metadata
base_model: vinai/phobert-base-v2
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: PhoBERT-Final_Mixed-aug_replace_w2v
results: []
PhoBERT-Final_Mixed-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: 0.9771
- Accuracy: 0.73
- F1: 0.7251
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 |
|---|---|---|---|---|---|
| 0.9504 | 1.0 | 86 | 0.7392 | 0.65 | 0.6205 |
| 0.6517 | 2.0 | 172 | 0.7087 | 0.69 | 0.6783 |
| 0.4998 | 3.0 | 258 | 0.7396 | 0.69 | 0.6788 |
| 0.3663 | 4.0 | 344 | 0.7976 | 0.69 | 0.6714 |
| 0.2623 | 5.0 | 430 | 0.8181 | 0.72 | 0.7177 |
| 0.1751 | 6.0 | 516 | 0.8604 | 0.75 | 0.7498 |
| 0.1446 | 7.0 | 602 | 0.9600 | 0.72 | 0.7135 |
| 0.1061 | 8.0 | 688 | 0.9771 | 0.73 | 0.7251 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3