results

This model is a fine-tuned version of umm-maybe/AI-image-detector on an unknown dataset. It achieves the following results on the evaluation set:

• eval_loss: 0.1365
• eval_accuracy: 0.9612
• eval_runtime: 20.7986
• eval_samples_per_second: 28.511
• eval_steps_per_second: 3.606
• epoch: 1.86
• step: 550

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: 3

Framework versions

• Transformers 4.37.2
• Pytorch 2.1.0+cu121
• Tokenizers 0.15.2