metadata
library_name: transformers
base_model: airesearch/wangchanberta-base-att-spm-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
model-index:
- name: fined-tune-thai-sentiment
results: []
fined-tune-thai-sentiment
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: 0.3544
- Accuracy: 0.9282
- F1-score: 0.9278
- Precision: 0.9276
- Recall: 0.9282
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 181
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1-score | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.8746 | 1.0 | 91 | 0.8613 | 0.6133 | 0.4662 | 0.3761 | 0.6133 |
| 0.8086 | 2.0 | 182 | 0.8758 | 0.5746 | 0.4955 | 0.4768 | 0.5746 |
| 0.9223 | 3.0 | 273 | 0.9218 | 0.6133 | 0.4662 | 0.3761 | 0.6133 |
| 0.8561 | 4.0 | 364 | 0.7430 | 0.6630 | 0.5899 | 0.6325 | 0.6630 |
| 0.6694 | 5.0 | 455 | 0.5335 | 0.7845 | 0.7507 | 0.7289 | 0.7845 |
| 0.5792 | 6.0 | 546 | 0.4365 | 0.8287 | 0.8227 | 0.8239 | 0.8287 |
| 0.3046 | 7.0 | 637 | 0.4033 | 0.8840 | 0.8834 | 0.8930 | 0.8840 |
| 0.2004 | 8.0 | 728 | 0.3544 | 0.9282 | 0.9278 | 0.9276 | 0.9282 |
| 0.1443 | 9.0 | 819 | 0.4025 | 0.9171 | 0.9180 | 0.9199 | 0.9171 |
| 0.0765 | 10.0 | 910 | 0.4116 | 0.9227 | 0.9238 | 0.9269 | 0.9227 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1