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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_1209_v5 |
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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_1209_v5 |
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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: 0.0129 |
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- Precision: 0.9884 |
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- Recall: 0.9845 |
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- F1: 0.9865 |
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- Accuracy: 0.9958 |
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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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| 0.2592 | 1.0 | 1951 | 0.1973 | 0.7990 | 0.7403 | 0.7686 | 0.9462 | |
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| 0.2036 | 2.0 | 3902 | 0.1430 | 0.8304 | 0.7969 | 0.8133 | 0.9591 | |
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| 0.1643 | 3.0 | 5853 | 0.1090 | 0.8775 | 0.8292 | 0.8527 | 0.9688 | |
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| 0.1339 | 4.0 | 7804 | 0.0898 | 0.8971 | 0.8539 | 0.8750 | 0.9743 | |
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| 0.1143 | 5.0 | 9755 | 0.0788 | 0.9104 | 0.8768 | 0.8933 | 0.9773 | |
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| 0.0996 | 6.0 | 11706 | 0.0648 | 0.9240 | 0.8929 | 0.9082 | 0.9810 | |
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| 0.0874 | 7.0 | 13657 | 0.0568 | 0.9349 | 0.9035 | 0.9189 | 0.9829 | |
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| 0.0797 | 8.0 | 15608 | 0.0496 | 0.9439 | 0.9215 | 0.9326 | 0.9851 | |
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| 0.0696 | 9.0 | 17559 | 0.0426 | 0.9538 | 0.9289 | 0.9412 | 0.9868 | |
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| 0.0647 | 10.0 | 19510 | 0.0385 | 0.9596 | 0.9372 | 0.9482 | 0.9880 | |
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| 0.0532 | 11.0 | 21461 | 0.0335 | 0.9636 | 0.9465 | 0.9550 | 0.9895 | |
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| 0.0481 | 12.0 | 23412 | 0.0298 | 0.9704 | 0.9570 | 0.9636 | 0.9907 | |
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| 0.0443 | 13.0 | 25363 | 0.0240 | 0.9745 | 0.9654 | 0.9699 | 0.9923 | |
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| 0.0414 | 14.0 | 27314 | 0.0229 | 0.9795 | 0.9671 | 0.9732 | 0.9926 | |
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| 0.0369 | 15.0 | 29265 | 0.0195 | 0.9809 | 0.9737 | 0.9773 | 0.9938 | |
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| 0.0339 | 16.0 | 31216 | 0.0171 | 0.9831 | 0.9778 | 0.9805 | 0.9944 | |
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| 0.0312 | 17.0 | 33167 | 0.0156 | 0.9859 | 0.9797 | 0.9828 | 0.9949 | |
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| 0.0276 | 18.0 | 35118 | 0.0140 | 0.9874 | 0.9821 | 0.9847 | 0.9954 | |
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| 0.0277 | 19.0 | 37069 | 0.0133 | 0.9880 | 0.9840 | 0.9860 | 0.9957 | |
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| 0.0253 | 20.0 | 39020 | 0.0129 | 0.9884 | 0.9845 | 0.9865 | 0.9958 | |
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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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