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fine-tuned-DatasetQAS-TYDI-QA-ID-with-indobert-base-uncased-with-ITTL-without-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: 1.2784
- Exact Match: 53.4392
- F1: 68.7244
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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 32
- 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 |
|---|---|---|---|---|---|
| 6.1764 | 0.5 | 19 | 3.7674 | 10.4056 | 23.6332 |
| 6.1764 | 1.0 | 38 | 2.7985 | 19.5767 | 32.6228 |
| 3.8085 | 1.49 | 57 | 2.4169 | 22.0459 | 35.4084 |
| 3.8085 | 1.99 | 76 | 2.2811 | 25.9259 | 38.3963 |
| 3.8085 | 2.49 | 95 | 2.1607 | 28.0423 | 40.3901 |
| 2.3932 | 2.99 | 114 | 2.0488 | 31.0406 | 43.7059 |
| 2.3932 | 3.49 | 133 | 1.9787 | 34.3915 | 46.3655 |
| 2.0772 | 3.98 | 152 | 1.8661 | 37.2134 | 49.1483 |
| 2.0772 | 4.48 | 171 | 1.7893 | 40.2116 | 52.4989 |
| 2.0772 | 4.98 | 190 | 1.7014 | 41.9753 | 54.9197 |
| 1.7645 | 5.48 | 209 | 1.5940 | 44.2681 | 58.2134 |
| 1.7645 | 5.98 | 228 | 1.4972 | 46.2081 | 60.4997 |
| 1.7645 | 6.47 | 247 | 1.4214 | 48.8536 | 63.4371 |
| 1.5035 | 6.97 | 266 | 1.3676 | 50.6173 | 65.4663 |
| 1.5035 | 7.47 | 285 | 1.3357 | 52.2046 | 67.1759 |
| 1.3206 | 7.97 | 304 | 1.3149 | 53.0864 | 68.0698 |
| 1.3206 | 8.47 | 323 | 1.2988 | 53.4392 | 68.3971 |
| 1.3206 | 8.96 | 342 | 1.2894 | 53.6155 | 68.8897 |
| 1.2472 | 9.46 | 361 | 1.2820 | 53.4392 | 68.5835 |
| 1.2472 | 9.96 | 380 | 1.2784 | 53.4392 | 68.7244 |
Framework versions
- Transformers 4.27.4
- Pytorch 1.13.1+cu117
- Datasets 2.2.0
- Tokenizers 0.13.2
