| NUM_GPUS=1 | |
| MASTER_ADDR=ip-10-0-136-246 | |
| MASTER_PORT=16668 | |
| WORLD_SIZE=1 | |
| PID of this process = 565724 | |
| ------ ARGS ------- | |
| Namespace(model_suffix='beta', hcp_flat_path='/weka/proj-medarc/shared/HCP-Flat', batch_size=128, wandb_log=True, num_epochs=20, lr_scheduler_type='cycle', save_ckpt=False, seed=42, max_lr=0.1, target='sex', num_workers=15, weight_decay=1e-05) | |
| Input dimension: 737280 | |
| total_steps 17400 | |
| wandb_config: | |
| {'model_name': 'HCPflat_raw_sex', 'batch_size': 128, 'weight_decay': 1e-05, 'num_epochs': 20, 'seed': 42, 'lr_scheduler_type': 'cycle', 'save_ckpt': False, 'max_lr': 0.1, 'target': 'sex', 'num_workers': 15} | |
| wandb_id: HCPflat_raw_beta_sex_83810 | |
| Step [100/870] - Training Loss: 24.6087 - Training Accuracy: 52.39% | |
| Step [200/870] - Training Loss: 28.9030 - Training Accuracy: 52.85% | |
| Step [300/870] - Training Loss: 50.2400 - Training Accuracy: 53.05% | |
| Step [400/870] - Training Loss: 74.8264 - Training Accuracy: 53.27% | |
| Step [500/870] - Training Loss: 91.1850 - Training Accuracy: 53.40% | |
| Step [600/870] - Training Loss: 165.0463 - Training Accuracy: 53.63% | |
| Step [700/870] - Training Loss: 201.5126 - Training Accuracy: 53.66% | |
| Step [800/870] - Training Loss: 209.5273 - Training Accuracy: 53.74% | |
| Epoch [1/20] - Training Loss: 110.8142, Training Accuracy: 53.88% - Validation Loss: 296.1424, Validation Accuracy: 53.70% | |
| Step [100/870] - Training Loss: 298.0217 - Training Accuracy: 66.52% | |
| Step [200/870] - Training Loss: 265.3320 - Training Accuracy: 65.68% | |
| Step [300/870] - Training Loss: 293.1298 - Training Accuracy: 64.77% | |
| Step [400/870] - Training Loss: 553.0426 - Training Accuracy: 64.16% | |
| Step [500/870] - Training Loss: 594.5250 - Training Accuracy: 63.51% | |
| Step [600/870] - Training Loss: 708.0252 - Training Accuracy: 62.87% | |
| Step [700/870] - Training Loss: 722.7825 - Training Accuracy: 62.39% | |
| Step [800/870] - Training Loss: 798.4144 - Training Accuracy: 61.97% | |
| Epoch [2/20] - Training Loss: 449.1676, Training Accuracy: 61.70% - Validation Loss: 808.8942, Validation Accuracy: 54.41% | |
| Step [100/870] - Training Loss: 396.8062 - Training Accuracy: 75.48% | |
| Step [200/870] - Training Loss: 465.8516 - Training Accuracy: 75.21% | |
| Step [300/870] - Training Loss: 334.3605 - Training Accuracy: 75.27% | |
| Step [400/870] - Training Loss: 362.5482 - Training Accuracy: 74.79% | |
| Step [500/870] - Training Loss: 458.4806 - Training Accuracy: 74.32% | |
| Step [600/870] - Training Loss: 336.7921 - Training Accuracy: 73.79% | |
| Step [700/870] - Training Loss: 595.4280 - Training Accuracy: 73.40% | |
| Step [800/870] - Training Loss: 591.4528 - Training Accuracy: 73.04% | |
| Epoch [3/20] - Training Loss: 434.5445, Training Accuracy: 72.76% - Validation Loss: 1042.0977, Validation Accuracy: 54.73% | |
| Step [100/870] - Training Loss: 270.8356 - Training Accuracy: 83.11% | |
| Step [200/870] - Training Loss: 361.4072 - Training Accuracy: 83.15% | |
