metadata
base_model: vinai/phobert-base-v2
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: PhoBERT-train-aug_insert_BERT
results: []
PhoBERT-train-aug_insert_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: 1.1962
- Accuracy: 0.72
- F1: 0.7303
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 |
|---|---|---|---|---|---|
| 0.8879 | 1.0 | 87 | 0.7145 | 0.68 | 0.6453 |
| 0.586 | 2.0 | 174 | 0.6479 | 0.72 | 0.7265 |
| 0.3982 | 3.0 | 261 | 0.7353 | 0.72 | 0.7292 |
| 0.2815 | 4.0 | 348 | 0.8297 | 0.71 | 0.7152 |
| 0.2042 | 5.0 | 435 | 0.9852 | 0.71 | 0.7197 |
| 0.1438 | 6.0 | 522 | 1.0917 | 0.71 | 0.7198 |
| 0.1327 | 7.0 | 609 | 1.1657 | 0.72 | 0.7303 |
| 0.1016 | 8.0 | 696 | 1.1962 | 0.72 | 0.7303 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3