| INFO 2026-01-06 01:04:54 ot_train.py:282 Logs will be saved locally. | |
| INFO 2026-01-06 01:04:54 ot_train.py:294 Creating dataset | |
| INFO 2026-01-06 01:04:54 ot_train.py:313 Creating policy | |
| Loading HuggingFaceTB/SmolVLM2-500M-Video-Instruct weights ... | |
| `torch_dtype` is deprecated! Use `dtype` instead! | |
| Reducing the number of VLM layers to 16 ... | |
| INFO 2026-01-06 01:05:03 ot_train.py:366 Creating optimizer and scheduler | |
| INFO 2026-01-06 01:05:03 hedulers.py:105 Auto-scaling LR scheduler: num_training_steps (20000) < num_decay_steps (30000). Scaling warmup: 1000 → 666, decay: 30000 → 20000 (scale factor: 0.667) | |
| INFO 2026-01-06 01:05:03 ot_train.py:401 Output dir: outputs/train/roco_smolvla | |
| INFO 2026-01-06 01:05:03 ot_train.py:408 cfg.steps=20000 (20K) | |
| INFO 2026-01-06 01:05:03 ot_train.py:409 dataset.num_frames=112690 (113K) | |
| INFO 2026-01-06 01:05:03 ot_train.py:410 dataset.num_episodes=191 | |
| INFO 2026-01-06 01:05:03 ot_train.py:413 Effective batch size: 64 x 1 = 64 | |
| INFO 2026-01-06 01:05:03 ot_train.py:414 num_learnable_params=99880992 (100M) | |
| INFO 2026-01-06 01:05:03 ot_train.py:415 num_total_params=450046176 (450M) | |
| INFO 2026-01-06 01:05:03 ot_train.py:471 Start offline training on a fixed dataset, with effective batch size: 64 | |
| INFO 2026-01-06 01:07:03 ot_train.py:501 step:100 smpl:6K ep:11 epch:0.06 loss:1.149 grdn:4.229 lr:7.7e-06 updt_s:1.191 data_s:0.012 | |
| INFO 2026-01-06 01:09:03 ot_train.py:501 step:200 smpl:13K ep:22 epch:0.11 loss:0.339 grdn:0.796 lr:2.3e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 01:11:02 ot_train.py:501 step:300 smpl:19K ep:33 epch:0.17 loss:0.180 grdn:0.723 lr:3.8e-05 updt_s:1.188 data_s:0.005 | |
| INFO 2026-01-06 01:13:01 ot_train.py:501 step:400 smpl:26K ep:43 epch:0.23 loss:0.133 grdn:0.739 lr:5.3e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 01:15:01 ot_train.py:501 step:500 smpl:32K ep:54 epch:0.28 loss:0.112 grdn:0.891 lr:6.8e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 01:17:00 ot_train.py:501 step:600 smpl:38K ep:65 epch:0.34 loss:0.099 grdn:0.798 lr:8.3e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 01:18:59 ot_train.py:501 step:700 smpl:45K ep:76 epch:0.40 loss:0.091 grdn:0.740 lr:9.7e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 01:20:59 ot_train.py:501 step:800 smpl:51K ep:87 epch:0.45 loss:0.082 grdn:0.649 lr:1.0e-04 updt_s:1.188 data_s:0.005 | |
| INFO 2026-01-06 01:22:58 ot_train.py:501 step:900 smpl:58K ep:98 epch:0.51 loss:0.073 grdn:0.594 lr:1.0e-04 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 01:24:57 ot_train.py:501 step:1K smpl:64K ep:108 epch:0.57 loss:0.067 grdn:0.565 lr:9.9e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 01:26:57 ot_train.py:501 step:1K smpl:70K ep:119 epch:0.62 loss:0.059 grdn:0.496 lr:9.9e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 01:28:56 ot_train.py:501 step:1K smpl:77K ep:130 epch:0.68 loss:0.055 grdn:0.499 lr:9.9e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 01:30:55 ot_train.py:501 step:1K smpl:83K ep:141 epch:0.74 loss:0.051 grdn:0.469 lr:9.9e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 01:32:55 ot_train.py:501 step:1K smpl:90K ep:152 epch:0.80 loss:0.047 grdn:0.449 lr:9.9e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 01:34:54 ot_train.py:501 step:2K smpl:96K ep:163 epch:0.85 loss:0.044 grdn:0.435 lr:9.9e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 01:36:53 ot_train.py:501 step:2K smpl:102K ep:174 epch:0.91 loss:0.044 grdn:0.447 lr:9.9e-05 updt_s:1.188 data_s:0.005 | |
| INFO 2026-01-06 01:38:53 ot_train.py:501 step:2K smpl:109K ep:184 epch:0.97 loss:0.040 grdn:0.412 lr:9.8e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 01:40:53 ot_train.py:501 step:2K smpl:115K ep:195 epch:1.02 loss:0.039 grdn:0.418 lr:9.8e-05 updt_s:1.186 data_s:0.011 | |
