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- results/celeba_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed47/d10/config.json +26 -0
- results/celeba_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed47/d10/metrics.jsonl +0 -0
- results/celeba_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed47/d10/runner.log +502 -0
- results/celeba_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed47/d100/config.json +26 -0
- results/celeba_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed47/d100/metrics.jsonl +0 -0
- results/celeba_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed47/d100/runner.log +502 -0
- results/celeba_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed47/d20/config.json +26 -0
- results/celeba_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed47/d20/metrics.jsonl +0 -0
- results/celeba_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed47/d20/runner.log +502 -0
- results/celeba_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed47/d30/config.json +26 -0
- results/celeba_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed47/d30/metrics.jsonl +0 -0
- results/celeba_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed47/d30/runner.log +502 -0
- results/celeba_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed47/d40/config.json +26 -0
- results/celeba_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed47/d40/metrics.jsonl +0 -0
- results/celeba_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed47/d40/runner.log +502 -0
- results/celeba_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed47/d50/config.json +26 -0
- results/celeba_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed47/d50/metrics.jsonl +0 -0
- results/celeba_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed47/d50/runner.log +502 -0
- results/celeba_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed47/d60/config.json +26 -0
- results/celeba_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed47/d60/metrics.jsonl +0 -0
- results/celeba_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed47/d60/runner.log +502 -0
- results/celeba_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed47/d70/config.json +26 -0
- results/celeba_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed47/d70/metrics.jsonl +0 -0
- results/celeba_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed47/d70/runner.log +502 -0
- results/celeba_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed47/d80/config.json +26 -0
- results/celeba_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed47/d80/metrics.jsonl +0 -0
- results/celeba_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed47/d80/runner.log +502 -0
- results/celeba_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed47/d90/config.json +26 -0
- results/celeba_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed47/d90/metrics.jsonl +0 -0
- results/celeba_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed47/d90/runner.log +502 -0
- results/cifar10_beta005_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed42/d100/config.json +25 -0
- results/cifar10_beta005_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed42/d100/metrics.jsonl +0 -0
- results/cifar10_beta005_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed42/d100/runner.log +502 -0
- results/cifar10_beta005_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed42/d120/config.json +25 -0
- results/cifar10_beta005_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed42/d120/metrics.jsonl +0 -0
- results/cifar10_beta005_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed42/d120/runner.log +502 -0
- results/cifar10_beta005_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed42/d140/config.json +25 -0
- results/cifar10_beta005_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed42/d140/metrics.jsonl +0 -0
- results/cifar10_beta005_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed42/d140/runner.log +502 -0
- results/cifar10_beta005_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed42/d160/config.json +25 -0
- results/cifar10_beta005_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed42/d160/metrics.jsonl +0 -0
- results/cifar10_beta005_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed42/d160/runner.log +502 -0
- results/cifar10_beta005_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed42/d180/config.json +25 -0
- results/cifar10_beta005_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed42/d180/fid_retry.json +78 -0
- results/cifar10_beta005_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed42/d180/fid_retry.log +6 -0
- results/cifar10_beta005_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed42/d180/metrics.jsonl +0 -0
- results/cifar10_beta005_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed42/d180/runner.log +293 -0
- results/cifar10_beta005_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed42/d20/config.json +25 -0
- results/cifar10_beta005_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed42/d20/metrics.jsonl +0 -0
- results/cifar10_beta005_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed42/d20/runner.log +502 -0
results/celeba_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed47/d10/config.json
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{
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"vae_checkpoint": "vae_checkpoints/celeba_resnet_modernloss_d10/vae.pt",
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"out": "results/celeba_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed47/d10",
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"subset_path": "diagnostics/celeba_diverse_1k_mean_plus_sd/subset_indices.json",
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"train_tar": "/overflow/data/cerberus/celeba_hq_256_partitioned_ws/train/celeba_hq_256-train-0000.tar",
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"n_train": 1000,
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"total_steps": 5000000,
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"eval_interval": 10000,
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"mem_interval": 100000,
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"fid_interval": 100000,
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"fid_n_real": 1000,
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"fid_n_gen": 10000,
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"n_gen_samples": 10000,
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"n_sde_steps": 500,
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"batch_size": 512,
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"hidden": 1024,
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"depth": 5,
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"optimizer": "sgd",
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"lr": 0.001,
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"momentum": 0.8,
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"t_min": 0.01,
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"t_max": 3.0,
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"t_eval": 0.1,
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"seed": 47,
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"device": null
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}
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results/celeba_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed47/d10/metrics.jsonl
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results/celeba_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed47/d10/runner.log
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| 1 |
+
FID real-side stats cached over 1000 diverse train images
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| 2 |
+
step 1 | 72s | train_loss=1.0028 | fid=194.7955
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| 3 |
+
step 10000 | 164s | train_loss=0.9251
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| 4 |
+
step 20000 | 257s | train_loss=0.9213
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| 5 |
+
step 30000 | 349s | train_loss=0.9198
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| 6 |
+
step 40000 | 442s | train_loss=0.9186
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| 7 |
+
step 50000 | 534s | train_loss=0.9178
|
| 8 |
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|
| 9 |
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|
| 10 |
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|
| 11 |
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|
| 12 |
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|
| 13 |
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|
| 14 |
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|
| 15 |
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|
| 16 |
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|
| 17 |
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|
| 18 |
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|
| 19 |
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|
| 20 |
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|
| 21 |
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|
| 22 |
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|
| 23 |
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|
| 24 |
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|
| 25 |
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| 26 |
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|
| 27 |
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|
| 28 |
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|
| 29 |
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|
| 30 |
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|
| 31 |
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|
| 32 |
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|
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| 34 |
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| 35 |
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| 36 |
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| 37 |
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| 38 |
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| 39 |
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| 40 |
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| 41 |
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| 42 |
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| 48 |
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| 474 |
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| 481 |
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| 482 |
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| 484 |
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| 485 |
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| 486 |
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| 487 |
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| 488 |
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|
| 489 |
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|
| 490 |
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|
| 491 |
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|
| 492 |
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|
| 493 |
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|
| 494 |
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|
| 495 |
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|
| 496 |
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|
| 497 |
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|
| 498 |
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|
| 499 |
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|
| 500 |
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|
| 501 |
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|
| 502 |
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|
results/celeba_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed47/d100/config.json
ADDED
|
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| 1 |
+
{
|
| 2 |
+
"vae_checkpoint": "vae_checkpoints/celeba_resnet_modernloss_d100/vae.pt",
|
| 3 |
+
"out": "results/celeba_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed47/d100",
|
| 4 |
+
"subset_path": "diagnostics/celeba_diverse_1k_mean_plus_sd/subset_indices.json",
|
| 5 |
+
"train_tar": "/overflow/data/cerberus/celeba_hq_256_partitioned_ws/train/celeba_hq_256-train-0000.tar",
|
| 6 |
+
"n_train": 1000,
|
| 7 |
+
"total_steps": 5000000,
|
| 8 |
+
"eval_interval": 10000,
|
| 9 |
+
"mem_interval": 100000,
|
| 10 |
+
"fid_interval": 100000,
|
| 11 |
+
"fid_n_real": 1000,
|
| 12 |
+
"fid_n_gen": 10000,
|
| 13 |
+
"n_gen_samples": 10000,
|
| 14 |
+
"n_sde_steps": 500,
|
| 15 |
+
"batch_size": 512,
|
| 16 |
+
"hidden": 1024,
|
| 17 |
+
"depth": 5,
|
| 18 |
+
"optimizer": "sgd",
|
| 19 |
+
"lr": 0.001,
|
| 20 |
+
"momentum": 0.8,
|
| 21 |
+
"t_min": 0.01,
|
| 22 |
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"t_max": 3.0,
|
| 23 |
+
"t_eval": 0.1,
|
| 24 |
+
"seed": 47,
|
| 25 |
+
"device": null
|
| 26 |
+
}
|
results/celeba_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed47/d100/metrics.jsonl
ADDED
|
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results/celeba_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed47/d100/runner.log
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|
| 1 |
+
FID real-side stats cached over 1000 diverse train images
|
| 2 |
+
step 1 | 73s | train_loss=0.9982 | fid=289.1489
|
| 3 |
+
step 10000 | 169s | train_loss=0.8036
|
| 4 |
+
step 20000 | 264s | train_loss=0.6788
|
| 5 |
+
step 30000 | 360s | train_loss=0.5423
|
| 6 |
+
step 40000 | 455s | train_loss=0.4010
|
| 7 |
+
step 50000 | 550s | train_loss=0.2892
|
| 8 |
+
step 60000 | 644s | train_loss=0.2172
|
| 9 |
+
step 70000 | 739s | train_loss=0.1769
|
| 10 |
+
step 80000 | 834s | train_loss=0.1561
|
| 11 |
+
step 90000 | 929s | train_loss=0.1375
|
| 12 |
+
step 100000 | 1092s | train_loss=0.1281 | fid=59.2126
|
| 13 |
+
step 110000 | 1187s | train_loss=0.1210
|
| 14 |
+
step 120000 | 1282s | train_loss=0.1140
|
| 15 |
+
step 130000 | 1377s | train_loss=0.1099
|
| 16 |
+
step 140000 | 1472s | train_loss=0.1030
|
| 17 |
+
step 150000 | 1565s | train_loss=0.0990
|
| 18 |
+
step 160000 | 1660s | train_loss=0.0975
|
| 19 |
+
step 170000 | 1755s | train_loss=0.0924
|
| 20 |
+
step 180000 | 1850s | train_loss=0.0919
|
| 21 |
+
step 190000 | 1939s | train_loss=0.0867
|
| 22 |
+
step 200000 | 2109s | train_loss=0.0839 | fid=57.9158
|
| 23 |
+
step 210000 | 2205s | train_loss=0.0818
|
| 24 |
+
step 220000 | 2300s | train_loss=0.0795
|
| 25 |
+
step 230000 | 2395s | train_loss=0.0768
|
| 26 |
+
step 240000 | 2489s | train_loss=0.0767
|
| 27 |
+
step 250000 | 2584s | train_loss=0.0731
|
| 28 |
+
step 260000 | 2679s | train_loss=0.0726
|
| 29 |
+
step 270000 | 2774s | train_loss=0.0699
|
| 30 |
+
step 280000 | 2862s | train_loss=0.0705
|
| 31 |
+
step 290000 | 2957s | train_loss=0.0669
|
| 32 |
+
step 300000 | 3116s | train_loss=0.0665 | fid=55.1474
|
| 33 |
+
step 310000 | 3211s | train_loss=0.0672
|
| 34 |
+
step 320000 | 3306s | train_loss=0.0647
|
| 35 |
+
step 330000 | 3400s | train_loss=0.0630
|
| 36 |
+
step 340000 | 3495s | train_loss=0.0620
|
| 37 |
+
step 350000 | 3590s | train_loss=0.0605
|
| 38 |
+
step 360000 | 3685s | train_loss=0.0608
|
| 39 |
+
step 370000 | 3774s | train_loss=0.0594
|
| 40 |
+
step 380000 | 3869s | train_loss=0.0584
|
| 41 |
+
step 390000 | 3964s | train_loss=0.0580
|
| 42 |
+
step 400000 | 4127s | train_loss=0.0577 | fid=53.8473
|
| 43 |
+
step 410000 | 4220s | train_loss=0.0568
|
| 44 |
+
step 420000 | 4309s | train_loss=0.0556
|
| 45 |
+
step 430000 | 4400s | train_loss=0.0556
|
| 46 |
+
step 440000 | 4490s | train_loss=0.0551
|
| 47 |
+
step 450000 | 4586s | train_loss=0.0542
|
| 48 |
+
step 460000 | 4676s | train_loss=0.0539
|
| 49 |
+
step 470000 | 4769s | train_loss=0.0531
|
| 50 |
+
step 480000 | 4864s | train_loss=0.0522
|
| 51 |
+
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|
| 52 |
+
step 500000 | 5122s | train_loss=0.0514 | fid=52.4779
|
| 53 |
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step 510000 | 5217s | train_loss=0.0506
|
| 54 |
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|
| 55 |
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step 530000 | 5406s | train_loss=0.0505
|
| 56 |
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|
| 57 |
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|
| 58 |
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step 560000 | 5685s | train_loss=0.0493
|
| 59 |
+
step 570000 | 5780s | train_loss=0.0480
|
| 60 |
+
step 580000 | 5875s | train_loss=0.0490
|
| 61 |
+
step 590000 | 5970s | train_loss=0.0476
|
| 62 |
+
step 600000 | 6122s | train_loss=0.0472 | fid=51.8697
|
| 63 |
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step 610000 | 6217s | train_loss=0.0466
|
| 64 |
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step 620000 | 6312s | train_loss=0.0473
|
| 65 |
+
step 630000 | 6407s | train_loss=0.0468
|
| 66 |
+
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|
| 67 |
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|
| 68 |
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|
| 69 |
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|
| 70 |
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|
| 71 |
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|
| 72 |
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|
| 73 |
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|
| 74 |
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|
| 75 |
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|
| 76 |
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|
| 77 |
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|
| 78 |
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|
| 79 |
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|
| 80 |
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|
| 81 |
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|
| 82 |
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|
| 83 |
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|
| 84 |
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|
| 85 |
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|
| 86 |
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|
| 87 |
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|
| 88 |
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|
| 89 |
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|
| 90 |
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|
| 91 |
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|
| 92 |
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|
| 93 |
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|
| 94 |
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|
| 95 |
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|
| 96 |
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|
| 97 |
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|
| 98 |
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|
| 99 |
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|
| 100 |
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|
| 101 |
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|
| 102 |
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|
| 103 |
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|
| 104 |
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|
| 105 |
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|
| 106 |
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|
| 107 |
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|
| 108 |
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|
| 109 |
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|
| 110 |
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|
| 111 |
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|
| 112 |
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|
| 113 |
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|
| 114 |
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|
| 115 |
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|
| 116 |
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|
| 117 |
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|
| 118 |
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|
| 119 |
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|
| 120 |
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|
| 121 |
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|
| 122 |
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|
| 123 |
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|
| 124 |
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|
| 125 |
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|
| 126 |
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|
| 127 |
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|
| 128 |
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|
| 129 |
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|
| 130 |
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|
| 131 |
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|
| 132 |
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|
| 133 |
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|
| 134 |
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|
| 135 |
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|
| 136 |
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|
| 137 |
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|
| 138 |
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|
| 139 |
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|
| 140 |
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|
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step 4130000 | 41579s | train_loss=0.0153
|
| 416 |
+
step 4140000 | 41674s | train_loss=0.0156
|
| 417 |
+
step 4150000 | 41769s | train_loss=0.0152
|
| 418 |
+
step 4160000 | 41865s | train_loss=0.0145
|
| 419 |
+
step 4170000 | 41959s | train_loss=0.0159
|
| 420 |
+
step 4180000 | 42053s | train_loss=0.0145
|
| 421 |
+
step 4190000 | 42148s | train_loss=0.0166
|
| 422 |
+
step 4200000 | 42312s | train_loss=0.0151 | fid=39.4750
|
| 423 |
+
step 4210000 | 42388s | train_loss=0.0145
|
| 424 |
+
step 4220000 | 42483s | train_loss=0.0147
|
| 425 |
+
step 4230000 | 42576s | train_loss=0.0159
|
| 426 |
+
step 4240000 | 42671s | train_loss=0.0146
|
| 427 |
+
step 4250000 | 42767s | train_loss=0.0152
|
| 428 |
+
step 4260000 | 42861s | train_loss=0.0156
|
| 429 |
+
step 4270000 | 42955s | train_loss=0.0174
|
| 430 |
+
step 4280000 | 43049s | train_loss=0.0152
|
| 431 |
+
step 4290000 | 43144s | train_loss=0.0146
|
| 432 |
+
step 4300000 | 43307s | train_loss=0.0142 | fid=40.5264
|
| 433 |
+
step 4310000 | 43391s | train_loss=0.0152
|
| 434 |
+
step 4320000 | 43485s | train_loss=0.0141
|
| 435 |
+
step 4330000 | 43580s | train_loss=0.0150
|
| 436 |
+
step 4340000 | 43675s | train_loss=0.0153
|
| 437 |
+
step 4350000 | 43769s | train_loss=0.0147
|
| 438 |
+
step 4360000 | 43864s | train_loss=0.0148
|
| 439 |
+
step 4370000 | 43960s | train_loss=0.0150
|
| 440 |
+
step 4380000 | 44054s | train_loss=0.0150
|
| 441 |
+
step 4390000 | 44146s | train_loss=0.0145
|
| 442 |
+
step 4400000 | 44311s | train_loss=0.0150 | fid=39.9049
|
| 443 |
+
step 4410000 | 44398s | train_loss=0.0141
|
| 444 |
+
step 4420000 | 44490s | train_loss=0.0146
|
| 445 |
+
step 4430000 | 44585s | train_loss=0.0142
|
| 446 |
+
step 4440000 | 44681s | train_loss=0.0147
|
| 447 |
+
step 4450000 | 44776s | train_loss=0.0157
|
| 448 |
+
step 4460000 | 44871s | train_loss=0.0144
|
| 449 |
+
step 4470000 | 44966s | train_loss=0.0158
|
| 450 |
+
step 4480000 | 45057s | train_loss=0.0156
|
| 451 |
+
step 4490000 | 45151s | train_loss=0.0145
|
| 452 |
+
step 4500000 | 45318s | train_loss=0.0150 | fid=39.9629
|
| 453 |
+
step 4510000 | 45410s | train_loss=0.0138
|
| 454 |
+
step 4520000 | 45505s | train_loss=0.0147
|
| 455 |
+
step 4530000 | 45600s | train_loss=0.0144
|
| 456 |
+
step 4540000 | 45695s | train_loss=0.0143
|
| 457 |
+
step 4550000 | 45788s | train_loss=0.0150
|
| 458 |
+
step 4560000 | 45883s | train_loss=0.0149
|
| 459 |
+
step 4570000 | 45954s | train_loss=0.0143
|
| 460 |
+
step 4580000 | 45998s | train_loss=0.0138
|
| 461 |
+
step 4590000 | 46037s | train_loss=0.0148
|
| 462 |
+
step 4600000 | 46112s | train_loss=0.0143 | fid=39.5570
|
| 463 |
+
step 4610000 | 46143s | train_loss=0.0141
|
| 464 |
+
step 4620000 | 46183s | train_loss=0.0150
|
| 465 |
+
step 4630000 | 46222s | train_loss=0.0146
|
| 466 |
+
step 4640000 | 46262s | train_loss=0.0135
|
| 467 |
+
step 4650000 | 46302s | train_loss=0.0140
|
| 468 |
+
step 4660000 | 46341s | train_loss=0.0138
|
| 469 |
+
step 4670000 | 46381s | train_loss=0.0138
|
| 470 |
+
step 4680000 | 46420s | train_loss=0.0136
|
| 471 |
+
step 4690000 | 46460s | train_loss=0.0131
|
| 472 |
+
step 4700000 | 46534s | train_loss=0.0139 | fid=40.4666
|
| 473 |
+
step 4710000 | 46568s | train_loss=0.0138
|
| 474 |
+
step 4720000 | 46608s | train_loss=0.0139
|
| 475 |
+
step 4730000 | 46648s | train_loss=0.0141
|
| 476 |
+
step 4740000 | 46687s | train_loss=0.0136
|
| 477 |
+
step 4750000 | 46727s | train_loss=0.0137
|
| 478 |
+
step 4760000 | 46766s | train_loss=0.0137
|
| 479 |
+
step 4770000 | 46806s | train_loss=0.0136
|
| 480 |
+
step 4780000 | 46846s | train_loss=0.0148
|
| 481 |
+
step 4790000 | 46885s | train_loss=0.0137
|
| 482 |
+
step 4800000 | 46960s | train_loss=0.0139 | fid=39.7265
|
| 483 |
+
step 4810000 | 46999s | train_loss=0.0132
|
| 484 |
+
step 4820000 | 47038s | train_loss=0.0130
|
| 485 |
+
step 4830000 | 47078s | train_loss=0.0134
|
| 486 |
+
step 4840000 | 47118s | train_loss=0.0129
|
| 487 |
+
step 4850000 | 47157s | train_loss=0.0137
|
| 488 |
+
step 4860000 | 47197s | train_loss=0.0140
|
| 489 |
+
step 4870000 | 47237s | train_loss=0.0131
|
| 490 |
+
step 4880000 | 47276s | train_loss=0.0132
|
| 491 |
+
step 4890000 | 47316s | train_loss=0.0132
|
| 492 |
+
step 4900000 | 47383s | train_loss=0.0140 | fid=40.0094
|
| 493 |
+
step 4910000 | 47422s | train_loss=0.0135
|
| 494 |
+
step 4920000 | 47462s | train_loss=0.0131
|
| 495 |
+
step 4930000 | 47501s | train_loss=0.0131
|
| 496 |
+
step 4940000 | 47541s | train_loss=0.0137
|
| 497 |
+
step 4950000 | 47580s | train_loss=0.0127
|
| 498 |
+
step 4960000 | 47619s | train_loss=0.0144
|
| 499 |
+
step 4970000 | 47659s | train_loss=0.0149
|
| 500 |
+
step 4980000 | 47698s | train_loss=0.0128
|
| 501 |
+
step 4990000 | 47738s | train_loss=0.0133
|
| 502 |
+
step 5000000 | 47800s | train_loss=0.0132 | fid=40.3210
|
results/celeba_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed47/d20/config.json
ADDED
|
@@ -0,0 +1,26 @@
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| 1 |
+
{
|
| 2 |
+
"vae_checkpoint": "vae_checkpoints/celeba_resnet_modernloss_d20/vae.pt",
|
| 3 |
+
"out": "results/celeba_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed47/d20",
|
| 4 |
+
"subset_path": "diagnostics/celeba_diverse_1k_mean_plus_sd/subset_indices.json",
|
| 5 |
+
"train_tar": "/overflow/data/cerberus/celeba_hq_256_partitioned_ws/train/celeba_hq_256-train-0000.tar",
|
| 6 |
+
"n_train": 1000,
|
| 7 |
+
"total_steps": 5000000,
|
| 8 |
+
"eval_interval": 10000,
|
| 9 |
+
"mem_interval": 100000,
|
| 10 |
+
"fid_interval": 100000,
|
| 11 |
+
"fid_n_real": 1000,
|
| 12 |
+
"fid_n_gen": 10000,
|
| 13 |
+
"n_gen_samples": 10000,
|
| 14 |
+
"n_sde_steps": 500,
|
| 15 |
+
"batch_size": 512,
|
| 16 |
+
"hidden": 1024,
|
| 17 |
+
"depth": 5,
|
| 18 |
+
"optimizer": "sgd",
|
| 19 |
+
"lr": 0.001,
|
| 20 |
+
"momentum": 0.8,
|
| 21 |
+
"t_min": 0.01,
|
| 22 |
+
"t_max": 3.0,
|
| 23 |
+
"t_eval": 0.1,
|
| 24 |
+
"seed": 47,
|
| 25 |
+
"device": null
|
| 26 |
+
}
|
results/celeba_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed47/d20/metrics.jsonl
ADDED
|
The diff for this file is too large to render.
