metadata
base_model: vinai/phobert-base-v2
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: PhoBERT-Final_Mixed-aug_insert_BERT-2
results: []
PhoBERT-Final_Mixed-aug_insert_BERT-2
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: 1.0732
- Accuracy: 0.7
- F1: 0.7004
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: 40
- 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 |
|---|---|---|---|---|---|
| 0.944 | 1.0 | 88 | 0.8199 | 0.66 | 0.6427 |
| 0.6694 | 2.0 | 176 | 0.7223 | 0.7 | 0.7007 |
| 0.4933 | 3.0 | 264 | 0.7039 | 0.73 | 0.7321 |
| 0.3532 | 4.0 | 352 | 0.7914 | 0.73 | 0.7297 |
| 0.2619 | 5.0 | 440 | 0.8506 | 0.72 | 0.7176 |
| 0.1807 | 6.0 | 528 | 0.9830 | 0.71 | 0.7090 |
| 0.1365 | 7.0 | 616 | 1.0183 | 0.7 | 0.7016 |
| 0.1035 | 8.0 | 704 | 1.0732 | 0.7 | 0.7004 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3