| Step [300/870] - Training Loss: 275.5848 - Training Accuracy: 82.82% | |
| Step [400/870] - Training Loss: 307.0319 - Training Accuracy: 82.44% | |
| Step [500/870] - Training Loss: 326.9714 - Training Accuracy: 82.14% | |
| Step [600/870] - Training Loss: 271.0794 - Training Accuracy: 81.70% | |
| Step [700/870] - Training Loss: 260.8827 - Training Accuracy: 81.37% | |
| Step [800/870] - Training Loss: 419.5749 - Training Accuracy: 81.08% | |
| Epoch [4/20] - Training Loss: 296.3454, Training Accuracy: 80.79% - Validation Loss: 1187.6379, Validation Accuracy: 55.25% | |
| Step [100/870] - Training Loss: 214.9724 - Training Accuracy: 87.92% | |
| Step [200/870] - Training Loss: 77.4744 - Training Accuracy: 87.77% | |
| Step [300/870] - Training Loss: 149.2222 - Training Accuracy: 87.47% | |
| Step [400/870] - Training Loss: 141.0663 - Training Accuracy: 87.16% | |
| Step [500/870] - Training Loss: 231.0289 - Training Accuracy: 86.83% | |
| Step [600/870] - Training Loss: 186.0840 - Training Accuracy: 86.38% | |
| Step [700/870] - Training Loss: 163.8004 - Training Accuracy: 85.99% | |
| Step [800/870] - Training Loss: 304.4012 - Training Accuracy: 85.70% | |
| Epoch [5/20] - Training Loss: 211.2076, Training Accuracy: 85.50% - Validation Loss: 1311.0324, Validation Accuracy: 55.02% | |
| Step [100/870] - Training Loss: 112.8653 - Training Accuracy: 90.42% | |
| Step [200/870] - Training Loss: 182.0056 - Training Accuracy: 90.31% | |
| Step [300/870] - Training Loss: 151.2417 - Training Accuracy: 90.17% | |
| Step [400/870] - Training Loss: 174.8410 - Training Accuracy: 89.76% | |
| Step [500/870] - Training Loss: 164.9281 - Training Accuracy: 89.42% | |
| Step [600/870] - Training Loss: 176.1206 - Training Accuracy: 89.19% | |
| Step [700/870] - Training Loss: 189.1104 - Training Accuracy: 88.92% | |
| Step [800/870] - Training Loss: 164.0583 - Training Accuracy: 88.64% | |
| Epoch [6/20] - Training Loss: 161.3509, Training Accuracy: 88.49% - Validation Loss: 1458.8603, Validation Accuracy: 54.97% | |
| Step [100/870] - Training Loss: 96.9147 - Training Accuracy: 91.70% | |
| Step [200/870] - Training Loss: 89.6436 - Training Accuracy: 91.68% | |
| Step [300/870] - Training Loss: 88.9899 - Training Accuracy: 91.55% | |
| Step [400/870] - Training Loss: 90.7214 - Training Accuracy: 91.36% | |
| Step [500/870] - Training Loss: 246.9420 - Training Accuracy: 91.10% | |
| Step [600/870] - Training Loss: 143.6372 - Training Accuracy: 90.95% | |
| Step [700/870] - Training Loss: 132.4662 - Training Accuracy: 90.78% | |
| Step [800/870] - Training Loss: 199.1868 - Training Accuracy: 90.55% | |
| Epoch [7/20] - Training Loss: 130.6820, Training Accuracy: 90.41% - Validation Loss: 1515.6320, Validation Accuracy: 55.45% | |
| Step [100/870] - Training Loss: 40.2281 - Training Accuracy: 93.41% | |
| Step [200/870] - Training Loss: 31.9451 - Training Accuracy: 93.21% | |
| Step [300/870] - Training Loss: 51.2280 - Training Accuracy: 93.23% | |
| Step [400/870] - Training Loss: 100.9511 - Training Accuracy: 93.02% | |
