---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: spellcorrector_1709_v7
  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_1709_v7

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: 0.0885
- Precision: 0.9610
- Recall: 0.9739
- F1: 0.9674
- Accuracy: 0.9742

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.2583        | 1.0   | 1951  | 0.2210          | 0.8849    | 0.9710 | 0.9260 | 0.9443   |
| 0.2244        | 2.0   | 3902  | 0.1992          | 0.8954    | 0.9685 | 0.9305 | 0.9466   |
| 0.2099        | 3.0   | 5853  | 0.1868          | 0.9021    | 0.9684 | 0.9341 | 0.9482   |
| 0.1989        | 4.0   | 7804  | 0.1789          | 0.9109    | 0.9634 | 0.9364 | 0.9500   |
| 0.1926        | 5.0   | 9755  | 0.1694          | 0.9141    | 0.9652 | 0.9389 | 0.9518   |
| 0.1837        | 6.0   | 11706 | 0.1605          | 0.9160    | 0.9697 | 0.9421 | 0.9540   |
| 0.1817        | 7.0   | 13657 | 0.1547          | 0.9209    | 0.9656 | 0.9427 | 0.9549   |
| 0.1723        | 8.0   | 15608 | 0.1484          | 0.9226    | 0.9687 | 0.9451 | 0.9564   |
| 0.1692        | 9.0   | 17559 | 0.1442          | 0.9269    | 0.9649 | 0.9455 | 0.9571   |
| 0.1642        | 10.0  | 19510 | 0.1386          | 0.9269    | 0.9697 | 0.9478 | 0.9587   |
| 0.1578        | 11.0  | 21461 | 0.1327          | 0.9310    | 0.9693 | 0.9497 | 0.9600   |
| 0.148         | 12.0  | 23412 | 0.1231          | 0.9393    | 0.9674 | 0.9532 | 0.9630   |
| 0.1455        | 13.0  | 25363 | 0.1172          | 0.9413    | 0.9711 | 0.9560 | 0.9653   |
| 0.1402        | 14.0  | 27314 | 0.1123          | 0.9476    | 0.9673 | 0.9573 | 0.9662   |
| 0.1323        | 15.0  | 29265 | 0.1056          | 0.9511    | 0.9694 | 0.9602 | 0.9685   |
| 0.1269        | 16.0  | 31216 | 0.0989          | 0.9521    | 0.9740 | 0.9629 | 0.9709   |
| 0.1225        | 17.0  | 33167 | 0.0953          | 0.9575    | 0.9716 | 0.9645 | 0.9720   |
| 0.1186        | 18.0  | 35118 | 0.0907          | 0.9582    | 0.9744 | 0.9662 | 0.9735   |
| 0.1169        | 19.0  | 37069 | 0.0897          | 0.9606    | 0.9734 | 0.9670 | 0.9738   |
| 0.113         | 20.0  | 39020 | 0.0885          | 0.9610    | 0.9739 | 0.9674 | 0.9742   |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3