---
library_name: transformers
base_model: dmis-lab/biobert-v1.1
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: biobert-v1.1-finetuned-medmcqa-2024-11-30-T10-40-37
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# biobert-v1.1-finetuned-medmcqa-2024-11-30-T10-40-37

This model is a fine-tuned version of [dmis-lab/biobert-v1.1](https://huggingface.co./dmis-lab/biobert-v1.1) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9611
- Accuracy: 0.5735
- F1: 0.5746

## 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: 0.000159
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|
| 0.741         | 0.9993 | 571  | 0.9445          | 0.5420   | 0.5435 |
| 0.5108        | 1.9989 | 1142 | 0.9611          | 0.5735   | 0.5746 |
| 0.4273        | 2.9985 | 1713 | 1.0719          | 0.5694   | 0.5702 |


### Framework versions

- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3