---
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: 0.1114
- Precision: 0.7951
- Recall: 0.7809
- F1: 0.7879
- Accuracy: 0.9690

## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1541        | 0.9998 | 2608 | 0.1456          | 0.6888    | 0.7147 | 0.7015 | 0.9601   |
| 0.1073        | 2.0    | 5217 | 0.1244          | 0.7397    | 0.7450 | 0.7423 | 0.9645   |
| 0.0744        | 2.9994 | 7824 | 0.1114          | 0.7951    | 0.7809 | 0.7879 | 0.9690   |


### Framework versions

- Transformers 4.44.0
- Pytorch 2.4.0+cu124
- Datasets 2.21.0
- Tokenizers 0.19.1