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---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: spellcorrector_2510_v15_canine-s
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_2510_v15_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: 0.1599
- Precision: 0.9768
- Recall: 0.9820
- F1: 0.9794
- Accuracy: 0.9786
## 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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1921 | 1.0 | 1951 | 0.1677 | 0.9417 | 0.9774 | 0.9592 | 0.9650 |
| 0.1627 | 2.0 | 3902 | 0.1436 | 0.9500 | 0.9779 | 0.9637 | 0.9674 |
| 0.1395 | 3.0 | 5853 | 0.1266 | 0.9545 | 0.9788 | 0.9665 | 0.9697 |
| 0.1266 | 4.0 | 7804 | 0.1172 | 0.9661 | 0.9698 | 0.9680 | 0.9702 |
| 0.1105 | 5.0 | 9755 | 0.1064 | 0.9669 | 0.9766 | 0.9717 | 0.9731 |
| 0.1011 | 6.0 | 11706 | 0.1011 | 0.9705 | 0.9757 | 0.9731 | 0.9745 |
| 0.0933 | 7.0 | 13657 | 0.0987 | 0.9718 | 0.9766 | 0.9742 | 0.9752 |
| 0.0851 | 8.0 | 15608 | 0.0973 | 0.9715 | 0.9787 | 0.9751 | 0.9755 |
| 0.0758 | 9.0 | 17559 | 0.0998 | 0.9734 | 0.9765 | 0.9750 | 0.9756 |
| 0.069 | 10.0 | 19510 | 0.0993 | 0.9732 | 0.9810 | 0.9771 | 0.9764 |
| 0.0635 | 11.0 | 21461 | 0.1055 | 0.9739 | 0.9808 | 0.9773 | 0.9766 |
| 0.0576 | 12.0 | 23412 | 0.1072 | 0.9751 | 0.9794 | 0.9772 | 0.9765 |
| 0.0493 | 13.0 | 25363 | 0.1078 | 0.9754 | 0.9807 | 0.9780 | 0.9776 |
| 0.0469 | 14.0 | 27314 | 0.1145 | 0.9757 | 0.9815 | 0.9786 | 0.9777 |
| 0.0409 | 15.0 | 29265 | 0.1174 | 0.9758 | 0.9806 | 0.9782 | 0.9764 |
| 0.0373 | 16.0 | 31216 | 0.1218 | 0.9763 | 0.9801 | 0.9782 | 0.9769 |
| 0.0338 | 17.0 | 33167 | 0.1239 | 0.9768 | 0.9805 | 0.9787 | 0.9773 |
| 0.0326 | 18.0 | 35118 | 0.1312 | 0.9770 | 0.9787 | 0.9779 | 0.9773 |
| 0.029 | 19.0 | 37069 | 0.1320 | 0.9764 | 0.9809 | 0.9786 | 0.9773 |
| 0.0245 | 20.0 | 39020 | 0.1376 | 0.9767 | 0.9802 | 0.9784 | 0.9777 |
| 0.0231 | 21.0 | 40971 | 0.1382 | 0.9763 | 0.9814 | 0.9788 | 0.9776 |
| 0.0212 | 22.0 | 42922 | 0.1473 | 0.9762 | 0.9826 | 0.9794 | 0.9780 |
| 0.0201 | 23.0 | 44873 | 0.1485 | 0.9762 | 0.9816 | 0.9789 | 0.9778 |
| 0.0187 | 24.0 | 46824 | 0.1494 | 0.9763 | 0.9818 | 0.9790 | 0.9775 |
| 0.0166 | 25.0 | 48775 | 0.1502 | 0.9769 | 0.9813 | 0.9791 | 0.9781 |
| 0.0163 | 26.0 | 50726 | 0.1560 | 0.9769 | 0.9813 | 0.9791 | 0.9785 |
| 0.0149 | 27.0 | 52677 | 0.1556 | 0.9764 | 0.9824 | 0.9794 | 0.9784 |
| 0.0143 | 28.0 | 54628 | 0.1587 | 0.9767 | 0.9818 | 0.9792 | 0.9784 |
| 0.0126 | 29.0 | 56579 | 0.1589 | 0.9766 | 0.9821 | 0.9793 | 0.9784 |
| 0.013 | 30.0 | 58530 | 0.1599 | 0.9768 | 0.9820 | 0.9794 | 0.9786 |
### Framework versions
- Transformers 4.28.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.13.3
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