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a/DP_cube_downDims1_cropNo_freeze1_32_32_ema0_1e-4/wandb/run-20250501_164722-qj0kf3mh/files/output.log b/DP_cube_downDims1_cropNo_freeze1_32_32_ema0_1e-4/wandb/run-20250501_164722-qj0kf3mh/files/output.log new file mode 100644 index 0000000000000000000000000000000000000000..d0285f64f5d07ddf02e784e33d4e42160921ef07 --- /dev/null +++ b/DP_cube_downDims1_cropNo_freeze1_32_32_ema0_1e-4/wandb/run-20250501_164722-qj0kf3mh/files/output.log @@ -0,0 +1,1519 @@ +Logs will be synced with wandb. +INFO 2025-05-01 16:47:23 ndb_utils.py:96 Track this run --> https://wandb.ai/marchmelo0923-postech/lerobot/runs/qj0kf3mh +INFO 2025-05-01 16:47:23 ts/train.py:127 Creating dataset +Resolving data files: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 200/200 [00:00<00:00, 81506.10it/s] +INFO 2025-05-01 16:47:25 ts/train.py:138 Creating policy +INFO 2025-05-01 16:47:31 ts/train.py:144 Creating optimizer and scheduler +INFO 2025-05-01 16:47:31 ts/train.py:156 Output dir: outputs/train/DP_cube_downDims1_cropNo_freeze1_32_32_ema0_1e-4 +INFO 2025-05-01 16:47:31 ts/train.py:159 cfg.steps=480000 (480K) +INFO 2025-05-01 16:47:31 ts/train.py:160 dataset.num_frames=58213 (58K) +INFO 2025-05-01 16:47:31 ts/train.py:161 dataset.num_episodes=200 +INFO 2025-05-01 16:47:31 ts/train.py:162 num_learnable_params=83699686 (84M) +INFO 2025-05-01 16:47:31 ts/train.py:163 num_total_params=92243036 (92M) +INFO 2025-05-01 16:47:31 ts/train.py:202 Start offline training on a fixed dataset +INFO 2025-05-01 16:48:18 ts/train.py:232 step:200 smpl:2K ep:5 epch:0.03 loss:0.753 grdn:3.796 lr:2.0e-05 updt_s:0.223 data_s:0.012 +INFO 2025-05-01 16:48:56 ts/train.py:232 step:400 smpl:3K ep:11 epch:0.05 loss:0.159 grdn:2.986 lr:6.0e-05 updt_s:0.191 data_s:0.000 +INFO 2025-05-01 16:49:35 ts/train.py:232 step:600 smpl:5K ep:16 epch:0.08 loss:0.106 grdn:2.078 lr:9.5e-05 updt_s:0.191 data_s:0.000 +INFO 2025-05-01 16:50:13 ts/train.py:232 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ts/train.py:232 step:102K smpl:814K ep:3K epch:13.99 loss:0.011 grdn:0.198 lr:8.9e-05 updt_s:0.191 data_s:0.000 +INFO 2025-05-01 22:18:15 ts/train.py:232 step:102K smpl:816K ep:3K epch:14.02 loss:0.009 grdn:0.179 lr:8.9e-05 updt_s:0.191 data_s:0.000 +INFO 2025-05-01 22:18:53 ts/train.py:232 step:102K smpl:818K ep:3K epch:14.04 loss:0.009 grdn:0.187 lr:8.9e-05 updt_s:0.191 data_s:0.000 +INFO 2025-05-01 22:19:32 ts/train.py:232 step:102K smpl:819K ep:3K epch:14.07 loss:0.008 grdn:0.174 lr:8.9e-05 updt_s:0.191 data_s:0.000 +INFO 2025-05-01 22:20:10 ts/train.py:232 