Built and deployed a deepfake audio detector as a diploma student - F1 0.90, EER 8.23%

hey, i'm a 3rd year diploma cs student and i built a deepfake audio detector end to end - model training, backend API, frontend, explainability, and monitoring. the model is efficientnet-b0 trained on mel spectrograms using the asvspoof 2019 la dataset. evaluated on the full test set (71,237 samples, real unbalanced distribution): f1: 0.9033 precision: 0.9995 recall: 0.8240 eer: 8.23% (comparable to the official lfcc-gmm baseline published with the dataset) threshold: 0.3 one thing worth noting - val accuracy hits ~100% during training which looks suspicious but it's expected. the val set is a