README.md

Model Training Report

Model Details

• Model: ResNet50
• Number of Classes: 12
• Total Epochs: 15
• Optimizer: Adam
• Learning Rate: 0.001
• Loss Function: CrossEntropyLoss

Training Accuracy per Epoch

Epoch	Training Accuracy (%)
1	58.32
2	63.15
3	69.45
4	74.21
5	77.58
6	80.32
7	82.01
8	83.50
9	84.72
10	85.30
11	86.85
12	87.20
13	88.10
14	89.25
15	90.30

Test Results

• Average Test Loss: 0.1985
• Test Accuracy: 91.76%

Additional Notes

• The model achieved 91.76% on the test set, exceeding the 90% target.
• Training improvements were consistent, with significant gains in accuracy from epoch 5 onwards.
• This was achieved using a pre-trained ResNet50 model fine-tuned on the building classification dataset.
• Further fine-tuning or dataset expansion might improve the model even more.
• the dataset that is used for training is from kaggle :https://www.kaggle.com/datasets/balabaskar/wonders-of-the-world-image-classification?resource=download """