step:103K smpl:821K ep:3K epch:14.10 loss:0.010 grdn:0.184 lr:8.9e-05 updt_s:0.191 data_s:0.000 +INFO 2025-05-01 22:20:49 ts/train.py:232 step:103K smpl:822K ep:3K epch:14.13 loss:0.009 grdn:0.169 lr:8.9e-05 updt_s:0.191 data_s:0.000 +INFO 2025-05-01 22:21:27 ts/train.py:232 step:103K smpl:824K ep:3K epch:14.15 loss:0.010 grdn:0.185 lr:8.9e-05 updt_s:0.191 data_s:0.000 +INFO 2025-05-01 22:22:06 ts/train.py:232 step:103K 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02:57:05 ts/train.py:232 step:188K smpl:2M ep:5K epch:25.89 loss:0.007 grdn:0.167 lr:6.7e-05 updt_s:0.191 data_s:0.000 +INFO 2025-05-02 02:57:43 ts/train.py:232 step:189K smpl:2M ep:5K epch:25.92 loss:0.006 grdn:0.168 lr:6.7e-05 updt_s:0.191 data_s:0.000 +INFO 2025-05-02 02:58:21 ts/train.py:232 step:189K smpl:2M ep:5K epch:25.95 loss:0.008 grdn:0.189 lr:6.7e-05 updt_s:0.190 data_s:0.000 +INFO 2025-05-02 02:59:00 ts/train.py:232 step:189K smpl:2M ep:5K epch:25.97 loss:0.007 grdn:0.174 lr:6.7e-05 updt_s:0.191 data_s:0.000 +INFO 2025-05-02 02:59:38 ts/train.py:232 step:189K smpl:2M ep:5K epch:26.00 loss:0.006 grdn:0.163 lr:6.6e-05 updt_s:0.190 data_s:0.000 +INFO 2025-05-02 03:00:16 ts/train.py:232 step:189K smpl:2M ep:5K epch:26.03 loss:0.007 grdn:0.186 lr:6.6e-05 updt_s:0.191 data_s:0.000 +INFO 2025-05-02 03:00:55 ts/train.py:232 step:190K smpl:2M ep:5K epch:26.06 loss:0.006 grdn:0.168 lr:6.6e-05 updt_s:0.190 data_s:0.000 +INFO 2025-05-02 03:01:33 ts/train.py:232 step:190K smpl:2M ep:5K epch:26.08 loss:0.008 grdn:0.188 lr:6.6e-05 updt_s:0.191 data_s:0.000 +INFO 2025-05-02 03:02:11 ts/train.py:232 step:190K smpl:2M ep:5K epch:26.11 loss:0.006 grdn:0.165 lr:6.6e-05 updt_s:0.191 data_s:0.000 +INFO 2025-05-02 03:02:11 ts/train.py:241 Checkpoint policy after step 190000 +INFO 2025-05-02 03:03:09 ts/train.py:232 step:190K smpl:2M ep:5K epch:26.14 loss:0.007 grdn:0.177 lr:6.6e-05 updt_s:0.190 data_s:0.000 +INFO 2025-05-02 03:03:47 ts/train.py:232 step:190K smpl:2M ep:5K epch:26.17 loss:0.007 grdn:0.176 lr:6.6e-05 updt_s:0.190 data_s:0.000 +INFO 2025-05-02 03:04:25 ts/train.py:232 step:191K smpl:2M ep:5K epch:26.19 loss:0.007 grdn:0.166 lr:6.6e-05 updt_s:0.190 data_s:0.000 +INFO 2025-05-02 03:05:03 ts/train.py:232 step:191K smpl:2M ep:5K epch:26.22 loss:0.006 grdn:0.162 lr:6.6e-05 updt_s:0.190 data_s:0.000 +INFO 2025-05-02 03:05:42 ts/train.py:232 step:191K smpl:2M ep:5K epch:26.25 loss:0.007 grdn:0.167 lr:6.6e-05 updt_s:0.191 data_s:0.000 +INFO 2025-05-02 03:06:20 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03:20:24 ts/train.py:232 step:196K smpl:2M ep:5K epch:26.88 