metadata
base_model: dmis-lab/biobert-base-cased-v1.1
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: cer_model-i
results: []
cer_model-i
This model is a fine-tuned version of dmis-lab/biobert-base-cased-v1.1 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4254
- Precision: 0.9224
- Recall: 0.8589
- F1: 0.8895
- Accuracy: 0.9318
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.2
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.0212 | 1.0 | 4841 | 0.3474 | 0.9107 | 0.8663 | 0.8879 | 0.9305 |
| 0.0029 | 2.0 | 9682 | 0.3771 | 0.9206 | 0.8603 | 0.8894 | 0.9322 |
| 0.0008 | 3.0 | 14523 | 0.4254 | 0.9224 | 0.8589 | 0.8895 | 0.9318 |
Framework versions
- Transformers 4.37.0
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.1