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spellcorrector_0511_v3_30_epoch

Token Classification
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canine
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  1. README.md +95 -0
  2. model.safetensors +1 -1
  3. runs/Nov05_21-35-02_702a8d08e357/events.out.tfevents.1699220103.702a8d08e357.2847.3 +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_v3_30_epoch
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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_v3_30_epoch
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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: 0.1888
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+ - Precision: 0.9708
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+ - Recall: 0.9751
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+ - F1: 0.9730
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+ - Accuracy: 0.9745
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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: 30
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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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+ | 0.2233 | 1.0 | 1945 | 0.1721 | 0.9292 | 0.9619 | 0.9453 | 0.9570 |
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+ | 0.1589 | 2.0 | 3890 | 0.1346 | 0.9455 | 0.9670 | 0.9561 | 0.9646 |
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+ | 0.1387 | 3.0 | 5835 | 0.1208 | 0.9545 | 0.9684 | 0.9614 | 0.9680 |
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+ | 0.1201 | 4.0 | 7780 | 0.1173 | 0.9620 | 0.9616 | 0.9618 | 0.9682 |
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+ | 0.1067 | 5.0 | 9725 | 0.1138 | 0.9628 | 0.9662 | 0.9645 | 0.9699 |
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+ | 0.0951 | 6.0 | 11670 | 0.1096 | 0.9653 | 0.9680 | 0.9666 | 0.9714 |
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+ | 0.0864 | 7.0 | 13615 | 0.1122 | 0.9673 | 0.9663 | 0.9668 | 0.9715 |
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+ | 0.0757 | 8.0 | 15560 | 0.1141 | 0.9680 | 0.9699 | 0.9689 | 0.9719 |
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+ | 0.0676 | 9.0 | 17505 | 0.1154 | 0.9687 | 0.9718 | 0.9703 | 0.9723 |
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+ | 0.0606 | 10.0 | 19450 | 0.1193 | 0.9679 | 0.9730 | 0.9705 | 0.9731 |
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+ | 0.0548 | 11.0 | 21395 | 0.1246 | 0.9701 | 0.9696 | 0.9698 | 0.9724 |
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+ | 0.0478 | 12.0 | 23340 | 0.1279 | 0.9708 | 0.9705 | 0.9706 | 0.9730 |
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+ | 0.0417 | 13.0 | 25285 | 0.1316 | 0.9707 | 0.9706 | 0.9706 | 0.9733 |
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+ | 0.0375 | 14.0 | 27230 | 0.1387 | 0.9706 | 0.9734 | 0.9720 | 0.9729 |
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+ | 0.0334 | 15.0 | 29175 | 0.1405 | 0.9704 | 0.9748 | 0.9726 | 0.9741 |
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+ | 0.0292 | 16.0 | 31120 | 0.1450 | 0.9704 | 0.9736 | 0.9720 | 0.9733 |
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+ | 0.0261 | 17.0 | 33065 | 0.1492 | 0.9684 | 0.9744 | 0.9714 | 0.9734 |
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+ | 0.0233 | 18.0 | 35010 | 0.1529 | 0.9701 | 0.9755 | 0.9728 | 0.9739 |
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+ | 0.0205 | 19.0 | 36955 | 0.1580 | 0.9708 | 0.9733 | 0.9720 | 0.9735 |
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+ | 0.0174 | 20.0 | 38900 | 0.1636 | 0.9710 | 0.9749 | 0.9729 | 0.9741 |
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+ | 0.0166 | 21.0 | 40845 | 0.1674 | 0.9700 | 0.9763 | 0.9732 | 0.9742 |
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+ | 0.0142 | 22.0 | 42790 | 0.1729 | 0.9706 | 0.9742 | 0.9724 | 0.9733 |
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+ | 0.0126 | 23.0 | 44735 | 0.1737 | 0.9711 | 0.9742 | 0.9726 | 0.9743 |
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+ | 0.0116 | 24.0 | 46680 | 0.1788 | 0.9706 | 0.9762 | 0.9734 | 0.9747 |
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+ | 0.0102 | 25.0 | 48625 | 0.1808 | 0.9712 | 0.9750 | 0.9731 | 0.9745 |
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+ | 0.0093 | 26.0 | 50570 | 0.1817 | 0.9710 | 0.9741 | 0.9725 | 0.9742 |
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+ | 0.0082 | 27.0 | 52515 | 0.1838 | 0.9706 | 0.9748 | 0.9727 | 0.9741 |
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+ | 0.0082 | 28.0 | 54460 | 0.1865 | 0.9711 | 0.9754 | 0.9733 | 0.9745 |
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+ | 0.0076 | 29.0 | 56405 | 0.1873 | 0.9706 | 0.9753 | 0.9729 | 0.9745 |
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+ | 0.0069 | 30.0 | 58350 | 0.1888 | 0.9708 | 0.9751 | 0.9730 | 0.9745 |
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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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