| INFO 2026-01-06 01:42:52 ot_train.py:501 step:2K smpl:122K ep:206 epch:1.08 loss:0.038 grdn:0.429 lr:9.8e-05 updt_s:1.188 data_s:0.005 | |
| INFO 2026-01-06 01:44:51 ot_train.py:501 step:2K smpl:128K ep:217 epch:1.14 loss:0.036 grdn:0.384 lr:9.8e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 01:46:51 ot_train.py:501 step:2K smpl:134K ep:228 epch:1.19 loss:0.035 grdn:0.413 lr:9.7e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 01:48:50 ot_train.py:501 step:2K smpl:141K ep:239 epch:1.25 loss:0.034 grdn:0.405 lr:9.7e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 01:50:49 ot_train.py:501 step:2K smpl:147K ep:249 epch:1.31 loss:0.033 grdn:0.400 lr:9.7e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 01:52:49 ot_train.py:501 step:2K smpl:154K ep:260 epch:1.36 loss:0.031 grdn:0.389 lr:9.7e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 01:54:48 ot_train.py:501 step:2K smpl:160K ep:271 epch:1.42 loss:0.031 grdn:0.378 lr:9.6e-05 updt_s:1.188 data_s:0.005 | |
| INFO 2026-01-06 01:56:47 ot_train.py:501 step:3K smpl:166K ep:282 epch:1.48 loss:0.029 grdn:0.361 lr:9.6e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 01:58:47 ot_train.py:501 step:3K smpl:173K ep:293 epch:1.53 loss:0.030 grdn:0.380 lr:9.6e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 02:00:46 ot_train.py:501 step:3K smpl:179K ep:304 epch:1.59 loss:0.028 grdn:0.362 lr:9.6e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 02:02:45 ot_train.py:501 step:3K smpl:186K ep:315 epch:1.65 loss:0.028 grdn:0.379 lr:9.5e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 02:04:45 ot_train.py:501 step:3K smpl:192K ep:325 epch:1.70 loss:0.029 grdn:0.397 lr:9.5e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 02:06:44 ot_train.py:501 step:3K smpl:198K ep:336 epch:1.76 loss:0.026 grdn:0.364 lr:9.5e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 02:08:43 ot_train.py:501 step:3K smpl:205K ep:347 epch:1.82 loss:0.025 grdn:0.341 lr:9.4e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 02:10:43 ot_train.py:501 step:3K smpl:211K ep:358 epch:1.87 loss:0.027 grdn:0.371 lr:9.4e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 02:12:42 ot_train.py:501 step:3K smpl:218K ep:369 epch:1.93 loss:0.025 grdn:0.335 lr:9.3e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 02:14:41 ot_train.py:501 step:4K smpl:224K ep:380 epch:1.99 loss:0.026 grdn:0.367 lr:9.3e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 02:16:41 ot_train.py:501 step:4K smpl:230K ep:391 epch:2.04 loss:0.025 grdn:0.346 lr:9.3e-05 updt_s:1.185 data_s:0.012 | |
| INFO 2026-01-06 02:18:40 ot_train.py:501 step:4K smpl:237K ep:401 epch:2.10 loss:0.024 grdn:0.347 lr:9.2e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 02:20:40 ot_train.py:501 step:4K smpl:243K ep:412 epch:2.16 loss:0.022 grdn:0.307 lr:9.2e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 02:22:39 ot_train.py:501 step:4K smpl:250K ep:423 epch:2.21 loss:0.023 grdn:0.362 lr:9.1e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 02:24:38 ot_train.py:501 step:4K smpl:256K ep:434 epch:2.27 loss:0.022 grdn:0.361 lr:9.1e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 02:26:38 ot_train.py:501 step:4K smpl:262K ep:445 epch:2.33 loss:0.022 grdn:0.343 lr:9.0e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 02:28:37 ot_train.py:501 step:4K smpl:269K ep:456 epch:2.39 loss:0.022 grdn:0.337 lr:9.0e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 02:30:36 ot_train.py:501 step:4K smpl:275K ep:466 epch:2.44 loss:0.022 grdn:0.344 lr:9.0e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 02:32:35 ot_train.py:501 step:4K smpl:282K ep:477 epch:2.50 