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fine-tuned-DatasetQAS-IDK-MRC-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: 1.2364
- Exact Match: 50.2618
- F1: 57.5214
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 |
|---|---|---|---|---|---|
| 6.151 | 0.49 | 36 | 2.7223 | 32.5916 | 35.4445 |
| 3.5424 | 0.98 | 72 | 2.0664 | 24.2147 | 31.0371 |
| 2.2082 | 1.48 | 108 | 1.7388 | 28.0105 | 37.2690 |
| 2.2082 | 1.97 | 144 | 1.4742 | 37.0419 | 45.3625 |
| 1.6932 | 2.46 | 180 | 1.3193 | 43.3246 | 51.1270 |
| 1.3154 | 2.95 | 216 | 1.2731 | 46.2042 | 53.5503 |
| 1.1699 | 3.45 | 252 | 1.2327 | 46.4660 | 53.5656 |
| 1.1699 | 3.94 | 288 | 1.1998 | 48.1675 | 55.1907 |
| 1.0749 | 4.44 | 324 | 1.1949 | 51.0471 | 57.7164 |
| 0.9423 | 4.93 | 360 | 1.1855 | 50.6545 | 57.3903 |
| 0.9423 | 5.42 | 396 | 1.1931 | 51.3089 | 58.5981 |
| 0.9036 | 5.91 | 432 | 1.2045 | 50.3927 | 57.7468 |
| 0.8324 | 6.41 | 468 | 1.2363 | 48.2984 | 55.5302 |
| 0.7846 | 6.9 | 504 | 1.2364 | 50.2618 | 57.5214 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu117
- Datasets 2.2.0
- Tokenizers 0.13.2
