---
base_model: dmis-lab/biobert-v1.1
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: biobert
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# biobert

This model is a fine-tuned version of [dmis-lab/biobert-v1.1](https://huggingface.co./dmis-lab/biobert-v1.1) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4906
- Accuracy: 0.9444

## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 256
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| No log        | 1.0   | 791   | 0.2279          | 0.9384   |
| 0.1997        | 2.0   | 1582  | 0.3086          | 0.9326   |
| 0.0772        | 3.0   | 2373  | 0.3142          | 0.9305   |
| 0.0504        | 4.0   | 3164  | 0.3149          | 0.9417   |
| 0.0504        | 5.0   | 3955  | 0.3344          | 0.9414   |
| 0.0367        | 6.0   | 4746  | 0.3333          | 0.9430   |
| 0.0245        | 7.0   | 5537  | 0.3671          | 0.9409   |
| 0.0204        | 8.0   | 6328  | 0.4249          | 0.9395   |
| 0.0134        | 9.0   | 7119  | 0.3557          | 0.9456   |
| 0.0134        | 10.0  | 7910  | 0.4586          | 0.9384   |
| 0.0109        | 11.0  | 8701  | 0.5423          | 0.9374   |
| 0.0087        | 12.0  | 9492  | 0.4680          | 0.9458   |
| 0.0052        | 13.0  | 10283 | 0.4594          | 0.9458   |
| 0.0071        | 14.0  | 11074 | 0.5178          | 0.9389   |
| 0.0071        | 15.0  | 11865 | 0.4706          | 0.9421   |
| 0.0056        | 16.0  | 12656 | 0.4917          | 0.9435   |
| 0.0034        | 17.0  | 13447 | 0.4678          | 0.9447   |
| 0.0026        | 18.0  | 14238 | 0.4793          | 0.9447   |
| 0.0023        | 19.0  | 15029 | 0.4869          | 0.9458   |
| 0.0023        | 20.0  | 15820 | 0.4906          | 0.9444   |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.2.2+cu118
- Datasets 2.18.0
- Tokenizers 0.15.2