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fine-tuned-DatasetQAS-TYDI-QA-ID-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: 1.3132
- Exact Match: 53.2628
- F1: 68.3641
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 |
|---|---|---|---|---|---|
| 6.3129 | 0.5 | 19 | 3.9006 | 5.6437 | 16.4748 |
| 6.3129 | 1.0 | 38 | 2.8272 | 17.1076 | 30.0839 |
| 3.8917 | 1.5 | 57 | 2.4681 | 18.8713 | 32.8962 |
| 3.8917 | 2.0 | 76 | 2.2891 | 25.3968 | 38.0874 |
| 3.8917 | 2.5 | 95 | 2.1835 | 26.9841 | 39.5053 |
| 2.3963 | 3.0 | 114 | 2.0885 | 28.5714 | 42.0243 |
| 2.3963 | 3.5 | 133 | 1.9971 | 32.4515 | 45.4085 |
| 2.112 | 4.0 | 152 | 1.9124 | 34.3915 | 48.2893 |
| 2.112 | 4.5 | 171 | 1.8358 | 37.0370 | 50.6492 |
| 2.112 | 5.0 | 190 | 1.7545 | 40.7407 | 54.7031 |
| 1.8205 | 5.5 | 209 | 1.6432 | 44.4444 | 58.2669 |
| 1.8205 | 6.0 | 228 | 1.5589 | 46.9136 | 60.8052 |
| 1.8205 | 6.5 | 247 | 1.4861 | 48.1481 | 62.5185 |
| 1.573 | 7.0 | 266 | 1.4381 | 49.7354 | 64.1985 |
| 1.573 | 7.5 | 285 | 1.3944 | 51.6755 | 66.0223 |
| 1.387 | 8.0 | 304 | 1.3534 | 53.2628 | 67.6841 |
| 1.387 | 8.5 | 323 | 1.3384 | 53.0864 | 67.8619 |
| 1.387 | 9.0 | 342 | 1.3344 | 52.9101 | 68.0618 |
| 1.2998 | 9.5 | 361 | 1.3182 | 53.2628 | 68.4149 |
| 1.2998 | 10.0 | 380 | 1.3132 | 53.2628 | 68.3641 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu117
- Datasets 2.2.0
- Tokenizers 0.13.2