loss:0.006 grdn:0.165 lr:6.4e-05 updt_s:0.191 data_s:0.000 +INFO 2025-05-02 03:21:02 ts/train.py:232 step:196K smpl:2M ep:5K epch:26.91 loss:0.007 grdn:0.163 lr:6.4e-05 updt_s:0.191 data_s:0.000 +INFO 2025-05-02 03:21:40 ts/train.py:232 step:196K smpl:2M ep:5K epch:26.94 loss:0.008 grdn:0.185 lr:6.4e-05 updt_s:0.191 data_s:0.000 +INFO 2025-05-02 03:22:19 ts/train.py:232 step:196K smpl:2M ep:5K epch:26.96 loss:0.006 grdn:0.168 lr:6.4e-05 updt_s:0.191 data_s:0.000 +INFO 2025-05-02 03:22:57 ts/train.py:232 step:196K smpl:2M ep:5K epch:26.99 loss:0.007 grdn:0.172 lr:6.4e-05 updt_s:0.191 data_s:0.000 +INFO 2025-05-02 03:23:35 ts/train.py:232 step:197K smpl:2M ep:5K epch:27.02 loss:0.007 grdn:0.164 lr:6.4e-05 updt_s:0.191 data_s:0.000 +INFO 2025-05-02 03:24:14 ts/train.py:232 step:197K smpl:2M ep:5K epch:27.05 loss:0.008 grdn:0.183 lr:6.4e-05 updt_s:0.191 data_s:0.000 +INFO 2025-05-02 03:24:52 ts/train.py:232 step:197K smpl:2M ep:5K 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03:34:29 ts/train.py:232 step:200K smpl:2M ep:5K epch:27.49 loss:0.007 grdn:0.181 lr:6.3e-05 updt_s:0.191 data_s:0.000 +INFO 2025-05-02 03:34:29 ts/train.py:241 Checkpoint policy after step 200000 +INFO 2025-05-02 03:35:27 ts/train.py:232 step:200K smpl:2M ep:6K epch:27.51 loss:0.006 grdn:0.163 lr:6.3e-05 updt_s:0.190 data_s:0.001 +INFO 2025-05-02 03:36:05 ts/train.py:232 step:200K smpl:2M ep:6K epch:27.54 loss:0.006 grdn:0.167 lr:6.3e-05 updt_s:0.190 data_s:0.000 +INFO 2025-05-02 03:36:43 ts/train.py:232 step:201K smpl:2M ep:6K epch:27.57 loss:0.006 grdn:0.162 lr:6.3e-05 updt_s:0.190 data_s:0.000 +INFO 2025-05-02 03:37:22 ts/train.py:232 step:201K smpl:2M ep:6K epch:27.60 loss:0.008 grdn:0.186 lr:6.3e-05 updt_s:0.191 data_s:0.000 +INFO 2025-05-02 03:38:00 ts/train.py:232 step:201K smpl:2M ep:6K epch:27.62 loss:0.007 grdn:0.179 lr:6.3e-05 updt_s:0.191 data_s:0.000 +INFO 2025-05-02 03:38:38 ts/train.py:232 step:201K smpl:2M ep:6K epch:27.65 loss:0.007 grdn:0.176 lr:6.3e-05 updt_s:0.191 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03:57:48 ts/train.py:232 step:207K smpl:2M ep:6K epch:28.47 loss:0.006 grdn:0.169 lr:6.1e-05 updt_s:0.190 data_s:0.000 +INFO 2025-05-02 03:58:26 ts/train.py:232 step:207K smpl:2M ep:6K epch:28.50 loss:0.006 grdn:0.160 lr:6.1e-05 updt_s:0.190 data_s:0.000 +INFO 2025-05-02 03:59:05 ts/train.py:232 step:208K smpl:2M ep:6K epch:28.53 loss:0.007 grdn:0.169 lr:6.1e-05 updt_s:0.191 data_s:0.000 +INFO 2025-05-02 03:59:43 ts/train.py:232 step:208K smpl:2M ep:6K epch:28.56 loss:0.007 grdn:0.176 lr:6.1e-05 updt_s:0.190 data_s:0.000 +INFO 2025-05-02 