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End of training

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README.md ADDED
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+ ---
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+ license: mit
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: clickbait_binary_detection_DeBERTa
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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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+ # clickbait_binary_detection_DeBERTa
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+
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+ This model is a fine-tuned version of [microsoft/deberta-v3-large](https://huggingface.co/microsoft/deberta-v3-large) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.7269
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+ - Macro F1: 0.9010
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+ - Micro F1: 0.9069
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+ - Accuracy: 0.9069
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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-06
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+ - train_batch_size: 4
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - gradient_accumulation_steps: 2
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+ - total_train_batch_size: 8
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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: 10
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Macro F1 | Micro F1 | Accuracy |
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+ |:-------------:|:-----:|:-----:|:---------------:|:--------:|:--------:|:--------:|
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+ | 0.2692 | 1.0 | 5475 | 0.2676 | 0.9051 | 0.9142 | 0.9142 |
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+ | 0.2492 | 2.0 | 10951 | 0.3331 | 0.9078 | 0.9156 | 0.9156 |
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+ | 0.2189 | 3.0 | 16426 | 0.3909 | 0.9107 | 0.9169 | 0.9169 |
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+ | 0.1769 | 4.0 | 21902 | 0.3799 | 0.9114 | 0.9178 | 0.9178 |
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+ | 0.1479 | 5.0 | 27377 | 0.5103 | 0.8980 | 0.9032 | 0.9032 |
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+ | 0.108 | 6.0 | 32853 | 0.5215 | 0.9123 | 0.9183 | 0.9183 |
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+ | 0.0957 | 7.0 | 38328 | 0.6549 | 0.8974 | 0.9028 | 0.9028 |
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+ | 0.0773 | 8.0 | 43804 | 0.6768 | 0.9044 | 0.9101 | 0.9101 |
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+ | 0.0586 | 9.0 | 49279 | 0.6837 | 0.9023 | 0.9083 | 0.9083 |
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+ | 0.0439 | 10.0 | 54750 | 0.7269 | 0.9010 | 0.9069 | 0.9069 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.27.1
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+ - Pytorch 2.0.1+cu118
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+ - Datasets 2.9.0
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+ - Tokenizers 0.13.3
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