See raw diff
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|
results/celeba_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed47/d20/runner.log
ADDED
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@@ -0,0 +1,502 @@
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| 1 |
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FID real-side stats cached over 1000 diverse train images
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| 2 |
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step 1 | 64s | train_loss=1.0024 | fid=224.9717
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| 3 |
+
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| 4 |
+
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| 5 |
+
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| 6 |
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| 7 |
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| 8 |
+
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| 9 |
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| 10 |
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| 11 |
+
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| 12 |
+
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| 13 |
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| 14 |
+
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| 15 |
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| 16 |
+
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| 17 |
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| 18 |
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| 19 |
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| 20 |
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| 21 |
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| 22 |
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| 23 |
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| 24 |
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| 29 |
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| 32 |
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| 490 |
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| 495 |
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| 496 |
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|
| 497 |
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|
| 498 |
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|
| 499 |
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|
| 500 |
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|
| 501 |
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|
results/celeba_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed47/d30/config.json
ADDED
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+
{
|
| 2 |
+
"vae_checkpoint": "vae_checkpoints/celeba_resnet_modernloss_d30/vae.pt",
|
| 3 |
+
"out": "results/celeba_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed47/d30",
|
| 4 |
+
"subset_path": "diagnostics/celeba_diverse_1k_mean_plus_sd/subset_indices.json",
|
| 5 |
+
"train_tar": "/overflow/data/cerberus/celeba_hq_256_partitioned_ws/train/celeba_hq_256-train-0000.tar",
|
| 6 |
+
"n_train": 1000,
|
| 7 |
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"total_steps": 5000000,
|
| 8 |
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|
| 9 |
+
"mem_interval": 100000,
|
| 10 |
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"fid_interval": 100000,
|
| 11 |
+
"fid_n_real": 1000,
|
| 12 |
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"fid_n_gen": 10000,
|
| 13 |
+
"n_gen_samples": 10000,
|
| 14 |
+
"n_sde_steps": 500,
|
| 15 |
+
"batch_size": 512,
|
| 16 |
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"hidden": 1024,
|
| 17 |
+
"depth": 5,
|
| 18 |
+
"optimizer": "sgd",
|
| 19 |
+
"lr": 0.001,
|
| 20 |
+
"momentum": 0.8,
|
| 21 |
+
"t_min": 0.01,
|
| 22 |
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|
| 23 |
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"t_eval": 0.1,
|
| 24 |
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"seed": 47,
|
| 25 |
+
"device": null
|
| 26 |
+
}
|
results/celeba_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed47/d30/metrics.jsonl
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|
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results/celeba_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed47/d30/runner.log
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|
| 1 |
+
FID real-side stats cached over 1000 diverse train images
|
| 2 |
+
step 1 | 68s | train_loss=1.0027 | fid=247.0267
|
| 3 |
+
step 10000 | 155s | train_loss=0.8753
|
| 4 |
+
step 20000 | 244s | train_loss=0.8634
|
| 5 |
+
step 30000 | 333s | train_loss=0.8477
|
| 6 |
+
step 40000 | 422s | train_loss=0.8134
|
| 7 |
+
step 50000 | 512s | train_loss=0.7557
|
| 8 |
+
step 60000 | 600s | train_loss=0.6717
|
| 9 |
+
step 70000 | 689s | train_loss=0.5556
|
| 10 |
+
step 80000 | 778s | train_loss=0.4367
|
| 11 |
+
step 90000 | 867s | train_loss=0.3412
|
| 12 |
+
step 100000 | 1020s | train_loss=0.2731 | fid=61.8627
|
| 13 |
+
step 110000 | 1102s | train_loss=0.2329
|
| 14 |
+
step 120000 | 1191s | train_loss=0.2035
|
| 15 |
+
step 130000 | 1280s | train_loss=0.1841
|
| 16 |
+
step 140000 | 1368s | train_loss=0.1704
|
| 17 |
+
step 150000 | 1457s | train_loss=0.1548
|
| 18 |
+
step 160000 | 1546s | train_loss=0.1459
|
| 19 |
+
step 170000 | 1635s | train_loss=0.1393
|
| 20 |
+
step 180000 | 1724s | train_loss=0.1315
|
| 21 |
+
step 190000 | 1813s | train_loss=0.1246
|
| 22 |
+
step 200000 | 1968s | train_loss=0.1200 | fid=61.9822
|
| 23 |
+
step 210000 | 2050s | train_loss=0.1137
|
| 24 |
+
step 220000 | 2139s | train_loss=0.1096
|
| 25 |
+
step 230000 | 2228s | train_loss=0.1051
|
| 26 |
+
step 240000 | 2317s | train_loss=0.1010
|
| 27 |
+
step 250000 | 2406s | train_loss=0.0971
|
| 28 |
+
step 260000 | 2494s | train_loss=0.0936
|
| 29 |
+
step 270000 | 2583s | train_loss=0.0923
|
| 30 |
+
step 280000 | 2672s | train_loss=0.0884
|
| 31 |
+
step 290000 | 2760s | train_loss=0.0851
|
| 32 |
+
step 300000 | 2960s | train_loss=0.0819 | fid=60.5129
|
| 33 |
+
step 310000 | 3028s | train_loss=0.0793
|
| 34 |
+
step 320000 | 3117s | train_loss=0.0795
|
| 35 |
+
step 330000 | 3206s | train_loss=0.0757
|
| 36 |
+
step 340000 | 3295s | train_loss=0.0743
|
| 37 |
+
step 350000 | 3383s | train_loss=0.0723
|
| 38 |
+
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|
| 39 |
+
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|
| 40 |
+
step 380000 | 3648s | train_loss=0.0677
|
| 41 |
+
step 390000 | 3734s | train_loss=0.0663
|
| 42 |
+
step 400000 | 3892s | train_loss=0.0645 | fid=60.4828
|
| 43 |
+
step 410000 | 3982s | train_loss=0.0640
|
| 44 |
+
step 420000 | 4063s | train_loss=0.0634
|
| 45 |
+
step 430000 | 4152s | train_loss=0.0615
|
| 46 |
+
step 440000 | 4240s | train_loss=0.0605
|
| 47 |
+
step 450000 | 4328s | train_loss=0.0590
|
| 48 |
+
step 460000 | 4416s | train_loss=0.0584
|
| 49 |
+
step 470000 | 4504s | train_loss=0.0567
|
| 50 |
+
step 480000 | 4591s | train_loss=0.0559
|
| 51 |
+
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|
| 52 |
+
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|
| 53 |
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|
| 54 |
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|
| 55 |
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|
| 56 |
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|
| 57 |
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|
| 58 |
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|
| 59 |
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|
| 60 |
+
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|
| 61 |
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|
| 62 |
+
step 600000 | 5808s | train_loss=0.0482 | fid=59.4603
|
| 63 |
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step 610000 | 5897s | train_loss=0.0472
|
| 64 |
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|
| 65 |
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|
| 66 |
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|
| 67 |
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|
| 68 |
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|
| 69 |
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|
| 70 |
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|
| 71 |
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|
| 72 |
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|
| 73 |
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|
| 74 |
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|
| 75 |
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|
| 76 |
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|
| 77 |
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|
| 78 |
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|
| 79 |
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|
| 80 |
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|
| 81 |
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|
| 82 |
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|
| 83 |
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|
| 84 |
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|
| 85 |
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|
| 86 |
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|
| 87 |
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|
| 88 |
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|
| 89 |
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|
| 90 |
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|
| 91 |
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|
| 92 |
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|
| 93 |
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|
| 94 |
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|
| 95 |
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|
| 96 |
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|
| 97 |
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|
| 98 |
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|
| 99 |
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|
| 100 |
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|
| 101 |
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|
| 102 |
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|
| 103 |
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|
| 104 |
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|
| 105 |
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|
| 106 |
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|
| 107 |
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|
| 108 |
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|
| 109 |
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|
| 110 |
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|
| 111 |
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|
| 112 |
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|
| 113 |
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|
| 114 |
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|
| 115 |
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|
| 116 |
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|
| 117 |
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|
| 118 |
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|
| 119 |
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|
| 120 |
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|
| 121 |
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|
| 122 |
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|
| 123 |
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|
| 124 |
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|
| 125 |
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|
| 126 |
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|
| 127 |
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|
| 128 |
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|
| 129 |
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|
| 130 |
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|
| 131 |
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|
| 132 |
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|
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+
step 4060000 | 38773s | train_loss=0.0121
|
| 409 |
+
step 4070000 | 38859s | train_loss=0.0120
|
| 410 |
+
step 4080000 | 38948s | train_loss=0.0120
|
| 411 |
+
step 4090000 | 39037s | train_loss=0.0118
|
| 412 |
+
step 4100000 | 39232s | train_loss=0.0121 | fid=56.6704
|
| 413 |
+
step 4110000 | 39321s | train_loss=0.0121
|
| 414 |
+
step 4120000 | 39409s | train_loss=0.0117
|
| 415 |
+
step 4130000 | 39499s | train_loss=0.0118
|
| 416 |
+
step 4140000 | 39579s | train_loss=0.0119
|
| 417 |
+
step 4150000 | 39659s | train_loss=0.0122
|
| 418 |
+
step 4160000 | 39732s | train_loss=0.0114
|
| 419 |
+
step 4170000 | 39821s | train_loss=0.0116
|
| 420 |
+
step 4180000 | 39910s | train_loss=0.0114
|
| 421 |
+
step 4190000 | 39998s | train_loss=0.0115
|
| 422 |
+
step 4200000 | 40182s | train_loss=0.0116 | fid=55.9841
|
| 423 |
+
step 4210000 | 40268s | train_loss=0.0116
|
| 424 |
+
step 4220000 | 40357s | train_loss=0.0114
|
| 425 |
+
step 4230000 | 40446s | train_loss=0.0115
|
| 426 |
+
step 4240000 | 40535s | train_loss=0.0116
|
| 427 |
+
step 4250000 | 40603s | train_loss=0.0119
|
| 428 |
+
step 4260000 | 40679s | train_loss=0.0113
|
| 429 |
+
step 4270000 | 40768s | train_loss=0.0115
|
| 430 |
+
step 4280000 | 40856s | train_loss=0.0112
|
| 431 |
+
step 4290000 | 40945s | train_loss=0.0117
|
| 432 |
+
step 4300000 | 41142s | train_loss=0.0118 | fid=56.3611
|
| 433 |
+
step 4310000 | 41219s | train_loss=0.0117
|
| 434 |
+
step 4320000 | 41307s | train_loss=0.0113
|
| 435 |
+
step 4330000 | 41396s | train_loss=0.0115
|
| 436 |
+
step 4340000 | 41483s | train_loss=0.0114
|
| 437 |
+
step 4350000 | 41554s | train_loss=0.0114
|
| 438 |
+
step 4360000 | 41634s | train_loss=0.0117
|
| 439 |
+
step 4370000 | 41723s | train_loss=0.0111
|
| 440 |
+
step 4380000 | 41812s | train_loss=0.0109
|
| 441 |
+
step 4390000 | 41900s | train_loss=0.0114
|
| 442 |
+
step 4400000 | 42094s | train_loss=0.0113 | fid=56.9317
|
| 443 |
+
step 4410000 | 42170s | train_loss=0.0111
|
| 444 |
+
step 4420000 | 42256s | train_loss=0.0113
|
| 445 |
+
step 4430000 | 42343s | train_loss=0.0110
|
| 446 |
+
step 4440000 | 42432s | train_loss=0.0112
|
| 447 |
+
step 4450000 | 42507s | train_loss=0.0110
|
| 448 |
+
step 4460000 | 42586s | train_loss=0.0109
|
| 449 |
+
step 4470000 | 42675s | train_loss=0.0110
|
| 450 |
+
step 4480000 | 42764s | train_loss=0.0107
|
| 451 |
+
step 4490000 | 42852s | train_loss=0.0111
|
| 452 |
+
step 4500000 | 43028s | train_loss=0.0108 | fid=56.7840
|
| 453 |
+
step 4510000 | 43118s | train_loss=0.0107
|
| 454 |
+
step 4520000 | 43188s | train_loss=0.0112
|
| 455 |
+
step 4530000 | 43276s | train_loss=0.0116
|
| 456 |
+
step 4540000 | 43365s | train_loss=0.0108
|
| 457 |
+
step 4550000 | 43444s | train_loss=0.0105
|
| 458 |
+
step 4560000 | 43524s | train_loss=0.0106
|
| 459 |
+
step 4570000 | 43604s | train_loss=0.0109
|
| 460 |
+
step 4580000 | 43693s | train_loss=0.0108
|
| 461 |
+
step 4590000 | 43781s | train_loss=0.0106
|
| 462 |
+
step 4600000 | 44003s | train_loss=0.0109 | fid=56.7650
|
| 463 |
+
step 4610000 | 44079s | train_loss=0.0106
|
| 464 |
+
step 4620000 | 44135s | train_loss=0.0109
|
| 465 |
+
step 4630000 | 44195s | train_loss=0.0108
|
| 466 |
+
step 4640000 | 44256s | train_loss=0.0105
|
| 467 |
+
step 4650000 | 44319s | train_loss=0.0108
|
| 468 |
+
step 4660000 | 44388s | train_loss=0.0106
|
| 469 |
+
step 4670000 | 44447s | train_loss=0.0104
|
| 470 |
+
step 4680000 | 44519s | train_loss=0.0105
|
| 471 |
+
step 4690000 | 44590s | train_loss=0.0107
|
| 472 |
+
step 4700000 | 44722s | train_loss=0.0106 | fid=56.4528
|
| 473 |
+
step 4710000 | 44793s | train_loss=0.0108
|
| 474 |
+
step 4720000 | 44865s | train_loss=0.0107
|
| 475 |
+
step 4730000 | 44933s | train_loss=0.0102
|
| 476 |
+
step 4740000 | 45002s | train_loss=0.0102
|
| 477 |
+
step 4750000 | 45072s | train_loss=0.0102
|
| 478 |
+
step 4760000 | 45143s | train_loss=0.0104
|
| 479 |
+
step 4770000 | 45211s | train_loss=0.0104
|
| 480 |
+
step 4780000 | 45283s | train_loss=0.0105
|
| 481 |
+
step 4790000 | 45354s | train_loss=0.0103
|
| 482 |
+
step 4800000 | 45486s | train_loss=0.0106 | fid=56.4745
|
| 483 |
+
step 4810000 | 45557s | train_loss=0.0104
|
| 484 |
+
step 4820000 | 45629s | train_loss=0.0107
|
| 485 |
+
step 4830000 | 45701s | train_loss=0.0109
|
| 486 |
+
step 4840000 | 45759s | train_loss=0.0105
|
| 487 |
+
step 4850000 | 45814s | train_loss=0.0102
|
| 488 |
+
step 4860000 | 45868s | train_loss=0.0099
|
| 489 |
+
step 4870000 | 45923s | train_loss=0.0100
|
| 490 |
+
step 4880000 | 45971s | train_loss=0.0101
|
| 491 |
+
step 4890000 | 46026s | train_loss=0.0100
|
| 492 |
+
step 4900000 | 46127s | train_loss=0.0107 | fid=55.9971
|
| 493 |
+
step 4910000 | 46181s | train_loss=0.0102
|
| 494 |
+
step 4920000 | 46235s | train_loss=0.0101
|
| 495 |
+
step 4930000 | 46290s | train_loss=0.0099
|
| 496 |
+
step 4940000 | 46338s | train_loss=0.0102
|
| 497 |
+
step 4950000 | 46393s | train_loss=0.0100
|
| 498 |
+
step 4960000 | 46448s | train_loss=0.0103
|
| 499 |
+
step 4970000 | 46502s | train_loss=0.0101
|
| 500 |
+
step 4980000 | 46551s | train_loss=0.0105
|
| 501 |
+
step 4990000 | 46606s | train_loss=0.0098
|
| 502 |
+
step 5000000 | 46705s | train_loss=0.0103 | fid=56.5140
|
results/celeba_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed47/d40/config.json
ADDED
|
@@ -0,0 +1,26 @@
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| 1 |
+
{
|
| 2 |
+
"vae_checkpoint": "vae_checkpoints/celeba_resnet_modernloss_d40/vae.pt",
|
| 3 |
+
"out": "results/celeba_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed47/d40",
|
| 4 |
+
"subset_path": "diagnostics/celeba_diverse_1k_mean_plus_sd/subset_indices.json",
|
| 5 |
+
"train_tar": "/overflow/data/cerberus/celeba_hq_256_partitioned_ws/train/celeba_hq_256-train-0000.tar",
|
| 6 |
+
"n_train": 1000,
|
| 7 |
+
"total_steps": 5000000,
|
| 8 |
+
"eval_interval": 10000,
|
| 9 |
+
"mem_interval": 100000,
|
| 10 |
+
"fid_interval": 100000,
|
| 11 |
+
"fid_n_real": 1000,
|
| 12 |
+
"fid_n_gen": 10000,
|
| 13 |
+
"n_gen_samples": 10000,
|
| 14 |
+
"n_sde_steps": 500,
|
| 15 |
+
"batch_size": 512,
|
| 16 |
+
"hidden": 1024,
|
| 17 |
+
"depth": 5,
|
| 18 |
+
"optimizer": "sgd",
|
| 19 |
+
"lr": 0.001,
|
| 20 |
+
"momentum": 0.8,
|
| 21 |
+
"t_min": 0.01,
|
| 22 |
+
"t_max": 3.0,
|
| 23 |
+
"t_eval": 0.1,
|
| 24 |
+
"seed": 47,
|
| 25 |
+
"device": null
|
| 26 |
+
}
|
results/celeba_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed47/d40/metrics.jsonl
ADDED
|
The diff for this file is too large to render.
