metadata
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: []
BioBERT-full-finetuned-ner-pablo
This model is a fine-tuned version of 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