---
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: 0.9429
- Recall: 0.9449
- F1: 0.9439
- Accuracy: 0.9737

## 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             | 0.9429    | 0.9449 | 0.9439 | 0.9737   |
| No log        | 2.0   | 162  | nan             | 0.9198    | 0.9470 | 0.9332 | 0.9615   |
| No log        | 3.0   | 243  | nan             | 0.9196    | 0.9449 | 0.9321 | 0.9653   |
| No log        | 4.0   | 324  | nan             | 0.9379    | 0.9280 | 0.9329 | 0.9719   |
| No log        | 5.0   | 405  | nan             | 0.9245    | 0.9343 | 0.9294 | 0.9690   |
| No log        | 6.0   | 486  | nan             | 0.9450    | 0.9470 | 0.9460 | 0.9747   |
| 0.0945        | 7.0   | 567  | nan             | 0.9446    | 0.9386 | 0.9416 | 0.9747   |
| 0.0945        | 8.0   | 648  | nan             | 0.9189    | 0.9364 | 0.9276 | 0.9672   |
| 0.0945        | 9.0   | 729  | nan             | 0.9245    | 0.9343 | 0.9294 | 0.9662   |
| 0.0945        | 10.0  | 810  | nan             | 0.9407    | 0.9407 | 0.9407 | 0.9728   |


### Framework versions

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