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datasets:
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- DataScienceProject/Art_Images_Ai_And_Real_
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library_name: keras
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---
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# Model Card for Model ID
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## Evaluation
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### Testing Data, Factors & Metrics
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confusion_matrix
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accuracy
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#### Testing Data
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#### Factors
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#### Metrics
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### Results
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datasets:
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- DataScienceProject/Art_Images_Ai_And_Real_
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library_name: keras
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language:
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- en
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pipeline_tag: image-classification
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---
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# Model Card for Model ID
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## Evaluation
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The model takes 7-10 minutes to run , based on our dataset , equipped with pc hardware: i9 13900 , 32gb ram , rtx 3080
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your mileage may vary.
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### Testing Data, Factors & Metrics
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confusion_matrix
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accuracy
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### Results
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test accuracy = 0.853
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precision = 0.866
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recall = 0.8357
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f1 = 0.8509
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#### Summary
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The model preforms well and meet our initial goal ,thus this model can handle the task of image classification real image vs ai generated image.
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