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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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- f1 |
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- precision |
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- recall |
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model-index: |
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- name: clickbait_binary_detection |
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results: [] |
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datasets: |
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- christinacdl/clickbait_notclickbait_dataset |
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language: |
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- en |
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pipeline_tag: text-classification |
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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 |
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This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4630 |
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- Macro F1: 0.9155 |
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- Micro F1: 0.9215 |
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- Accuracy: 0.9215 |
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Performance on test set: |
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- Accuracy: 0.9257990867579908 |
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- F1 score: 0.9199282431058413 |
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- Precision: 0.9233793490724882 |
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- Recall : 0.9168756883647268 |
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- Matthews Correlation Coefficient: 0.8402298675576902 |
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- Precision of each class: [0.931899 0.91485969] |
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- Recall of each class: [0.95152505 0.88222632] |
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- F1 score of each class: [0.94160977 0.89824671] |
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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: 6 |
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- eval_batch_size: 10 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 12 |
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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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| 0.2296 | 1.0 | 3650 | 0.2236 | 0.9105 | 0.9183 | 0.9183 | |
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| 0.228 | 2.0 | 7301 | 0.2708 | 0.9115 | 0.9192 | 0.9192 | |
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| 0.2075 | 3.0 | 10951 | 0.3141 | 0.9164 | 0.9224 | 0.9224 | |
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| 0.1881 | 4.0 | 14602 | 0.3211 | 0.9143 | 0.9201 | 0.9201 | |
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| 0.18 | 5.0 | 18252 | 0.3852 | 0.9130 | 0.9188 | 0.9188 | |
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| 0.1818 | 6.0 | 21903 | 0.3784 | 0.9110 | 0.9174 | 0.9174 | |
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| 0.1495 | 7.0 | 25553 | 0.4606 | 0.9106 | 0.9156 | 0.9156 | |
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| 0.1453 | 8.0 | 29204 | 0.4630 | 0.9155 | 0.9215 | 0.9215 | |
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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 |
