qa_en_ms_model_v2
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: 0.8644
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: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.365 | 1.0 | 1047 | 1.0902 |
| 1.1222 | 2.0 | 2094 | 0.9886 |
| 1.0316 | 3.0 | 3141 | 0.9431 |
| 0.9622 | 4.0 | 4188 | 0.9205 |
| 0.9098 | 5.0 | 5235 | 0.8920 |
| 0.8769 | 6.0 | 6282 | 0.8792 |
| 0.8612 | 7.0 | 7329 | 0.8734 |
| 0.8527 | 8.0 | 8376 | 0.8667 |
| 0.8248 | 9.0 | 9423 | 0.8638 |
| 0.8285 | 10.0 | 10470 | 0.8644 |
Framework versions
- Transformers 4.52.4
- Pytorch 2.5.1+cu121
- Datasets 3.6.0
- Tokenizers 0.21.1
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