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fine-tuned-DatasetQAS-IDK-MRC-with-indobert-large-p2-without-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: 1.2405
- Exact Match: 51.9634
- F1: 58.9740
- Precision: 59.9859
- Recall: 63.1982
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 |
|---|---|---|---|---|---|---|---|
| 3.4722 | 0.49 | 73 | 2.4443 | 9.6859 | 19.2463 | 17.0064 | 36.4763 |
| 2.4592 | 0.99 | 146 | 1.8046 | 26.4398 | 35.0647 | 34.6691 | 45.8354 |
| 1.6685 | 1.49 | 219 | 1.3839 | 42.0157 | 49.2034 | 49.8767 | 57.6434 |
| 1.4304 | 1.98 | 292 | 1.3337 | 42.4084 | 50.0207 | 51.1139 | 56.5044 |
| 1.074 | 2.48 | 365 | 1.2313 | 49.6073 | 56.5977 | 57.6801 | 61.6748 |
| 1.0704 | 2.97 | 438 | 1.1639 | 52.0942 | 58.7433 | 59.7956 | 64.2988 |
| 0.8772 | 3.47 | 511 | 1.1926 | 53.6649 | 61.0220 | 61.4728 | 66.7934 |
| 0.8887 | 3.97 | 584 | 1.2182 | 51.0471 | 58.0581 | 59.1383 | 62.9618 |
| 0.7141 | 4.47 | 657 | 1.1726 | 54.3194 | 61.1547 | 62.0500 | 66.0011 |
| 0.7238 | 4.96 | 730 | 1.2156 | 54.0576 | 60.4732 | 61.7775 | 64.5058 |
| 0.5929 | 5.46 | 803 | 1.3549 | 52.7487 | 59.0996 | 60.3930 | 62.9242 |
| 0.6201 | 5.95 | 876 | 1.2405 | 51.9634 | 58.9740 | 59.9859 | 63.1982 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu117
- Datasets 2.2.0
- Tokenizers 0.13.2
