License
license: apache-2.0
Base-Model
base_model: albert/albert-base-v2 tags:
generated_from_trainer metrics:
accuracy f1 precision recall model-index: 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. Model description Built to identify ISIN vs ISIN_null titles.
Intended uses & limitations
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.
Training and evaluation data
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
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: 280
Framework versions
- Transformers 4.43.3
- Datasets 2.20.0
- Tokenizers 0.19.1
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