loss:0.020 grdn:0.348 lr:8.9e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 02:34:35 ot_train.py:501 step:4K smpl:288K ep:488 epch:2.56 loss:0.022 grdn:0.352 lr:8.9e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 02:36:34 ot_train.py:501 step:5K smpl:294K ep:499 epch:2.61 loss:0.021 grdn:0.337 lr:8.8e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 02:38:33 ot_train.py:501 step:5K smpl:301K ep:510 epch:2.67 loss:0.021 grdn:0.311 lr:8.8e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 02:40:33 ot_train.py:501 step:5K smpl:307K ep:521 epch:2.73 loss:0.019 grdn:0.336 lr:8.7e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 02:42:32 ot_train.py:501 step:5K smpl:314K ep:532 epch:2.78 loss:0.020 grdn:0.331 lr:8.7e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 02:44:31 ot_train.py:501 step:5K smpl:320K ep:542 epch:2.84 loss:0.019 grdn:0.334 lr:8.6e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 02:44:31 ot_train.py:521 Checkpoint policy after step 5000 | |
| INFO 2026-01-06 02:46:31 ot_train.py:501 step:5K smpl:326K ep:553 epch:2.90 loss:0.019 grdn:0.328 lr:8.5e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 02:48:31 ot_train.py:501 step:5K smpl:333K ep:564 epch:2.95 loss:0.019 grdn:0.332 lr:8.5e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 02:50:30 ot_train.py:501 step:5K smpl:339K ep:575 epch:3.01 loss:0.019 grdn:0.332 lr:8.4e-05 updt_s:1.185 data_s:0.012 | |
| INFO 2026-01-06 02:52:30 ot_train.py:501 step:5K smpl:346K ep:586 epch:3.07 loss:0.019 grdn:0.332 lr:8.4e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 02:54:29 ot_train.py:501 step:6K smpl:352K ep:597 epch:3.12 loss:0.019 grdn:0.328 lr:8.3e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 02:56:28 ot_train.py:501 step:6K smpl:358K ep:607 epch:3.18 loss:0.018 grdn:0.333 lr:8.3e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 02:58:28 ot_train.py:501 step:6K smpl:365K ep:618 epch:3.24 loss:0.017 grdn:0.312 lr:8.2e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 03:00:27 ot_train.py:501 step:6K smpl:371K ep:629 epch:3.29 loss:0.016 grdn:0.313 lr:8.1e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 03:02:26 ot_train.py:501 step:6K smpl:378K ep:640 epch:3.35 loss:0.016 grdn:0.301 lr:8.1e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 03:04:26 ot_train.py:501 step:6K smpl:384K ep:651 epch:3.41 loss:0.017 grdn:0.313 lr:8.0e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 03:06:25 ot_train.py:501 step:6K smpl:390K ep:662 epch:3.46 loss:0.016 grdn:0.317 lr:8.0e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 03:08:24 ot_train.py:501 step:6K smpl:397K ep:673 epch:3.52 loss:0.016 grdn:0.321 lr:7.9e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 03:10:24 ot_train.py:501 step:6K smpl:403K ep:683 epch:3.58 loss:0.015 grdn:0.293 lr:7.8e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 03:12:23 ot_train.py:501 step:6K smpl:410K ep:694 epch:3.63 loss:0.016 grdn:0.312 lr:7.8e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 03:14:22 ot_train.py:501 step:6K smpl:416K ep:705 epch:3.69 loss:0.015 grdn:0.318 lr:7.7e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 03:16:22 ot_train.py:501 step:7K smpl:422K ep:716 epch:3.75 loss:0.016 grdn:0.304 lr:7.6e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 03:18:21 ot_train.py:501 step:7K smpl:429K ep:727 epch:3.81 loss:0.015 grdn:0.326 lr:7.6e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 03:20:20 ot_train.py:501 step:7K smpl:435K ep:738 epch:3.86 loss:0.014 grdn:0.322 lr:7.5e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 03:22:20 ot_train.py:501 step:7K smpl:442K ep:748 epch:3.92 loss:0.014 grdn:0.300 lr:7.4e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 03:24:19 ot_train.py:501 step:7K smpl:448K ep:759 epch:3.98 loss:0.014 grdn:0.303 lr:7.4e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 03:26:19 ot_train.py:501 step:7K smpl:454K ep:770 epch:4.03 loss:0.016 grdn:0.331 lr:7.3e-05 updt_s:1.185 data_s:0.012 | |
