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fine-tuned-DatasetQAS-IDK-MRC-with-indobert-base-uncased-with-ITTL-with-freeze-LR-1e-05
This model is a fine-tuned version of indolem/indobert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.0641
- Exact Match: 65.1832
- F1: 70.4300
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 |
|---|---|---|---|---|---|
| 6.31 | 0.49 | 36 | 2.5380 | 50.0 | 50.0 |
| 3.7784 | 0.98 | 72 | 1.9420 | 49.8691 | 49.8691 |
| 2.192 | 1.48 | 108 | 1.8160 | 48.8220 | 50.2574 |
| 2.192 | 1.97 | 144 | 1.7327 | 48.8220 | 51.7831 |
| 1.9694 | 2.46 | 180 | 1.6016 | 48.9529 | 53.9425 |
| 1.7482 | 2.95 | 216 | 1.4743 | 54.4503 | 58.8011 |
| 1.5835 | 3.45 | 252 | 1.3414 | 57.4607 | 62.1340 |
| 1.5835 | 3.94 | 288 | 1.2884 | 58.2461 | 63.2663 |
| 1.4053 | 4.44 | 324 | 1.2001 | 60.4712 | 65.7454 |
| 1.2521 | 4.93 | 360 | 1.1738 | 60.7330 | 66.8019 |
| 1.2521 | 5.42 | 396 | 1.1551 | 60.8639 | 66.5188 |
| 1.1668 | 5.91 | 432 | 1.1128 | 63.8743 | 68.7421 |
| 1.097 | 6.41 | 468 | 1.0863 | 63.7435 | 69.1933 |
| 1.0251 | 6.9 | 504 | 1.0843 | 63.0890 | 68.4132 |
| 1.0251 | 7.4 | 540 | 1.0507 | 66.3613 | 71.1898 |
| 1.0031 | 7.89 | 576 | 1.0732 | 63.6126 | 68.7281 |
| 0.9616 | 8.38 | 612 | 1.0689 | 65.0524 | 70.2879 |
| 0.9616 | 8.87 | 648 | 1.0376 | 66.2304 | 71.2857 |
| 0.9322 | 9.37 | 684 | 1.0474 | 65.7068 | 70.7885 |
| 0.9227 | 9.86 | 720 | 1.0641 | 65.1832 | 70.4300 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu117
- Datasets 2.2.0
- Tokenizers 0.13.2
