metadata
base_model: dmis-lab/biobert-v1.1
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: biobert-finetuned-ner
results: []
biobert-finetuned-ner
This model is a fine-tuned version of dmis-lab/biobert-v1.1 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4144
- Precision: 0.6250
- Recall: 0.6815
- F1: 0.6520
- Accuracy: 0.8601
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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 305 | 0.4106 | 0.6036 | 0.6678 | 0.6340 | 0.8556 |
| 0.4536 | 2.0 | 610 | 0.3975 | 0.6211 | 0.6825 | 0.6503 | 0.8601 |
| 0.4536 | 3.0 | 915 | 0.4144 | 0.6250 | 0.6815 | 0.6520 | 0.8601 |
Framework versions
- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1