| INFO 2026-01-06 03:28:18 ot_train.py:501 step:7K smpl:461K ep:781 epch:4.09 loss:0.015 grdn:0.322 lr:7.2e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 03:30:17 ot_train.py:501 step:7K smpl:467K ep:792 epch:4.15 loss:0.014 grdn:0.286 lr:7.2e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 03:32:17 ot_train.py:501 step:7K smpl:474K ep:803 epch:4.20 loss:0.013 grdn:0.286 lr:7.1e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 03:34:16 ot_train.py:501 step:8K smpl:480K ep:814 epch:4.26 loss:0.015 grdn:0.357 lr:7.0e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 03:36:15 ot_train.py:501 step:8K smpl:486K ep:824 epch:4.32 loss:0.013 grdn:0.302 lr:7.0e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 03:38:15 ot_train.py:501 step:8K smpl:493K ep:835 epch:4.37 loss:0.013 grdn:0.305 lr:6.9e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 03:40:14 ot_train.py:501 step:8K smpl:499K ep:846 epch:4.43 loss:0.013 grdn:0.302 lr:6.8e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 03:42:13 ot_train.py:501 step:8K smpl:506K ep:857 epch:4.49 loss:0.012 grdn:0.278 lr:6.7e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 03:44:13 ot_train.py:501 step:8K smpl:512K ep:868 epch:4.54 loss:0.013 grdn:0.301 lr:6.7e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 03:46:12 ot_train.py:501 step:8K smpl:518K ep:879 epch:4.60 loss:0.013 grdn:0.294 lr:6.6e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 03:48:11 ot_train.py:501 step:8K smpl:525K ep:889 epch:4.66 loss:0.013 grdn:0.296 lr:6.5e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 03:50:11 ot_train.py:501 step:8K smpl:531K ep:900 epch:4.71 loss:0.012 grdn:0.291 lr:6.4e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 03:52:10 ot_train.py:501 step:8K smpl:538K ep:911 epch:4.77 loss:0.012 grdn:0.293 lr:6.4e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 03:54:09 ot_train.py:501 step:8K smpl:544K ep:922 epch:4.83 loss:0.011 grdn:0.265 lr:6.3e-05 updt_s:1.188 data_s:0.005 | |
| INFO 2026-01-06 03:56:09 ot_train.py:501 step:9K smpl:550K ep:933 epch:4.88 loss:0.012 grdn:0.290 lr:6.2e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 03:58:08 ot_train.py:501 step:9K smpl:557K ep:944 epch:4.94 loss:0.012 grdn:0.279 lr:6.2e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 04:00:07 ot_train.py:501 step:9K smpl:563K ep:955 epch:5.00 loss:0.011 grdn:0.306 lr:6.1e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 04:02:07 ot_train.py:501 step:9K smpl:570K ep:965 epch:5.05 loss:0.011 grdn:0.290 lr:6.0e-05 updt_s:1.185 data_s:0.012 | |
| INFO 2026-01-06 04:04:06 ot_train.py:501 step:9K smpl:576K ep:976 epch:5.11 loss:0.011 grdn:0.276 lr:5.9e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 04:06:06 ot_train.py:501 step:9K smpl:582K ep:987 epch:5.17 loss:0.012 grdn:0.299 lr:5.8e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 04:08:05 ot_train.py:501 step:9K smpl:589K ep:998 epch:5.22 loss:0.010 grdn:0.254 lr:5.8e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 04:10:04 ot_train.py:501 step:9K smpl:595K ep:1K epch:5.28 loss:0.011 grdn:0.312 lr:5.7e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 04:12:04 ot_train.py:501 step:9K smpl:602K ep:1K epch:5.34 loss:0.010 grdn:0.274 lr:5.6e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 04:14:03 ot_train.py:501 step:10K smpl:608K ep:1K epch:5.40 loss:0.010 grdn:0.310 lr:5.5e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 04:16:02 ot_train.py:501 step:10K smpl:614K ep:1K epch:5.45 loss:0.011 grdn:0.293 