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---
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-2024-11-25-T16-48-24
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-2024-11-25-T16-48-24
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: 0.7763
- Accuracy: 0.8095
- F1: 0.8138
## 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- 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: 5
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|
| 1.3838 | 0.9739 | 14 | 1.0207 | 0.6905 | 0.6764 |
| 1.086 | 1.9478 | 28 | 0.9525 | 0.6190 | 0.6189 |
| 0.6655 | 2.9913 | 43 | 0.7763 | 0.8095 | 0.8138 |
| 0.5349 | 3.9652 | 57 | 0.8631 | 0.7381 | 0.7368 |
| 0.3138 | 4.8696 | 70 | 0.8401 | 0.7857 | 0.7854 |
### Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3