Artef
/

X-ray-ai-detection

Image Classification

Generated from Trainer

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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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Safetensors

Model size

86.8M params

Tensor type

I64

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F32

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Model tree for Artef/X-ray-ai-detection

Base model

umm-maybe/AI-image-detector

Finetuned

(2)

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