See raw diff
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|
results/celeba_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed47/d40/runner.log
ADDED
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@@ -0,0 +1,502 @@
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| 1 |
+
FID real-side stats cached over 1000 diverse train images
|
| 2 |
+
step 1 | 66s | train_loss=1.0018 | fid=278.6993
|
| 3 |
+
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|
| 4 |
+
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|
| 5 |
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|
| 6 |
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|
| 7 |
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|
| 8 |
+
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|
| 9 |
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|
| 10 |
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|
| 11 |
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|
| 12 |
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|
| 13 |
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|
| 14 |
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| 15 |
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| 16 |
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| 17 |
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|
| 18 |
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|
| 19 |
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| 20 |
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|
| 21 |
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|
| 22 |
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|
| 23 |
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|
| 24 |
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| 39 |
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| 42 |
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| 490 |
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|
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|
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|
| 499 |
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|
| 500 |
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|
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|
results/celeba_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed47/d50/config.json
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|
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| 1 |
+
{
|
| 2 |
+
"vae_checkpoint": "vae_checkpoints/celeba_resnet_modernloss_d50/vae.pt",
|
| 3 |
+
"out": "results/celeba_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed47/d50",
|
| 4 |
+
"subset_path": "diagnostics/celeba_diverse_1k_mean_plus_sd/subset_indices.json",
|
| 5 |
+
"train_tar": "/overflow/data/cerberus/celeba_hq_256_partitioned_ws/train/celeba_hq_256-train-0000.tar",
|
| 6 |
+
"n_train": 1000,
|
| 7 |
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"total_steps": 5000000,
|
| 8 |
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|
| 9 |
+
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|
| 10 |
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"fid_interval": 100000,
|
| 11 |
+
"fid_n_real": 1000,
|
| 12 |
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"fid_n_gen": 10000,
|
| 13 |
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"n_gen_samples": 10000,
|
| 14 |
+
"n_sde_steps": 500,
|
| 15 |
+
"batch_size": 512,
|
| 16 |
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"hidden": 1024,
|
| 17 |
+
"depth": 5,
|
| 18 |
+
"optimizer": "sgd",
|
| 19 |
+
"lr": 0.001,
|
| 20 |
+
"momentum": 0.8,
|
| 21 |
+
"t_min": 0.01,
|
| 22 |
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|
| 23 |
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"t_eval": 0.1,
|
| 24 |
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"seed": 47,
|
| 25 |
+
"device": null
|
| 26 |
+
}
|
results/celeba_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed47/d50/metrics.jsonl
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|
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results/celeba_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed47/d50/runner.log
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|
| 1 |
+
FID real-side stats cached over 1000 diverse train images
|
| 2 |
+
step 1 | 71s | train_loss=1.0052 | fid=245.2532
|
| 3 |
+
step 10000 | 162s | train_loss=0.8573
|
| 4 |
+
step 20000 | 254s | train_loss=0.7986
|
| 5 |
+
step 30000 | 346s | train_loss=0.7134
|
| 6 |
+
step 40000 | 438s | train_loss=0.5788
|
| 7 |
+
step 50000 | 530s | train_loss=0.4096
|
| 8 |
+
step 60000 | 620s | train_loss=0.2888
|
| 9 |
+
step 70000 | 712s | train_loss=0.2184
|
| 10 |
+
step 80000 | 803s | train_loss=0.1814
|
| 11 |
+
step 90000 | 895s | train_loss=0.1585
|
| 12 |
+
step 100000 | 1056s | train_loss=0.1451 | fid=59.9314
|
| 13 |
+
step 110000 | 1146s | train_loss=0.1356
|
| 14 |
+
step 120000 | 1238s | train_loss=0.1256
|
| 15 |
+
step 130000 | 1329s | train_loss=0.1183
|
| 16 |
+
step 140000 | 1421s | train_loss=0.1115
|
| 17 |
+
step 150000 | 1512s | train_loss=0.1058
|
| 18 |
+
step 160000 | 1603s | train_loss=0.1016
|
| 19 |
+
step 170000 | 1695s | train_loss=0.0978
|
| 20 |
+
step 180000 | 1786s | train_loss=0.0929
|
| 21 |
+
step 190000 | 1876s | train_loss=0.0904
|
| 22 |
+
step 200000 | 2039s | train_loss=0.0871 | fid=56.8623
|
| 23 |
+
step 210000 | 2129s | train_loss=0.0838
|
| 24 |
+
step 220000 | 2221s | train_loss=0.0817
|
| 25 |
+
step 230000 | 2313s | train_loss=0.0786
|
| 26 |
+
step 240000 | 2404s | train_loss=0.0764
|
| 27 |
+
step 250000 | 2495s | train_loss=0.0737
|
| 28 |
+
step 260000 | 2587s | train_loss=0.0721
|
| 29 |
+
step 270000 | 2679s | train_loss=0.0705
|
| 30 |
+
step 280000 | 2768s | train_loss=0.0681
|
| 31 |
+
step 290000 | 2856s | train_loss=0.0667
|
| 32 |
+
step 300000 | 3029s | train_loss=0.0667 | fid=54.2983
|
| 33 |
+
step 310000 | 3120s | train_loss=0.0638
|
| 34 |
+
step 320000 | 3212s | train_loss=0.0630
|
| 35 |
+
step 330000 | 3303s | train_loss=0.0617
|
| 36 |
+
step 340000 | 3394s | train_loss=0.0600
|
| 37 |
+
step 350000 | 3486s | train_loss=0.0585
|
| 38 |
+
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|
| 39 |
+
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|
| 40 |
+
step 380000 | 3756s | train_loss=0.0557
|
| 41 |
+
step 390000 | 3847s | train_loss=0.0549
|
| 42 |
+
step 400000 | 4013s | train_loss=0.0541 | fid=52.7477
|
| 43 |
+
step 410000 | 4104s | train_loss=0.0523
|
| 44 |
+
step 420000 | 4195s | train_loss=0.0527
|
| 45 |
+
step 430000 | 4282s | train_loss=0.0515
|
| 46 |
+
step 440000 | 4370s | train_loss=0.0509
|
| 47 |
+
step 450000 | 4458s | train_loss=0.0494
|
| 48 |
+
step 460000 | 4546s | train_loss=0.0492
|
| 49 |
+
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|
| 50 |
+
step 480000 | 4726s | train_loss=0.0475
|
| 51 |
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|
| 52 |
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|
| 53 |
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step 510000 | 5073s | train_loss=0.0473
|
| 54 |
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|
| 55 |
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|
| 56 |
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|
| 57 |
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|
| 58 |
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|
| 59 |
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|
| 60 |
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|
| 61 |
+
step 590000 | 5795s | train_loss=0.0430
|
| 62 |
+
step 600000 | 5987s | train_loss=0.0420 | fid=50.8781
|
| 63 |
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step 610000 | 6078s | train_loss=0.0425
|
| 64 |
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step 620000 | 6168s | train_loss=0.0419
|
| 65 |
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|
| 66 |
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|
| 67 |
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|
| 68 |
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|
| 69 |
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|
| 70 |
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|
| 71 |
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|
| 72 |
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|
| 73 |
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|
| 74 |
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|
| 75 |
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|
| 76 |
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|
| 77 |
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|
| 78 |
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|
| 79 |
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|
| 80 |
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|
| 81 |
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|
| 82 |
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|
| 83 |
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|
| 84 |
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|
| 85 |
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|
| 86 |
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|
| 87 |
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|
| 88 |
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|
| 89 |
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|
| 90 |
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|
| 91 |
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|
| 92 |
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|
| 93 |
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|
| 94 |
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|
| 95 |
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|
| 96 |
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|
| 97 |
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|
| 98 |
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|
| 99 |
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|
| 100 |
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|
| 101 |
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|
| 102 |
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|
| 103 |
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|
| 104 |
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|
| 105 |
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|
| 106 |
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|
| 107 |
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|
| 108 |
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|
| 109 |
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|
| 110 |
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|
| 111 |
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|
| 112 |
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|
| 113 |
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|
| 114 |
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|
| 115 |
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|
| 116 |
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|
| 117 |
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|
| 118 |
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|
| 119 |
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|
| 120 |
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|
| 121 |
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|
| 122 |
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|
| 123 |
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|
| 124 |
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|
| 125 |
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|
| 126 |
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|
| 127 |
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|
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step 4010000 | 39688s | train_loss=0.0102
|
| 404 |
+
step 4020000 | 39770s | train_loss=0.0106
|
| 405 |
+
step 4030000 | 39861s | train_loss=0.0100
|
| 406 |
+
step 4040000 | 39953s | train_loss=0.0103
|
| 407 |
+
step 4050000 | 40044s | train_loss=0.0103
|
| 408 |
+
step 4060000 | 40136s | train_loss=0.0101
|
| 409 |
+
step 4070000 | 40201s | train_loss=0.0104
|
| 410 |
+
step 4080000 | 40292s | train_loss=0.0100
|
| 411 |
+
step 4090000 | 40383s | train_loss=0.0100
|
| 412 |
+
step 4100000 | 40592s | train_loss=0.0101 | fid=46.3033
|
| 413 |
+
step 4110000 | 40667s | train_loss=0.0105
|
| 414 |
+
step 4120000 | 40759s | train_loss=0.0102
|
| 415 |
+
step 4130000 | 40851s | train_loss=0.0100
|
| 416 |
+
step 4140000 | 40942s | train_loss=0.0097
|
| 417 |
+
step 4150000 | 41032s | train_loss=0.0101
|
| 418 |
+
step 4160000 | 41118s | train_loss=0.0096
|
| 419 |
+
step 4170000 | 41185s | train_loss=0.0097
|
| 420 |
+
step 4180000 | 41275s | train_loss=0.0101
|
| 421 |
+
step 4190000 | 41365s | train_loss=0.0100
|
| 422 |
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step 4200000 | 41563s | train_loss=0.0096 | fid=47.0134
|
| 423 |
+
step 4210000 | 41649s | train_loss=0.0098
|
| 424 |
+
step 4220000 | 41741s | train_loss=0.0099
|
| 425 |
+
step 4230000 | 41833s | train_loss=0.0099
|
| 426 |
+
step 4240000 | 41923s | train_loss=0.0100
|
| 427 |
+
step 4250000 | 42014s | train_loss=0.0096
|
| 428 |
+
step 4260000 | 42094s | train_loss=0.0094
|
| 429 |
+
step 4270000 | 42172s | train_loss=0.0098
|
| 430 |
+
step 4280000 | 42261s | train_loss=0.0095
|
| 431 |
+
step 4290000 | 42350s | train_loss=0.0098
|
| 432 |
+
step 4300000 | 42547s | train_loss=0.0092 | fid=46.6035
|
| 433 |
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step 4310000 | 42638s | train_loss=0.0096
|
| 434 |
+
step 4320000 | 42730s | train_loss=0.0099
|
| 435 |
+
step 4330000 | 42821s | train_loss=0.0093
|
| 436 |
+
step 4340000 | 42913s | train_loss=0.0101
|
| 437 |
+
step 4350000 | 43003s | train_loss=0.0092
|
| 438 |
+
step 4360000 | 43088s | train_loss=0.0097
|
| 439 |
+
step 4370000 | 43166s | train_loss=0.0092
|
| 440 |
+
step 4380000 | 43252s | train_loss=0.0093
|
| 441 |
+
step 4390000 | 43344s | train_loss=0.0096
|
| 442 |
+
step 4400000 | 43560s | train_loss=0.0093 | fid=46.5800
|
| 443 |
+
step 4410000 | 43652s | train_loss=0.0095
|
| 444 |
+
step 4420000 | 43743s | train_loss=0.0091
|
| 445 |
+
step 4430000 | 43834s | train_loss=0.0090
|
| 446 |
+
step 4440000 | 43926s | train_loss=0.0097
|
| 447 |
+
step 4450000 | 44000s | train_loss=0.0094
|
| 448 |
+
step 4460000 | 44078s | train_loss=0.0090
|
| 449 |
+
step 4470000 | 44137s | train_loss=0.0094
|
| 450 |
+
step 4480000 | 44199s | train_loss=0.0090
|
| 451 |
+
step 4490000 | 44260s | train_loss=0.0093
|
| 452 |
+
step 4500000 | 44423s | train_loss=0.0092 | fid=47.0829
|
| 453 |
+
step 4510000 | 44497s | train_loss=0.0091
|
| 454 |
+
step 4520000 | 44571s | train_loss=0.0096
|
| 455 |
+
step 4530000 | 44644s | train_loss=0.0096
|
| 456 |
+
step 4540000 | 44716s | train_loss=0.0091
|
| 457 |
+
step 4550000 | 44787s | train_loss=0.0089
|
| 458 |
+
step 4560000 | 44861s | train_loss=0.0092
|
| 459 |
+
step 4570000 | 44931s | train_loss=0.0087
|
| 460 |
+
step 4580000 | 45003s | train_loss=0.0091
|
| 461 |
+
step 4590000 | 45075s | train_loss=0.0090
|
| 462 |
+
step 4600000 | 45213s | train_loss=0.0093 | fid=47.9626
|
| 463 |
+
step 4610000 | 45286s | train_loss=0.0089
|
| 464 |
+
step 4620000 | 45360s | train_loss=0.0088
|
| 465 |
+
step 4630000 | 45434s | train_loss=0.0091
|
| 466 |
+
step 4640000 | 45504s | train_loss=0.0087
|
| 467 |
+
step 4650000 | 45577s | train_loss=0.0093
|
| 468 |
+
step 4660000 | 45651s | train_loss=0.0091
|
| 469 |
+
step 4670000 | 45721s | train_loss=0.0085
|
| 470 |
+
step 4680000 | 45779s | train_loss=0.0087
|
| 471 |
+
step 4690000 | 45835s | train_loss=0.0086
|
| 472 |
+
step 4700000 | 45944s | train_loss=0.0089 | fid=47.4242
|
| 473 |
+
step 4710000 | 46000s | train_loss=0.0088
|
| 474 |
+
step 4720000 | 46056s | train_loss=0.0087
|
| 475 |
+
step 4730000 | 46112s | train_loss=0.0085
|
| 476 |
+
step 4740000 | 46163s | train_loss=0.0086
|
| 477 |
+
step 4750000 | 46219s | train_loss=0.0090
|
| 478 |
+
step 4760000 | 46275s | train_loss=0.0089
|
| 479 |
+
step 4770000 | 46324s | train_loss=0.0086
|
| 480 |
+
step 4780000 | 46381s | train_loss=0.0092
|
| 481 |
+
step 4790000 | 46437s | train_loss=0.0088
|
| 482 |
+
step 4800000 | 46545s | train_loss=0.0092 | fid=46.3174
|
| 483 |
+
step 4810000 | 46601s | train_loss=0.0085
|
| 484 |
+
step 4820000 | 46658s | train_loss=0.0088
|
| 485 |
+
step 4830000 | 46709s | train_loss=0.0093
|
| 486 |
+
step 4840000 | 46747s | train_loss=0.0088
|
| 487 |
+
step 4850000 | 46786s | train_loss=0.0089
|
| 488 |
+
step 4860000 | 46825s | train_loss=0.0086
|
| 489 |
+
step 4870000 | 46860s | train_loss=0.0085
|
| 490 |
+
step 4880000 | 46898s | train_loss=0.0090
|
| 491 |
+
step 4890000 | 46936s | train_loss=0.0085
|
| 492 |
+
step 4900000 | 47010s | train_loss=0.0086 | fid=47.0189
|
| 493 |
+
step 4910000 | 47049s | train_loss=0.0085
|
| 494 |
+
step 4920000 | 47088s | train_loss=0.0081
|
| 495 |
+
step 4930000 | 47126s | train_loss=0.0083
|
| 496 |
+
step 4940000 | 47165s | train_loss=0.0085
|
| 497 |
+
step 4950000 | 47203s | train_loss=0.0083
|
| 498 |
+
step 4960000 | 47242s | train_loss=0.0085
|
| 499 |
+
step 4970000 | 47279s | train_loss=0.0085
|
| 500 |
+
step 4980000 | 47303s | train_loss=0.0084
|
| 501 |
+
step 4990000 | 47327s | train_loss=0.0082
|
| 502 |
+
step 5000000 | 47368s | train_loss=0.0086 | fid=46.4381
|
results/celeba_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed47/d60/config.json
ADDED
|
@@ -0,0 +1,26 @@
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| 1 |
+
{
|
| 2 |
+
"vae_checkpoint": "vae_checkpoints/celeba_resnet_modernloss_d60/vae.pt",
|
| 3 |
+
"out": "results/celeba_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed47/d60",
|
| 4 |
+
"subset_path": "diagnostics/celeba_diverse_1k_mean_plus_sd/subset_indices.json",
|
| 5 |
+
"train_tar": "/overflow/data/cerberus/celeba_hq_256_partitioned_ws/train/celeba_hq_256-train-0000.tar",
|
| 6 |
+
"n_train": 1000,
|
| 7 |
+
"total_steps": 5000000,
|
| 8 |
+
"eval_interval": 10000,
|
| 9 |
+
"mem_interval": 100000,
|
| 10 |
+
"fid_interval": 100000,
|
| 11 |
+
"fid_n_real": 1000,
|
| 12 |
+
"fid_n_gen": 10000,
|
| 13 |
+
"n_gen_samples": 10000,
|
| 14 |
+
"n_sde_steps": 500,
|
| 15 |
+
"batch_size": 512,
|
| 16 |
+
"hidden": 1024,
|
| 17 |
+
"depth": 5,
|
| 18 |
+
"optimizer": "sgd",
|
| 19 |
+
"lr": 0.001,
|
| 20 |
+
"momentum": 0.8,
|
| 21 |
+
"t_min": 0.01,
|
| 22 |
+
"t_max": 3.0,
|
| 23 |
+
"t_eval": 0.1,
|
| 24 |
+
"seed": 47,
|
| 25 |
+
"device": null
|
| 26 |
+
}
|
results/celeba_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed47/d60/metrics.jsonl
ADDED
|
The diff for this file is too large to render.
