metadata
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: best_model
results: []
best_model
This model is a fine-tuned version of dmis-lab/biobert-base-cased-v1.1 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2832
- Accuracy: 0.8934
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: 5e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.3587 | 0.14 | 5000 | 0.3137 | 0.8834 |
| 0.3318 | 0.29 | 10000 | 0.3100 | 0.8831 |
| 0.3286 | 0.43 | 15000 | 0.3033 | 0.8864 |
| 0.3236 | 0.58 | 20000 | 0.3037 | 0.8862 |
| 0.3182 | 0.72 | 25000 | 0.2939 | 0.8876 |
| 0.3129 | 0.87 | 30000 | 0.2910 | 0.8885 |
| 0.3078 | 1.01 | 35000 | 0.2914 | 0.8887 |
| 0.2791 | 1.16 | 40000 | 0.2975 | 0.8874 |
| 0.2723 | 1.3 | 45000 | 0.2913 | 0.8906 |
| 0.2724 | 1.45 | 50000 | 0.2879 | 0.8904 |
| 0.27 | 1.59 | 55000 | 0.2874 | 0.8911 |
| 0.2681 | 1.74 | 60000 | 0.2848 | 0.8928 |
| 0.2672 | 1.88 | 65000 | 0.2832 | 0.8934 |
Framework versions
- Transformers 4.18.0.dev0
- Pytorch 1.10.0+cu111
- Datasets 1.18.4
- Tokenizers 0.11.6