---
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