update model card README.md

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: biolinkbert-base-medqa-usmle-MPNet-context
+  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. -->
+
+# biolinkbert-base-medqa-usmle-MPNet-context
+
+This model is a fine-tuned version of [michiyasunaga/BioLinkBERT-base](https://huggingface.co/michiyasunaga/BioLinkBERT-base) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.4506
+- Accuracy: 0.3936
+
+## 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
+- num_epochs: 8
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| No log        | 1.0   | 318  | 1.3518          | 0.3354   |
+| 1.3648        | 2.0   | 636  | 1.3308          | 0.3684   |
+| 1.3648        | 3.0   | 954  | 1.3267          | 0.3943   |
+| 1.2711        | 4.0   | 1272 | 1.3455          | 0.3865   |
+| 1.1769        | 5.0   | 1590 | 1.3739          | 0.3943   |
+| 1.1769        | 6.0   | 1908 | 1.3960          | 0.4069   |
+| 1.0815        | 7.0   | 2226 | 1.4320          | 0.3959   |
+| 1.0092        | 8.0   | 2544 | 1.4506          | 0.3936   |
+
+
+### Framework versions
+
+- Transformers 4.27.2
+- Pytorch 1.13.1+cu116
+- Datasets 2.10.1
+- Tokenizers 0.13.2