See raw diff
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|
results/celeba_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed47/d60/runner.log
ADDED
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@@ -0,0 +1,502 @@
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| 1 |
+
FID real-side stats cached over 1000 diverse train images
|
| 2 |
+
step 1 | 73s | train_loss=1.0038 | fid=301.1004
|
| 3 |
+
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|
| 4 |
+
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|
| 5 |
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|
| 6 |
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|
| 7 |
+
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|
| 8 |
+
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|
| 9 |
+
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|
| 10 |
+
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|
| 11 |
+
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|
| 12 |
+
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|
| 13 |
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|
| 14 |
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|
| 15 |
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|
| 16 |
+
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|
| 17 |
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|
| 18 |
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|
| 19 |
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|
| 20 |
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|
| 21 |
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|
| 22 |
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|
| 23 |
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|
| 24 |
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|
| 25 |
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|
| 26 |
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|
| 27 |
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|
| 28 |
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|
| 29 |
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|
| 30 |
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|
| 31 |
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|
| 32 |
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|
| 33 |
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|
| 34 |
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|
| 35 |
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|
| 36 |
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|
| 37 |
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|
| 38 |
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|
| 39 |
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|
| 40 |
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|
| 41 |
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|
| 42 |
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|
| 43 |
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|
| 44 |
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| 45 |
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| 46 |
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| 47 |
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| 48 |
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| 49 |
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| 50 |
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results/celeba_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed47/d70/config.json
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|
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+
{
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+
"vae_checkpoint": "vae_checkpoints/celeba_resnet_modernloss_d70/vae.pt",
|
| 3 |
+
"out": "results/celeba_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed47/d70",
|
| 4 |
+
"subset_path": "diagnostics/celeba_diverse_1k_mean_plus_sd/subset_indices.json",
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+
"train_tar": "/overflow/data/cerberus/celeba_hq_256_partitioned_ws/train/celeba_hq_256-train-0000.tar",
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|
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|
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|
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|
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|
| 11 |
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|
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|
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|
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|
| 16 |
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|
| 17 |
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|
| 18 |
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|
| 19 |
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|
| 20 |
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|
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| 23 |
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|
| 24 |
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|
| 25 |
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|
| 26 |
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|
results/celeba_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed47/d70/metrics.jsonl
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results/celeba_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed47/d70/runner.log
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| 1 |
+
FID real-side stats cached over 1000 diverse train images
|
| 2 |
+
step 1 | 66s | train_loss=0.9991 | fid=280.5044
|
| 3 |
+
step 10000 | 145s | train_loss=0.8288
|
| 4 |
+
step 20000 | 231s | train_loss=0.7366
|
| 5 |
+
step 30000 | 318s | train_loss=0.6130
|
| 6 |
+
step 40000 | 404s | train_loss=0.4532
|
| 7 |
+
step 50000 | 491s | train_loss=0.3090
|
| 8 |
+
step 60000 | 577s | train_loss=0.2280
|
| 9 |
+
step 70000 | 664s | train_loss=0.1815
|
| 10 |
+
step 80000 | 750s | train_loss=0.1561
|
| 11 |
+
step 90000 | 837s | train_loss=0.1402
|
| 12 |
+
step 100000 | 988s | train_loss=0.1303 | fid=56.3556
|
| 13 |
+
step 110000 | 1070s | train_loss=0.1239
|
| 14 |
+
step 120000 | 1154s | train_loss=0.1149
|
| 15 |
+
step 130000 | 1240s | train_loss=0.1101
|
| 16 |
+
step 140000 | 1327s | train_loss=0.1049
|
| 17 |
+
step 150000 | 1413s | train_loss=0.1001
|
| 18 |
+
step 160000 | 1499s | train_loss=0.0968
|
| 19 |
+
step 170000 | 1586s | train_loss=0.0927
|
| 20 |
+
step 180000 | 1672s | train_loss=0.0886
|
| 21 |
+
step 190000 | 1758s | train_loss=0.0864
|
| 22 |
+
step 200000 | 1910s | train_loss=0.0835 | fid=55.1908
|
| 23 |
+
step 210000 | 1995s | train_loss=0.0801
|
| 24 |
+
step 220000 | 2079s | train_loss=0.0795
|
| 25 |
+
step 230000 | 2162s | train_loss=0.0759
|
| 26 |
+
step 240000 | 2249s | train_loss=0.0739
|
| 27 |
+
step 250000 | 2335s | train_loss=0.0724
|
| 28 |
+
step 260000 | 2421s | train_loss=0.0703
|
| 29 |
+
step 270000 | 2508s | train_loss=0.0686
|
| 30 |
+
step 280000 | 2594s | train_loss=0.0669
|
| 31 |
+
step 290000 | 2681s | train_loss=0.0673
|
| 32 |
+
step 300000 | 2832s | train_loss=0.0649 | fid=53.4547
|
| 33 |
+
step 310000 | 2917s | train_loss=0.0643
|
| 34 |
+
step 320000 | 3003s | train_loss=0.0626
|
| 35 |
+
step 330000 | 3082s | train_loss=0.0603
|
| 36 |
+
step 340000 | 3167s | train_loss=0.0607
|
| 37 |
+
step 350000 | 3253s | train_loss=0.0589
|
| 38 |
+
step 360000 | 3339s | train_loss=0.0594
|
| 39 |
+
step 370000 | 3426s | train_loss=0.0571
|
| 40 |
+
step 380000 | 3512s | train_loss=0.0565
|
| 41 |
+
step 390000 | 3599s | train_loss=0.0557
|
| 42 |
+
step 400000 | 3750s | train_loss=0.0542 | fid=50.5135
|
| 43 |
+
step 410000 | 3835s | train_loss=0.0547
|
| 44 |
+
step 420000 | 3922s | train_loss=0.0536
|
| 45 |
+
step 430000 | 4008s | train_loss=0.0536
|
| 46 |
+
step 440000 | 4092s | train_loss=0.0516
|
| 47 |
+
step 450000 | 4177s | train_loss=0.0515
|
| 48 |
+
step 460000 | 4263s | train_loss=0.0519
|
| 49 |
+
step 470000 | 4348s | train_loss=0.0501
|
| 50 |
+
step 480000 | 4434s | train_loss=0.0491
|
| 51 |
+
step 490000 | 4520s | train_loss=0.0506
|
| 52 |
+
step 500000 | 4671s | train_loss=0.0480 | fid=50.0921
|
| 53 |
+
step 510000 | 4756s | train_loss=0.0481
|
| 54 |
+
step 520000 | 4842s | train_loss=0.0477
|
| 55 |
+
step 530000 | 4929s | train_loss=0.0468
|
| 56 |
+
step 540000 | 5014s | train_loss=0.0470
|
| 57 |
+
step 550000 | 5099s | train_loss=0.0456
|
| 58 |
+
step 560000 | 5184s | train_loss=0.0452
|
| 59 |
+
step 570000 | 5270s | train_loss=0.0457
|
| 60 |
+
step 580000 | 5357s | train_loss=0.0458
|
| 61 |
+
step 590000 | 5443s | train_loss=0.0448
|
| 62 |
+
step 600000 | 5594s | train_loss=0.0435 | fid=48.6845
|
| 63 |
+
step 610000 | 5679s | train_loss=0.0442
|
| 64 |
+
step 620000 | 5766s | train_loss=0.0440
|
| 65 |
+
step 630000 | 5852s | train_loss=0.0435
|
| 66 |
+
step 640000 | 5939s | train_loss=0.0419
|
| 67 |
+
step 650000 | 6020s | train_loss=0.0421
|
| 68 |
+
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|
| 69 |
+
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|
| 70 |
+
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|
| 71 |
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|
| 72 |
+
step 700000 | 6505s | train_loss=0.0406 | fid=47.1572
|
| 73 |
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|
| 74 |
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|
| 75 |
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|
| 76 |
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|
| 77 |
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|
| 78 |
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|
| 79 |
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|
| 80 |
+
step 780000 | 7186s | train_loss=0.0379
|
| 81 |
+
step 790000 | 7273s | train_loss=0.0374
|
| 82 |
+
step 800000 | 7424s | train_loss=0.0374 | fid=47.1213
|
| 83 |
+
step 810000 | 7509s | train_loss=0.0376
|
| 84 |
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step 820000 | 7595s | train_loss=0.0373
|
| 85 |
+
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|
| 86 |
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|
| 87 |
+
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|
| 88 |
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|
| 89 |
+
step 870000 | 8027s | train_loss=0.0360
|
| 90 |
+
step 880000 | 8098s | train_loss=0.0356
|
| 91 |
+
step 890000 | 8180s | train_loss=0.0351
|
| 92 |
+
step 900000 | 8332s | train_loss=0.0354 | fid=46.9063
|
| 93 |
+
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|
| 94 |
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|
| 95 |
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step 930000 | 8589s | train_loss=0.0344
|
| 96 |
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|
| 97 |
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|
| 98 |
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step 960000 | 8849s | train_loss=0.0342
|
| 99 |
+
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|
| 100 |
+
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|
| 101 |
+
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|
| 102 |
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step 1000000 | 9244s | train_loss=0.0328 | fid=45.6970
|
| 103 |
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|
| 104 |
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|
| 105 |
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|
| 106 |
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|
| 107 |
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|
| 108 |
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|
| 109 |
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|
| 110 |
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|
| 111 |
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|
| 112 |
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|
| 113 |
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|
| 114 |
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|
| 115 |
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|
| 116 |
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|
| 117 |
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|
| 118 |
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|
| 119 |
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|
| 120 |
+
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|
| 121 |
+
step 1190000 | 10942s | train_loss=0.0289
|
| 122 |
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|
| 397 |
+
step 3950000 | 36289s | train_loss=0.0111
|
| 398 |
+
step 3960000 | 36376s | train_loss=0.0111
|
| 399 |
+
step 3970000 | 36462s | train_loss=0.0119
|
| 400 |
+
step 3980000 | 36548s | train_loss=0.0111
|
| 401 |
+
step 3990000 | 36635s | train_loss=0.0111
|
| 402 |
+
step 4000000 | 36786s | train_loss=0.0116 | fid=41.8293
|
| 403 |
+
step 4010000 | 36870s | train_loss=0.0116
|
| 404 |
+
step 4020000 | 36957s | train_loss=0.0113
|
| 405 |
+
step 4030000 | 37043s | train_loss=0.0115
|
| 406 |
+
step 4040000 | 37129s | train_loss=0.0115
|
| 407 |
+
step 4050000 | 37216s | train_loss=0.0111
|
| 408 |
+
step 4060000 | 37293s | train_loss=0.0107
|
| 409 |
+
step 4070000 | 37379s | train_loss=0.0110
|
| 410 |
+
step 4080000 | 37465s | train_loss=0.0117
|
| 411 |
+
step 4090000 | 37552s | train_loss=0.0110
|
| 412 |
+
step 4100000 | 37703s | train_loss=0.0109 | fid=41.9478
|
| 413 |
+
step 4110000 | 37787s | train_loss=0.0112
|
| 414 |
+
step 4120000 | 37874s | train_loss=0.0111
|
| 415 |
+
step 4130000 | 37960s | train_loss=0.0107
|
| 416 |
+
step 4140000 | 38046s | train_loss=0.0105
|
| 417 |
+
step 4150000 | 38133s | train_loss=0.0112
|
| 418 |
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step 4160000 | 38220s | train_loss=0.0103
|
| 419 |
+
step 4170000 | 38296s | train_loss=0.0108
|
| 420 |
+
step 4180000 | 38381s | train_loss=0.0109
|
| 421 |
+
step 4190000 | 38468s | train_loss=0.0112
|
| 422 |
+
step 4200000 | 38620s | train_loss=0.0105 | fid=41.7243
|
| 423 |
+
step 4210000 | 38704s | train_loss=0.0111
|
| 424 |
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step 4220000 | 38790s | train_loss=0.0109
|
| 425 |
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step 4230000 | 38877s | train_loss=0.0111
|
| 426 |
+
step 4240000 | 38963s | train_loss=0.0111
|
| 427 |
+
step 4250000 | 39050s | train_loss=0.0109
|
| 428 |
+
step 4260000 | 39136s | train_loss=0.0105
|
| 429 |
+
step 4270000 | 39223s | train_loss=0.0101
|
| 430 |
+
step 4280000 | 39294s | train_loss=0.0105
|
| 431 |
+
step 4290000 | 39373s | train_loss=0.0106
|
| 432 |
+
step 4300000 | 39524s | train_loss=0.0103 | fid=41.8865
|
| 433 |
+
step 4310000 | 39609s | train_loss=0.0105
|
| 434 |
+
step 4320000 | 39695s | train_loss=0.0106
|
| 435 |
+
step 4330000 | 39782s | train_loss=0.0106
|
| 436 |
+
step 4340000 | 39868s | train_loss=0.0108
|
| 437 |
+
step 4350000 | 39955s | train_loss=0.0101
|
| 438 |
+
step 4360000 | 40041s | train_loss=0.0107
|
| 439 |
+
step 4370000 | 40127s | train_loss=0.0103
|
| 440 |
+
step 4380000 | 40214s | train_loss=0.0103
|
| 441 |
+
step 4390000 | 40299s | train_loss=0.0105
|
| 442 |
+
step 4400000 | 40437s | train_loss=0.0102 | fid=42.7575
|
| 443 |
+
step 4410000 | 40522s | train_loss=0.0110
|
| 444 |
+
step 4420000 | 40608s | train_loss=0.0100
|
| 445 |
+
step 4430000 | 40695s | train_loss=0.0106
|
| 446 |
+
step 4440000 | 40781s | train_loss=0.0107
|
| 447 |
+
step 4450000 | 40868s | train_loss=0.0100
|
| 448 |
+
step 4460000 | 40954s | train_loss=0.0098
|
| 449 |
+
step 4470000 | 41040s | train_loss=0.0103
|
| 450 |
+
step 4480000 | 41126s | train_loss=0.0098
|
| 451 |
+
step 4490000 | 41213s | train_loss=0.0102
|
| 452 |
+
step 4500000 | 41347s | train_loss=0.0101 | fid=42.4429
|
| 453 |
+
step 4510000 | 41432s | train_loss=0.0103
|
| 454 |
+
step 4520000 | 41518s | train_loss=0.0105
|
| 455 |
+
step 4530000 | 41604s | train_loss=0.0101
|
| 456 |
+
step 4540000 | 41691s | train_loss=0.0104
|
| 457 |
+
step 4550000 | 41777s | train_loss=0.0099
|
| 458 |
+
step 4560000 | 41864s | train_loss=0.0098
|
| 459 |
+
step 4570000 | 41950s | train_loss=0.0097
|
| 460 |
+
step 4580000 | 42037s | train_loss=0.0097
|
| 461 |
+
step 4590000 | 42123s | train_loss=0.0098
|
| 462 |
+
step 4600000 | 42275s | train_loss=0.0099 | fid=42.2832
|
| 463 |
+
step 4610000 | 42348s | train_loss=0.0098
|
| 464 |
+
step 4620000 | 42427s | train_loss=0.0097
|
| 465 |
+
step 4630000 | 42514s | train_loss=0.0097
|
| 466 |
+
step 4640000 | 42600s | train_loss=0.0098
|
| 467 |
+
step 4650000 | 42686s | train_loss=0.0101
|
| 468 |
+
step 4660000 | 42773s | train_loss=0.0098
|
| 469 |
+
step 4670000 | 42859s | train_loss=0.0095
|
| 470 |
+
step 4680000 | 42946s | train_loss=0.0102
|
| 471 |
+
step 4690000 | 43032s | train_loss=0.0100
|
| 472 |
+
step 4700000 | 43184s | train_loss=0.0099 | fid=42.4238
|
| 473 |
+
step 4710000 | 43268s | train_loss=0.0099
|
| 474 |
+
step 4720000 | 43353s | train_loss=0.0100
|
| 475 |
+
step 4730000 | 43428s | train_loss=0.0095
|
| 476 |
+
step 4740000 | 43515s | train_loss=0.0096
|
| 477 |
+
step 4750000 | 43601s | train_loss=0.0100
|
| 478 |
+
step 4760000 | 43688s | train_loss=0.0099
|
| 479 |
+
step 4770000 | 43774s | train_loss=0.0098
|
| 480 |
+
step 4780000 | 43861s | train_loss=0.0100
|
| 481 |
+
step 4790000 | 43947s | train_loss=0.0096
|
| 482 |
+
step 4800000 | 44098s | train_loss=0.0099 | fid=41.8688
|
| 483 |
+
step 4810000 | 44182s | train_loss=0.0099
|
| 484 |
+
step 4820000 | 44269s | train_loss=0.0104
|
| 485 |
+
step 4830000 | 44354s | train_loss=0.0099
|
| 486 |
+
step 4840000 | 44431s | train_loss=0.0096
|
| 487 |
+
step 4850000 | 44518s | train_loss=0.0098
|
| 488 |
+
step 4860000 | 44604s | train_loss=0.0093
|
| 489 |
+
step 4870000 | 44691s | train_loss=0.0091
|
| 490 |
+
step 4880000 | 44777s | train_loss=0.0099
|
| 491 |
+
step 4890000 | 44864s | train_loss=0.0100
|
| 492 |
+
step 4900000 | 45015s | train_loss=0.0098 | fid=41.9554
|
| 493 |
+
step 4910000 | 45100s | train_loss=0.0092
|
| 494 |
+
step 4920000 | 45186s | train_loss=0.0098
|
| 495 |
+
step 4930000 | 45273s | train_loss=0.0096
|
| 496 |
+
step 4940000 | 45358s | train_loss=0.0092
|
| 497 |
+
step 4950000 | 45441s | train_loss=0.0092
|
| 498 |
+
step 4960000 | 45528s | train_loss=0.0097
|
| 499 |
+
step 4970000 | 45614s | train_loss=0.0097
|
| 500 |
+
step 4980000 | 45701s | train_loss=0.0093
|
| 501 |
+
step 4990000 | 45787s | train_loss=0.0090
|
| 502 |
+
step 5000000 | 45934s | train_loss=0.0094 | fid=42.0381
|
results/celeba_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed47/d80/config.json
ADDED
|
@@ -0,0 +1,26 @@
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| 1 |
+
{
|
| 2 |
+
"vae_checkpoint": "vae_checkpoints/celeba_resnet_modernloss_d80/vae.pt",
|
| 3 |
+
"out": "results/celeba_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed47/d80",
|
| 4 |
+
"subset_path": "diagnostics/celeba_diverse_1k_mean_plus_sd/subset_indices.json",
|
| 5 |
+
"train_tar": "/overflow/data/cerberus/celeba_hq_256_partitioned_ws/train/celeba_hq_256-train-0000.tar",
|
| 6 |
+
"n_train": 1000,
|
| 7 |
+
"total_steps": 5000000,
|
| 8 |
+
"eval_interval": 10000,
|
| 9 |
+
"mem_interval": 100000,
|
| 10 |
+
"fid_interval": 100000,
|
| 11 |
+
"fid_n_real": 1000,
|
| 12 |
+
"fid_n_gen": 10000,
|
| 13 |
+
"n_gen_samples": 10000,
|
| 14 |
+
"n_sde_steps": 500,
|
| 15 |
+
"batch_size": 512,
|
| 16 |
+
"hidden": 1024,
|
| 17 |
+
"depth": 5,
|
| 18 |
+
"optimizer": "sgd",
|
| 19 |
+
"lr": 0.001,
|
| 20 |
+
"momentum": 0.8,
|
| 21 |
+
"t_min": 0.01,
|
| 22 |
+
"t_max": 3.0,
|
| 23 |
+
"t_eval": 0.1,
|
| 24 |
+
"seed": 47,
|
| 25 |
+
"device": null
|
| 26 |
+
}
|
results/celeba_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed47/d80/metrics.jsonl
ADDED
|
The diff for this file is too large to render.
