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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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metrics: |
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- precision |
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- recall |
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- f1 |
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- accuracy |
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model-index: |
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- name: spellcorrector_1709_v7 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# spellcorrector_1709_v7 |
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This model is a fine-tuned version of [google/canine-s](https://huggingface.co/google/canine-s) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0885 |
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- Precision: 0.9610 |
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- Recall: 0.9739 |
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- F1: 0.9674 |
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- Accuracy: 0.9742 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 20 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| 0.2583 | 1.0 | 1951 | 0.2210 | 0.8849 | 0.9710 | 0.9260 | 0.9443 | |
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| 0.2244 | 2.0 | 3902 | 0.1992 | 0.8954 | 0.9685 | 0.9305 | 0.9466 | |
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| 0.2099 | 3.0 | 5853 | 0.1868 | 0.9021 | 0.9684 | 0.9341 | 0.9482 | |
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| 0.1989 | 4.0 | 7804 | 0.1789 | 0.9109 | 0.9634 | 0.9364 | 0.9500 | |
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| 0.1926 | 5.0 | 9755 | 0.1694 | 0.9141 | 0.9652 | 0.9389 | 0.9518 | |
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| 0.1837 | 6.0 | 11706 | 0.1605 | 0.9160 | 0.9697 | 0.9421 | 0.9540 | |
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| 0.1817 | 7.0 | 13657 | 0.1547 | 0.9209 | 0.9656 | 0.9427 | 0.9549 | |
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| 0.1723 | 8.0 | 15608 | 0.1484 | 0.9226 | 0.9687 | 0.9451 | 0.9564 | |
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| 0.1692 | 9.0 | 17559 | 0.1442 | 0.9269 | 0.9649 | 0.9455 | 0.9571 | |
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| 0.1642 | 10.0 | 19510 | 0.1386 | 0.9269 | 0.9697 | 0.9478 | 0.9587 | |
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| 0.1578 | 11.0 | 21461 | 0.1327 | 0.9310 | 0.9693 | 0.9497 | 0.9600 | |
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| 0.148 | 12.0 | 23412 | 0.1231 | 0.9393 | 0.9674 | 0.9532 | 0.9630 | |
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| 0.1455 | 13.0 | 25363 | 0.1172 | 0.9413 | 0.9711 | 0.9560 | 0.9653 | |
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| 0.1402 | 14.0 | 27314 | 0.1123 | 0.9476 | 0.9673 | 0.9573 | 0.9662 | |
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| 0.1323 | 15.0 | 29265 | 0.1056 | 0.9511 | 0.9694 | 0.9602 | 0.9685 | |
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| 0.1269 | 16.0 | 31216 | 0.0989 | 0.9521 | 0.9740 | 0.9629 | 0.9709 | |
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| 0.1225 | 17.0 | 33167 | 0.0953 | 0.9575 | 0.9716 | 0.9645 | 0.9720 | |
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| 0.1186 | 18.0 | 35118 | 0.0907 | 0.9582 | 0.9744 | 0.9662 | 0.9735 | |
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| 0.1169 | 19.0 | 37069 | 0.0897 | 0.9606 | 0.9734 | 0.9670 | 0.9738 | |
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| 0.113 | 20.0 | 39020 | 0.0885 | 0.9610 | 0.9739 | 0.9674 | 0.9742 | |
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### Framework versions |
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- Transformers 4.28.0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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