| --- |
| license: mit |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| - f1 |
| - precision |
| - recall |
| model-index: |
| - name: clickbait_binary_detection |
| results: [] |
| datasets: |
| - christinacdl/clickbait_notclickbait_dataset |
| language: |
| - en |
| pipeline_tag: text-classification |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # clickbait_binary_detection |
|
|
| This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.4630 |
| - Macro F1: 0.9155 |
| - Micro F1: 0.9215 |
| - Accuracy: 0.9215 |
|
|
|
|
| Performance on test set: |
|
|
| - Accuracy: 0.9257990867579908 |
| |
| - F1 score: 0.9199282431058413 |
|
|
| - Precision: 0.9233793490724882 |
|
|
| - Recall : 0.9168756883647268 |
|
|
| - Matthews Correlation Coefficient: 0.8402298675576902 |
|
|
| - Precision of each class: [0.931899 0.91485969] |
|
|
| - Recall of each class: [0.95152505 0.88222632] |
|
|
| - F1 score of each class: [0.94160977 0.89824671] |
|
|
|
|
| ## Model description |
|
|
| More information needed |
|
|
| ## Intended uses & limitations |
|
|
| More information needed |
|
|
| ## Training and evaluation data |
|
|
| More information needed |
|
|
| ## Training procedure |
|
|
| ### Training hyperparameters |
|
|
| The following hyperparameters were used during training: |
| - learning_rate: 2e-06 |
| - train_batch_size: 6 |
| - eval_batch_size: 10 |
| - seed: 42 |
| - gradient_accumulation_steps: 2 |
| - total_train_batch_size: 12 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 10 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Macro F1 | Micro F1 | Accuracy | |
| |:-------------:|:-----:|:-----:|:---------------:|:--------:|:--------:|:--------:| |
| | 0.2296 | 1.0 | 3650 | 0.2236 | 0.9105 | 0.9183 | 0.9183 | |
| | 0.228 | 2.0 | 7301 | 0.2708 | 0.9115 | 0.9192 | 0.9192 | |
| | 0.2075 | 3.0 | 10951 | 0.3141 | 0.9164 | 0.9224 | 0.9224 | |
| | 0.1881 | 4.0 | 14602 | 0.3211 | 0.9143 | 0.9201 | 0.9201 | |
| | 0.18 | 5.0 | 18252 | 0.3852 | 0.9130 | 0.9188 | 0.9188 | |
| | 0.1818 | 6.0 | 21903 | 0.3784 | 0.9110 | 0.9174 | 0.9174 | |
| | 0.1495 | 7.0 | 25553 | 0.4606 | 0.9106 | 0.9156 | 0.9156 | |
| | 0.1453 | 8.0 | 29204 | 0.4630 | 0.9155 | 0.9215 | 0.9215 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.27.1 |
| - Pytorch 2.0.1+cu118 |
| - Datasets 2.9.0 |
| - Tokenizers 0.13.3 |