| Step [500/870] - Training Loss: 103.3127 - Training Accuracy: 92.90% | |
| Step [600/870] - Training Loss: 152.1203 - Training Accuracy: 92.78% | |
| Step [700/870] - Training Loss: 108.2650 - Training Accuracy: 92.67% | |
| Step [800/870] - Training Loss: 93.6054 - Training Accuracy: 92.52% | |
| Epoch [8/20] - Training Loss: 96.2420, Training Accuracy: 92.41% - Validation Loss: 1629.8896, Validation Accuracy: 55.26% | |
| Step [100/870] - Training Loss: 48.9615 - Training Accuracy: 95.19% | |
| Step [200/870] - Training Loss: 37.2198 - Training Accuracy: 95.09% | |
| Step [300/870] - Training Loss: 57.5891 - Training Accuracy: 94.78% | |
| Step [400/870] - Training Loss: 116.6951 - Training Accuracy: 94.65% | |
| Step [500/870] - Training Loss: 106.4395 - Training Accuracy: 94.49% | |
| Step [600/870] - Training Loss: 67.2050 - Training Accuracy: 94.33% | |
| Step [700/870] - Training Loss: 29.4207 - Training Accuracy: 94.26% | |
| Step [800/870] - Training Loss: 19.4606 - Training Accuracy: 94.18% | |
| Epoch [9/20] - Training Loss: 70.5700, Training Accuracy: 94.06% - Validation Loss: 1667.6055, Validation Accuracy: 54.94% | |
| Step [100/870] - Training Loss: 133.2186 - Training Accuracy: 95.77% | |
| Step [200/870] - Training Loss: 39.1579 - Training Accuracy: 96.05% | |
| Step [300/870] - Training Loss: 19.6516 - Training Accuracy: 95.85% | |
| Step [400/870] - Training Loss: 14.1961 - Training Accuracy: 95.73% | |
| Step [500/870] - Training Loss: 69.0657 - Training Accuracy: 95.66% | |
| Step [600/870] - Training Loss: 86.5776 - Training Accuracy: 95.54% | |
| Step [700/870] - Training Loss: 40.0283 - Training Accuracy: 95.48% | |
| Step [800/870] - Training Loss: 74.8730 - Training Accuracy: 95.35% | |
| Epoch [10/20] - Training Loss: 51.8441, Training Accuracy: 95.28% - Validation Loss: 1732.3389, Validation Accuracy: 55.58% | |
| Step [100/870] - Training Loss: 15.9613 - Training Accuracy: 97.03% | |
| Step [200/870] - Training Loss: 17.7464 - Training Accuracy: 96.98% | |
| Step [300/870] - Training Loss: 22.3283 - Training Accuracy: 96.74% | |
| Step [400/870] - Training Loss: 38.1730 - Training Accuracy: 96.69% | |
| Step [500/870] - Training Loss: 4.6681 - Training Accuracy: 96.59% | |
| Step [600/870] - Training Loss: 28.4868 - Training Accuracy: 96.55% | |
| Step [700/870] - Training Loss: 55.0123 - Training Accuracy: 96.50% | |
| Step [800/870] - Training Loss: 26.6057 - Training Accuracy: 96.43% | |
| Epoch [11/20] - Training Loss: 36.3423, Training Accuracy: 96.41% - Validation Loss: 1742.7579, Validation Accuracy: 55.19% | |
| Step [100/870] - Training Loss: 8.1488 - Training Accuracy: 97.70% | |
| Step [200/870] - Training Loss: 18.2396 - Training Accuracy: 97.66% | |
| Step [300/870] - Training Loss: 0.0000 - Training Accuracy: 97.64% | |
| Step [400/870] - Training Loss: 2.1231 - Training Accuracy: 97.49% | |
| Step [500/870] - Training Loss: 8.7330 - Training Accuracy: 97.50% | |
| Step [600/870] - Training Loss: 15.5849 - Training Accuracy: 97.42% | |
| Step [700/870] - Training Loss: 5.5085 - Training Accuracy: 97.39% | |
