metadata
base_model: vinai/phobert-base-v2
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: PhoBERT-Final_Mixed-aug_replace_BERT
results: []
PhoBERT-Final_Mixed-aug_replace_BERT
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: 0.8746
- Accuracy: 0.74
- F1: 0.7344
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: 42
- 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 |
|---|---|---|---|---|---|
| 0.972 | 1.0 | 88 | 0.7868 | 0.62 | 0.5610 |
| 0.7723 | 2.0 | 176 | 0.7641 | 0.7 | 0.6953 |
| 0.6104 | 3.0 | 264 | 0.7508 | 0.7 | 0.6967 |
| 0.5009 | 4.0 | 352 | 0.7608 | 0.68 | 0.6727 |
| 0.377 | 5.0 | 440 | 0.7301 | 0.72 | 0.7217 |
| 0.3016 | 6.0 | 528 | 0.8430 | 0.73 | 0.7241 |
| 0.2305 | 7.0 | 616 | 0.8625 | 0.74 | 0.7346 |
| 0.2054 | 8.0 | 704 | 0.8746 | 0.74 | 0.7344 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3