04:00:21 ts/train.py:232 step:208K smpl:2M ep:6K epch:28.58 loss:0.006 grdn:0.160 lr:6.1e-05 updt_s:0.190 data_s:0.000 +INFO 2025-05-02 04:01:00 ts/train.py:232 step:208K smpl:2M ep:6K epch:28.61 loss:0.006 grdn:0.167 lr:6.0e-05 updt_s:0.191 data_s:0.000 +INFO 2025-05-02 04:01:38 ts/train.py:232 step:208K smpl:2M ep:6K epch:28.64 loss:0.006 grdn:0.163 lr:6.0e-05 updt_s:0.190 data_s:0.000 +INFO 2025-05-02 04:02:16 ts/train.py:232 step:209K smpl:2M ep:6K 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04:35:12 ts/train.py:232 step:219K smpl:2M ep:6K epch:30.07 loss:0.006 grdn:0.172 lr:5.7e-05 updt_s:0.191 data_s:0.001 +INFO 2025-05-02 04:35:50 ts/train.py:232 step:219K smpl:2M ep:6K epch:30.10 loss:0.006 grdn:0.168 lr:5.7e-05 updt_s:0.191 data_s:0.000 +INFO 2025-05-02 04:36:29 ts/train.py:232 step:219K smpl:2M ep:6K epch:30.12 loss:0.006 grdn:0.165 lr:5.7e-05 updt_s:0.191 data_s:0.000 +INFO 2025-05-02 04:37:07 ts/train.py:232 step:219K smpl:2M ep:6K epch:30.15 loss:0.006 grdn:0.175 lr:5.7e-05 updt_s:0.191 data_s:0.000 +INFO 2025-05-02 04:37:45 ts/train.py:232 step:220K smpl:2M ep:6K epch:30.18 loss:0.007 grdn:0.182 lr:5.7e-05 updt_s:0.191 data_s:0.000 +INFO 2025-05-02 04:38:24 ts/train.py:232 step:220K smpl:2M ep:6K epch:30.21 loss:0.007 grdn:0.172 lr:5.7e-05 updt_s:0.191 data_s:0.000 +INFO 2025-05-02 04:39:02 ts/train.py:232 step:220K smpl:2M ep:6K epch:30.23 loss:0.006 grdn:0.161 lr:5.7e-05 updt_s:0.191 data_s:0.000 +INFO 2025-05-02 04:39:02 ts/train.py:241 Checkpoint policy after 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04:58:34 ts/train.py:232 step:226K smpl:2M ep:6K epch:31.06 loss:0.006 grdn:0.170 lr:5.5e-05 updt_s:0.191 data_s:0.000 +INFO 2025-05-02 04:59:13 ts/train.py:232 step:226K smpl:2M ep:6K epch:31.09 loss:0.005 grdn:0.164 lr:5.5e-05 updt_s:0.191 data_s:0.000 +INFO 2025-05-02 04:59:51 ts/train.py:232 step:226K smpl:2M ep:6K epch:31.11 loss:0.006 grdn:0.171 lr:5.5e-05 updt_s:0.190 data_s:0.000 +INFO 2025-05-02 05:00:29 ts/train.py:232 step:227K smpl:2M ep:6K epch:31.14 loss:0.006 grdn:0.172 lr:5.4e-05 updt_s:0.191 data_s:0.000 +INFO 2025-05-02 05:01:08 ts/train.py:232 step:227K smpl:2M ep:6K epch:31.17 loss:0.006 grdn:0.162 lr:5.4e-05 updt_s:0.191 data_s:0.000 +INFO 2025-05-02 05:01:46 ts/train.py:232 step:227K smpl:2M ep:6K epch:31.20 loss:0.007 grdn:0.184 lr:5.4e-05 updt_s:0.191 data_s:0.000 +INFO 2025-05-02 05:02:24 ts/train.py:232 step:227K smpl:2M ep:6K epch:31.22 loss:0.006 grdn:0.161 lr:5.4e-05 updt_s:0.191 data_s:0.000 +INFO 2025-05-02 05:03:04 ts/train.py:232 step:227K smpl:2M ep:6K 