lst20-baseline-new
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: 0.1359
- Precision: 0.8427
- Recall: 0.6944
- F1: 0.7614
- Accuracy: 0.9474
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: 1e-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 | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.1354 | 1.0 | 1274 | 0.1384 | 0.8232 | 0.6967 | 0.7547 | 0.9453 |
| 0.1392 | 2.0 | 2548 | 0.1396 | 0.8570 | 0.6681 | 0.7508 | 0.9464 |
| 0.1325 | 3.0 | 3822 | 0.1352 | 0.8148 | 0.7212 | 0.7651 | 0.9465 |
| 0.1266 | 4.0 | 5096 | 0.1366 | 0.8536 | 0.6746 | 0.7536 | 0.9467 |
| 0.1195 | 5.0 | 6370 | 0.1359 | 0.8427 | 0.6944 | 0.7614 | 0.9474 |
Framework versions
- Transformers 4.38.1
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2
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