metadata
base_model: vinai/phobert-base-v2
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: PhoBERT-Final_Mixed-aug_replace_w2v-2
results: []
PhoBERT-Final_Mixed-aug_replace_w2v-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: 1.2163
- Accuracy: 0.66
- F1: 0.6693
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 |
|---|---|---|---|---|---|
| 0.923 | 1.0 | 84 | 0.7740 | 0.63 | 0.6027 |
| 0.6028 | 2.0 | 168 | 0.6747 | 0.69 | 0.6920 |
| 0.4285 | 3.0 | 252 | 0.7204 | 0.71 | 0.7139 |
| 0.3282 | 4.0 | 336 | 0.7519 | 0.69 | 0.7000 |
| 0.2309 | 5.0 | 420 | 0.8302 | 0.69 | 0.6970 |
| 0.1562 | 6.0 | 504 | 1.0497 | 0.66 | 0.6696 |
| 0.1158 | 7.0 | 588 | 1.1606 | 0.67 | 0.6771 |
| 0.0992 | 8.0 | 672 | 1.2163 | 0.66 | 0.6693 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3