---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: spellcorrector_1209_v5
  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_1209_v5

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: 0.0129
- Precision: 0.9884
- Recall: 0.9845
- F1: 0.9865
- Accuracy: 0.9958

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.2592        | 1.0   | 1951  | 0.1973          | 0.7990    | 0.7403 | 0.7686 | 0.9462   |
| 0.2036        | 2.0   | 3902  | 0.1430          | 0.8304    | 0.7969 | 0.8133 | 0.9591   |
| 0.1643        | 3.0   | 5853  | 0.1090          | 0.8775    | 0.8292 | 0.8527 | 0.9688   |
| 0.1339        | 4.0   | 7804  | 0.0898          | 0.8971    | 0.8539 | 0.8750 | 0.9743   |
| 0.1143        | 5.0   | 9755  | 0.0788          | 0.9104    | 0.8768 | 0.8933 | 0.9773   |
| 0.0996        | 6.0   | 11706 | 0.0648          | 0.9240    | 0.8929 | 0.9082 | 0.9810   |
| 0.0874        | 7.0   | 13657 | 0.0568          | 0.9349    | 0.9035 | 0.9189 | 0.9829   |
| 0.0797        | 8.0   | 15608 | 0.0496          | 0.9439    | 0.9215 | 0.9326 | 0.9851   |
| 0.0696        | 9.0   | 17559 | 0.0426          | 0.9538    | 0.9289 | 0.9412 | 0.9868   |
| 0.0647        | 10.0  | 19510 | 0.0385          | 0.9596    | 0.9372 | 0.9482 | 0.9880   |
| 0.0532        | 11.0  | 21461 | 0.0335          | 0.9636    | 0.9465 | 0.9550 | 0.9895   |
| 0.0481        | 12.0  | 23412 | 0.0298          | 0.9704    | 0.9570 | 0.9636 | 0.9907   |
| 0.0443        | 13.0  | 25363 | 0.0240          | 0.9745    | 0.9654 | 0.9699 | 0.9923   |
| 0.0414        | 14.0  | 27314 | 0.0229          | 0.9795    | 0.9671 | 0.9732 | 0.9926   |
| 0.0369        | 15.0  | 29265 | 0.0195          | 0.9809    | 0.9737 | 0.9773 | 0.9938   |
| 0.0339        | 16.0  | 31216 | 0.0171          | 0.9831    | 0.9778 | 0.9805 | 0.9944   |
| 0.0312        | 17.0  | 33167 | 0.0156          | 0.9859    | 0.9797 | 0.9828 | 0.9949   |
| 0.0276        | 18.0  | 35118 | 0.0140          | 0.9874    | 0.9821 | 0.9847 | 0.9954   |
| 0.0277        | 19.0  | 37069 | 0.0133          | 0.9880    | 0.9840 | 0.9860 | 0.9957   |
| 0.0253        | 20.0  | 39020 | 0.0129          | 0.9884    | 0.9845 | 0.9865 | 0.9958   |


### Framework versions

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