See raw diff
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|
results/celeba_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed47/d80/runner.log
ADDED
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@@ -0,0 +1,502 @@
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| 1 |
+
FID real-side stats cached over 1000 diverse train images
|
| 2 |
+
step 1 | 65s | train_loss=0.9996 | fid=276.1425
|
| 3 |
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|
| 4 |
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|
| 5 |
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|
| 6 |
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|
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|
| 8 |
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|
| 9 |
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|
| 10 |
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|
| 11 |
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|
| 12 |
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|
| 13 |
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|
| 14 |
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| 15 |
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|
| 16 |
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|
| 17 |
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|
| 18 |
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| 19 |
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| 20 |
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|
| 21 |
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| 22 |
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|
| 23 |
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|
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|
| 35 |
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| 36 |
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| 42 |
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| 495 |
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| 496 |
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| 497 |
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| 498 |
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| 499 |
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|
| 500 |
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| 501 |
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|
| 502 |
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step 5000000 | 45909s | train_loss=0.0111 | fid=38.6220
|
results/celeba_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed47/d90/config.json
ADDED
|
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| 1 |
+
{
|
| 2 |
+
"vae_checkpoint": "vae_checkpoints/celeba_resnet_modernloss_d90/vae.pt",
|
| 3 |
+
"out": "results/celeba_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed47/d90",
|
| 4 |
+
"subset_path": "diagnostics/celeba_diverse_1k_mean_plus_sd/subset_indices.json",
|
| 5 |
+
"train_tar": "/overflow/data/cerberus/celeba_hq_256_partitioned_ws/train/celeba_hq_256-train-0000.tar",
|
| 6 |
+
"n_train": 1000,
|
| 7 |
+
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|
| 8 |
+
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|
| 9 |
+
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|
| 10 |
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"fid_interval": 100000,
|
| 11 |
+
"fid_n_real": 1000,
|
| 12 |
+
"fid_n_gen": 10000,
|
| 13 |
+
"n_gen_samples": 10000,
|
| 14 |
+
"n_sde_steps": 500,
|
| 15 |
+
"batch_size": 512,
|
| 16 |
+
"hidden": 1024,
|
| 17 |
+
"depth": 5,
|
| 18 |
+
"optimizer": "sgd",
|
| 19 |
+
"lr": 0.001,
|
| 20 |
+
"momentum": 0.8,
|
| 21 |
+
"t_min": 0.01,
|
| 22 |
+
"t_max": 3.0,
|
| 23 |
+
"t_eval": 0.1,
|
| 24 |
+
"seed": 47,
|
| 25 |
+
"device": null
|
| 26 |
+
}
|
results/celeba_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed47/d90/metrics.jsonl
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
results/celeba_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed47/d90/runner.log
ADDED
|
@@ -0,0 +1,502 @@
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|
| 1 |
+
FID real-side stats cached over 1000 diverse train images
|
| 2 |
+
step 1 | 69s | train_loss=0.9995 | fid=306.2379
|
| 3 |
+
step 10000 | 153s | train_loss=0.8112
|
| 4 |
+
step 20000 | 240s | train_loss=0.6968
|
| 5 |
+
step 30000 | 326s | train_loss=0.5647
|
| 6 |
+
step 40000 | 413s | train_loss=0.4195
|
| 7 |
+
step 50000 | 500s | train_loss=0.3005
|
| 8 |
+
step 60000 | 586s | train_loss=0.2226
|
| 9 |
+
step 70000 | 673s | train_loss=0.1804
|
| 10 |
+
step 80000 | 759s | train_loss=0.1545
|
| 11 |
+
step 90000 | 846s | train_loss=0.1398
|
| 12 |
+
step 100000 | 998s | train_loss=0.1315 | fid=58.9029
|
| 13 |
+
step 110000 | 1082s | train_loss=0.1240
|
| 14 |
+
step 120000 | 1166s | train_loss=0.1151
|
| 15 |
+
step 130000 | 1253s | train_loss=0.1100
|
| 16 |
+
step 140000 | 1339s | train_loss=0.1052
|
| 17 |
+
step 150000 | 1426s | train_loss=0.1003
|
| 18 |
+
step 160000 | 1512s | train_loss=0.0980
|
| 19 |
+
step 170000 | 1599s | train_loss=0.0927
|
| 20 |
+
step 180000 | 1685s | train_loss=0.0899
|
| 21 |
+
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|
| 22 |
+
step 200000 | 1922s | train_loss=0.0856 | fid=58.2538
|
| 23 |
+
step 210000 | 2009s | train_loss=0.0835
|
| 24 |
+
step 220000 | 2093s | train_loss=0.0805
|
| 25 |
+
step 230000 | 2176s | train_loss=0.0776
|
| 26 |
+
step 240000 | 2262s | train_loss=0.0753
|
| 27 |
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|
| 28 |
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step 260000 | 2435s | train_loss=0.0731
|
| 29 |
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|
| 30 |
+
step 280000 | 2608s | train_loss=0.0698
|
| 31 |
+
step 290000 | 2695s | train_loss=0.0671
|
| 32 |
+
step 300000 | 2845s | train_loss=0.0676 | fid=55.2758
|
| 33 |
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|
| 34 |
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|
| 35 |
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|
| 36 |
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|
| 37 |
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|
| 38 |
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|
| 39 |
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|
| 40 |
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|
| 41 |
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|
| 42 |
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|
| 43 |
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|
| 44 |
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|
| 45 |
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|
| 46 |
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|
| 47 |
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|
| 48 |
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|
| 49 |
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|
| 50 |
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|
| 51 |
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|
| 52 |
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|
| 53 |
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|
| 54 |
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step 520000 | 4858s | train_loss=0.0517
|
| 55 |
+
step 530000 | 4944s | train_loss=0.0497
|
| 56 |
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|
| 57 |
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|
| 58 |
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|
| 59 |
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|
| 60 |
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|
| 61 |
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|
| 62 |
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step 600000 | 5608s | train_loss=0.0478 | fid=49.5994
|
| 63 |
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|
| 64 |
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|
| 65 |
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|
| 66 |
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|
| 67 |
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|
| 68 |
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|
| 69 |
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|
| 70 |
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|
| 71 |
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|
| 72 |
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|
| 73 |
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|
| 74 |
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|
| 75 |
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|
| 76 |
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|
| 77 |
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|
| 78 |
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|
| 79 |
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|
| 80 |
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|
| 81 |
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|
| 82 |
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|
| 83 |
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|
| 84 |
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|
| 85 |
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|
| 86 |
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|
| 87 |
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|
| 88 |
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|
| 89 |
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|
| 90 |
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|
| 91 |
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|
| 92 |
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|
| 93 |
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|
| 94 |
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|
| 95 |
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|
| 96 |
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|
| 97 |
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|
| 98 |
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|
| 99 |
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|
| 100 |
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|
| 101 |
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|
| 102 |
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|
| 103 |
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|
| 104 |
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|
| 105 |
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|
| 106 |
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|
| 107 |
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|
| 108 |
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|
| 109 |
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|
| 110 |
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|
| 111 |
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|
| 112 |
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|
| 113 |
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|
| 114 |
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|
| 115 |
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|
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|
| 391 |
+
step 3890000 | 35767s | train_loss=0.0142
|
| 392 |
+
step 3900000 | 35918s | train_loss=0.0142 | fid=40.2856
|
| 393 |
+
step 3910000 | 36004s | train_loss=0.0148
|
| 394 |
+
step 3920000 | 36091s | train_loss=0.0144
|
| 395 |
+
step 3930000 | 36178s | train_loss=0.0147
|
| 396 |
+
step 3940000 | 36254s | train_loss=0.0142
|
| 397 |
+
step 3950000 | 36339s | train_loss=0.0143
|
| 398 |
+
step 3960000 | 36426s | train_loss=0.0142
|
| 399 |
+
step 3970000 | 36512s | train_loss=0.0141
|
| 400 |
+
step 3980000 | 36599s | train_loss=0.0135
|
| 401 |
+
step 3990000 | 36685s | train_loss=0.0143
|
| 402 |
+
step 4000000 | 36835s | train_loss=0.0140 | fid=40.3688
|
| 403 |
+
step 4010000 | 36922s | train_loss=0.0146
|
| 404 |
+
step 4020000 | 37009s | train_loss=0.0138
|
| 405 |
+
step 4030000 | 37095s | train_loss=0.0145
|
| 406 |
+
step 4040000 | 37182s | train_loss=0.0141
|
| 407 |
+
step 4050000 | 37260s | train_loss=0.0138
|
| 408 |
+
step 4060000 | 37345s | train_loss=0.0140
|
| 409 |
+
step 4070000 | 37432s | train_loss=0.0146
|
| 410 |
+
step 4080000 | 37518s | train_loss=0.0148
|
| 411 |
+
step 4090000 | 37605s | train_loss=0.0143
|
| 412 |
+
step 4100000 | 37755s | train_loss=0.0153 | fid=39.8453
|
| 413 |
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step 4110000 | 37841s | train_loss=0.0139
|
| 414 |
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step 4120000 | 37928s | train_loss=0.0143
|
| 415 |
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step 4130000 | 38014s | train_loss=0.0141
|
| 416 |
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step 4140000 | 38101s | train_loss=0.0145
|
| 417 |
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step 4150000 | 38188s | train_loss=0.0138
|
| 418 |
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step 4160000 | 38265s | train_loss=0.0136
|
| 419 |
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step 4170000 | 38350s | train_loss=0.0142
|
| 420 |
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step 4180000 | 38436s | train_loss=0.0136
|
| 421 |
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step 4190000 | 38523s | train_loss=0.0146
|
| 422 |
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step 4200000 | 38673s | train_loss=0.0141 | fid=39.9167
|
| 423 |
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step 4210000 | 38759s | train_loss=0.0133
|
| 424 |
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step 4220000 | 38846s | train_loss=0.0136
|
| 425 |
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step 4230000 | 38932s | train_loss=0.0147
|
| 426 |
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step 4240000 | 39019s | train_loss=0.0141
|
| 427 |
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step 4250000 | 39105s | train_loss=0.0131
|
| 428 |
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step 4260000 | 39192s | train_loss=0.0140
|
| 429 |
+
step 4270000 | 39269s | train_loss=0.0147
|
| 430 |
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step 4280000 | 39342s | train_loss=0.0132
|
| 431 |
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step 4290000 | 39429s | train_loss=0.0134
|
| 432 |
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step 4300000 | 39578s | train_loss=0.0135 | fid=40.0564
|
| 433 |
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step 4310000 | 39665s | train_loss=0.0133
|
| 434 |
+
step 4320000 | 39751s | train_loss=0.0132
|
| 435 |
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step 4330000 | 39838s | train_loss=0.0136
|
| 436 |
+
step 4340000 | 39925s | train_loss=0.0140
|
| 437 |
+
step 4350000 | 40011s | train_loss=0.0136
|
| 438 |
+
step 4360000 | 40098s | train_loss=0.0131
|
| 439 |
+
step 4370000 | 40184s | train_loss=0.0138
|
| 440 |
+
step 4380000 | 40271s | train_loss=0.0135
|
| 441 |
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step 4390000 | 40343s | train_loss=0.0135
|
| 442 |
+
step 4400000 | 40492s | train_loss=0.0135 | fid=39.1747
|
| 443 |
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step 4410000 | 40579s | train_loss=0.0131
|
| 444 |
+
step 4420000 | 40665s | train_loss=0.0133
|
| 445 |
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step 4430000 | 40752s | train_loss=0.0133
|
| 446 |
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step 4440000 | 40838s | train_loss=0.0130
|
| 447 |
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step 4450000 | 40925s | train_loss=0.0140
|
| 448 |
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step 4460000 | 41011s | train_loss=0.0133
|
| 449 |
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step 4470000 | 41098s | train_loss=0.0144
|
| 450 |
+
step 4480000 | 41184s | train_loss=0.0139
|
| 451 |
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step 4490000 | 41271s | train_loss=0.0134
|
| 452 |
+
step 4500000 | 41401s | train_loss=0.0137 | fid=39.3096
|
| 453 |
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step 4510000 | 41487s | train_loss=0.0122
|
| 454 |
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step 4520000 | 41574s | train_loss=0.0131
|
| 455 |
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step 4530000 | 41660s | train_loss=0.0137
|
| 456 |
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step 4540000 | 41747s | train_loss=0.0128
|
| 457 |
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step 4550000 | 41833s | train_loss=0.0128
|
| 458 |
+
step 4560000 | 41920s | train_loss=0.0135
|
| 459 |
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step 4570000 | 42006s | train_loss=0.0133
|
| 460 |
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step 4580000 | 42093s | train_loss=0.0126
|
| 461 |
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step 4590000 | 42179s | train_loss=0.0131
|
| 462 |
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step 4600000 | 42326s | train_loss=0.0122 | fid=39.1951
|
| 463 |
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step 4610000 | 42401s | train_loss=0.0132
|
| 464 |
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step 4620000 | 42487s | train_loss=0.0136
|
| 465 |
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step 4630000 | 42573s | train_loss=0.0127
|
| 466 |
+
step 4640000 | 42660s | train_loss=0.0121
|
| 467 |
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step 4650000 | 42747s | train_loss=0.0131
|
| 468 |
+
step 4660000 | 42833s | train_loss=0.0127
|
| 469 |
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step 4670000 | 42919s | train_loss=0.0134
|
| 470 |
+
step 4680000 | 43006s | train_loss=0.0124
|
| 471 |
+
step 4690000 | 43092s | train_loss=0.0121
|
| 472 |
+
step 4700000 | 43242s | train_loss=0.0121 | fid=40.1110
|
| 473 |
+
step 4710000 | 43328s | train_loss=0.0122
|
| 474 |
+
step 4720000 | 43403s | train_loss=0.0129
|
| 475 |
+
step 4730000 | 43489s | train_loss=0.0124
|
| 476 |
+
step 4740000 | 43576s | train_loss=0.0121
|
| 477 |
+
step 4750000 | 43662s | train_loss=0.0126
|
| 478 |
+
step 4760000 | 43749s | train_loss=0.0126
|
| 479 |
+
step 4770000 | 43836s | train_loss=0.0121
|
| 480 |
+
step 4780000 | 43922s | train_loss=0.0138
|
| 481 |
+
step 4790000 | 44009s | train_loss=0.0123
|
| 482 |
+
step 4800000 | 44159s | train_loss=0.0130 | fid=39.0514
|
| 483 |
+
step 4810000 | 44245s | train_loss=0.0119
|
| 484 |
+
step 4820000 | 44330s | train_loss=0.0115
|
| 485 |
+
step 4830000 | 44408s | train_loss=0.0124
|
| 486 |
+
step 4840000 | 44495s | train_loss=0.0118
|
| 487 |
+
step 4850000 | 44581s | train_loss=0.0122
|
| 488 |
+
step 4860000 | 44668s | train_loss=0.0127
|
| 489 |
+
step 4870000 | 44754s | train_loss=0.0121
|
| 490 |
+
step 4880000 | 44841s | train_loss=0.0123
|
| 491 |
+
step 4890000 | 44927s | train_loss=0.0121
|
| 492 |
+
step 4900000 | 45077s | train_loss=0.0129 | fid=39.4174
|
| 493 |
+
step 4910000 | 45164s | train_loss=0.0123
|
| 494 |
+
step 4920000 | 45250s | train_loss=0.0119
|
| 495 |
+
step 4930000 | 45335s | train_loss=0.0123
|
| 496 |
+
step 4940000 | 45419s | train_loss=0.0129
|
| 497 |
+
step 4950000 | 45506s | train_loss=0.0121
|
| 498 |
+
step 4960000 | 45592s | train_loss=0.0124
|
| 499 |
+
step 4970000 | 45679s | train_loss=0.0128
|
| 500 |
+
step 4980000 | 45765s | train_loss=0.0119
|
| 501 |
+
step 4990000 | 45852s | train_loss=0.0120
|
| 502 |
+
step 5000000 | 45973s | train_loss=0.0123 | fid=38.6482
|
results/cifar10_beta005_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed42/d100/config.json
ADDED
|
@@ -0,0 +1,25 @@
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|
| 1 |
+
{
|
| 2 |
+
"vae_checkpoint": "vae_checkpoints/cifar10_resnet_beta005_d100/vae.pt",
|
| 3 |
+
"out": "results/cifar10_beta005_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed42/d100",
|
| 4 |
+
"subset_path": "diagnostics/cifar10_diverse_1k_mean_plus_sd/subset_indices.json",
|
| 5 |
+
"n_train": 1000,
|
| 6 |
+
"total_steps": 5000000,
|
| 7 |
+
"eval_interval": 10000,
|
| 8 |
+
"mem_interval": 100000,
|
| 9 |
+
"fid_interval": 100000,
|
| 10 |
+
"fid_n_real": 1000,
|
| 11 |
+
"fid_n_gen": 10000,
|
| 12 |
+
"n_gen_samples": 10000,
|
| 13 |
+
"n_sde_steps": 500,
|
| 14 |
+
"batch_size": 512,
|
| 15 |
+
"hidden": 1024,
|
| 16 |
+
"depth": 5,
|
| 17 |
+
"optimizer": "sgd",
|
| 18 |
+
"lr": 0.001,
|
| 19 |
+
"momentum": 0.8,
|
| 20 |
+
"t_min": 0.01,
|
| 21 |
+
"t_max": 3.0,
|
| 22 |
+
"t_eval": 0.1,
|
| 23 |
+
"seed": 42,
|
| 24 |
+
"device": null
|
| 25 |
+
}
|
results/cifar10_beta005_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed42/d100/metrics.jsonl
ADDED
|
The diff for this file is too large to render.
