metadata
base_model: vinai/phobert-base-v2
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: model
results: []
model
This model is a fine-tuned version of vinai/phobert-base-v2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1123
- Accuracy: 0.9762
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: 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 | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 95 | 1.0711 | 0.8386 |
| No log | 2.0 | 190 | 0.5620 | 0.9286 |
| No log | 3.0 | 285 | 0.2919 | 0.9471 |
| No log | 4.0 | 380 | 0.1902 | 0.9550 |
| No log | 5.0 | 475 | 0.1740 | 0.9656 |
| 0.6945 | 6.0 | 570 | 0.1462 | 0.9709 |
| 0.6945 | 7.0 | 665 | 0.1347 | 0.9735 |
| 0.6945 | 8.0 | 760 | 0.1146 | 0.9762 |
| 0.6945 | 9.0 | 855 | 0.1154 | 0.9762 |
| 0.6945 | 10.0 | 950 | 0.1123 | 0.9762 |
Framework versions
- Transformers 4.36.0
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0