| --- |
| license: apache-2.0 |
| tags: |
| - generated_from_trainer |
| metrics: |
| - precision |
| - recall |
| - f1 |
| - accuracy |
| model-index: |
| - name: spellcorrector_0411 |
| 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_0411 |
| |
| 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: 0.0830 |
| - Precision: 0.9784 |
| - Recall: 0.9815 |
| - F1: 0.9799 |
| - Accuracy: 0.9828 |
| |
| ## 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: 8 |
| - eval_batch_size: 8 |
| - 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 | |
| |:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:| |
| | 0.2319 | 1.0 | 975 | 0.1268 | 0.9458 | 0.9834 | 0.9642 | 0.9741 | |
| | 0.1296 | 2.0 | 1950 | 0.1063 | 0.9530 | 0.9812 | 0.9669 | 0.9754 | |
| | 0.1095 | 3.0 | 2925 | 0.0883 | 0.9653 | 0.9788 | 0.9720 | 0.9786 | |
| | 0.0934 | 4.0 | 3900 | 0.0842 | 0.9692 | 0.9776 | 0.9734 | 0.9790 | |
| | 0.0829 | 5.0 | 4875 | 0.0794 | 0.9716 | 0.9797 | 0.9756 | 0.9809 | |
| | 0.0753 | 6.0 | 5850 | 0.0755 | 0.9729 | 0.9816 | 0.9773 | 0.9817 | |
| | 0.0695 | 7.0 | 6825 | 0.0739 | 0.9751 | 0.9789 | 0.9770 | 0.9815 | |
| | 0.0641 | 8.0 | 7800 | 0.0736 | 0.9767 | 0.9798 | 0.9782 | 0.9821 | |
| | 0.0591 | 9.0 | 8775 | 0.0744 | 0.9767 | 0.9805 | 0.9786 | 0.9822 | |
| | 0.0537 | 10.0 | 9750 | 0.0742 | 0.9777 | 0.9798 | 0.9787 | 0.9822 | |
| | 0.0502 | 11.0 | 10725 | 0.0753 | 0.9773 | 0.9806 | 0.9790 | 0.9825 | |
| | 0.0472 | 12.0 | 11700 | 0.0757 | 0.9780 | 0.9808 | 0.9794 | 0.9827 | |
| | 0.044 | 13.0 | 12675 | 0.0768 | 0.9772 | 0.9816 | 0.9794 | 0.9827 | |
| | 0.0407 | 14.0 | 13650 | 0.0784 | 0.9775 | 0.9815 | 0.9795 | 0.9827 | |
| | 0.039 | 15.0 | 14625 | 0.0790 | 0.9779 | 0.9816 | 0.9798 | 0.9828 | |
| | 0.0364 | 16.0 | 15600 | 0.0804 | 0.9778 | 0.9813 | 0.9795 | 0.9825 | |
| | 0.0343 | 17.0 | 16575 | 0.0811 | 0.9783 | 0.9811 | 0.9797 | 0.9828 | |
| | 0.0329 | 18.0 | 17550 | 0.0819 | 0.9785 | 0.9820 | 0.9803 | 0.9829 | |
| | 0.0314 | 19.0 | 18525 | 0.0822 | 0.9785 | 0.9808 | 0.9797 | 0.9826 | |
| | 0.0308 | 20.0 | 19500 | 0.0830 | 0.9784 | 0.9815 | 0.9799 | 0.9828 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.28.0 |
| - Pytorch 2.1.0+cu118 |
| - Datasets 2.14.6 |
| - Tokenizers 0.13.3 |
| |
