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Buseak
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spellcorrector_0511_v2

Token Classification
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canine
Generated from Trainer
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  1. README.md +90 -0
  2. model.safetensors +1 -1
  3. runs/Nov05_18-52-45_702a8d08e357/events.out.tfevents.1699210366.702a8d08e357.2847.2 +2 -2
README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: google/canine-s
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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_0511_v2
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+ results: []
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+ ---
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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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+
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+ # spellcorrector_0511_v2
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+
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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: 0.1552
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+ - Precision: 0.9703
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+ - Recall: 0.9736
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+ - F1: 0.9720
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+ - Accuracy: 0.9734
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 25
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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+ |:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | 0.2251 | 1.0 | 1945 | 0.1881 | 0.9152 | 0.9603 | 0.9372 | 0.9531 |
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+ | 0.1741 | 2.0 | 3890 | 0.1464 | 0.9391 | 0.9651 | 0.9520 | 0.9619 |
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+ | 0.1467 | 3.0 | 5835 | 0.1302 | 0.9536 | 0.9585 | 0.9560 | 0.9645 |
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+ | 0.1278 | 4.0 | 7780 | 0.1230 | 0.9576 | 0.9637 | 0.9606 | 0.9665 |
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+ | 0.1158 | 5.0 | 9725 | 0.1126 | 0.9627 | 0.9651 | 0.9639 | 0.9695 |
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+ | 0.1047 | 6.0 | 11670 | 0.1099 | 0.9638 | 0.9668 | 0.9653 | 0.9703 |
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+ | 0.0964 | 7.0 | 13615 | 0.1090 | 0.9641 | 0.9684 | 0.9663 | 0.9712 |
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+ | 0.0856 | 8.0 | 15560 | 0.1087 | 0.9664 | 0.9688 | 0.9676 | 0.9714 |
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+ | 0.0778 | 9.0 | 17505 | 0.1120 | 0.9675 | 0.9679 | 0.9677 | 0.9712 |
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+ | 0.0712 | 10.0 | 19450 | 0.1126 | 0.9664 | 0.9722 | 0.9693 | 0.9724 |
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+ | 0.0656 | 11.0 | 21395 | 0.1144 | 0.9678 | 0.9701 | 0.9690 | 0.9718 |
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+ | 0.0582 | 12.0 | 23340 | 0.1184 | 0.9682 | 0.9696 | 0.9689 | 0.9723 |
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+ | 0.0532 | 13.0 | 25285 | 0.1215 | 0.9686 | 0.9712 | 0.9699 | 0.9727 |
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+ | 0.0485 | 14.0 | 27230 | 0.1269 | 0.9697 | 0.9718 | 0.9707 | 0.9721 |
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+ | 0.0447 | 15.0 | 29175 | 0.1293 | 0.9693 | 0.9717 | 0.9705 | 0.9727 |
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+ | 0.039 | 16.0 | 31120 | 0.1317 | 0.9690 | 0.9719 | 0.9705 | 0.9723 |
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+ | 0.0363 | 17.0 | 33065 | 0.1376 | 0.9689 | 0.9721 | 0.9705 | 0.9724 |
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+ | 0.0333 | 18.0 | 35010 | 0.1396 | 0.9695 | 0.9721 | 0.9708 | 0.9721 |
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+ | 0.0303 | 19.0 | 36955 | 0.1424 | 0.9700 | 0.9740 | 0.9720 | 0.9731 |
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+ | 0.0274 | 20.0 | 38900 | 0.1456 | 0.9700 | 0.9734 | 0.9717 | 0.9736 |
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+ | 0.0262 | 21.0 | 40845 | 0.1499 | 0.9692 | 0.9732 | 0.9712 | 0.9726 |
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+ | 0.0232 | 22.0 | 42790 | 0.1522 | 0.9702 | 0.9732 | 0.9717 | 0.9733 |
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+ | 0.0229 | 23.0 | 44735 | 0.1543 | 0.9706 | 0.9732 | 0.9719 | 0.9736 |
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+ | 0.0214 | 24.0 | 46680 | 0.1543 | 0.9703 | 0.9738 | 0.9721 | 0.9733 |
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+ | 0.0204 | 25.0 | 48625 | 0.1552 | 0.9703 | 0.9736 | 0.9720 | 0.9734 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.0
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+ - Pytorch 2.1.0+cu118
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+ - Datasets 2.14.6
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+ - Tokenizers 0.14.1
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