This model is a fine-tuned version of bert-base-multilingual-cased on the id_clickbait dataset. It achieves the following results on the evaluation set:

Loss: 1.2628
Accuracy: 0.8025

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
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.51	1.0	675	0.4566	0.7792
0.419	2.0	1350	0.4388	0.7908
0.2972	3.0	2025	0.5607	0.8017
0.2428	4.0	2700	0.5913	0.7983
0.2086	5.0	3375	0.8132	0.7883
0.1564	6.0	4050	0.9334	0.7917
0.1114	7.0	4725	1.0183	0.7975
0.1023	8.0	5400	1.1756	0.8008
0.0649	9.0	6075	1.2468	0.7975
0.0465	10.0	6750	1.2628	0.8025

Framework versions

Transformers 4.27.4
Pytorch 2.0.0+cu118
Datasets 2.11.0
Tokenizers 0.13.3

intanm/clickbait-classifier-20230408-002

clickbait-classifier-20230408-002

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

intanm/
clickbait-classifier-20230408-002