 1.4239          | 0.2869   |
+
+
+### Framework versions
+
+- Transformers 4.18.0
+- Pytorch 1.11.0
+- Datasets 2.3.2
+- Tokenizers 0.11.0