---
license: apache-2.0
base_model: google/canine-s
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: spellcorrector_0511_v2
  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_0511_v2

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: 0.1552
- Precision: 0.9703
- Recall: 0.9736
- F1: 0.9720
- Accuracy: 0.9734

## 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: 25

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.2251        | 1.0   | 1945  | 0.1881          | 0.9152    | 0.9603 | 0.9372 | 0.9531   |
| 0.1741        | 2.0   | 3890  | 0.1464          | 0.9391    | 0.9651 | 0.9520 | 0.9619   |
| 0.1467        | 3.0   | 5835  | 0.1302          | 0.9536    | 0.9585 | 0.9560 | 0.9645   |
| 0.1278        | 4.0   | 7780  | 0.1230          | 0.9576    | 0.9637 | 0.9606 | 0.9665   |
| 0.1158        | 5.0   | 9725  | 0.1126          | 0.9627    | 0.9651 | 0.9639 | 0.9695   |
| 0.1047        | 6.0   | 11670 | 0.1099          | 0.9638    | 0.9668 | 0.9653 | 0.9703   |
| 0.0964        | 7.0   | 13615 | 0.1090          | 0.9641    | 0.9684 | 0.9663 | 0.9712   |
| 0.0856        | 8.0   | 15560 | 0.1087          | 0.9664    | 0.9688 | 0.9676 | 0.9714   |
| 0.0778        | 9.0   | 17505 | 0.1120          | 0.9675    | 0.9679 | 0.9677 | 0.9712   |
| 0.0712        | 10.0  | 19450 | 0.1126          | 0.9664    | 0.9722 | 0.9693 | 0.9724   |
| 0.0656        | 11.0  | 21395 | 0.1144          | 0.9678    | 0.9701 | 0.9690 | 0.9718   |
| 0.0582        | 12.0  | 23340 | 0.1184          | 0.9682    | 0.9696 | 0.9689 | 0.9723   |
| 0.0532        | 13.0  | 25285 | 0.1215          | 0.9686    | 0.9712 | 0.9699 | 0.9727   |
| 0.0485        | 14.0  | 27230 | 0.1269          | 0.9697    | 0.9718 | 0.9707 | 0.9721   |
| 0.0447        | 15.0  | 29175 | 0.1293          | 0.9693    | 0.9717 | 0.9705 | 0.9727   |
| 0.039         | 16.0  | 31120 | 0.1317          | 0.9690    | 0.9719 | 0.9705 | 0.9723   |
| 0.0363        | 17.0  | 33065 | 0.1376          | 0.9689    | 0.9721 | 0.9705 | 0.9724   |
| 0.0333        | 18.0  | 35010 | 0.1396          | 0.9695    | 0.9721 | 0.9708 | 0.9721   |
| 0.0303        | 19.0  | 36955 | 0.1424          | 0.9700    | 0.9740 | 0.9720 | 0.9731   |
| 0.0274        | 20.0  | 38900 | 0.1456          | 0.9700    | 0.9734 | 0.9717 | 0.9736   |
| 0.0262        | 21.0  | 40845 | 0.1499          | 0.9692    | 0.9732 | 0.9712 | 0.9726   |
| 0.0232        | 22.0  | 42790 | 0.1522          | 0.9702    | 0.9732 | 0.9717 | 0.9733   |
| 0.0229        | 23.0  | 44735 | 0.1543          | 0.9706    | 0.9732 | 0.9719 | 0.9736   |
| 0.0214        | 24.0  | 46680 | 0.1543          | 0.9703    | 0.9738 | 0.9721 | 0.9733   |
| 0.0204        | 25.0  | 48625 | 0.1552          | 0.9703    | 0.9736 | 0.9720 | 0.9734   |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1