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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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<!-- 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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# clickbait_binary_detection_DeBERTa |
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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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## 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-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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### Training results |
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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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### Framework versions |
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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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