metadata
base_model: vinai/phobert-base-v2
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: PhoBERT-Final_Mixed-aug_insert_tfidf-1
results: []
PhoBERT-Final_Mixed-aug_insert_tfidf-1
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: 1.3291
- Accuracy: 0.7
- F1: 0.7078
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: 41
- 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 |
|---|---|---|---|---|---|
| 0.8766 | 1.0 | 87 | 0.6882 | 0.73 | 0.7304 |
| 0.5162 | 2.0 | 174 | 0.6549 | 0.74 | 0.7429 |
| 0.3162 | 3.0 | 261 | 0.7789 | 0.72 | 0.7270 |
| 0.2051 | 4.0 | 348 | 0.9573 | 0.67 | 0.6755 |
| 0.1572 | 5.0 | 435 | 1.1190 | 0.69 | 0.7008 |
| 0.1101 | 6.0 | 522 | 1.3021 | 0.69 | 0.6986 |
| 0.0763 | 7.0 | 609 | 1.3159 | 0.7 | 0.7078 |
| 0.0788 | 8.0 | 696 | 1.3291 | 0.7 | 0.7078 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3