---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: spellcorrector_1709_v6
  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_v6

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: 0.0158
- Precision: 0.9871
- Recall: 0.9831
- F1: 0.9851
- Accuracy: 0.9951

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.2794        | 1.0   | 1951  | 0.2144          | 0.7935    | 0.7534 | 0.7729 | 0.9414   |
| 0.2179        | 2.0   | 3902  | 0.1587          | 0.8333    | 0.7994 | 0.8160 | 0.9555   |
| 0.1752        | 3.0   | 5853  | 0.1272          | 0.8639    | 0.8239 | 0.8434 | 0.9642   |
| 0.1507        | 4.0   | 7804  | 0.1063          | 0.8844    | 0.8510 | 0.8674 | 0.9699   |
| 0.1273        | 5.0   | 9755  | 0.0859          | 0.9044    | 0.8753 | 0.8896 | 0.9755   |
| 0.1106        | 6.0   | 11706 | 0.0762          | 0.9197    | 0.8838 | 0.9014 | 0.9779   |
| 0.0984        | 7.0   | 13657 | 0.0670          | 0.9255    | 0.9035 | 0.9144 | 0.9805   |
| 0.0861        | 8.0   | 15608 | 0.0571          | 0.9402    | 0.9150 | 0.9274 | 0.9832   |
| 0.0754        | 9.0   | 17559 | 0.0517          | 0.9469    | 0.9269 | 0.9368 | 0.9844   |
| 0.07          | 10.0  | 19510 | 0.0442          | 0.9559    | 0.9361 | 0.9459 | 0.9866   |
| 0.0636        | 11.0  | 21461 | 0.0387          | 0.9604    | 0.9477 | 0.9540 | 0.9882   |
| 0.0597        | 12.0  | 23412 | 0.0315          | 0.9673    | 0.9559 | 0.9616 | 0.9903   |
| 0.0523        | 13.0  | 25363 | 0.0296          | 0.9723    | 0.9612 | 0.9667 | 0.9909   |
| 0.0449        | 14.0  | 27314 | 0.0258          | 0.9744    | 0.9683 | 0.9713 | 0.9920   |
| 0.0407        | 15.0  | 29265 | 0.0226          | 0.9797    | 0.9715 | 0.9756 | 0.9930   |
| 0.0395        | 16.0  | 31216 | 0.0212          | 0.9817    | 0.9758 | 0.9788 | 0.9934   |
| 0.0357        | 17.0  | 33167 | 0.0181          | 0.9843    | 0.9783 | 0.9813 | 0.9943   |
| 0.0356        | 18.0  | 35118 | 0.0172          | 0.9859    | 0.9812 | 0.9836 | 0.9947   |
| 0.0328        | 19.0  | 37069 | 0.0162          | 0.9865    | 0.9829 | 0.9847 | 0.9950   |
| 0.0316        | 20.0  | 39020 | 0.0158          | 0.9871    | 0.9831 | 0.9851 | 0.9951   |


### Framework versions

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