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: 0.0319
- Accuracy: 0.9918
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 | 122 | 0.8579 | 0.8574 |
| No log | 2.0 | 244 | 0.3430 | 0.9645 |
| No log | 3.0 | 366 | 0.1552 | 0.9810 |
| No log | 4.0 | 488 | 0.0981 | 0.9840 |
| 0.6956 | 5.0 | 610 | 0.0636 | 0.9887 |
| 0.6956 | 6.0 | 732 | 0.0499 | 0.9892 |
| 0.6956 | 7.0 | 854 | 0.0398 | 0.9907 |
| 0.6956 | 8.0 | 976 | 0.0346 | 0.9918 |
| 0.0742 | 9.0 | 1098 | 0.0321 | 0.9918 |
| 0.0742 | 10.0 | 1220 | 0.0319 | 0.9918 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0