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spellcorrector_2610_v16_canine-s
This model is a fine-tuned version of google/canine-s on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0974
- Precision: 0.9789
- Recall: 0.9829
- F1: 0.9809
- Accuracy: 0.9838
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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.252 | 1.0 | 976 | 0.1462 | 0.9386 | 0.9800 | 0.9589 | 0.9702 |
| 0.1463 | 2.0 | 1952 | 0.1256 | 0.9479 | 0.9794 | 0.9634 | 0.9721 |
| 0.1266 | 3.0 | 2928 | 0.1049 | 0.9578 | 0.9769 | 0.9673 | 0.9745 |
| 0.1081 | 4.0 | 3904 | 0.0938 | 0.9634 | 0.9787 | 0.9710 | 0.9772 |
| 0.0963 | 5.0 | 4880 | 0.0856 | 0.9663 | 0.9793 | 0.9727 | 0.9788 |
| 0.0863 | 6.0 | 5856 | 0.0838 | 0.9705 | 0.9759 | 0.9732 | 0.9786 |
| 0.077 | 7.0 | 6832 | 0.0804 | 0.9734 | 0.9757 | 0.9745 | 0.9797 |
| 0.0713 | 8.0 | 7808 | 0.0779 | 0.9726 | 0.9804 | 0.9765 | 0.9809 |
| 0.066 | 9.0 | 8784 | 0.0794 | 0.9749 | 0.9767 | 0.9758 | 0.9801 |
| 0.0602 | 10.0 | 9760 | 0.0748 | 0.9741 | 0.9823 | 0.9782 | 0.9821 |
| 0.0555 | 11.0 | 10736 | 0.0763 | 0.9750 | 0.9815 | 0.9782 | 0.9822 |
| 0.0512 | 12.0 | 11712 | 0.0764 | 0.9769 | 0.9800 | 0.9784 | 0.9823 |
| 0.048 | 13.0 | 12688 | 0.0767 | 0.9769 | 0.9822 | 0.9796 | 0.9832 |
| 0.0453 | 14.0 | 13664 | 0.0793 | 0.9767 | 0.9819 | 0.9793 | 0.9829 |
| 0.0412 | 15.0 | 14640 | 0.0809 | 0.9774 | 0.9822 | 0.9798 | 0.9832 |
| 0.0384 | 16.0 | 15616 | 0.0796 | 0.9765 | 0.9830 | 0.9798 | 0.9831 |
| 0.0364 | 17.0 | 16592 | 0.0830 | 0.9779 | 0.9825 | 0.9802 | 0.9833 |
| 0.0344 | 18.0 | 17568 | 0.0834 | 0.9779 | 0.9819 | 0.9799 | 0.9831 |
| 0.0307 | 19.0 | 18544 | 0.0857 | 0.9777 | 0.9823 | 0.9800 | 0.9832 |
| 0.0283 | 20.0 | 19520 | 0.0869 | 0.9776 | 0.9819 | 0.9797 | 0.9832 |
| 0.0269 | 21.0 | 20496 | 0.0885 | 0.9781 | 0.9822 | 0.9802 | 0.9833 |
| 0.0252 | 22.0 | 21472 | 0.0906 | 0.9784 | 0.9814 | 0.9799 | 0.9833 |
| 0.0229 | 23.0 | 22448 | 0.0932 | 0.9785 | 0.9820 | 0.9802 | 0.9833 |
| 0.0223 | 24.0 | 23424 | 0.0910 | 0.9785 | 0.9832 | 0.9809 | 0.9835 |
| 0.0209 | 25.0 | 24400 | 0.0936 | 0.9787 | 0.9824 | 0.9805 | 0.9836 |
| 0.0199 | 26.0 | 25376 | 0.0948 | 0.9791 | 0.9823 | 0.9807 | 0.9838 |
| 0.0189 | 27.0 | 26352 | 0.0961 | 0.9792 | 0.9828 | 0.9810 | 0.9838 |
| 0.0184 | 28.0 | 27328 | 0.0965 | 0.9786 | 0.9834 | 0.9810 | 0.9840 |
| 0.0178 | 29.0 | 28304 | 0.0970 | 0.9789 | 0.9829 | 0.9809 | 0.9838 |
| 0.0174 | 30.0 | 29280 | 0.0974 | 0.9789 | 0.9829 | 0.9809 | 0.9838 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.13.3
