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fine-tuned-DatasetQAS-Squad-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: 1.7872
- Exact Match: 46.1526
- F1: 62.7803
- Precision: 64.0856
- Recall: 68.4802
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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 16
Training results
| Training Loss | Epoch | Step | Validation Loss | Exact Match | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 1.7454 | 0.5 | 1024 | 1.8066 | 39.3967 | 56.5617 | 57.9148 | 64.1074 |
| 1.585 | 1.0 | 2048 | 1.6658 | 42.3134 | 59.7125 | 61.0679 | 67.5221 |
| 1.391 | 1.5 | 3072 | 1.6455 | 43.6763 | 60.8729 | 62.4910 | 67.0820 |
| 1.3937 | 2.0 | 4096 | 1.6125 | 44.9892 | 62.0278 | 63.7779 | 67.7429 |
| 1.1464 | 2.5 | 5120 | 1.6549 | 44.9892 | 61.6232 | 62.7582 | 68.2833 |
| 1.1611 | 3.0 | 6144 | 1.6369 | 45.5958 | 62.8723 | 64.0481 | 68.8869 |
| 1.0415 | 3.5 | 7168 | 1.7452 | 45.7038 | 62.3827 | 63.6067 | 68.6888 |
| 0.9972 | 4.0 | 8192 | 1.7086 | 45.7288 | 62.5511 | 64.1824 | 67.9289 |
| 0.9043 | 4.5 | 9216 | 1.7872 | 46.1526 | 62.7803 | 64.0856 | 68.4802 |
Framework versions
- Transformers 4.27.0
- Pytorch 2.0.0+cu117
- Datasets 2.2.0
- Tokenizers 0.13.2