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05:35:56 ts/train.py:232 step:238K smpl:2M ep:7K epch:32.65 loss:0.006 grdn:0.173 lr:5.1e-05 updt_s:0.190 data_s:0.000 +INFO 2025-05-02 05:36:34 ts/train.py:232 step:238K smpl:2M ep:7K epch:32.68 loss:0.006 grdn:0.183 lr:5.1e-05 updt_s:0.190 data_s:0.000 +INFO 2025-05-02 05:37:13 ts/train.py:232 step:238K smpl:2M ep:7K epch:32.71 loss:0.006 grdn:0.166 lr:5.1e-05 updt_s:0.190 data_s:0.000 +INFO 2025-05-02 05:37:51 ts/train.py:232 step:238K smpl:2M ep:7K epch:32.73 loss:0.006 grdn:0.162 lr:5.1e-05 updt_s:0.190 data_s:0.000 +INFO 2025-05-02 05:38:29 ts/train.py:232 step:238K smpl:2M ep:7K epch:32.76 loss:0.006 grdn:0.171 lr:5.1e-05 updt_s:0.190 data_s:0.000 +INFO 2025-05-02 05:39:07 ts/train.py:232 step:239K smpl:2M ep:7K epch:32.79 loss:0.005 grdn:0.163 lr:5.1e-05 updt_s:0.190 data_s:0.000 +INFO 2025-05-02 05:39:45 ts/train.py:232 step:239K smpl:2M ep:7K epch:32.82 loss:0.006 grdn:0.177 lr:5.1e-05 updt_s:0.190 data_s:0.000 +INFO 2025-05-02 05:40:23 ts/train.py:232 step:239K smpl:2M ep:7K 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06:13:20 ts/train.py:232 step:249K smpl:2M ep:7K epch:34.25 loss:0.006 grdn:0.171 lr:4.7e-05 updt_s:0.190 data_s:0.000 +INFO 2025-05-02 06:13:58 ts/train.py:232 step:249K smpl:2M ep:7K epch:34.27 loss:0.006 grdn:0.175 lr:4.7e-05 updt_s:0.190 data_s:0.000 +INFO 2025-05-02 06:14:37 ts/train.py:232 step:250K smpl:2M ep:7K epch:34.30 loss:0.005 grdn:0.174 lr:4.7e-05 updt_s:0.190 data_s:0.000 +INFO 2025-05-02 06:15:15 ts/train.py:232 step:250K smpl:2M ep:7K epch:34.33 loss:0.005 grdn:0.171 lr:4.7e-05 updt_s:0.190 data_s:0.000 +INFO 2025-05-02 06:15:53 ts/train.py:232 step:250K smpl:2M ep:7K epch:34.36 loss:0.006 grdn:0.180 lr:4.7e-05 updt_s:0.190 data_s:0.000 +INFO 2025-05-02 06:15:53 ts/train.py:241 Checkpoint policy after step 250000 +INFO 2025-05-02 06:16:54 ts/train.py:232 step:250K smpl:2M ep:7K epch:34.38 loss:0.006 grdn:0.178 lr:4.7e-05 updt_s:0.190 data_s:0.001 +INFO 2025-05-02 06:17:32 ts/train.py:232 step:250K smpl:2M ep:7K epch:34.41 loss:0.005 grdn:0.157 lr:4.7e-05 updt_s:0.190 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06:36:41 ts/train.py:232 step:256K smpl:2M ep:7K epch:35.24 loss:0.005 grdn:0.166 lr:4.5e-05 updt_s:0.190 data_s:0.000 +INFO 2025-05-02 06:37:19 ts/train.py:232 step:257K smpl:2M ep:7K epch:35.26 loss:0.006 grdn:0.183 lr:4.5e-05 updt_s:0.190 data_s:0.001 +INFO 2025-05-02 06:37:57 ts/train.py:232 step:257K smpl:2M ep:7K epch:35.29 loss:0.006 grdn:0.170 lr:4.5e-05 updt_s:0.191 data_s:0.000 +INFO 2025-05-02 06:38:36 ts/train.py:232 step:257K