spellcorrector_20_02_all_proportions_only_del_consonant_v15
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: 0.0117
- Precision: 0.9973
- Recall: 0.9936
- F1: 0.9954
- Accuracy: 0.9969
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: 20
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
0.3519 | 1.0 | 967 | 0.0926 | 0.9946 | 0.9855 | 0.9900 | 0.9797 |
0.0946 | 2.0 | 1934 | 0.0813 | 0.9935 | 0.9850 | 0.9892 | 0.9813 |
0.0845 | 3.0 | 2901 | 0.0720 | 0.9914 | 0.9855 | 0.9884 | 0.9827 |
0.0763 | 4.0 | 3868 | 0.0652 | 0.9849 | 0.9828 | 0.9839 | 0.9840 |
0.0714 | 5.0 | 4835 | 0.0589 | 0.9898 | 0.9855 | 0.9876 | 0.9855 |
0.0641 | 6.0 | 5802 | 0.0524 | 0.9941 | 0.9877 | 0.9909 | 0.9866 |
0.0592 | 7.0 | 6769 | 0.0465 | 0.9892 | 0.9871 | 0.9882 | 0.9878 |
0.0545 | 8.0 | 7736 | 0.0411 | 0.9930 | 0.9882 | 0.9906 | 0.9892 |
0.0505 | 9.0 | 8703 | 0.0367 | 0.9882 | 0.9866 | 0.9874 | 0.9902 |
0.0473 | 10.0 | 9670 | 0.0318 | 0.9951 | 0.9893 | 0.9922 | 0.9914 |
0.0426 | 11.0 | 10637 | 0.0280 | 0.9941 | 0.9898 | 0.9919 | 0.9924 |
0.0406 | 12.0 | 11604 | 0.0243 | 0.9946 | 0.9893 | 0.9919 | 0.9933 |
0.0369 | 13.0 | 12571 | 0.0218 | 0.9968 | 0.9914 | 0.9941 | 0.9942 |
0.0343 | 14.0 | 13538 | 0.0192 | 0.9973 | 0.9941 | 0.9957 | 0.9947 |
0.0309 | 15.0 | 14505 | 0.0172 | 0.9957 | 0.9930 | 0.9944 | 0.9954 |
0.0289 | 16.0 | 15472 | 0.0152 | 0.9957 | 0.9925 | 0.9941 | 0.9959 |
0.028 | 17.0 | 16439 | 0.0138 | 0.9957 | 0.9936 | 0.9946 | 0.9963 |
0.0264 | 18.0 | 17406 | 0.0125 | 0.9973 | 0.9936 | 0.9954 | 0.9967 |
0.025 | 19.0 | 18373 | 0.0121 | 0.9973 | 0.9936 | 0.9954 | 0.9968 |
0.0244 | 20.0 | 19340 | 0.0117 | 0.9973 | 0.9936 | 0.9954 | 0.9969 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2
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