lr:5.5e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 04:18:02 ot_train.py:501 step:10K smpl:621K ep:1K epch:5.51 loss:0.010 grdn:0.286 lr:5.4e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 04:20:01 ot_train.py:501 step:10K smpl:627K ep:1K epch:5.57 loss:0.010 grdn:0.256 lr:5.3e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 04:22:00 ot_train.py:501 step:10K smpl:634K ep:1K epch:5.62 loss:0.010 grdn:0.270 lr:5.2e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 04:24:00 ot_train.py:501 step:10K smpl:640K ep:1K epch:5.68 loss:0.010 grdn:0.279 lr:5.2e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 04:24:00 ot_train.py:521 Checkpoint policy after step 10000 | |
| INFO 2026-01-06 04:26:00 ot_train.py:501 step:10K smpl:646K ep:1K epch:5.74 loss:0.010 grdn:0.256 lr:5.1e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 04:27:59 ot_train.py:501 step:10K smpl:653K ep:1K epch:5.79 loss:0.010 grdn:0.262 lr:5.0e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 04:29:58 ot_train.py:501 step:10K smpl:659K ep:1K epch:5.85 loss:0.010 grdn:0.248 lr:4.9e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 04:31:58 ot_train.py:501 step:10K smpl:666K ep:1K epch:5.91 loss:0.009 grdn:0.279 lr:4.9e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 04:33:57 ot_train.py:501 step:10K smpl:672K ep:1K epch:5.96 loss:0.010 grdn:0.258 lr:4.8e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 04:35:57 ot_train.py:501 step:11K smpl:678K ep:1K epch:6.02 loss:0.010 grdn:0.298 lr:4.7e-05 updt_s:1.185 data_s:0.011 | |
| INFO 2026-01-06 04:37:56 ot_train.py:501 step:11K smpl:685K ep:1K epch:6.08 loss:0.009 grdn:0.241 lr:4.6e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 04:39:55 ot_train.py:501 step:11K smpl:691K ep:1K epch:6.13 loss:0.009 grdn:0.307 lr:4.6e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 04:41:55 ot_train.py:501 step:11K smpl:698K ep:1K epch:6.19 loss:0.009 grdn:0.267 lr:4.5e-05 updt_s:1.188 data_s:0.005 | |
| INFO 2026-01-06 04:43:54 ot_train.py:501 step:11K smpl:704K ep:1K epch:6.25 loss:0.009 grdn:0.246 lr:4.4e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 04:45:53 ot_train.py:501 step:11K smpl:710K ep:1K epch:6.30 loss:0.009 grdn:0.275 lr:4.3e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 04:47:53 ot_train.py:501 step:11K smpl:717K ep:1K epch:6.36 loss:0.009 grdn:0.240 lr:4.2e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 04:49:52 ot_train.py:501 step:11K smpl:723K ep:1K epch:6.42 loss:0.009 grdn:0.315 lr:4.2e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 04:51:51 ot_train.py:501 step:11K smpl:730K ep:1K epch:6.47 loss:0.009 grdn:0.230 lr:4.1e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 04:53:51 ot_train.py:501 step:12K smpl:736K ep:1K epch:6.53 loss:0.009 grdn:0.254 lr:4.0e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 04:55:50 ot_train.py:501 step:12K smpl:742K ep:1K epch:6.59 loss:0.008 grdn:0.286 lr:3.9e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 04:57:49 ot_train.py:501 step:12K smpl:749K ep:1K epch:6.64 loss:0.008 grdn:0.247 lr:3.9e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 04:59:49 ot_train.py:501 step:12K smpl:755K ep:1K epch:6.70 loss:0.008 grdn:0.248 lr:3.8e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 05:01:48 ot_train.py:501 step:12K smpl:762K ep:1K epch:6.76 loss:0.009 grdn:0.257 lr:3.7e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 05:03:47 ot_train.py:501 step:12K smpl:768K ep:1K epch:6.82 loss:0.008 grdn:0.274 lr:3.7e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 05:05:47 ot_train.py:501 step:12K smpl:774K ep:1K epch:6.87 loss:0.008 grdn:0.243 lr:3.6e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 05:07:46 ot_train.py:501 step:12K smpl:781K ep:1K epch:6.93 loss:0.008 grdn:0.241 lr:3.5e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 05:09:45 ot_train.py:501 step:12K smpl:787K ep:1K epch:6.99 loss:0.008 grdn:0.242 lr:3.4e-05 updt_s:1.188 data_s:0.005 | |
