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--- |
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license: apache-2.0 |
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language: |
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- en |
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library_name: adapter-transformers |
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--- |
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## License |
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license: apache-2.0 |
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## Base-Model |
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base_model: albert/albert-base-v2 tags: |
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### generated_from_trainer metrics: |
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accuracy |
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f1 |
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precision |
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recall model-index: |
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name: classify-clickbait-titll results: [] Identify Clickbait Articles This model is a fine-tuned version of albert/albert-base-v2 on a synthetic dataset with 65% ISIN titles and 35% ISIN_null titles. |
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Model description |
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Built to identify ISIN vs ISIN_null titles. |
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### Intended uses & limitations |
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Use it on any title to understand how the model is interpreting the title, whether it is ISIN or ISIN_null. Go ahead and try a few of your own. |
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### Training and evaluation data |
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It achieves the following results on the evaluation set: Loss: 0.0173 Accuracy: 0.9951 F1: 0.9951 Precision: 0.9951 Recall: 0.9951 Accuracy Label ISIN: 0.95 Accuracy Label ISIN_null: .095 Training procedure Training hyperparameters |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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learning_rate: 2e-05 |
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train_batch_size: 16 |
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eval_batch_size: 16 |
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seed: 42 |
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gradient_accumulation_steps: 2 |
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total_train_batch_size: 32 |
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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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lr_scheduler_warmup_steps: 500 |
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num_epochs: 280 |
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## Framework versions |
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- Transformers 4.43.3 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
