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DD0101
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disfluency_base_augmented_90_90

Token Classification
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roberta
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+ ---
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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: disfluency-large-3
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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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+ # disfluency-large-3
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+
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+ This model is a fine-tuned version of [vinai/phobert-large](https://huggingface.co/vinai/phobert-large) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0364
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+ - Precision: 0.9849
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+ - Recall: 0.9802
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+ - F1: 0.9825
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+ - Accuracy: 0.9936
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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: 5e-05
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+ - train_batch_size: 32
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+ - eval_batch_size: 32
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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: 50
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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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+ | No log | 1.0 | 140 | 0.0713 | 0.8955 | 0.9165 | 0.9059 | 0.9816 |
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+ | No log | 2.0 | 280 | 0.0334 | 0.9706 | 0.9730 | 0.9718 | 0.9925 |
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+ | No log | 3.0 | 420 | 0.0584 | 0.9656 | 0.9609 | 0.9633 | 0.9880 |
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+ | 0.1335 | 4.0 | 560 | 0.0352 | 0.9742 | 0.9742 | 0.9742 | 0.9922 |
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+ | 0.1335 | 5.0 | 700 | 0.0539 | 0.9651 | 0.9633 | 0.9642 | 0.9894 |
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+ | 0.1335 | 6.0 | 840 | 0.0293 | 0.9730 | 0.9754 | 0.9742 | 0.9924 |
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+ | 0.1335 | 7.0 | 980 | 0.0364 | 0.9849 | 0.9802 | 0.9825 | 0.9936 |
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+ | 0.0146 | 8.0 | 1120 | 0.0343 | 0.9795 | 0.9778 | 0.9786 | 0.9941 |
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+ | 0.0146 | 9.0 | 1260 | 0.0268 | 0.9802 | 0.9814 | 0.9808 | 0.9947 |
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+ | 0.0146 | 10.0 | 1400 | 0.0427 | 0.9682 | 0.9688 | 0.9685 | 0.9918 |
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+ | 0.0076 | 11.0 | 1540 | 0.0429 | 0.9576 | 0.9633 | 0.9605 | 0.9899 |
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+ | 0.0076 | 12.0 | 1680 | 0.0343 | 0.9735 | 0.9730 | 0.9732 | 0.9933 |
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+ | 0.0076 | 13.0 | 1820 | 0.0305 | 0.9801 | 0.9754 | 0.9777 | 0.9939 |
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+ | 0.0076 | 14.0 | 1960 | 0.0437 | 0.9765 | 0.9742 | 0.9753 | 0.9924 |
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+ | 0.0047 | 15.0 | 2100 | 0.0363 | 0.9778 | 0.9778 | 0.9778 | 0.9939 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.29.2
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+ - Pytorch 2.0.1+cu118
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+ - Datasets 2.12.0
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+ - Tokenizers 0.13.3