See raw diff
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|
results/cifar10_beta005_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed42/d100/runner.log
ADDED
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@@ -0,0 +1,502 @@
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| 1 |
+
FID real-side stats cached over 1000 diverse train images
|
| 2 |
+
step 1 | 75s | train_loss=0.9952 | fid=311.2346
|
| 3 |
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|
| 4 |
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|
| 5 |
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|
| 6 |
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|
| 7 |
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|
| 8 |
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|
| 9 |
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|
| 10 |
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|
| 11 |
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|
| 12 |
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|
| 13 |
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|
| 14 |
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|
| 15 |
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|
| 16 |
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|
| 17 |
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|
| 18 |
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| 19 |
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| 20 |
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|
| 21 |
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|
| 22 |
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|
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| 24 |
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| 28 |
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| 29 |
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| 32 |
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|
| 33 |
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| 34 |
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| 35 |
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| 42 |
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| 43 |
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| 460 |
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| 472 |
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| 474 |
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| 476 |
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| 477 |
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| 478 |
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| 479 |
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| 480 |
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| 482 |
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| 484 |
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| 485 |
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| 486 |
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| 488 |
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| 489 |
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|
| 490 |
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| 491 |
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|
| 492 |
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|
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|
| 494 |
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|
| 495 |
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|
| 496 |
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|
| 497 |
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|
| 498 |
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step 4960000 | 51010s | train_loss=0.0137
|
| 499 |
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|
| 500 |
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|
| 501 |
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step 4990000 | 51081s | train_loss=0.0126
|
| 502 |
+
step 5000000 | 51122s | train_loss=0.0132 | fid=107.3757
|
results/cifar10_beta005_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed42/d120/config.json
ADDED
|
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|
| 1 |
+
{
|
| 2 |
+
"vae_checkpoint": "vae_checkpoints/cifar10_resnet_beta005_d120/vae.pt",
|
| 3 |
+
"out": "results/cifar10_beta005_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed42/d120",
|
| 4 |
+
"subset_path": "diagnostics/cifar10_diverse_1k_mean_plus_sd/subset_indices.json",
|
| 5 |
+
"n_train": 1000,
|
| 6 |
+
"total_steps": 5000000,
|
| 7 |
+
"eval_interval": 10000,
|
| 8 |
+
"mem_interval": 100000,
|
| 9 |
+
"fid_interval": 100000,
|
| 10 |
+
"fid_n_real": 1000,
|
| 11 |
+
"fid_n_gen": 10000,
|
| 12 |
+
"n_gen_samples": 10000,
|
| 13 |
+
"n_sde_steps": 500,
|
| 14 |
+
"batch_size": 512,
|
| 15 |
+
"hidden": 1024,
|
| 16 |
+
"depth": 5,
|
| 17 |
+
"optimizer": "sgd",
|
| 18 |
+
"lr": 0.001,
|
| 19 |
+
"momentum": 0.8,
|
| 20 |
+
"t_min": 0.01,
|
| 21 |
+
"t_max": 3.0,
|
| 22 |
+
"t_eval": 0.1,
|
| 23 |
+
"seed": 42,
|
| 24 |
+
"device": null
|
| 25 |
+
}
|
results/cifar10_beta005_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed42/d120/metrics.jsonl
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
results/cifar10_beta005_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed42/d120/runner.log
ADDED
|
@@ -0,0 +1,502 @@
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|
| 1 |
+
FID real-side stats cached over 1000 diverse train images
|
| 2 |
+
step 1 | 79s | train_loss=1.0000 | fid=305.9184
|
| 3 |
+
step 10000 | 176s | train_loss=0.8098
|
| 4 |
+
step 20000 | 275s | train_loss=0.6801
|
| 5 |
+
step 30000 | 374s | train_loss=0.5493
|
| 6 |
+
step 40000 | 473s | train_loss=0.4204
|
| 7 |
+
step 50000 | 570s | train_loss=0.3138
|
| 8 |
+
step 60000 | 670s | train_loss=0.2384
|
| 9 |
+
step 70000 | 770s | train_loss=0.1958
|
| 10 |
+
step 80000 | 869s | train_loss=0.1617
|
| 11 |
+
step 90000 | 969s | train_loss=0.1442
|
| 12 |
+
step 100000 | 1146s | train_loss=0.1335 | fid=179.7661
|
| 13 |
+
step 110000 | 1239s | train_loss=0.1194
|
| 14 |
+
step 120000 | 1337s | train_loss=0.1134
|
| 15 |
+
step 130000 | 1435s | train_loss=0.1104
|
| 16 |
+
step 140000 | 1534s | train_loss=0.1046
|
| 17 |
+
step 150000 | 1632s | train_loss=0.0993
|
| 18 |
+
step 160000 | 1731s | train_loss=0.0955
|
| 19 |
+
step 170000 | 1830s | train_loss=0.0951
|
| 20 |
+
step 180000 | 1929s | train_loss=0.0940
|
| 21 |
+
step 190000 | 2025s | train_loss=0.0913
|
| 22 |
+
step 200000 | 2205s | train_loss=0.0860 | fid=174.9677
|
| 23 |
+
step 210000 | 2297s | train_loss=0.0835
|
| 24 |
+
step 220000 | 2396s | train_loss=0.0838
|
| 25 |
+
step 230000 | 2497s | train_loss=0.0843
|
| 26 |
+
step 240000 | 2595s | train_loss=0.0782
|
| 27 |
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|
| 28 |
+
step 260000 | 2794s | train_loss=0.0775
|
| 29 |
+
step 270000 | 2893s | train_loss=0.0742
|
| 30 |
+
step 280000 | 2993s | train_loss=0.0737
|
| 31 |
+
step 290000 | 3090s | train_loss=0.0714
|
| 32 |
+
step 300000 | 3267s | train_loss=0.0705 | fid=173.0907
|
| 33 |
+
step 310000 | 3361s | train_loss=0.0677
|
| 34 |
+
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|
| 35 |
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|
| 36 |
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|
| 37 |
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|
| 38 |
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|
| 39 |
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|
| 40 |
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|
| 41 |
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|
| 42 |
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step 400000 | 4324s | train_loss=0.0612 | fid=169.2907
|
| 43 |
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step 410000 | 4418s | train_loss=0.0604
|
| 44 |
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|
| 45 |
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|
| 46 |
+
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|
| 47 |
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|
| 48 |
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step 460000 | 4911s | train_loss=0.0563
|
| 49 |
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|
| 50 |
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|
| 51 |
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step 490000 | 5207s | train_loss=0.0547
|
| 52 |
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step 500000 | 5386s | train_loss=0.0533 | fid=161.5933
|
| 53 |
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step 510000 | 5481s | train_loss=0.0540
|
| 54 |
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step 520000 | 5579s | train_loss=0.0521
|
| 55 |
+
step 530000 | 5675s | train_loss=0.0528
|
| 56 |
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step 540000 | 5774s | train_loss=0.0516
|
| 57 |
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|
| 58 |
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|
| 59 |
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step 570000 | 6067s | train_loss=0.0505
|
| 60 |
+
step 580000 | 6165s | train_loss=0.0496
|
| 61 |
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|
| 62 |
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step 600000 | 6440s | train_loss=0.0496 | fid=154.7887
|
| 63 |
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|
| 64 |
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|
| 65 |
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|
| 66 |
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|
| 67 |
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|
| 68 |
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|
| 69 |
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|
| 70 |
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|
| 71 |
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|
| 72 |
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|
| 73 |
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|
| 74 |
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|
| 75 |
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|
| 76 |
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|
| 77 |
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|
| 78 |
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|
| 79 |
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|
| 80 |
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|
| 81 |
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|
| 82 |
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|
| 83 |
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|
| 84 |
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|
| 85 |
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|
| 86 |
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|
| 87 |
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|
| 88 |
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|
| 89 |
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|
| 90 |
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|
| 91 |
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|
| 92 |
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|
| 93 |
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|
| 94 |
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|
| 95 |
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|
| 96 |
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|
| 97 |
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|
| 98 |
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|
| 99 |
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|
| 100 |
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|
| 101 |
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|
| 102 |
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|
| 103 |
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|
| 104 |
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|
| 105 |
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|
| 106 |
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|
| 107 |
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|
| 108 |
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|
| 109 |
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|
| 110 |
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|
| 111 |
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step 3840000 | 38117s | train_loss=0.0175
|
| 387 |
+
step 3850000 | 38198s | train_loss=0.0191
|
| 388 |
+
step 3860000 | 38279s | train_loss=0.0173
|
| 389 |
+
step 3870000 | 38360s | train_loss=0.0173
|
| 390 |
+
step 3880000 | 38424s | train_loss=0.0182
|
| 391 |
+
step 3890000 | 38506s | train_loss=0.0175
|
| 392 |
+
step 3900000 | 38673s | train_loss=0.0174 | fid=118.1084
|
| 393 |
+
step 3910000 | 38755s | train_loss=0.0178
|
| 394 |
+
step 3920000 | 38826s | train_loss=0.0172
|
| 395 |
+
step 3930000 | 38906s | train_loss=0.0182
|
| 396 |
+
step 3940000 | 38987s | train_loss=0.0181
|
| 397 |
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step 3950000 | 39067s | train_loss=0.0180
|
| 398 |
+
step 3960000 | 39148s | train_loss=0.0174
|
| 399 |
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step 3970000 | 39228s | train_loss=0.0179
|
| 400 |
+
step 3980000 | 39302s | train_loss=0.0189
|
| 401 |
+
step 3990000 | 39369s | train_loss=0.0172
|
| 402 |
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step 4000000 | 39544s | train_loss=0.0181 | fid=115.6983
|
| 403 |
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step 4010000 | 39626s | train_loss=0.0172
|
| 404 |
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step 4020000 | 39691s | train_loss=0.0169
|
| 405 |
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step 4030000 | 39773s | train_loss=0.0178
|
| 406 |
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step 4040000 | 39854s | train_loss=0.0175
|
| 407 |
+
step 4050000 | 39934s | train_loss=0.0179
|
| 408 |
+
step 4060000 | 40015s | train_loss=0.0169
|
| 409 |
+
step 4070000 | 40097s | train_loss=0.0173
|
| 410 |
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step 4080000 | 40177s | train_loss=0.0179
|
| 411 |
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step 4090000 | 40247s | train_loss=0.0167
|
| 412 |
+
step 4100000 | 40435s | train_loss=0.0163 | fid=115.4803
|
| 413 |
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step 4110000 | 40511s | train_loss=0.0173
|
| 414 |
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step 4120000 | 40575s | train_loss=0.0186
|
| 415 |
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step 4130000 | 40656s | train_loss=0.0178
|
| 416 |
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step 4140000 | 40737s | train_loss=0.0168
|
| 417 |
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step 4150000 | 40818s | train_loss=0.0190
|
| 418 |
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step 4160000 | 40899s | train_loss=0.0185
|
| 419 |
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step 4170000 | 40979s | train_loss=0.0178
|
| 420 |
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step 4180000 | 41056s | train_loss=0.0170
|
| 421 |
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step 4190000 | 41119s | train_loss=0.0172
|
| 422 |
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step 4200000 | 41299s | train_loss=0.0180 | fid=113.8607
|
| 423 |
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step 4210000 | 41381s | train_loss=0.0174
|
| 424 |
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step 4220000 | 41444s | train_loss=0.0166
|
| 425 |
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step 4230000 | 41525s | train_loss=0.0171
|
| 426 |
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step 4240000 | 41607s | train_loss=0.0178
|
| 427 |
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step 4250000 | 41689s | train_loss=0.0165
|
| 428 |
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step 4260000 | 41771s | train_loss=0.0171
|
| 429 |
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step 4270000 | 41852s | train_loss=0.0166
|
| 430 |
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step 4280000 | 41932s | train_loss=0.0169
|
| 431 |
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step 4290000 | 41988s | train_loss=0.0169
|
| 432 |
+
step 4300000 | 42155s | train_loss=0.0165 | fid=112.9609
|
| 433 |
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step 4310000 | 42237s | train_loss=0.0177
|
| 434 |
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step 4320000 | 42309s | train_loss=0.0175
|
| 435 |
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step 4330000 | 42390s | train_loss=0.0170
|
| 436 |
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step 4340000 | 42471s | train_loss=0.0165
|
| 437 |
+
step 4350000 | 42552s | train_loss=0.0167
|
| 438 |
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step 4360000 | 42634s | train_loss=0.0157
|
| 439 |
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step 4370000 | 42715s | train_loss=0.0176
|
| 440 |
+
step 4380000 | 42797s | train_loss=0.0172
|
| 441 |
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step 4390000 | 42859s | train_loss=0.0161
|
| 442 |
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step 4400000 | 43040s | train_loss=0.0165 | fid=111.1223
|
| 443 |
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step 4410000 | 43122s | train_loss=0.0170
|
| 444 |
+
step 4420000 | 43192s | train_loss=0.0162
|
| 445 |
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step 4430000 | 43273s | train_loss=0.0164
|
| 446 |
+
step 4440000 | 43355s | train_loss=0.0167
|
| 447 |
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step 4450000 | 43437s | train_loss=0.0179
|
| 448 |
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step 4460000 | 43518s | train_loss=0.0174
|
| 449 |
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step 4470000 | 43600s | train_loss=0.0161
|
| 450 |
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step 4480000 | 43681s | train_loss=0.0161
|
| 451 |
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step 4490000 | 43748s | train_loss=0.0161
|
| 452 |
+
step 4500000 | 43907s | train_loss=0.0164 | fid=111.1135
|
| 453 |
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step 4510000 | 43987s | train_loss=0.0179
|
| 454 |
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step 4520000 | 44053s | train_loss=0.0159
|
| 455 |
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step 4530000 | 44133s | train_loss=0.0175
|
| 456 |
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step 4540000 | 44214s | train_loss=0.0162
|
| 457 |
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step 4550000 | 44295s | train_loss=0.0158
|
| 458 |
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step 4560000 | 44377s | train_loss=0.0165
|
| 459 |
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step 4570000 | 44459s | train_loss=0.0185
|
| 460 |
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step 4580000 | 44538s | train_loss=0.0158
|
| 461 |
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step 4590000 | 44601s | train_loss=0.0173
|
| 462 |
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step 4600000 | 44769s | train_loss=0.0157 | fid=111.4766
|
| 463 |
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step 4610000 | 44852s | train_loss=0.0160
|
| 464 |
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step 4620000 | 44913s | train_loss=0.0162
|
| 465 |
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step 4630000 | 44992s | train_loss=0.0162
|
| 466 |
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step 4640000 | 45074s | train_loss=0.0154
|
| 467 |
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step 4650000 | 45155s | train_loss=0.0159
|
| 468 |
+
step 4660000 | 45235s | train_loss=0.0168
|
| 469 |
+
step 4670000 | 45317s | train_loss=0.0160
|
| 470 |
+
step 4680000 | 45400s | train_loss=0.0163
|
| 471 |
+
step 4690000 | 45467s | train_loss=0.0166
|
| 472 |
+
step 4700000 | 45647s | train_loss=0.0165 | fid=108.4691
|
| 473 |
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step 4710000 | 45728s | train_loss=0.0155
|
| 474 |
+
step 4720000 | 45790s | train_loss=0.0152
|
| 475 |
+
step 4730000 | 45867s | train_loss=0.0166
|
| 476 |
+
step 4740000 | 45947s | train_loss=0.0166
|
| 477 |
+
step 4750000 | 46027s | train_loss=0.0167
|
| 478 |
+
step 4760000 | 46107s | train_loss=0.0152
|
| 479 |
+
step 4770000 | 46188s | train_loss=0.0156
|
| 480 |
+
step 4780000 | 46262s | train_loss=0.0163
|
| 481 |
+
step 4790000 | 46331s | train_loss=0.0152
|
| 482 |
+
step 4800000 | 46474s | train_loss=0.0156 | fid=107.5621
|
| 483 |
+
step 4810000 | 46556s | train_loss=0.0157
|
| 484 |
+
step 4820000 | 46637s | train_loss=0.0153
|
| 485 |
+
step 4830000 | 46716s | train_loss=0.0152
|
| 486 |
+
step 4840000 | 46798s | train_loss=0.0158
|
| 487 |
+
step 4850000 | 46880s | train_loss=0.0155
|
| 488 |
+
step 4860000 | 46961s | train_loss=0.0146
|
| 489 |
+
step 4870000 | 47042s | train_loss=0.0161
|
| 490 |
+
step 4880000 | 47124s | train_loss=0.0156
|
| 491 |
+
step 4890000 | 47200s | train_loss=0.0150
|
| 492 |
+
step 4900000 | 47348s | train_loss=0.0154 | fid=107.3022
|
| 493 |
+
step 4910000 | 47424s | train_loss=0.0150
|
| 494 |
+
step 4920000 | 47505s | train_loss=0.0157
|
| 495 |
+
step 4930000 | 47584s | train_loss=0.0173
|
| 496 |
+
step 4940000 | 47666s | train_loss=0.0155
|
| 497 |
+
step 4950000 | 47747s | train_loss=0.0164
|
| 498 |
+
step 4960000 | 47828s | train_loss=0.0157
|
| 499 |
+
step 4970000 | 47910s | train_loss=0.0156
|
| 500 |
+
step 4980000 | 47991s | train_loss=0.0150
|
| 501 |
+
step 4990000 | 48052s | train_loss=0.0145
|
| 502 |
+
step 5000000 | 48163s | train_loss=0.0155 | fid=105.2974
|
results/cifar10_beta005_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed42/d140/config.json
ADDED
|
@@ -0,0 +1,25 @@
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| 1 |
+
{
|
| 2 |
+
"vae_checkpoint": "vae_checkpoints/cifar10_resnet_beta005_d140/vae.pt",
|
| 3 |
+
"out": "results/cifar10_beta005_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed42/d140",
|
| 4 |
+
"subset_path": "diagnostics/cifar10_diverse_1k_mean_plus_sd/subset_indices.json",
|
| 5 |
+
"n_train": 1000,
|
| 6 |
+
"total_steps": 5000000,
|
| 7 |
+
"eval_interval": 10000,
|
| 8 |
+
"mem_interval": 100000,
|
| 9 |
+
"fid_interval": 100000,
|
| 10 |
+
"fid_n_real": 1000,
|
| 11 |
+
"fid_n_gen": 10000,
|
| 12 |
+
"n_gen_samples": 10000,
|
| 13 |
+
"n_sde_steps": 500,
|
| 14 |
+
"batch_size": 512,
|
| 15 |
+
"hidden": 1024,
|
| 16 |
+
"depth": 5,
|
| 17 |
+
"optimizer": "sgd",
|
| 18 |
+
"lr": 0.001,
|
| 19 |
+
"momentum": 0.8,
|
| 20 |
+
"t_min": 0.01,
|
| 21 |
+
"t_max": 3.0,
|
| 22 |
+
"t_eval": 0.1,
|
| 23 |
+
"seed": 42,
|
| 24 |
+
"device": null
|
| 25 |
+
}
|
results/cifar10_beta005_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed42/d140/metrics.jsonl
ADDED
|
The diff for this file is too large to render.