| INFO 2026-01-06 05:11:45 ot_train.py:501 step:12K smpl:794K ep:1K epch:7.04 loss:0.008 grdn:0.256 lr:3.4e-05 updt_s:1.185 data_s:0.012 | |
| INFO 2026-01-06 05:13:44 ot_train.py:501 step:12K smpl:800K ep:1K epch:7.10 loss:0.008 grdn:0.233 lr:3.3e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 05:15:44 ot_train.py:501 step:13K smpl:806K ep:1K epch:7.16 loss:0.008 grdn:0.253 lr:3.2e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 05:17:43 ot_train.py:501 step:13K smpl:813K ep:1K epch:7.21 loss:0.008 grdn:0.247 lr:3.2e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 05:19:42 ot_train.py:501 step:13K smpl:819K ep:1K epch:7.27 loss:0.008 grdn:0.235 lr:3.1e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 05:21:42 ot_train.py:501 step:13K smpl:826K ep:1K epch:7.33 loss:0.007 grdn:0.235 lr:3.0e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 05:23:41 ot_train.py:501 step:13K smpl:832K ep:1K epch:7.38 loss:0.008 grdn:0.257 lr:2.9e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 05:25:40 ot_train.py:501 step:13K smpl:838K ep:1K epch:7.44 loss:0.007 grdn:0.246 lr:2.9e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 05:27:40 ot_train.py:501 step:13K smpl:845K ep:1K epch:7.50 loss:0.007 grdn:0.238 lr:2.8e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 05:29:39 ot_train.py:501 step:13K smpl:851K ep:1K epch:7.55 loss:0.007 grdn:0.251 lr:2.7e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 05:31:38 ot_train.py:501 step:13K smpl:858K ep:1K epch:7.61 loss:0.007 grdn:0.265 lr:2.7e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 05:33:38 ot_train.py:501 step:14K smpl:864K ep:1K epch:7.67 loss:0.007 grdn:0.229 lr:2.6e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 05:35:37 ot_train.py:501 step:14K smpl:870K ep:1K epch:7.72 loss:0.007 grdn:0.236 lr:2.5e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 05:37:36 ot_train.py:501 step:14K smpl:877K ep:1K epch:7.78 loss:0.007 grdn:0.221 lr:2.5e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 05:39:36 ot_train.py:501 step:14K smpl:883K ep:1K epch:7.84 loss:0.007 grdn:0.264 lr:2.4e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 05:41:35 ot_train.py:501 step:14K smpl:890K ep:2K epch:7.89 loss:0.007 grdn:0.211 lr:2.4e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 05:43:34 ot_train.py:501 step:14K smpl:896K ep:2K epch:7.95 loss:0.007 grdn:0.227 lr:2.3e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 05:45:34 ot_train.py:501 step:14K smpl:902K ep:2K epch:8.01 loss:0.007 grdn:0.237 lr:2.2e-05 updt_s:1.185 data_s:0.012 | |
| INFO 2026-01-06 05:47:33 ot_train.py:501 step:14K smpl:909K ep:2K epch:8.06 loss:0.007 grdn:0.222 lr:2.2e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 05:49:33 ot_train.py:501 step:14K smpl:915K ep:2K epch:8.12 loss:0.007 grdn:0.249 lr:2.1e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 05:51:32 ot_train.py:501 step:14K smpl:922K ep:2K epch:8.18 loss:0.007 grdn:0.227 lr:2.0e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 05:53:31 ot_train.py:501 step:14K smpl:928K ep:2K epch:8.23 loss:0.007 grdn:0.242 lr:2.0e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 05:55:31 ot_train.py:501 step:15K smpl:934K ep:2K epch:8.29 loss:0.007 grdn:0.229 lr:1.9e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 05:57:30 ot_train.py:501 step:15K smpl:941K ep:2K epch:8.35 loss:0.007 grdn:0.228 lr:1.9e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 05:59:29 ot_train.py:501 step:15K smpl:947K ep:2K epch:8.41 loss:0.007 grdn:0.220 lr:1.8e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 06:01:29 ot_train.py:501 step:15K smpl:954K ep:2K epch:8.46 loss:0.006 grdn:0.238 lr:1.8e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 06:03:28 ot_train.py:501 step:15K smpl:960K ep:2K epch:8.52 loss:0.006 grdn:0.231 lr:1.7e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 06:03:28 ot_train.py:521 Checkpoint policy after step 15000 | |
