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---
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
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