---
license: apache-2.0

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