fine-tune-wangchanberta-stock-thai
This model is a fine-tuned version of airesearch/wangchanberta-base-att-spm-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5882
- Accuracy: 0.7334
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: 32
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 7
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.6786 | 1.0 | 485 | 0.5857 | 0.7334 |
0.6504 | 2.0 | 970 | 0.5811 | 0.7334 |
0.6493 | 3.0 | 1455 | 0.5850 | 0.7334 |
0.6472 | 4.0 | 1940 | 0.5853 | 0.7334 |
0.6443 | 5.0 | 2425 | 0.5848 | 0.7334 |
0.6449 | 6.0 | 2910 | 0.5876 | 0.7334 |
0.6437 | 7.0 | 3395 | 0.5882 | 0.7334 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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