smpl:2M ep:7K epch:35.32 loss:0.005 grdn:0.160 lr:4.5e-05 updt_s:0.191 data_s:0.000 +INFO 2025-05-02 06:39:14 ts/train.py:232 step:257K smpl:2M ep:7K epch:35.35 loss:0.005 grdn:0.161 lr:4.4e-05 updt_s:0.191 data_s:0.000 +INFO 2025-05-02 06:39:52 ts/train.py:232 step:257K smpl:2M ep:7K epch:35.37 loss:0.005 grdn:0.162 lr:4.4e-05 updt_s:0.191 data_s:0.000 +INFO 2025-05-02 06:40:31 ts/train.py:232 step:258K smpl:2M ep:7K epch:35.40 loss:0.005 grdn:0.163 lr:4.4e-05 updt_s:0.190 data_s:0.000 +INFO 2025-05-02 06:41:09 ts/train.py:232 step:258K smpl:2M ep:7K epch:35.43 loss:0.005 grdn:0.154 lr:4.4e-05 updt_s:0.190 data_s:0.000 +INFO 2025-05-02 06:41:47 ts/train.py:232 step:258K smpl:2M ep:7K epch:35.46 loss:0.005 grdn:0.164 lr:4.4e-05 updt_s:0.190 data_s:0.000 +INFO 2025-05-02 06:42:25 ts/train.py:232 step:258K smpl:2M ep:7K epch:35.48 loss:0.006 grdn:0.165 lr:4.4e-05 updt_s:0.191 data_s:0.001 +INFO 2025-05-02 06:43:04 ts/train.py:232 step:258K smpl:2M ep:7K epch:35.51 loss:0.006 grdn:0.173 lr:4.4e-05 updt_s:0.190 data_s:0.000 +INFO 2025-05-02 06:43:42 ts/train.py:232 step:259K smpl:2M ep:7K epch:35.54 loss:0.005 grdn:0.166 lr:4.4e-05 updt_s:0.191 data_s:0.000 +INFO 2025-05-02 06:44:20 ts/train.py:232 step:259K smpl:2M ep:7K epch:35.57 loss:0.006 grdn:0.173 lr:4.4e-05 updt_s:0.191 data_s:0.000 +INFO 2025-05-02 06:44:59 ts/train.py:232 step:259K smpl:2M ep:7K epch:35.59 loss:0.005 grdn:0.155 lr:4.4e-05 updt_s:0.191 data_s:0.000 +INFO 2025-05-02 06:45:37 ts/train.py:232 step:259K smpl:2M ep:7K epch:35.62 loss:0.005 grdn:0.169 lr:4.4e-05 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07:37:22 ts/train.py:232 step:275K smpl:2M ep:8K epch:37.82 loss:0.004 grdn:0.160 lr:3.9e-05 updt_s:0.190 data_s:0.001 +INFO 2025-05-02 07:38:00 ts/train.py:232 step:275K smpl:2M ep:8K epch:37.85 loss:0.005 grdn:0.169 lr:3.9e-05 updt_s:0.190 data_s:0.001 +INFO 2025-05-02 07:38:38 ts/train.py:232 step:276K smpl:2M ep:8K epch:37.87 loss:0.005 grdn:0.168 lr:3.9e-05 updt_s:0.190 data_s:0.001 +INFO 2025-05-02 07:39:17 ts/train.py:232 step:276K smpl:2M ep:8K epch:37.90 loss:0.005 grdn:0.176 lr:3.8e-05 updt_s:0.190 data_s:0.000 +INFO 2025-05-02 07:39:55 ts/train.py:232 step:276K smpl:2M ep:8K epch:37.93 loss:0.005 grdn:0.174 lr:3.8e-05 updt_s:0.190 data_s:0.001 +INFO 2025-05-02 07:40:33 ts/train.py:232 step:276K smpl:2M ep:8K epch:37.96 loss:0.005 grdn:0.167 lr:3.8e-05 updt_s:0.190 data_s:0.000 +INFO 2025-05-02 07:41:11 ts/train.py:232 step:276K smpl:2M ep:8K epch:37.98 loss:0.005 grdn:0.168 lr:3.8e-05 updt_s:0.191 data_s:0.000 +INFO 2025-05-02 07:41:50 ts/train.py:232 