fine-tune-wangchanberta-TOG-split-headline1
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: 1.1026
- Accuracy: 0.3876
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 |
|---|---|---|---|---|
| 1.0948 | 1.0 | 27 | 1.1114 | 0.3828 |
| 1.0961 | 2.0 | 54 | 1.1019 | 0.3828 |
| 1.0971 | 3.0 | 81 | 1.1144 | 0.3876 |
| 1.0908 | 4.0 | 108 | 1.0994 | 0.3876 |
| 1.0703 | 5.0 | 135 | 1.1032 | 0.3876 |
| 1.0711 | 6.0 | 162 | 1.1057 | 0.3828 |
| 1.0658 | 7.0 | 189 | 1.1026 | 0.3876 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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