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spellcorrector_1009_v1
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: 0.0188
- Precision: 0.9947
- Recall: 0.9968
- F1: 0.9958
- Accuracy: 0.9941
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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
0.2712 | 1.0 | 1951 | 0.2093 | 0.9634 | 0.9655 | 0.9645 | 0.9423 |
0.2165 | 2.0 | 3902 | 0.1618 | 0.9645 | 0.9671 | 0.9658 | 0.9541 |
0.1801 | 3.0 | 5853 | 0.1308 | 0.9667 | 0.9708 | 0.9687 | 0.9641 |
0.1473 | 4.0 | 7804 | 0.1003 | 0.9714 | 0.9734 | 0.9724 | 0.9713 |
0.1278 | 5.0 | 9755 | 0.0872 | 0.9761 | 0.9772 | 0.9766 | 0.9757 |
0.1058 | 6.0 | 11706 | 0.0774 | 0.9752 | 0.9825 | 0.9788 | 0.9779 |
0.0948 | 7.0 | 13657 | 0.0682 | 0.9815 | 0.9851 | 0.9833 | 0.9806 |
0.0865 | 8.0 | 15608 | 0.0609 | 0.9847 | 0.9899 | 0.9873 | 0.9825 |
0.0812 | 9.0 | 17559 | 0.0516 | 0.9842 | 0.9904 | 0.9873 | 0.9849 |
0.071 | 10.0 | 19510 | 0.0477 | 0.9873 | 0.9926 | 0.9899 | 0.9862 |
0.0658 | 11.0 | 21461 | 0.0404 | 0.9873 | 0.9920 | 0.9897 | 0.9880 |
0.0571 | 12.0 | 23412 | 0.0360 | 0.9899 | 0.9915 | 0.9907 | 0.9891 |
0.0512 | 13.0 | 25363 | 0.0316 | 0.9905 | 0.9936 | 0.9920 | 0.9904 |
0.0511 | 14.0 | 27314 | 0.0307 | 0.9884 | 0.9936 | 0.9910 | 0.9908 |
0.047 | 15.0 | 29265 | 0.0261 | 0.9921 | 0.9947 | 0.9934 | 0.9919 |
0.0413 | 16.0 | 31216 | 0.0239 | 0.9926 | 0.9958 | 0.9942 | 0.9925 |
0.0412 | 17.0 | 33167 | 0.0220 | 0.9947 | 0.9963 | 0.9955 | 0.9932 |
0.0371 | 18.0 | 35118 | 0.0206 | 0.9947 | 0.9963 | 0.9955 | 0.9936 |
0.0368 | 19.0 | 37069 | 0.0191 | 0.9947 | 0.9968 | 0.9958 | 0.9940 |
0.032 | 20.0 | 39020 | 0.0188 | 0.9947 | 0.9968 | 0.9958 | 0.9941 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3