metadata
base_model: dmis-lab/biobert-base-cased-v1.2
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: devicebert-base-cased-v1.0
results: []
devicebert-base-cased-v1.0
This model is a fine-tuned version of dmis-lab/biobert-base-cased-v1.2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: nan
- Precision: 0.6816
- Recall: 0.6691
- F1: 0.6753
- Accuracy: 0.8547
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: 1e-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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 101 | nan | 0.5981 | 0.5740 | 0.5858 | 0.8131 |
| No log | 2.0 | 202 | nan | 0.6673 | 0.6197 | 0.6427 | 0.8424 |
| No log | 3.0 | 303 | nan | 0.6926 | 0.6673 | 0.6797 | 0.8498 |
| No log | 4.0 | 404 | nan | 0.686 | 0.6271 | 0.6552 | 0.8473 |
| 0.3891 | 5.0 | 505 | nan | 0.6853 | 0.6490 | 0.6667 | 0.8539 |
| 0.3891 | 6.0 | 606 | nan | 0.6857 | 0.7020 | 0.6938 | 0.8563 |
| 0.3891 | 7.0 | 707 | nan | 0.6900 | 0.6673 | 0.6784 | 0.8580 |
| 0.3891 | 8.0 | 808 | nan | 0.6795 | 0.6782 | 0.6789 | 0.8514 |
| 0.3891 | 9.0 | 909 | nan | 0.6906 | 0.6691 | 0.6797 | 0.8571 |
| 0.1315 | 10.0 | 1010 | nan | 0.6816 | 0.6691 | 0.6753 | 0.8547 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1