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: 0.1946
- Accuracy: 0.9576
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 | 101 | 1.0266 | 0.8504 |
| No log | 2.0 | 202 | 0.4850 | 0.9451 |
| No log | 3.0 | 303 | 0.2802 | 0.9551 |
| No log | 4.0 | 404 | 0.2025 | 0.9576 |
| 0.6615 | 5.0 | 505 | 0.2072 | 0.9501 |
| 0.6615 | 6.0 | 606 | 0.2131 | 0.9426 |
| 0.6615 | 7.0 | 707 | 0.2189 | 0.9551 |
| 0.6615 | 8.0 | 808 | 0.1967 | 0.9576 |
| 0.6615 | 9.0 | 909 | 0.1958 | 0.9576 |
| 0.0705 | 10.0 | 1010 | 0.1946 | 0.9576 |
Framework versions
- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1