---
base_model: dmis-lab/biobert-base-cased-v1.2
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: devicebert-base-cased-v1.0
  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. -->

# devicebert-base-cased-v1.0

This model is a fine-tuned version of [dmis-lab/biobert-base-cased-v1.2](https://huggingface.co/dmis-lab/biobert-base-cased-v1.2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: nan
- Precision: 0.8950
- Recall: 0.9045
- F1: 0.8997
- Accuracy: 0.9577

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 81   | nan             | 0.8950    | 0.9045 | 0.8997 | 0.9577   |
| No log        | 2.0   | 162  | nan             | 0.8815    | 0.8217 | 0.8505 | 0.9408   |
| No log        | 3.0   | 243  | nan             | 0.8950    | 0.9045 | 0.8997 | 0.9596   |
| No log        | 4.0   | 324  | nan             | 0.8730    | 0.8025 | 0.8363 | 0.9390   |
| No log        | 5.0   | 405  | nan             | 0.9048    | 0.8875 | 0.8960 | 0.9587   |
| No log        | 6.0   | 486  | nan             | 0.9030    | 0.9087 | 0.9058 | 0.9568   |
| 0.136         | 7.0   | 567  | nan             | 0.8961    | 0.8790 | 0.8875 | 0.9531   |
| 0.136         | 8.0   | 648  | nan             | 0.8894    | 0.9045 | 0.8968 | 0.9549   |
| 0.136         | 9.0   | 729  | nan             | 0.8921    | 0.8599 | 0.8757 | 0.9512   |
| 0.136         | 10.0  | 810  | nan             | 0.9079    | 0.9002 | 0.9041 | 0.9606   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1