metadata
base_model: vinai/phobert-base-v2
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: PhoBERT-Final_Mixed-aug_insert_tfidf
results: []
PhoBERT-Final_Mixed-aug_insert_tfidf
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: 1.2673
- Accuracy: 0.73
- F1: 0.7262
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 |
|---|---|---|---|---|---|
| 0.894 | 1.0 | 88 | 0.7277 | 0.66 | 0.6187 |
| 0.5738 | 2.0 | 176 | 0.7561 | 0.7 | 0.6957 |
| 0.3647 | 3.0 | 264 | 0.8054 | 0.72 | 0.7149 |
| 0.2496 | 4.0 | 352 | 1.0288 | 0.69 | 0.6842 |
| 0.1633 | 5.0 | 440 | 1.1435 | 0.7 | 0.6943 |
| 0.1162 | 6.0 | 528 | 1.1985 | 0.72 | 0.7157 |
| 0.0909 | 7.0 | 616 | 1.2491 | 0.73 | 0.7262 |
| 0.0722 | 8.0 | 704 | 1.2673 | 0.73 | 0.7262 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3