| INFO 2026-01-06 06:05:28 ot_train.py:501 step:15K smpl:966K ep:2K epch:8.58 loss:0.007 grdn:0.209 lr:1.7e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 06:07:27 ot_train.py:501 step:15K smpl:973K ep:2K epch:8.63 loss:0.006 grdn:0.215 lr:1.6e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 06:09:27 ot_train.py:501 step:15K smpl:979K ep:2K epch:8.69 loss:0.007 grdn:0.228 lr:1.5e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 06:11:26 ot_train.py:501 step:15K smpl:986K ep:2K epch:8.75 loss:0.006 grdn:0.191 lr:1.5e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 06:13:25 ot_train.py:501 step:16K smpl:992K ep:2K epch:8.80 loss:0.006 grdn:0.210 lr:1.4e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 06:15:25 ot_train.py:501 step:16K smpl:998K ep:2K epch:8.86 loss:0.006 grdn:0.204 lr:1.4e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 06:17:24 ot_train.py:501 step:16K smpl:1M ep:2K epch:8.92 loss:0.007 grdn:0.223 lr:1.3e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 06:19:23 ot_train.py:501 step:16K smpl:1M ep:2K epch:8.97 loss:0.007 grdn:0.213 lr:1.3e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 06:21:23 ot_train.py:501 step:16K smpl:1M ep:2K epch:9.03 loss:0.006 grdn:0.227 lr:1.2e-05 updt_s:1.185 data_s:0.012 | |
| INFO 2026-01-06 06:23:22 ot_train.py:501 step:16K smpl:1M ep:2K epch:9.09 loss:0.006 grdn:0.210 lr:1.2e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 06:25:22 ot_train.py:501 step:16K smpl:1M ep:2K epch:9.14 loss:0.006 grdn:0.210 lr:1.2e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 06:27:21 ot_train.py:501 step:16K smpl:1M ep:2K epch:9.20 loss:0.006 grdn:0.209 lr:1.1e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 06:29:21 ot_train.py:501 step:16K smpl:1M ep:2K epch:9.26 loss:0.006 grdn:0.202 lr:1.1e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 06:31:20 ot_train.py:501 step:16K smpl:1M ep:2K epch:9.31 loss:0.006 grdn:0.206 lr:1.0e-05 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 06:33:19 ot_train.py:501 step:16K smpl:1M ep:2K epch:9.37 loss:0.006 grdn:0.206 lr:9.9e-06 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 06:35:18 ot_train.py:501 step:17K smpl:1M ep:2K epch:9.43 loss:0.006 grdn:0.205 lr:9.5e-06 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 06:37:18 ot_train.py:501 step:17K smpl:1M ep:2K epch:9.48 loss:0.006 grdn:0.188 lr:9.1e-06 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 06:39:17 ot_train.py:501 step:17K smpl:1M ep:2K epch:9.54 loss:0.006 grdn:0.204 lr:8.7e-06 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 06:41:16 ot_train.py:501 step:17K smpl:1M ep:2K epch:9.60 loss:0.006 grdn:0.184 lr:8.3e-06 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 06:43:16 ot_train.py:501 step:17K smpl:1M ep:2K epch:9.65 loss:0.006 grdn:0.215 lr:8.0e-06 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 06:45:15 ot_train.py:501 step:17K smpl:1M ep:2K epch:9.71 loss:0.006 grdn:0.199 lr:7.6e-06 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 06:47:14 ot_train.py:501 step:17K smpl:1M ep:2K epch:9.77 loss:0.006 grdn:0.196 lr:7.3e-06 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 06:49:14 ot_train.py:501 step:17K smpl:1M ep:2K epch:9.83 loss:0.006 grdn:0.187 lr:7.0e-06 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 06:51:13 ot_train.py:501 step:17K smpl:1M ep:2K epch:9.88 loss:0.006 grdn:0.183 lr:6.7e-06 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 06:53:12 ot_train.py:501 step:18K smpl:1M ep:2K epch:9.94 loss:0.006 grdn:0.202 lr:6.4e-06 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 06:55:12 ot_train.py:501 step:18K smpl:1M ep:2K epch:10.00 loss:0.006 grdn:0.212 lr:6.1e-06 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 06:57:11 ot_train.py:501 step:18K smpl:1M ep:2K epch:10.05 loss:0.006 grdn:0.208 lr:5.8e-06 updt_s:1.185 data_s:0.012 | |
