---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: spellcorrector_2410_v14_canine-s
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# spellcorrector_2410_v14_canine-s

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: 0.0043
- Precision: 0.9996
- Recall: 0.9994
- F1: 0.9995
- Accuracy: 0.9989

## 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: 25

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.19          | 1.0   | 1951  | 0.1535          | 0.9437    | 0.9787 | 0.9609 | 0.9670   |
| 0.1486        | 2.0   | 3902  | 0.1187          | 0.9591    | 0.9774 | 0.9682 | 0.9716   |
| 0.126         | 3.0   | 5853  | 0.1029          | 0.9671    | 0.9792 | 0.9731 | 0.9739   |
| 0.1082        | 4.0   | 7804  | 0.0888          | 0.9740    | 0.9785 | 0.9763 | 0.9769   |
| 0.0992        | 5.0   | 9755  | 0.0719          | 0.9762    | 0.9852 | 0.9807 | 0.9813   |
| 0.0871        | 6.0   | 11706 | 0.0624          | 0.9805    | 0.9861 | 0.9833 | 0.9832   |
| 0.0782        | 7.0   | 13657 | 0.0527          | 0.9835    | 0.9885 | 0.9860 | 0.9858   |
| 0.0693        | 8.0   | 15608 | 0.0446          | 0.9866    | 0.9898 | 0.9882 | 0.9876   |
| 0.0604        | 9.0   | 17559 | 0.0375          | 0.9888    | 0.9906 | 0.9897 | 0.9893   |
| 0.0543        | 10.0  | 19510 | 0.0318          | 0.9915    | 0.9926 | 0.9921 | 0.9914   |
| 0.046         | 11.0  | 21461 | 0.0272          | 0.9932    | 0.9940 | 0.9936 | 0.9925   |
| 0.0425        | 12.0  | 23412 | 0.0217          | 0.9942    | 0.9950 | 0.9946 | 0.9939   |
| 0.0378        | 13.0  | 25363 | 0.0188          | 0.9953    | 0.9963 | 0.9958 | 0.9946   |
| 0.0333        | 14.0  | 27314 | 0.0160          | 0.9963    | 0.9962 | 0.9962 | 0.9954   |
| 0.0286        | 15.0  | 29265 | 0.0140          | 0.9972    | 0.9970 | 0.9971 | 0.9960   |
| 0.0261        | 16.0  | 31216 | 0.0121          | 0.9977    | 0.9978 | 0.9978 | 0.9966   |
| 0.0235        | 17.0  | 33167 | 0.0104          | 0.9984    | 0.9979 | 0.9982 | 0.9972   |
| 0.021         | 18.0  | 35118 | 0.0090          | 0.9987    | 0.9986 | 0.9986 | 0.9976   |
| 0.0196        | 19.0  | 37069 | 0.0073          | 0.9990    | 0.9988 | 0.9989 | 0.9980   |
| 0.0166        | 20.0  | 39020 | 0.0064          | 0.9992    | 0.9991 | 0.9991 | 0.9983   |
| 0.0158        | 21.0  | 40971 | 0.0059          | 0.9994    | 0.9991 | 0.9992 | 0.9984   |
| 0.0136        | 22.0  | 42922 | 0.0053          | 0.9995    | 0.9994 | 0.9994 | 0.9986   |
| 0.0134        | 23.0  | 44873 | 0.0047          | 0.9996    | 0.9993 | 0.9994 | 0.9988   |
| 0.0125        | 24.0  | 46824 | 0.0045          | 0.9996    | 0.9993 | 0.9995 | 0.9989   |
| 0.0116        | 25.0  | 48775 | 0.0043          | 0.9996    | 0.9994 | 0.9995 | 0.9989   |


### Framework versions

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