| Step [800/870] - Training Loss: 93.1239 - Training Accuracy: 97.39% | |
| Epoch [12/20] - Training Loss: 23.7009, Training Accuracy: 97.35% - Validation Loss: 1784.1253, Validation Accuracy: 55.40% | |
| Step [100/870] - Training Loss: 4.8382 - Training Accuracy: 98.20% | |
| Step [200/870] - Training Loss: 25.5308 - Training Accuracy: 98.27% | |
| Step [300/870] - Training Loss: 11.4365 - Training Accuracy: 98.38% | |
| Step [400/870] - Training Loss: 0.1192 - Training Accuracy: 98.33% | |
| Step [500/870] - Training Loss: 13.1149 - Training Accuracy: 98.35% | |
| Step [600/870] - Training Loss: 0.7187 - Training Accuracy: 98.30% | |
| Step [700/870] - Training Loss: 18.9833 - Training Accuracy: 98.26% | |
| Step [800/870] - Training Loss: 10.3944 - Training Accuracy: 98.25% | |
| Epoch [13/20] - Training Loss: 12.9698, Training Accuracy: 98.21% - Validation Loss: 1779.4520, Validation Accuracy: 55.43% | |
| Step [100/870] - Training Loss: 0.2771 - Training Accuracy: 98.88% | |
| Step [200/870] - Training Loss: 6.9764 - Training Accuracy: 98.95% | |
| Step [300/870] - Training Loss: 6.0478 - Training Accuracy: 98.99% | |
| Step [400/870] - Training Loss: 7.7897 - Training Accuracy: 98.92% | |
| Step [500/870] - Training Loss: 0.0729 - Training Accuracy: 98.92% | |
| Step [600/870] - Training Loss: 24.3455 - Training Accuracy: 98.91% | |
| Step [700/870] - Training Loss: 3.5273 - Training Accuracy: 98.91% | |
| Step [800/870] - Training Loss: 1.3470 - Training Accuracy: 98.88% | |
| Epoch [14/20] - Training Loss: 6.8809, Training Accuracy: 98.87% - Validation Loss: 1781.8475, Validation Accuracy: 55.26% | |
| Step [100/870] - Training Loss: 14.5071 - Training Accuracy: 99.46% | |
| Step [200/870] - Training Loss: 15.6453 - Training Accuracy: 99.30% | |
| Step [300/870] - Training Loss: 8.2637 - Training Accuracy: 99.29% | |
| Step [400/870] - Training Loss: 0.0000 - Training Accuracy: 99.34% | |
| Step [500/870] - Training Loss: 0.0000 - Training Accuracy: 99.35% | |
| Step [600/870] - Training Loss: 5.3401 - Training Accuracy: 99.34% | |
| Step [700/870] - Training Loss: 0.0000 - Training Accuracy: 99.30% | |
| Step [800/870] - Training Loss: 2.4279 - Training Accuracy: 99.29% | |
| Epoch [15/20] - Training Loss: 3.5025, Training Accuracy: 99.29% - Validation Loss: 1785.6069, Validation Accuracy: 55.18% | |
| Step [100/870] - Training Loss: 0.0000 - Training Accuracy: 99.59% | |
| Step [200/870] - Training Loss: 0.0000 - Training Accuracy: 99.59% | |
| Step [300/870] - Training Loss: 0.0000 - Training Accuracy: 99.60% | |
| Step [400/870] - Training Loss: 0.0000 - Training Accuracy: 99.59% | |
| Step [500/870] - Training Loss: 0.6290 - Training Accuracy: 99.60% | |
| Step [600/870] - Training Loss: 0.0002 - Training Accuracy: 99.60% | |
| Step [700/870] - Training Loss: 4.8578 - Training Accuracy: 99.60% | |
| Step [800/870] - Training Loss: 5.8444 - Training Accuracy: 99.59% | |
| Epoch [16/20] - Training Loss: 1.6734, Training Accuracy: 99.58% - Validation Loss: 1784.3434, Validation Accuracy: 55.04% | |
