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File size: 14,280 Bytes
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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%
wandb: 🚀 View run HCPflat_raw_beta_sex at: https://stability.wandb.io/ckadirt/fMRI-foundation-model/runs/HCPflat_raw_beta_sex_83810
wandb: Find logs at: wandb/run-20241126_204427-HCPflat_raw_beta_sex_83810/logs