---
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: biobert-base-cased-v1.2-finetuned-ner
  results: []
---

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# biobert-base-cased-v1.2-finetuned-ner

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: 0.2662
- Precision: 0.8204
- Recall: 0.8577
- F1: 0.8386
- Accuracy: 0.9521

## 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: 3e-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: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0189        | 1.0   | 680  | 0.2662          | 0.8204    | 0.8577 | 0.8386 | 0.9521   |
| 0.0141        | 2.0   | 1360 | 0.3010          | 0.8188    | 0.8407 | 0.8296 | 0.9491   |
| 0.0119        | 3.0   | 2040 | 0.3169          | 0.8316    | 0.8463 | 0.8389 | 0.9517   |
| 0.0101        | 4.0   | 2720 | 0.2845          | 0.8286    | 0.8588 | 0.8434 | 0.9541   |


### Framework versions

- Transformers 4.27.2
- Pytorch 1.13.0+cu117
- Datasets 2.7.1
- Tokenizers 0.13.2