epoch, train/loss, metrics/accuracy_top1, metrics/accuracy_top5, val/loss, lr/pg0, lr/pg1, lr/pg2 1, 0.10874, 0.9838, 0.9982, 4.5731, 0.0033292, 0.0033292, 0.0033292 2, 0.1148, 0.97765, 0.99775, 4.582, 0.0063327, 0.0063327, 0.0063327 3, 0.18212, 0.95289, 0.99145, 4.6177, 0.0090062, 0.0090062, 0.0090062 4, 0.2902, 0.96002, 0.99437, 4.6062, 0.008515, 0.008515, 0.008515 5, 0.25844, 0.96422, 0.99542, 4.602, 0.008515, 0.008515, 0.008515 6, 0.22865, 0.97044, 0.99617, 4.5933, 0.00802, 0.00802, 0.00802 7, 0.20787, 0.97442, 0.99685, 4.5874, 0.007525, 0.007525, 0.007525 8, 0.18537, 0.97697, 0.99707, 4.5828, 0.00703, 0.00703, 0.00703 9, 0.17489, 0.9805, 0.99752, 4.5769, 0.006535, 0.006535, 0.006535 10, 0.15562, 0.98267, 0.99812, 4.5758, 0.00604, 0.00604, 0.00604 11, 0.14943, 0.9826, 0.99812, 4.5749, 0.005545, 0.005545, 0.005545 12, 0.13509, 0.98455, 0.99812, 4.5721, 0.00505, 0.00505, 0.00505 13, 0.12734, 0.9847, 0.99812, 4.5712, 0.004555, 0.004555, 0.004555 14, 0.1194, 0.98582, 0.9985, 4.5698, 0.00406, 0.00406, 0.00406 15, 0.11144, 0.9868, 0.99857, 4.5683, 0.003565, 0.003565, 0.003565 16, 0.10575, 0.98762, 0.99842, 4.5676, 0.00307, 0.00307, 0.00307 17, 0.09393, 0.98747, 0.9985, 4.5673, 0.002575, 0.002575, 0.002575 18, 0.08822, 0.9871, 0.9985, 4.568, 0.00208, 0.00208, 0.00208 19, 0.08305, 0.98732, 0.9985, 4.5672, 0.001585, 0.001585, 0.001585 20, 0.07704, 0.98717, 0.99842, 4.5667, 0.00109, 0.00109, 0.00109