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| # image_classification(trash_classification) | |
| This model is a fine-tuned version of resnet50. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.591041 | |
| - Accuracy: 0.848 | |
| ## Model description | |
| More information needed | |
| ## Intended uses & limitations | |
| More information needed | |
| ## Training and evaluation data | |
| -Epoch 1/15, Loss: 1.460609, Test accuracy: 0.4246666666666667 | |
| -Epoch 2/15, Loss: 1.285436, Test accuracy: 0.628 | |
| -Epoch 3/15, Loss: 1.083138, Test accuracy: 0.7173333333333334 | |
| -Epoch 4/15, Loss: 0.940875, Test accuracy: 0.7366666666666667 | |
| -Epoch 5/15, Loss: 0.880119, Test accuracy: 0.7546666666666667 | |
| -Epoch 6/15, Loss: 0.763511, Test accuracy: 0.782 | |
| -Epoch 7/15, Loss: 0.728582, Test accuracy: 0.7926666666666666 | |
| -Epoch 8/15, Loss: 0.742196, Test accuracy: 0.808 | |
| -Epoch 9/15, Loss: 0.680452, Test accuracy: 0.8166666666666667 | |
| -Epoch 10/15, Loss: 0.619245, Test accuracy: 0.8226666666666667 | |
| -Epoch 11/15, Loss: 0.690268, Test accuracy: 0.828 | |
| -Epoch 12/15, Loss: 0.623389, Test accuracy: 0.84 | |
| -Epoch 13/15, Loss: 0.595914, Test accuracy: 0.8413333333333334 | |
| -Epoch 14/15, Loss: 0.531754, Test accuracy: 0.846 | |
| -Epoch 15/15, Loss: 0.591041, Test accuracy: 0.8486666666666667 | |