---
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