metadata
base_model: vinai/phobert-base-v2
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: PhoBERT-Final_Mixed-aug_replace_BERT-2
results: []
PhoBERT-Final_Mixed-aug_replace_BERT-2
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: 0.9152
- Accuracy: 0.69
- F1: 0.6904
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: 40
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.9875 | 1.0 | 88 | 0.7870 | 0.66 | 0.6416 |
| 0.7566 | 2.0 | 176 | 0.7744 | 0.68 | 0.6746 |
| 0.6209 | 3.0 | 264 | 0.7497 | 0.69 | 0.6889 |
| 0.486 | 4.0 | 352 | 0.7477 | 0.71 | 0.7082 |
| 0.3713 | 5.0 | 440 | 0.7671 | 0.72 | 0.7198 |
| 0.2809 | 6.0 | 528 | 0.8839 | 0.69 | 0.6869 |
| 0.2235 | 7.0 | 616 | 0.8809 | 0.7 | 0.6989 |
| 0.1745 | 8.0 | 704 | 0.9152 | 0.69 | 0.6904 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3