---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: spellcorrector_3110_v17
  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_3110_v17

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: 0.0086
- Precision: 0.9991
- Recall: 0.9990
- F1: 0.9990
- Accuracy: 0.9977

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1377        | 1.0   | 1949  | 0.1114          | 0.9542    | 0.9820 | 0.9679 | 0.9757   |
| 0.1079        | 2.0   | 3898  | 0.0851          | 0.9680    | 0.9801 | 0.9740 | 0.9795   |
| 0.0904        | 3.0   | 5847  | 0.0717          | 0.9733    | 0.9842 | 0.9787 | 0.9823   |
| 0.0788        | 4.0   | 7796  | 0.0612          | 0.9773    | 0.9859 | 0.9816 | 0.9845   |
| 0.0709        | 5.0   | 9745  | 0.0548          | 0.9824    | 0.9843 | 0.9833 | 0.9858   |
| 0.0646        | 6.0   | 11694 | 0.0483          | 0.9847    | 0.9890 | 0.9868 | 0.9876   |
| 0.0579        | 7.0   | 13643 | 0.0426          | 0.9875    | 0.9889 | 0.9882 | 0.9889   |
| 0.0532        | 8.0   | 15592 | 0.0385          | 0.9897    | 0.9889 | 0.9893 | 0.9898   |
| 0.0477        | 9.0   | 17541 | 0.0320          | 0.9913    | 0.9932 | 0.9922 | 0.9916   |
| 0.044         | 10.0  | 19490 | 0.0268          | 0.9926    | 0.9952 | 0.9939 | 0.9929   |
| 0.0401        | 11.0  | 21439 | 0.0232          | 0.9937    | 0.9960 | 0.9949 | 0.9936   |
| 0.0366        | 12.0  | 23388 | 0.0200          | 0.9957    | 0.9961 | 0.9959 | 0.9944   |
| 0.0317        | 13.0  | 25337 | 0.0172          | 0.9968    | 0.9969 | 0.9968 | 0.9953   |
| 0.0294        | 14.0  | 27286 | 0.0146          | 0.9971    | 0.9979 | 0.9975 | 0.9959   |
| 0.0269        | 15.0  | 29235 | 0.0126          | 0.9979    | 0.9982 | 0.9981 | 0.9965   |
| 0.0248        | 16.0  | 31184 | 0.0119          | 0.9984    | 0.9982 | 0.9983 | 0.9968   |
| 0.0228        | 17.0  | 33133 | 0.0098          | 0.9987    | 0.9987 | 0.9987 | 0.9973   |
| 0.0203        | 18.0  | 35082 | 0.0091          | 0.9989    | 0.9987 | 0.9988 | 0.9975   |
| 0.0189        | 19.0  | 37031 | 0.0087          | 0.9990    | 0.9989 | 0.9990 | 0.9976   |
| 0.0198        | 20.0  | 38980 | 0.0086          | 0.9991    | 0.9990 | 0.9990 | 0.9977   |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.13.3