metadata
base_model: vinai/phobert-base-v2
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: model
results: []
model
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: 0.2895
- Accuracy: 0.9434
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: 5e-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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 93 | 1.1467 | 0.7871 |
| No log | 2.0 | 186 | 0.5867 | 0.9057 |
| No log | 3.0 | 279 | 0.3947 | 0.9272 |
| No log | 4.0 | 372 | 0.3269 | 0.9407 |
| No log | 5.0 | 465 | 0.3065 | 0.9407 |
| 0.7171 | 6.0 | 558 | 0.2895 | 0.9434 |
| 0.7171 | 7.0 | 651 | 0.2980 | 0.9407 |
| 0.7171 | 8.0 | 744 | 0.3061 | 0.9407 |
| 0.7171 | 9.0 | 837 | 0.3153 | 0.9407 |
| 0.7171 | 10.0 | 930 | 0.3177 | 0.9407 |
Framework versions
- Transformers 4.36.0
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0