---
license: apache-2.0
base_model: google/canine-s
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: spellcorrector_0511_v3_30_epoch
  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_v3_30_epoch

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: 0.1888
- Precision: 0.9708
- Recall: 0.9751
- F1: 0.9730
- Accuracy: 0.9745

## 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: 30

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.2233        | 1.0   | 1945  | 0.1721          | 0.9292    | 0.9619 | 0.9453 | 0.9570   |
| 0.1589        | 2.0   | 3890  | 0.1346          | 0.9455    | 0.9670 | 0.9561 | 0.9646   |
| 0.1387        | 3.0   | 5835  | 0.1208          | 0.9545    | 0.9684 | 0.9614 | 0.9680   |
| 0.1201        | 4.0   | 7780  | 0.1173          | 0.9620    | 0.9616 | 0.9618 | 0.9682   |
| 0.1067        | 5.0   | 9725  | 0.1138          | 0.9628    | 0.9662 | 0.9645 | 0.9699   |
| 0.0951        | 6.0   | 11670 | 0.1096          | 0.9653    | 0.9680 | 0.9666 | 0.9714   |
| 0.0864        | 7.0   | 13615 | 0.1122          | 0.9673    | 0.9663 | 0.9668 | 0.9715   |
| 0.0757        | 8.0   | 15560 | 0.1141          | 0.9680    | 0.9699 | 0.9689 | 0.9719   |
| 0.0676        | 9.0   | 17505 | 0.1154          | 0.9687    | 0.9718 | 0.9703 | 0.9723   |
| 0.0606        | 10.0  | 19450 | 0.1193          | 0.9679    | 0.9730 | 0.9705 | 0.9731   |
| 0.0548        | 11.0  | 21395 | 0.1246          | 0.9701    | 0.9696 | 0.9698 | 0.9724   |
| 0.0478        | 12.0  | 23340 | 0.1279          | 0.9708    | 0.9705 | 0.9706 | 0.9730   |
| 0.0417        | 13.0  | 25285 | 0.1316          | 0.9707    | 0.9706 | 0.9706 | 0.9733   |
| 0.0375        | 14.0  | 27230 | 0.1387          | 0.9706    | 0.9734 | 0.9720 | 0.9729   |
| 0.0334        | 15.0  | 29175 | 0.1405          | 0.9704    | 0.9748 | 0.9726 | 0.9741   |
| 0.0292        | 16.0  | 31120 | 0.1450          | 0.9704    | 0.9736 | 0.9720 | 0.9733   |
| 0.0261        | 17.0  | 33065 | 0.1492          | 0.9684    | 0.9744 | 0.9714 | 0.9734   |
| 0.0233        | 18.0  | 35010 | 0.1529          | 0.9701    | 0.9755 | 0.9728 | 0.9739   |
| 0.0205        | 19.0  | 36955 | 0.1580          | 0.9708    | 0.9733 | 0.9720 | 0.9735   |
| 0.0174        | 20.0  | 38900 | 0.1636          | 0.9710    | 0.9749 | 0.9729 | 0.9741   |
| 0.0166        | 21.0  | 40845 | 0.1674          | 0.9700    | 0.9763 | 0.9732 | 0.9742   |
| 0.0142        | 22.0  | 42790 | 0.1729          | 0.9706    | 0.9742 | 0.9724 | 0.9733   |
| 0.0126        | 23.0  | 44735 | 0.1737          | 0.9711    | 0.9742 | 0.9726 | 0.9743   |
| 0.0116        | 24.0  | 46680 | 0.1788          | 0.9706    | 0.9762 | 0.9734 | 0.9747   |
| 0.0102        | 25.0  | 48625 | 0.1808          | 0.9712    | 0.9750 | 0.9731 | 0.9745   |
| 0.0093        | 26.0  | 50570 | 0.1817          | 0.9710    | 0.9741 | 0.9725 | 0.9742   |
| 0.0082        | 27.0  | 52515 | 0.1838          | 0.9706    | 0.9748 | 0.9727 | 0.9741   |
| 0.0082        | 28.0  | 54460 | 0.1865          | 0.9711    | 0.9754 | 0.9733 | 0.9745   |
| 0.0076        | 29.0  | 56405 | 0.1873          | 0.9706    | 0.9753 | 0.9729 | 0.9745   |
| 0.0069        | 30.0  | 58350 | 0.1888          | 0.9708    | 0.9751 | 0.9730 | 0.9745   |


### Framework versions

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