X-ray-ai-detection
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: 0.0077
- eval_accuracy: 0.9983
- eval_runtime: 20.0476
- eval_samples_per_second: 29.53
- eval_steps_per_second: 3.691
- epoch: 2.91
- step: 860
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
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Model tree for Artef/X-ray-ai-detection
Base model
umm-maybe/AI-image-detector