See raw diff
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|
results/cifar10_beta005_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed42/d140/runner.log
ADDED
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@@ -0,0 +1,502 @@
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| 1 |
+
FID real-side stats cached over 1000 diverse train images
|
| 2 |
+
step 1 | 78s | train_loss=0.9987 | fid=277.3399
|
| 3 |
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|
| 4 |
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|
| 5 |
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|
| 6 |
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|
| 7 |
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|
| 8 |
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|
| 9 |
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|
| 10 |
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|
| 11 |
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|
| 12 |
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|
| 13 |
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| 14 |
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|
| 15 |
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|
| 16 |
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|
| 17 |
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|
| 18 |
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|
| 19 |
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| 20 |
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| 21 |
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| 22 |
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|
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| 24 |
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| 28 |
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| 29 |
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| 31 |
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| 32 |
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|
| 33 |
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| 34 |
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|
| 35 |
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| 36 |
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| 37 |
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| 39 |
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| 42 |
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| 43 |
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| 47 |
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| 475 |
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| 476 |
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| 477 |
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| 478 |
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| 479 |
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| 480 |
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| 484 |
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| 489 |
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|
| 490 |
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| 495 |
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|
| 496 |
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|
| 497 |
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|
| 498 |
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|
| 499 |
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|
| 500 |
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|
| 501 |
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step 4990000 | 47857s | train_loss=0.0154
|
| 502 |
+
step 5000000 | 48006s | train_loss=0.0165 | fid=119.3447
|
results/cifar10_beta005_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed42/d160/config.json
ADDED
|
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| 1 |
+
{
|
| 2 |
+
"vae_checkpoint": "vae_checkpoints/cifar10_resnet_beta005_d160/vae.pt",
|
| 3 |
+
"out": "results/cifar10_beta005_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed42/d160",
|
| 4 |
+
"subset_path": "diagnostics/cifar10_diverse_1k_mean_plus_sd/subset_indices.json",
|
| 5 |
+
"n_train": 1000,
|
| 6 |
+
"total_steps": 5000000,
|
| 7 |
+
"eval_interval": 10000,
|
| 8 |
+
"mem_interval": 100000,
|
| 9 |
+
"fid_interval": 100000,
|
| 10 |
+
"fid_n_real": 1000,
|
| 11 |
+
"fid_n_gen": 10000,
|
| 12 |
+
"n_gen_samples": 10000,
|
| 13 |
+
"n_sde_steps": 500,
|
| 14 |
+
"batch_size": 512,
|
| 15 |
+
"hidden": 1024,
|
| 16 |
+
"depth": 5,
|
| 17 |
+
"optimizer": "sgd",
|
| 18 |
+
"lr": 0.001,
|
| 19 |
+
"momentum": 0.8,
|
| 20 |
+
"t_min": 0.01,
|
| 21 |
+
"t_max": 3.0,
|
| 22 |
+
"t_eval": 0.1,
|
| 23 |
+
"seed": 42,
|
| 24 |
+
"device": null
|
| 25 |
+
}
|
results/cifar10_beta005_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed42/d160/metrics.jsonl
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
results/cifar10_beta005_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed42/d160/runner.log
ADDED
|
@@ -0,0 +1,502 @@
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|
| 1 |
+
FID real-side stats cached over 1000 diverse train images
|
| 2 |
+
step 1 | 76s | train_loss=0.9995 | fid=310.4628
|
| 3 |
+
step 10000 | 174s | train_loss=0.7863
|
| 4 |
+
step 20000 | 274s | train_loss=0.6554
|
| 5 |
+
step 30000 | 374s | train_loss=0.5371
|
| 6 |
+
step 40000 | 474s | train_loss=0.4403
|
| 7 |
+
step 50000 | 573s | train_loss=0.3544
|
| 8 |
+
step 60000 | 674s | train_loss=0.2865
|
| 9 |
+
step 70000 | 774s | train_loss=0.2399
|
| 10 |
+
step 80000 | 874s | train_loss=0.1999
|
| 11 |
+
step 90000 | 975s | train_loss=0.1710
|
| 12 |
+
step 100000 | 1149s | train_loss=0.1572 | fid=198.6737
|
| 13 |
+
step 110000 | 1246s | train_loss=0.1452
|
| 14 |
+
step 120000 | 1346s | train_loss=0.1349
|
| 15 |
+
step 130000 | 1445s | train_loss=0.1247
|
| 16 |
+
step 140000 | 1545s | train_loss=0.1143
|
| 17 |
+
step 150000 | 1644s | train_loss=0.1120
|
| 18 |
+
step 160000 | 1745s | train_loss=0.1030
|
| 19 |
+
step 170000 | 1845s | train_loss=0.1018
|
| 20 |
+
step 180000 | 1945s | train_loss=0.0978
|
| 21 |
+
step 190000 | 2043s | train_loss=0.0980
|
| 22 |
+
step 200000 | 2215s | train_loss=0.0916 | fid=235.4555
|
| 23 |
+
step 210000 | 2311s | train_loss=0.0884
|
| 24 |
+
step 220000 | 2411s | train_loss=0.0876
|
| 25 |
+
step 230000 | 2511s | train_loss=0.0893
|
| 26 |
+
step 240000 | 2611s | train_loss=0.0826
|
| 27 |
+
step 250000 | 2711s | train_loss=0.0839
|
| 28 |
+
step 260000 | 2812s | train_loss=0.0851
|
| 29 |
+
step 270000 | 2912s | train_loss=0.0758
|
| 30 |
+
step 280000 | 3011s | train_loss=0.0777
|
| 31 |
+
step 290000 | 3111s | train_loss=0.0775
|
| 32 |
+
step 300000 | 3286s | train_loss=0.0740 | fid=259.8214
|
| 33 |
+
step 310000 | 3382s | train_loss=0.0740
|
| 34 |
+
step 320000 | 3482s | train_loss=0.0701
|
| 35 |
+
step 330000 | 3582s | train_loss=0.0718
|
| 36 |
+
step 340000 | 3682s | train_loss=0.0658
|
| 37 |
+
step 350000 | 3782s | train_loss=0.0684
|
| 38 |
+
step 360000 | 3882s | train_loss=0.0669
|
| 39 |
+
step 370000 | 3981s | train_loss=0.0662
|
| 40 |
+
step 380000 | 4081s | train_loss=0.0661
|
| 41 |
+
step 390000 | 4180s | train_loss=0.0608
|
| 42 |
+
step 400000 | 4353s | train_loss=0.0641 | fid=302.7278
|
| 43 |
+
step 410000 | 4454s | train_loss=0.0623
|
| 44 |
+
step 420000 | 4550s | train_loss=0.0603
|
| 45 |
+
step 430000 | 4650s | train_loss=0.0665
|
| 46 |
+
step 440000 | 4750s | train_loss=0.0618
|
| 47 |
+
step 450000 | 4851s | train_loss=0.0577
|
| 48 |
+
step 460000 | 4951s | train_loss=0.0565
|
| 49 |
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step 470000 | 5050s | train_loss=0.0581
|
| 50 |
+
step 480000 | 5149s | train_loss=0.0565
|
| 51 |
+
step 490000 | 5249s | train_loss=0.0565
|
| 52 |
+
step 500000 | 5425s | train_loss=0.0537 | fid=298.6909
|
| 53 |
+
step 510000 | 5525s | train_loss=0.0536
|
| 54 |
+
step 520000 | 5621s | train_loss=0.0608
|
| 55 |
+
step 530000 | 5721s | train_loss=0.0542
|
| 56 |
+
step 540000 | 5821s | train_loss=0.0560
|
| 57 |
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step 550000 | 5920s | train_loss=0.0517
|
| 58 |
+
step 560000 | 6019s | train_loss=0.0529
|
| 59 |
+
step 570000 | 6118s | train_loss=0.0529
|
| 60 |
+
step 580000 | 6218s | train_loss=0.0530
|
| 61 |
+
step 590000 | 6318s | train_loss=0.0541
|
| 62 |
+
step 600000 | 6495s | train_loss=0.0524 | fid=298.6196
|
| 63 |
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step 610000 | 6595s | train_loss=0.0528
|
| 64 |
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step 620000 | 6690s | train_loss=0.0546
|
| 65 |
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step 630000 | 6784s | train_loss=0.0494
|
| 66 |
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step 640000 | 6885s | train_loss=0.0504
|
| 67 |
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step 650000 | 6983s | train_loss=0.0502
|
| 68 |
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step 660000 | 7083s | train_loss=0.0484
|
| 69 |
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|
| 70 |
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step 680000 | 7283s | train_loss=0.0481
|
| 71 |
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step 690000 | 7382s | train_loss=0.0470
|
| 72 |
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step 700000 | 7594s | train_loss=0.0475 | fid=284.7142
|
| 73 |
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step 710000 | 7694s | train_loss=0.0458
|
| 74 |
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|
| 75 |
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|
| 76 |
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|
| 77 |
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|
| 78 |
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|
| 79 |
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step 770000 | 8284s | train_loss=0.0441
|
| 80 |
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step 780000 | 8384s | train_loss=0.0448
|
| 81 |
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step 790000 | 8485s | train_loss=0.0436
|
| 82 |
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step 800000 | 8658s | train_loss=0.0439 | fid=274.8453
|
| 83 |
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step 810000 | 8758s | train_loss=0.0451
|
| 84 |
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step 820000 | 8858s | train_loss=0.0442
|
| 85 |
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step 830000 | 8952s | train_loss=0.0456
|
| 86 |
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step 840000 | 9052s | train_loss=0.0439
|
| 87 |
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|
| 88 |
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|
| 89 |
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|
| 90 |
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step 880000 | 9453s | train_loss=0.0428
|
| 91 |
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step 890000 | 9553s | train_loss=0.0445
|
| 92 |
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step 900000 | 9727s | train_loss=0.0430 | fid=259.5052
|
| 93 |
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step 910000 | 9827s | train_loss=0.0421
|
| 94 |
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|
| 95 |
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step 930000 | 10021s | train_loss=0.0399
|
| 96 |
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|
| 97 |
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|
| 98 |
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|
| 99 |
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|
| 100 |
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step 980000 | 10522s | train_loss=0.0421
|
| 101 |
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|
| 102 |
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step 1000000 | 10822s | train_loss=0.0431 | fid=241.3494
|
| 103 |
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|
| 104 |
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|
| 105 |
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|
| 106 |
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|
| 107 |
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|
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|
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| 390 |
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| 392 |
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|
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|
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|
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| 412 |
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| 418 |
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| 420 |
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| 421 |
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| 422 |
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|
| 424 |
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| 426 |
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| 427 |
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|
| 428 |
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| 429 |
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| 430 |
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|
| 432 |
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|
| 433 |
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|
| 434 |
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|
| 435 |
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| 436 |
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|
| 437 |
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|
| 438 |
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|
| 439 |
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|
| 440 |
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| 441 |
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|
| 442 |
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|
| 443 |
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|
| 444 |
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|
| 445 |
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|
| 446 |
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|
| 447 |
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|
| 448 |
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|
| 449 |
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|
| 450 |
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|
| 452 |
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|
| 453 |
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|
| 454 |
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|
| 455 |
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| 456 |
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|
| 457 |
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|
| 458 |
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|
| 459 |
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|
| 460 |
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|
| 461 |
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|
| 462 |
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step 4600000 | 44914s | train_loss=0.0160 | fid=121.6880
|
| 463 |
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step 4610000 | 44995s | train_loss=0.0176
|
| 464 |
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step 4620000 | 45076s | train_loss=0.0183
|
| 465 |
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step 4630000 | 45158s | train_loss=0.0188
|
| 466 |
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step 4640000 | 45239s | train_loss=0.0164
|
| 467 |
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step 4650000 | 45321s | train_loss=0.0173
|
| 468 |
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step 4660000 | 45403s | train_loss=0.0188
|
| 469 |
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step 4670000 | 45470s | train_loss=0.0166
|
| 470 |
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step 4680000 | 45546s | train_loss=0.0176
|
| 471 |
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step 4690000 | 45604s | train_loss=0.0176
|
| 472 |
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step 4700000 | 45799s | train_loss=0.0178 | fid=128.3995
|
| 473 |
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step 4710000 | 45881s | train_loss=0.0170
|
| 474 |
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step 4720000 | 45963s | train_loss=0.0163
|
| 475 |
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step 4730000 | 46043s | train_loss=0.0179
|
| 476 |
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step 4740000 | 46124s | train_loss=0.0174
|
| 477 |
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step 4750000 | 46205s | train_loss=0.0190
|
| 478 |
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step 4760000 | 46275s | train_loss=0.0172
|
| 479 |
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step 4770000 | 46349s | train_loss=0.0173
|
| 480 |
+
step 4780000 | 46429s | train_loss=0.0167
|
| 481 |
+
step 4790000 | 46491s | train_loss=0.0171
|
| 482 |
+
step 4800000 | 46639s | train_loss=0.0194 | fid=116.3115
|
| 483 |
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step 4810000 | 46721s | train_loss=0.0165
|
| 484 |
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step 4820000 | 46803s | train_loss=0.0173
|
| 485 |
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step 4830000 | 46884s | train_loss=0.0182
|
| 486 |
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step 4840000 | 46966s | train_loss=0.0172
|
| 487 |
+
step 4850000 | 47047s | train_loss=0.0170
|
| 488 |
+
step 4860000 | 47129s | train_loss=0.0162
|
| 489 |
+
step 4870000 | 47205s | train_loss=0.0171
|
| 490 |
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step 4880000 | 47287s | train_loss=0.0175
|
| 491 |
+
step 4890000 | 47360s | train_loss=0.0166
|
| 492 |
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step 4900000 | 47510s | train_loss=0.0174 | fid=128.9319
|
| 493 |
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step 4910000 | 47592s | train_loss=0.0164
|
| 494 |
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step 4920000 | 47673s | train_loss=0.0174
|
| 495 |
+
step 4930000 | 47755s | train_loss=0.0228
|
| 496 |
+
step 4940000 | 47836s | train_loss=0.0166
|
| 497 |
+
step 4950000 | 47918s | train_loss=0.0183
|
| 498 |
+
step 4960000 | 47998s | train_loss=0.0174
|
| 499 |
+
step 4970000 | 48060s | train_loss=0.0160
|
| 500 |
+
step 4980000 | 48120s | train_loss=0.0162
|
| 501 |
+
step 4990000 | 48170s | train_loss=0.0164
|
| 502 |
+
step 5000000 | 48244s | train_loss=0.0171 | fid=116.2575
|
results/cifar10_beta005_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed42/d180/config.json
ADDED
|
@@ -0,0 +1,25 @@
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|
| 1 |
+
{
|
| 2 |
+
"vae_checkpoint": "vae_checkpoints/cifar10_resnet_beta005_d180/vae.pt",
|
| 3 |
+
"out": "results/cifar10_beta005_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed42/d180",
|
| 4 |
+
"subset_path": "diagnostics/cifar10_diverse_1k_mean_plus_sd/subset_indices.json",
|
| 5 |
+
"n_train": 1000,
|
| 6 |
+
"total_steps": 5000000,
|
| 7 |
+
"eval_interval": 10000,
|
| 8 |
+
"mem_interval": 100000,
|
| 9 |
+
"fid_interval": 100000,
|
| 10 |
+
"fid_n_real": 1000,
|
| 11 |
+
"fid_n_gen": 10000,
|
| 12 |
+
"n_gen_samples": 10000,
|
| 13 |
+
"n_sde_steps": 500,
|
| 14 |
+
"batch_size": 512,
|
| 15 |
+
"hidden": 1024,
|
| 16 |
+
"depth": 5,
|
| 17 |
+
"optimizer": "sgd",
|
| 18 |
+
"lr": 0.001,
|
| 19 |
+
"momentum": 0.8,
|
| 20 |
+
"t_min": 0.01,
|
| 21 |
+
"t_max": 3.0,
|
| 22 |
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"t_eval": 0.1,
|
| 23 |
+
"seed": 42,
|
| 24 |
+
"device": null
|
| 25 |
+
}
|
results/cifar10_beta005_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed42/d180/fid_retry.json
ADDED
|
@@ -0,0 +1,78 @@
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|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"run_dir": "results/cifar10_beta005_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed42/d180",
|
| 3 |
+
"d_latent": 180,
|
| 4 |
+
"attempts": [
|
| 5 |
+
{
|
| 6 |
+
"attempt": 0,
|
| 7 |
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"seed": 1042,
|
| 8 |
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"step": 5000000,
|
| 9 |
+
"latent_finite": true,
|
| 10 |
+
"pixel_finite": true,
|
| 11 |
+
"fid": 144.25575834607739,
|
| 12 |
+
"error": null
|
| 13 |
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},
|
| 14 |
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{
|
| 15 |
+
"attempt": 1,
|
| 16 |
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"seed": 1043,
|
| 17 |
+
"step": 5000000,
|
| 18 |
+
