---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: spellcorrector_1009_v4
  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_1009_v4

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: 0.3307
- Precision: 0.9681
- Recall: 0.9681
- F1: 0.9681
- Accuracy: 0.9573

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.2767        | 1.0   | 1951  | 0.2331          | 0.96      | 0.9562 | 0.9581 | 0.9383   |
| 0.2181        | 2.0   | 3902  | 0.2028          | 0.9524    | 0.9562 | 0.9543 | 0.9450   |
| 0.1776        | 3.0   | 5853  | 0.2019          | 0.96      | 0.9562 | 0.9581 | 0.9498   |
| 0.1519        | 4.0   | 7804  | 0.2038          | 0.9526    | 0.9602 | 0.9563 | 0.9498   |
| 0.1277        | 5.0   | 9755  | 0.2091          | 0.9567    | 0.9681 | 0.9624 | 0.9521   |
| 0.1133        | 6.0   | 11706 | 0.2187          | 0.9449    | 0.9562 | 0.9505 | 0.9540   |
| 0.1041        | 7.0   | 13657 | 0.2378          | 0.9762    | 0.9801 | 0.9781 | 0.9545   |
| 0.0906        | 8.0   | 15608 | 0.2371          | 0.9603    | 0.9641 | 0.9622 | 0.9558   |
| 0.0806        | 9.0   | 17559 | 0.2509          | 0.976     | 0.9721 | 0.9741 | 0.9532   |
| 0.0689        | 10.0  | 19510 | 0.2624          | 0.9681    | 0.9681 | 0.9681 | 0.9563   |
| 0.0623        | 11.0  | 21461 | 0.2623          | 0.976     | 0.9721 | 0.9741 | 0.9559   |
| 0.06          | 12.0  | 23412 | 0.2783          | 0.9643    | 0.9681 | 0.9662 | 0.9564   |
| 0.0537        | 13.0  | 25363 | 0.2938          | 0.976     | 0.9721 | 0.9741 | 0.9569   |
| 0.0507        | 14.0  | 27314 | 0.2976          | 0.9603    | 0.9641 | 0.9622 | 0.9565   |
| 0.0491        | 15.0  | 29265 | 0.3075          | 0.9681    | 0.9681 | 0.9681 | 0.9576   |
| 0.0426        | 16.0  | 31216 | 0.3182          | 0.9681    | 0.9681 | 0.9681 | 0.9571   |
| 0.0426        | 17.0  | 33167 | 0.3154          | 0.9681    | 0.9681 | 0.9681 | 0.9572   |
| 0.0387        | 18.0  | 35118 | 0.3266          | 0.9681    | 0.9681 | 0.9681 | 0.9573   |
| 0.0336        | 19.0  | 37069 | 0.3317          | 0.9681    | 0.9681 | 0.9681 | 0.9574   |
| 0.0341        | 20.0  | 39020 | 0.3307          | 0.9681    | 0.9681 | 0.9681 | 0.9573   |


### Framework versions

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