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RoBERTa-Clickbait-Detection – AI Model by christinacdl | AlphaNeural AI
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RoBERTa-Clickbait-Detection
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transformers
safetensors
roberta
text-classification
generated_from_trainer
FacebookAI/roberta-large
finetune
mit
autotrain_compatible
endpoints_compatible
us
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RoBERTa-Clickbait-Detection
This model is a fine-tuned version of
roberta-large
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.1089
Micro F1: 0.9847
Macro F1: 0.9846
Accuracy: 0.9847
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: 1e-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
num_epochs: 4
Training results
Framework versions
Transformers 4.36.1
Pytorch 2.1.0+cu121
Datasets 2.13.1
Tokenizers 0.15.0
