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---
license: apache-2.0
base_model: google/canine-s
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: spellcorrector_17_02_050_qwerty
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# spellcorrector_17_02_050_qwerty
This model is a fine-tuned version of [google/canine-s](https://huggingface.co/google/canine-s) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0163
- Precision: 0.9930
- Recall: 0.9887
- F1: 0.9909
- Accuracy: 0.9952
## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.4639 | 1.0 | 967 | 0.1649 | 0.9619 | 0.9624 | 0.9622 | 0.9608 |
| 0.1737 | 2.0 | 1934 | 0.1300 | 0.9620 | 0.9656 | 0.9638 | 0.9664 |
| 0.145 | 3.0 | 2901 | 0.1099 | 0.9678 | 0.9694 | 0.9686 | 0.9708 |
| 0.1222 | 4.0 | 3868 | 0.0906 | 0.9699 | 0.9699 | 0.9699 | 0.9752 |
| 0.105 | 5.0 | 4835 | 0.0736 | 0.9726 | 0.9699 | 0.9712 | 0.9792 |
| 0.0933 | 6.0 | 5802 | 0.0633 | 0.9758 | 0.9732 | 0.9745 | 0.9817 |
| 0.0807 | 7.0 | 6769 | 0.0531 | 0.9822 | 0.9780 | 0.9801 | 0.9844 |
| 0.0715 | 8.0 | 7736 | 0.0468 | 0.9839 | 0.9828 | 0.9834 | 0.9864 |
| 0.0643 | 9.0 | 8703 | 0.0404 | 0.9833 | 0.9823 | 0.9828 | 0.9880 |
| 0.0575 | 10.0 | 9670 | 0.0356 | 0.9903 | 0.9866 | 0.9884 | 0.9894 |
| 0.0525 | 11.0 | 10637 | 0.0317 | 0.9887 | 0.9866 | 0.9876 | 0.9905 |
| 0.0481 | 12.0 | 11604 | 0.0281 | 0.9908 | 0.9871 | 0.9890 | 0.9915 |
| 0.0444 | 13.0 | 12571 | 0.0255 | 0.9919 | 0.9871 | 0.9895 | 0.9923 |
| 0.0417 | 14.0 | 13538 | 0.0235 | 0.9924 | 0.9877 | 0.9900 | 0.9930 |
| 0.0382 | 15.0 | 14505 | 0.0211 | 0.9925 | 0.9882 | 0.9903 | 0.9937 |
| 0.0358 | 16.0 | 15472 | 0.0198 | 0.9930 | 0.9887 | 0.9909 | 0.9941 |
| 0.034 | 17.0 | 16439 | 0.0184 | 0.9930 | 0.9882 | 0.9906 | 0.9946 |
| 0.0323 | 18.0 | 17406 | 0.0173 | 0.9930 | 0.9882 | 0.9906 | 0.9949 |
| 0.0306 | 19.0 | 18373 | 0.0167 | 0.9930 | 0.9887 | 0.9909 | 0.9951 |
| 0.0304 | 20.0 | 19340 | 0.0163 | 0.9930 | 0.9887 | 0.9909 | 0.9952 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2
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