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About this paper
Konstantinos I. Roumeliotis, Nikolaos D. Tselikas, Dimitrios K. Nasiopoulos
The authors evaluate staged GPT-4o fine-tuning on labeled product images for 30-category classification. They divide training data into four increments, continuing from each prior checkpoint. On 180 test images, the Phase 3 model using 400-pixel images reaches 87.78% accuracy, versus 75% for zero-shot GPT-4o and 60% for tuned ConvNeXt-tiny. Progression’s causal role remains unestablished.
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