metadata
base_model: vinai/phobert-base-v2
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: PhoBERT-train-aug_replace_w2v
results: []
PhoBERT-train-aug_replace_w2v
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: 1.1784
- Accuracy: 0.69
- F1: 0.6954
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 |
|---|---|---|---|---|---|
| 0.91 | 1.0 | 84 | 0.7509 | 0.69 | 0.6518 |
| 0.6192 | 2.0 | 168 | 0.6326 | 0.76 | 0.7635 |
| 0.4457 | 3.0 | 252 | 0.6374 | 0.74 | 0.7464 |
| 0.3088 | 4.0 | 336 | 0.7942 | 0.71 | 0.7157 |
| 0.2422 | 5.0 | 420 | 0.8893 | 0.71 | 0.7165 |
| 0.1631 | 6.0 | 504 | 1.0951 | 0.7 | 0.7036 |
| 0.1408 | 7.0 | 588 | 1.1012 | 0.69 | 0.6982 |
| 0.1057 | 8.0 | 672 | 1.1784 | 0.69 | 0.6954 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3