| INFO 2026-01-06 06:59:11 ot_train.py:501 step:18K smpl:1M ep:2K epch:10.11 loss:0.006 grdn:0.183 lr:5.5e-06 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 07:01:10 ot_train.py:501 step:18K smpl:1M ep:2K epch:10.17 loss:0.006 grdn:0.189 lr:5.3e-06 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 07:03:09 ot_train.py:501 step:18K smpl:1M ep:2K epch:10.22 loss:0.006 grdn:0.188 lr:5.0e-06 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 07:05:09 ot_train.py:501 step:18K smpl:1M ep:2K epch:10.28 loss:0.006 grdn:0.196 lr:4.8e-06 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 07:07:08 ot_train.py:501 step:18K smpl:1M ep:2K epch:10.34 loss:0.006 grdn:0.176 lr:4.5e-06 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 07:09:07 ot_train.py:501 step:18K smpl:1M ep:2K epch:10.39 loss:0.006 grdn:0.205 lr:4.3e-06 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 07:11:07 ot_train.py:501 step:18K smpl:1M ep:2K epch:10.45 loss:0.006 grdn:0.198 lr:4.1e-06 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 07:13:06 ot_train.py:501 step:18K smpl:1M ep:2K epch:10.51 loss:0.006 grdn:0.179 lr:3.9e-06 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 07:15:05 ot_train.py:501 step:19K smpl:1M ep:2K epch:10.56 loss:0.006 grdn:0.182 lr:3.8e-06 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 07:17:05 ot_train.py:501 step:19K smpl:1M ep:2K epch:10.62 loss:0.006 grdn:0.186 lr:3.6e-06 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 07:19:04 ot_train.py:501 step:19K smpl:1M ep:2K epch:10.68 loss:0.006 grdn:0.189 lr:3.4e-06 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 07:21:03 ot_train.py:501 step:19K smpl:1M ep:2K epch:10.73 loss:0.006 grdn:0.190 lr:3.3e-06 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 07:23:03 ot_train.py:501 step:19K smpl:1M ep:2K epch:10.79 loss:0.006 grdn:0.188 lr:3.2e-06 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 07:25:02 ot_train.py:501 step:19K smpl:1M ep:2K epch:10.85 loss:0.006 grdn:0.190 lr:3.0e-06 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 07:27:01 ot_train.py:501 step:19K smpl:1M ep:2K epch:10.90 loss:0.006 grdn:0.194 lr:2.9e-06 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 07:29:01 ot_train.py:501 step:19K smpl:1M ep:2K epch:10.96 loss:0.006 grdn:0.186 lr:2.8e-06 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 07:31:00 ot_train.py:501 step:19K smpl:1M ep:2K epch:11.02 loss:0.006 grdn:0.201 lr:2.8e-06 updt_s:1.185 data_s:0.012 | |
| INFO 2026-01-06 07:33:00 ot_train.py:501 step:20K smpl:1M ep:2K epch:11.07 loss:0.006 grdn:0.168 lr:2.7e-06 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 07:34:59 ot_train.py:501 step:20K smpl:1M ep:2K epch:11.13 loss:0.006 grdn:0.196 lr:2.6e-06 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 07:36:58 ot_train.py:501 step:20K smpl:1M ep:2K epch:11.19 loss:0.006 grdn:0.178 lr:2.6e-06 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 07:38:58 ot_train.py:501 step:20K smpl:1M ep:2K epch:11.25 loss:0.006 grdn:0.183 lr:2.5e-06 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 07:40:57 ot_train.py:501 step:20K smpl:1M ep:2K epch:11.30 loss:0.006 grdn:0.185 lr:2.5e-06 updt_s:1.187 data_s:0.005 | |
| INFO 2026-01-06 07:42:56 ot_train.py:501 step:20K smpl:1M ep:2K epch:11.36 los | |