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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-50pct-2024-11-30-T14-52-07
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. -->
# biobert-v1.1-finetuned-medmcqa-50pct-2024-11-30-T14-52-07
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: 1.3867
- Accuracy: 0.3055
- F1: 0.2373
## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|
| 1.3878 | 0.9998 | 2856 | 1.3867 | 0.3031 | 0.2439 |
| 1.3872 | 1.9996 | 5712 | 1.3867 | 0.2955 | 0.2435 |
| 1.3858 | 2.9995 | 8568 | 1.3867 | 0.3055 | 0.2373 |
### Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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