wangchanberta-fine-tune-fin-news-sentiment-th
This model is a fine-tuned version of airesearch/wangchanberta-base-att-spm-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6650
- Accuracy: 0.7276
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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.9665 | 1.0 | 3054 | 0.9572 | 0.5602 |
| 0.8734 | 2.0 | 6108 | 0.8522 | 0.6439 |
| 0.7737 | 3.0 | 9162 | 0.7577 | 0.6992 |
| 0.6607 | 4.0 | 12216 | 0.6860 | 0.7205 |
| 0.6068 | 5.0 | 15270 | 0.6650 | 0.7276 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
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