clickbait_binary_detection – AI Model by christinacdl | AlphaNeural AI | AlphaNeural AI

You can deploy this model and start earning money today!

christinacdl/
clickbait_binary_detection

like

0

text-classification

generated_from_trainer

christinacdl/clickbait_notclickbait_dataset

autotrain_compatible

endpoints_compatible

Views

No views yet

clickbait_binary_detection

This model is a fine-tuned version of roberta-large on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.4630
Macro F1: 0.9155
Micro F1: 0.9215
Accuracy: 0.9215

Performance on test set:

Accuracy: 0.9257990867579908
F1 score: 0.9199282431058413
Precision: 0.9233793490724882
Recall : 0.9168756883647268
Matthews Correlation Coefficient: 0.8402298675576902
Precision of each class: [0.931899 0.91485969]
Recall of each class: [0.95152505 0.88222632]
F1 score of each class: [0.94160977 0.89824671]

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-06
train_batch_size: 6
eval_batch_size: 10
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 12
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Macro F1	Micro F1	Accuracy
0.2296	1.0	3650	0.2236	0.9105	0.9183	0.9183
0.228	2.0	7301	0.2708	0.9115	0.9192	0.9192
0.2075	3.0	10951	0.3141	0.9164	0.9224	0.9224
0.1881	4.0	14602	0.3211	0.9143	0.9201	0.9201
0.18	5.0	18252	0.3852	0.9130	0.9188	0.9188
0.1818	6.0	21903	0.3784	0.9110	0.9174	0.9174
0.1495	7.0	25553	0.4606	0.9106	0.9156	0.9156
0.1453	8.0	29204	0.4630	0.9155	0.9215	0.9215

Framework versions

Transformers 4.27.1
Pytorch 2.0.1+cu118
Datasets 2.9.0
Tokenizers 0.13.3