| | --- |
| | license: apache-2.0 |
| | base_model: albert/albert-base-v2 |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | - f1 |
| | - precision |
| | - recall |
| | model-index: |
| | - name: classify-clickbait |
| | results: [] |
| | --- |
| | |
| | <!-- 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. --> |
| |
|
| | # classify-clickbait |
| |
|
| | This model is a fine-tuned version of [albert/albert-base-v2](https://huggingface.co/albert/albert-base-v2) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.0010 |
| | - Accuracy: 1.0 |
| | - F1: 1.0 |
| | - Precision: 1.0 |
| | - Recall: 1.0 |
| | - Accuracy Label Clickbait: 1.0 |
| | - Accuracy Label Factual: 1.0 |
| |
|
| | ## 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-05 |
| | - train_batch_size: 16 |
| | - eval_batch_size: 16 |
| | - seed: 42 |
| | - gradient_accumulation_steps: 2 |
| | - total_train_batch_size: 32 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - lr_scheduler_warmup_steps: 500 |
| | - num_epochs: 3 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | Accuracy Label Clickbait | Accuracy Label Factual | |
| | |:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:------------------------:|:----------------------:| |
| | | 0.1089 | 1.1628 | 100 | 0.0617 | 0.9884 | 0.9884 | 0.9884 | 0.9884 | 0.9828 | 0.9941 | |
| | | 0.0118 | 2.3256 | 200 | 0.0093 | 0.9971 | 0.9971 | 0.9971 | 0.9971 | 0.9943 | 1.0 | |
| |
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| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.41.1 |
| | - Pytorch 2.3.0+cu121 |
| | - Datasets 2.19.1 |
| | - Tokenizers 0.19.1 |
| |
|
