AI_text_detection – Dataset by Varun53 | AlphaNeural AI

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Varun53/
AI_text_detection

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roberta-large-AI-detection

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

Loss: 0.5246
Accuracy: 0.7574
Recall: 0.8155
Precision: 0.7625
F1: 0.7881

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: 5e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Recall	Precision	F1
0.6903	1.0	197	0.6773	0.5533	1.0	0.5533	0.7124
0.5917	2.0	394	0.6918	0.7189	0.8503	0.7035	0.7700
0.6437	3.0	591	0.5689	0.7485	0.8209	0.7488	0.7832
0.5568	4.0	788	0.5246	0.7574	0.8155	0.7625	0.7881
0.6706	5.0	985	0.6416	0.7870	0.8690	0.7738	0.8186

Framework versions

Transformers 4.38.2
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2