| Step [100/870] - Training Loss: 0.0000 - Training Accuracy: 99.81% | |
| Step [200/870] - Training Loss: 0.0000 - Training Accuracy: 99.80% | |
| Step [300/870] - Training Loss: 3.4523 - Training Accuracy: 99.80% | |
| Step [400/870] - Training Loss: 0.0000 - Training Accuracy: 99.79% | |
| Step [500/870] - Training Loss: 2.6484 - Training Accuracy: 99.80% | |
| Step [600/870] - Training Loss: 0.0000 - Training Accuracy: 99.80% | |
| Step [700/870] - Training Loss: 0.0000 - Training Accuracy: 99.80% | |
| Step [800/870] - Training Loss: 0.0000 - Training Accuracy: 99.80% | |
| Epoch [17/20] - Training Loss: 0.6116, Training Accuracy: 99.80% - Validation Loss: 1777.6393, Validation Accuracy: 55.25% | |
| Step [100/870] - Training Loss: 0.0000 - Training Accuracy: 99.90% | |
| Step [200/870] - Training Loss: 0.0000 - Training Accuracy: 99.89% | |
| Step [300/870] - Training Loss: 1.4993 - Training Accuracy: 99.89% | |
| Step [400/870] - Training Loss: 1.9943 - Training Accuracy: 99.89% | |
| Step [500/870] - Training Loss: 0.0000 - Training Accuracy: 99.90% | |
| Step [600/870] - Training Loss: 0.0000 - Training Accuracy: 99.90% | |
| Step [700/870] - Training Loss: 0.0000 - Training Accuracy: 99.90% | |
| Step [800/870] - Training Loss: 0.0000 - Training Accuracy: 99.91% | |
| Epoch [18/20] - Training Loss: 0.1591, Training Accuracy: 99.91% - Validation Loss: 1778.0985, Validation Accuracy: 55.21% | |
| Step [100/870] - Training Loss: 0.0000 - Training Accuracy: 99.95% | |
| Step [200/870] - Training Loss: 0.0000 - Training Accuracy: 99.97% | |
| Step [300/870] - Training Loss: 0.0000 - Training Accuracy: 99.96% | |
| Step [400/870] - Training Loss: 0.0000 - Training Accuracy: 99.97% | |
| Step [500/870] - Training Loss: 0.0000 - Training Accuracy: 99.97% | |
| Step [600/870] - Training Loss: 0.0000 - Training Accuracy: 99.97% | |
| Step [700/870] - Training Loss: 0.0000 - Training Accuracy: 99.98% | |
| Step [800/870] - Training Loss: 0.0000 - Training Accuracy: 99.98% | |
| Epoch [19/20] - Training Loss: 0.0197, Training Accuracy: 99.98% - Validation Loss: 1777.6055, Validation Accuracy: 55.31% | |
| Step [100/870] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [200/870] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [300/870] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [400/870] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [500/870] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [600/870] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [700/870] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [800/870] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Epoch [20/20] - Training Loss: 0.0008, Training Accuracy: 100.00% - Validation Loss: 1777.4007, Validation Accuracy: 55.26% | |
| [1;34mwandb[0m: 🚀 View run [33mHCPflat_raw_beta_sex[0m at: [34mhttps://stability.wandb.io/ckadirt/fMRI-foundation-model/runs/HCPflat_raw_beta_sex_83810[0m | |
| [1;34mwandb[0m: Find logs at: [1;35mwandb/run-20241126_204427-HCPflat_raw_beta_sex_83810/logs[0m | |