---
license: apache-2.0
language:
- en
library_name: adapter-transformers
---
## 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