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fine-tuned-DatasetQAS-TYDI-QA-ID-with-indobert-large-p2-with-ITTL-without-freeze-LR-1e-05
This model is a fine-tuned version of indobenchmark/indobert-large-p2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.1732
- Exact Match: 60.2113
- F1: 73.6360
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Exact Match | F1 |
|---|---|---|---|---|---|
| 6.3258 | 0.5 | 19 | 3.5172 | 10.7394 | 21.8207 |
| 6.3258 | 0.99 | 38 | 2.7869 | 18.3099 | 28.8508 |
| 3.5421 | 1.5 | 57 | 2.3403 | 23.4155 | 35.8166 |
| 3.5421 | 1.99 | 76 | 2.0205 | 30.2817 | 42.8646 |
| 3.5421 | 2.5 | 95 | 1.7202 | 38.7324 | 51.9337 |
| 2.0678 | 2.99 | 114 | 1.4839 | 44.5423 | 59.5131 |
| 2.0678 | 3.5 | 133 | 1.3583 | 50.5282 | 64.3127 |
| 1.4302 | 3.99 | 152 | 1.2706 | 52.2887 | 66.7363 |
| 1.4302 | 4.5 | 171 | 1.2389 | 55.1056 | 69.3028 |
| 1.4302 | 4.99 | 190 | 1.2065 | 55.8099 | 69.9972 |
| 1.0965 | 5.5 | 209 | 1.1840 | 56.8662 | 70.7353 |
| 1.0965 | 5.99 | 228 | 1.1887 | 58.4507 | 71.9049 |
| 1.0965 | 6.5 | 247 | 1.1797 | 58.6268 | 72.5495 |
| 0.9291 | 6.99 | 266 | 1.1685 | 59.6831 | 73.0495 |
| 0.9291 | 7.5 | 285 | 1.1713 | 59.1549 | 73.1298 |
| 0.839 | 7.99 | 304 | 1.1721 | 60.0352 | 73.0300 |
| 0.839 | 8.5 | 323 | 1.1735 | 60.0352 | 73.5065 |
| 0.839 | 8.99 | 342 | 1.1725 | 60.2113 | 73.6033 |
| 0.7854 | 9.5 | 361 | 1.1738 | 60.2113 | 73.6432 |
| 0.7854 | 9.99 | 380 | 1.1732 | 60.2113 | 73.6360 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu117
- Datasets 2.2.0
- Tokenizers 0.13.2
