qa_en_ms_model_v3
This model is a fine-tuned version of mesolitica/finetune-qa-t5-small-standard-bahasa-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.8296
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: 24
- eval_batch_size: 24
- 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
- num_epochs: 20
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.3752 | 1.0 | 1047 | 1.0868 |
| 1.1233 | 2.0 | 2094 | 0.9799 |
| 1.0295 | 3.0 | 3141 | 0.9326 |
| 0.9485 | 4.0 | 4188 | 0.9051 |
| 0.8883 | 5.0 | 5235 | 0.8748 |
| 0.8485 | 6.0 | 6282 | 0.8605 |
| 0.8243 | 7.0 | 7329 | 0.8485 |
| 0.7977 | 8.0 | 8376 | 0.8417 |
| 0.7597 | 9.0 | 9423 | 0.8286 |
| 0.7495 | 10.0 | 10470 | 0.8306 |
| 0.7211 | 11.0 | 11517 | 0.8255 |
| 0.7076 | 12.0 | 12564 | 0.8291 |
| 0.7012 | 13.0 | 13611 | 0.8350 |
| 0.6833 | 14.0 | 14658 | 0.8288 |
| 0.6687 | 15.0 | 15705 | 0.8230 |
| 0.6574 | 16.0 | 16752 | 0.8313 |
| 0.6342 | 17.0 | 17799 | 0.8239 |
| 0.6419 | 18.0 | 18846 | 0.8271 |
| 0.6451 | 19.0 | 19893 | 0.8302 |
| 0.6278 | 20.0 | 20940 | 0.8296 |
Framework versions
- Transformers 4.52.4
- Pytorch 2.5.1+cu121
- Datasets 3.6.0
- Tokenizers 0.21.1
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