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spellcorrector_1009_v4
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: 0.3307
- Precision: 0.9681
- Recall: 0.9681
- F1: 0.9681
- Accuracy: 0.9573
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 |
|---|---|---|---|---|---|---|---|
| 0.2767 | 1.0 | 1951 | 0.2331 | 0.96 | 0.9562 | 0.9581 | 0.9383 |
| 0.2181 | 2.0 | 3902 | 0.2028 | 0.9524 | 0.9562 | 0.9543 | 0.9450 |
| 0.1776 | 3.0 | 5853 | 0.2019 | 0.96 | 0.9562 | 0.9581 | 0.9498 |
| 0.1519 | 4.0 | 7804 | 0.2038 | 0.9526 | 0.9602 | 0.9563 | 0.9498 |
| 0.1277 | 5.0 | 9755 | 0.2091 | 0.9567 | 0.9681 | 0.9624 | 0.9521 |
| 0.1133 | 6.0 | 11706 | 0.2187 | 0.9449 | 0.9562 | 0.9505 | 0.9540 |
| 0.1041 | 7.0 | 13657 | 0.2378 | 0.9762 | 0.9801 | 0.9781 | 0.9545 |
| 0.0906 | 8.0 | 15608 | 0.2371 | 0.9603 | 0.9641 | 0.9622 | 0.9558 |
| 0.0806 | 9.0 | 17559 | 0.2509 | 0.976 | 0.9721 | 0.9741 | 0.9532 |
| 0.0689 | 10.0 | 19510 | 0.2624 | 0.9681 | 0.9681 | 0.9681 | 0.9563 |
| 0.0623 | 11.0 | 21461 | 0.2623 | 0.976 | 0.9721 | 0.9741 | 0.9559 |
| 0.06 | 12.0 | 23412 | 0.2783 | 0.9643 | 0.9681 | 0.9662 | 0.9564 |
| 0.0537 | 13.0 | 25363 | 0.2938 | 0.976 | 0.9721 | 0.9741 | 0.9569 |
| 0.0507 | 14.0 | 27314 | 0.2976 | 0.9603 | 0.9641 | 0.9622 | 0.9565 |
| 0.0491 | 15.0 | 29265 | 0.3075 | 0.9681 | 0.9681 | 0.9681 | 0.9576 |
| 0.0426 | 16.0 | 31216 | 0.3182 | 0.9681 | 0.9681 | 0.9681 | 0.9571 |
| 0.0426 | 17.0 | 33167 | 0.3154 | 0.9681 | 0.9681 | 0.9681 | 0.9572 |
| 0.0387 | 18.0 | 35118 | 0.3266 | 0.9681 | 0.9681 | 0.9681 | 0.9573 |
| 0.0336 | 19.0 | 37069 | 0.3317 | 0.9681 | 0.9681 | 0.9681 | 0.9574 |
| 0.0341 | 20.0 | 39020 | 0.3307 | 0.9681 | 0.9681 | 0.9681 | 0.9573 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
