---
library_name: transformers
base_model: dmis-lab/biobert-base-cased-v1.2
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: BioBERT-full-finetuned-ner-pablo
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# BioBERT-full-finetuned-ner-pablo

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: 0.1081
- Precision: 0.8057
- Recall: 0.8003
- F1: 0.8030
- Accuracy: 0.9743

## 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: 0.0002
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 0.9970 | 252  | 0.0943          | 0.7586    | 0.7859 | 0.7720 | 0.9732   |
| 0.1716        | 1.9980 | 505  | 0.0917          | 0.7950    | 0.7738 | 0.7843 | 0.9745   |
| 0.1716        | 2.9990 | 758  | 0.0886          | 0.7956    | 0.7925 | 0.7940 | 0.9742   |
| 0.0465        | 4.0    | 1011 | 0.0956          | 0.8055    | 0.7971 | 0.8013 | 0.9743   |
| 0.0465        | 4.9852 | 1260 | 0.1081          | 0.8057    | 0.8003 | 0.8030 | 0.9743   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1