"latent_finite": true,
|
| 19 |
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"pixel_finite": true,
|
| 20 |
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"fid": 144.2392383180155,
|
| 21 |
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|
| 22 |
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},
|
| 23 |
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{
|
| 24 |
+
"attempt": 2,
|
| 25 |
+
"seed": 1044,
|
| 26 |
+
"step": 5000000,
|
| 27 |
+
"latent_finite": true,
|
| 28 |
+
"pixel_finite": true,
|
| 29 |
+
"fid": 143.73176131114323,
|
| 30 |
+
"error": null
|
| 31 |
+
},
|
| 32 |
+
{
|
| 33 |
+
"attempt": 3,
|
| 34 |
+
"seed": 1045,
|
| 35 |
+
"step": 5000000,
|
| 36 |
+
"latent_finite": false,
|
| 37 |
+
"fid": null,
|
| 38 |
+
"error": "nonfinite_latents"
|
| 39 |
+
},
|
| 40 |
+
{
|
| 41 |
+
"attempt": 4,
|
| 42 |
+
"seed": 1046,
|
| 43 |
+
"step": 5000000,
|
| 44 |
+
"latent_finite": false,
|
| 45 |
+
"fid": null,
|
| 46 |
+
"error": "nonfinite_latents"
|
| 47 |
+
},
|
| 48 |
+
{
|
| 49 |
+
"attempt": 5,
|
| 50 |
+
"seed": 1047,
|
| 51 |
+
"step": 5000000,
|
| 52 |
+
"latent_finite": false,
|
| 53 |
+
"fid": null,
|
| 54 |
+
"error": "nonfinite_latents"
|
| 55 |
+
},
|
| 56 |
+
{
|
| 57 |
+
"attempt": 6,
|
| 58 |
+
"seed": 1048,
|
| 59 |
+
"step": 5000000,
|
| 60 |
+
"latent_finite": true,
|
| 61 |
+
"pixel_finite": true,
|
| 62 |
+
"fid": 143.546935369175,
|
| 63 |
+
"error": null
|
| 64 |
+
},
|
| 65 |
+
{
|
| 66 |
+
"attempt": 7,
|
| 67 |
+
"seed": 1049,
|
| 68 |
+
"step": 5000000,
|
| 69 |
+
"latent_finite": true,
|
| 70 |
+
"pixel_finite": true,
|
| 71 |
+
"fid": 144.9163058421488,
|
| 72 |
+
"error": null
|
| 73 |
+
}
|
| 74 |
+
],
|
| 75 |
+
"best_fid": 143.546935369175,
|
| 76 |
+
"mean_fid": 144.137999837312,
|
| 77 |
+
"n_success": 5
|
| 78 |
+
}
|
results/cifar10_beta005_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed42/d180/fid_retry.log
ADDED
|
@@ -0,0 +1,6 @@
|
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|
| 1 |
+
{"attempt": 0, "seed": 1042, "step": 5000000, "latent_finite": true, "pixel_finite": true, "fid": 144.25575834607739, "error": null}
|
| 2 |
+
{"attempt": 1, "seed": 1043, "step": 5000000, "latent_finite": true, "pixel_finite": true, "fid": 144.2392383180155, "error": null}
|
| 3 |
+
{"attempt": 2, "seed": 1044, "step": 5000000, "latent_finite": true, "pixel_finite": true, "fid": 143.73176131114323, "error": null}
|
| 4 |
+
{"attempt": 6, "seed": 1048, "step": 5000000, "latent_finite": true, "pixel_finite": true, "fid": 143.546935369175, "error": null}
|
| 5 |
+
{"attempt": 7, "seed": 1049, "step": 5000000, "latent_finite": true, "pixel_finite": true, "fid": 144.9163058421488, "error": null}
|
| 6 |
+
SUMMARY {"run_dir": "results/cifar10_beta005_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed42/d180", "d_latent": 180, "attempts": [{"attempt": 0, "seed": 1042, "step": 5000000, "latent_finite": true, "pixel_finite": true, "fid": 144.25575834607739, "error": null}, {"attempt": 1, "seed": 1043, "step": 5000000, "latent_finite": true, "pixel_finite": true, "fid": 144.2392383180155, "error": null}, {"attempt": 2, "seed": 1044, "step": 5000000, "latent_finite": true, "pixel_finite": true, "fid": 143.73176131114323, "error": null}, {"attempt": 3, "seed": 1045, "step": 5000000, "latent_finite": false, "fid": null, "error": "nonfinite_latents"}, {"attempt": 4, "seed": 1046, "step": 5000000, "latent_finite": false, "fid": null, "error": "nonfinite_latents"}, {"attempt": 5, "seed": 1047, "step": 5000000, "latent_finite": false, "fid": null, "error": "nonfinite_latents"}, {"attempt": 6, "seed": 1048, "step": 5000000, "latent_finite": true, "pixel_finite": true, "fid": 143.546935369175, "error": null}, {"attempt": 7, "seed": 1049, "step": 5000000, "latent_finite": true, "pixel_finite": true, "fid": 144.9163058421488, "error": null}], "best_fid": 143.546935369175, "mean_fid": 144.137999837312, "n_success": 5}
|
results/cifar10_beta005_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed42/d180/metrics.jsonl
ADDED
|
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|
|
|
results/cifar10_beta005_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed42/d180/runner.log
ADDED
|
@@ -0,0 +1,293 @@
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|
| 1 |
+
FID real-side stats cached over 1000 diverse train images
|
| 2 |
+
step 1 | 72s | train_loss=0.9991 | fid=287.0402
|
| 3 |
+
step 10000 | 130s | train_loss=0.7726
|
| 4 |
+
step 20000 | 223s | train_loss=0.6673
|
| 5 |
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|
| 6 |
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|
| 7 |
+
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|
| 8 |
+
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|
| 9 |
+
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|
| 10 |
+
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|
| 11 |
+
step 90000 | 871s | train_loss=0.1939
|
| 12 |
+
step 100000 | 1035s | train_loss=0.1828 | fid=206.6450
|
| 13 |
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|
| 14 |
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step 120000 | 1205s | train_loss=0.1476
|
| 15 |
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|
| 16 |
+
step 140000 | 1390s | train_loss=0.1477
|
| 17 |
+
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|
| 18 |
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step 160000 | 1575s | train_loss=0.1170
|
| 19 |
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|
| 20 |
+
step 180000 | 1761s | train_loss=0.1103
|
| 21 |
+
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|
| 22 |
+
step 200000 | 2017s | train_loss=0.1073 | fid=277.6766
|
| 23 |
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|
| 24 |
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|
| 25 |
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|
| 26 |
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|
| 27 |
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|
| 28 |
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|
| 29 |
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|
| 30 |
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|
| 31 |
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|
| 32 |
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|
| 33 |
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|
| 34 |
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|
| 35 |
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|
| 36 |
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|
| 37 |
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|
| 38 |
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|
| 39 |
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|
| 40 |
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|
| 41 |
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|
| 42 |
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|
| 43 |
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|
| 44 |
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|
| 45 |
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|
| 46 |
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|
| 47 |
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|
| 48 |
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|
| 49 |
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| 50 |
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|
| 51 |
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| 52 |
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|
| 53 |
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| 54 |
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| 55 |
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| 56 |
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| 57 |
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| 58 |
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| 59 |
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| 60 |
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|
| 61 |
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| 62 |
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|
| 63 |
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|
| 64 |
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|
| 65 |
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|
| 66 |
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|
| 67 |
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|
| 68 |
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|
| 69 |
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| 70 |
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| 71 |
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|
| 72 |
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|
| 73 |
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| 74 |
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| 75 |
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| 76 |
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| 77 |
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|
| 79 |
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| 80 |
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| 81 |
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|
| 82 |
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|
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|
| 84 |
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|
| 85 |
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|
| 86 |
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|
| 87 |
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|
| 88 |
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|
| 89 |
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|
| 90 |
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|
| 91 |
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| 92 |
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|
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| 94 |
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| 95 |
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| 96 |
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| 97 |
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| 98 |
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| 99 |
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| 100 |
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| 101 |
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| 102 |
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step 1960000 | 19029s | train_loss=0.0295
|
| 199 |
+
step 1970000 | 19117s | train_loss=0.0267
|
| 200 |
+
step 1980000 | 19195s | train_loss=0.0318
|
| 201 |
+
step 1990000 | 19286s | train_loss=0.0290
|
| 202 |
+
step 2000000 | 19436s | train_loss=0.0352 | fid=207.8816
|
| 203 |
+
step 2010000 | 19528s | train_loss=0.0276
|
| 204 |
+
step 2020000 | 19621s | train_loss=0.0269
|
| 205 |
+
step 2030000 | 19713s | train_loss=0.0263
|
| 206 |
+
step 2040000 | 19806s | train_loss=0.0284
|
| 207 |
+
step 2050000 | 19899s | train_loss=0.0281
|
| 208 |
+
step 2060000 | 19991s | train_loss=0.0292
|
| 209 |
+
step 2070000 | 20076s | train_loss=0.0285
|
| 210 |
+
step 2080000 | 20159s | train_loss=0.0252
|
| 211 |
+
step 2090000 | 20241s | train_loss=0.0305
|
| 212 |
+
step 2100000 | 20397s | train_loss=0.0255 | fid=192.1762
|
| 213 |
+
step 2110000 | 20482s | train_loss=0.0338
|
| 214 |
+
step 2120000 | 20575s | train_loss=0.0274
|
| 215 |
+
step 2130000 | 20667s | train_loss=0.0273
|
| 216 |
+
step 2140000 | 20760s | train_loss=0.0260
|
| 217 |
+
step 2150000 | 20853s | train_loss=0.0314
|
| 218 |
+
step 2160000 | 20946s | train_loss=0.0267
|
| 219 |
+
step 2170000 | 21038s | train_loss=0.0263
|
| 220 |
+
step 2180000 | 21131s | train_loss=0.0266
|
| 221 |
+
step 2190000 | 21212s | train_loss=0.0269
|
| 222 |
+
step 2200000 | 21349s | train_loss=0.0270 | fid=181.8616
|
| 223 |
+
step 2210000 | 21439s | train_loss=0.0290
|
| 224 |
+
step 2220000 | 21524s | train_loss=0.0279
|
| 225 |
+
step 2230000 | 21613s | train_loss=0.0290
|
| 226 |
+
step 2240000 | 21706s | train_loss=0.0259
|
| 227 |
+
step 2250000 | 21798s | train_loss=0.0264
|
| 228 |
+
step 2260000 | 21891s | train_loss=0.0274
|
| 229 |
+
step 2270000 | 21984s | train_loss=0.0293
|
| 230 |
+
step 2280000 | 22077s | train_loss=0.0278
|
| 231 |
+
step 2290000 | 22169s | train_loss=0.0256
|
| 232 |
+
step 2300000 | 22316s | train_loss=0.0261 | fid=193.7930
|
| 233 |
+
step 2310000 | 22401s | train_loss=0.0267
|
| 234 |
+
step 2320000 | 22489s | train_loss=0.0256
|
| 235 |
+
step 2330000 | 22580s | train_loss=0.0251
|
| 236 |
+
step 2340000 | 22667s | train_loss=0.0241
|
| 237 |
+
step 2350000 | 22760s | train_loss=0.0274
|
| 238 |
+
step 2360000 | 22853s | train_loss=0.0252
|
| 239 |
+
step 2370000 | 22945s | train_loss=0.0272
|
| 240 |
+
step 2380000 | 23038s | train_loss=0.0260
|
| 241 |
+
step 2390000 | 23131s | train_loss=0.0262
|
| 242 |
+
step 2400000 | 23295s | train_loss=0.0251 | fid=198.3910
|
| 243 |
+
step 2410000 | 23385s | train_loss=0.0262
|
| 244 |
+
step 2420000 | 23468s | train_loss=0.0254
|
| 245 |
+
step 2430000 | 23549s | train_loss=0.0277
|
| 246 |
+
step 2440000 | 23641s | train_loss=0.0254
|
| 247 |
+
step 2450000 | 23731s | train_loss=0.0254
|
| 248 |
+
step 2460000 | 23824s | train_loss=0.0268
|
| 249 |
+
step 2470000 | 23917s | train_loss=0.0265
|
| 250 |
+
step 2480000 | 24010s | train_loss=0.0263
|
| 251 |
+
step 2490000 | 24102s | train_loss=0.0263
|
| 252 |
+
step 2500000 | 24265s | train_loss=0.0249 | fid=190.0751
|
| 253 |
+
step 2510000 | 24358s | train_loss=0.0237
|
| 254 |
+
step 2520000 | 24438s | train_loss=0.0255
|
| 255 |
+
step 2530000 | 24525s | train_loss=0.0304
|
| 256 |
+
step 2540000 | 24603s | train_loss=0.0243
|
| 257 |
+
step 2550000 | 24693s | train_loss=0.0262
|
| 258 |
+
step 2560000 | 24786s | train_loss=0.0229
|
| 259 |
+
step 2570000 | 24879s | train_loss=0.0280
|
| 260 |
+
step 2580000 | 24972s | train_loss=0.0303
|
| 261 |
+
step 2590000 | 25065s | train_loss=0.0284
|
| 262 |
+
step 2600000 | 25228s | train_loss=0.0248 | fid=188.3379
|
| 263 |
+
step 2610000 | 25320s | train_loss=0.0260
|
| 264 |
+
step 2620000 | 25413s | train_loss=0.0273
|
| 265 |
+
step 2630000 | 25492s | train_loss=0.0251
|
| 266 |
+
step 2640000 | 25584s | train_loss=0.0251
|
| 267 |
+
step 2650000 | 25658s | train_loss=0.0246
|
| 268 |
+
step 2660000 | 25748s | train_loss=0.0244
|
| 269 |
+
step 2670000 | 25841s | train_loss=0.0248
|
| 270 |
+
step 2680000 | 25934s | train_loss=0.0268
|
| 271 |
+
step 2690000 | 26027s | train_loss=0.0287
|
| 272 |
+
Traceback (most recent call last):
|
| 273 |
+
File "/home/trevor/latent_space_diffusion_analysis/code/v3/run_cifar_diverse_diffusion.py", line 297, in <module>
|
| 274 |
+
main()
|
| 275 |
+
File "/home/trevor/latent_space_diffusion_analysis/code/v3/run_cifar_diverse_diffusion.py", line 269, in main
|
| 276 |
+
training.train_loop(
|
| 277 |
+
File "/home/trevor/latent_space_diffusion_analysis/code/v3/lib/training.py", line 132, in train_loop
|
| 278 |
+
eval_results = eval_suite.run(step, model)
|
| 279 |
+
File "/home/trevor/latent_space_diffusion_analysis/code/v3/lib/training.py", line 56, in run
|
| 280 |
+
result = spec.fn(model, step)
|
| 281 |
+
File "/home/trevor/latent_space_diffusion_analysis/code/v3/run_cifar_diverse_diffusion.py", line 174, in fid_eval
|
| 282 |
+
score = fid_mod.fid_against_real(
|
| 283 |
+
File "/home/trevor/latent_space_diffusion_analysis/code/v3/lib/fid.py", line 163, in fid_against_real
|
| 284 |
+
return frechet_distance(real.mean, real.cov, mu_g, cov_g)
|
| 285 |
+
File "/home/trevor/latent_space_diffusion_analysis/code/v3/lib/fid.py", line 91, in frechet_distance
|
| 286 |
+
covmean, _ = linalg.sqrtm(cov_r @ cov_g, disp=False)
|
| 287 |
+
File "/usr/lib/python3/dist-packages/scipy/linalg/_matfuncs_sqrtm.py", line 161, in sqrtm
|
| 288 |
+
A = _asarray_validated(A, check_finite=True, as_inexact=True)
|
| 289 |
+
File "/usr/lib/python3/dist-packages/scipy/_lib/_util.py", line 287, in _asarray_validated
|
| 290 |
+
a = toarray(a)
|
| 291 |
+
File "/usr/lib/python3/dist-packages/numpy/lib/function_base.py", line 488, in asarray_chkfinite
|
| 292 |
+
raise ValueError(
|
| 293 |
+
ValueError: array must not contain infs or NaNs
|
results/cifar10_beta005_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed42/d20/config.json
ADDED
|
@@ -0,0 +1,25 @@
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|
| 1 |
+
{
|
| 2 |
+
"vae_checkpoint": "vae_checkpoints/cifar10_resnet_beta005_d20/vae.pt",
|
| 3 |
+
"out": "results/cifar10_beta005_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed42/d20",
|
| 4 |
+
"subset_path": "diagnostics/cifar10_diverse_1k_mean_plus_sd/subset_indices.json",
|
| 5 |
+
"n_train": 1000,
|
| 6 |
+
"total_steps": 5000000,
|
| 7 |
+
"eval_interval": 10000,
|
| 8 |
+
"mem_interval": 100000,
|
| 9 |
+
"fid_interval": 100000,
|
| 10 |
+
"fid_n_real": 1000,
|
| 11 |
+
"fid_n_gen": 10000,
|
| 12 |
+
"n_gen_samples": 10000,
|
| 13 |
+
"n_sde_steps": 500,
|
| 14 |
+
"batch_size": 512,
|
| 15 |
+
"hidden": 1024,
|
| 16 |
+
"depth": 5,
|
| 17 |
+
"optimizer": "sgd",
|
| 18 |
+
"lr": 0.001,
|
| 19 |
+
"momentum": 0.8,
|
| 20 |
+
"t_min": 0.01,
|
| 21 |
+
"t_max": 3.0,
|
| 22 |
+
"t_eval": 0.1,
|
| 23 |
+
"seed": 42,
|
| 24 |
+
"device": null
|
| 25 |
+
}
|
results/cifar10_beta005_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed42/d20/metrics.jsonl
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
results/cifar10_beta005_diverse1k_bigmlp_sgd_lr001_m08_10k_5m/seed42/d20/runner.log
ADDED
|
@@ -0,0 +1,502 @@
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| 1 |
+
FID real-side stats cached over 1000 diverse train images
|
| 2 |
+
step 1 | 73s | train_loss=0.9905 | fid=182.3710
|
| 3 |
+
step 10000 | 166s | train_loss=0.8974
|
| 4 |
+
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|
| 5 |
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|
| 6 |
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|
| 7 |
+
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|
| 8 |
+
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|
| 9 |
+
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|
| 10 |
+
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|
| 11 |
+
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|
| 12 |
+
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|
| 13 |
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|
| 14 |
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|
| 15 |
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|
| 16 |
+
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|
| 17 |
+
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|
| 18 |
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|
| 19 |
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|
| 20 |
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|
| 21 |
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|
| 22 |
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|
| 23 |
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|
| 24 |
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|
| 25 |
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|
| 26 |
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|
| 27 |
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|
| 28 |
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|
| 29 |
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|
| 30 |
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|
| 31 |
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|
| 32 |
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|
| 33 |
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|
| 34 |
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|
| 35 |
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|
| 36 |
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|
| 37 |
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|
| 38 |
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|
| 39 |
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|
| 40 |
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|
| 41 |
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|
| 42 |
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|
| 43 |
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|
| 44 |
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| 45 |
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| 46 |
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| 47 |
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| 48 |
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| 49 |
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| 50 |
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| 64 |
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