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