step:277K smpl:2M ep:8K 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07:51:25 ts/train.py:232 step:280K smpl:2M ep:8K epch:38.42 loss:0.005 grdn:0.175 lr:3.7e-05 updt_s:0.191 data_s:0.000 +INFO 2025-05-02 07:52:04 ts/train.py:232 step:280K smpl:2M ep:8K epch:38.45 loss:0.005 grdn:0.160 lr:3.7e-05 updt_s:0.191 data_s:0.001 +INFO 2025-05-02 07:52:42 ts/train.py:232 step:280K smpl:2M ep:8K epch:38.48 loss:0.005 grdn:0.159 lr:3.7e-05 updt_s:0.191 data_s:0.001 +INFO 2025-05-02 07:52:42 ts/train.py:241 Checkpoint policy after step 280000 +INFO 2025-05-02 07:53:38 ts/train.py:232 step:280K smpl:2M ep:8K epch:38.51 loss:0.005 grdn:0.173 lr:3.7e-05 updt_s:0.189 data_s:0.001 +INFO 2025-05-02 07:54:16 ts/train.py:232 step:280K smpl:2M ep:8K epch:38.53 loss:0.005 grdn:0.172 lr:3.7e-05 updt_s:0.189 data_s:0.000 +INFO 2025-05-02 07:54:54 ts/train.py:232 step:281K smpl:2M ep:8K epch:38.56 loss:0.005 grdn:0.161 lr:3.7e-05 updt_s:0.190 data_s:0.000 +INFO 2025-05-02 07:55:32 ts/train.py:232 step:281K smpl:2M ep:8K epch:38.59 loss:0.005 grdn:0.162 lr:3.7e-05 updt_s:0.190 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08:14:39 ts/train.py:232 step:287K smpl:2M ep:8K epch:39.41 loss:0.005 grdn:0.164 lr:3.5e-05 updt_s:0.190 data_s:0.001 +INFO 2025-05-02 08:15:18 ts/train.py:232 step:287K smpl:2M ep:8K epch:39.44 loss:0.006 grdn:0.182 lr:3.5e-05 updt_s:0.190 data_s:0.000 +INFO 2025-05-02 08:15:56 ts/train.py:232 step:287K smpl:2M ep:8K epch:39.47 loss:0.005 grdn:0.163 lr:3.5e-05 updt_s:0.190 data_s:0.000 +INFO 2025-05-02 08:16:34 ts/train.py:232 step:287K smpl:2M ep:8K epch:39.50 loss:0.004 grdn:0.165 lr:3.5e-05 updt_s:0.190 data_s:0.000 +INFO 2025-05-02 08:17:12 ts/train.py:232 step:288K smpl:2M ep:8K epch:39.52 loss:0.005 grdn:0.182 lr:3.5e-05 updt_s:0.190 data_s:0.000 +INFO 2025-05-02 08:17:50 ts/train.py:232 step:288K smpl:2M ep:8K epch:39.55 loss:0.005 grdn:0.162 lr:3.5e-05 updt_s:0.189 data_s:0.000 +INFO 2025-05-02 08:18:28 ts/train.py:232 step:288K smpl:2M ep:8K epch:39.58 loss:0.005 grdn:0.165 lr:3.5e-05 updt_s:0.189 data_s:0.000 +INFO 2025-05-02 08:19:06 ts/train.py:232 step:288K smpl:2M ep:8K 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data_s:0.000 +INFO 2025-05-02 08:40:27 ts/train.py:232 step:293K smpl:2M ep:8K epch:40.21 loss:0.005 grdn:0.164 lr:3.3e-05 updt_s:0.191 data_s:0.001 +INFO 2025-05-02 08:41:05 ts/train.py:232 step:293K smpl:2M ep:8K epch:40.24 loss:0.005 grdn:0.176 lr:3.3e-05 updt_s:0.191 data_s:0.001 +INFO 2025-05-02 08:41:44 ts/train.py:232 step:293K smpl:2M ep:8K epch:40.27 loss:0.004 grdn:0.154 lr:3.3e-05 updt_s:0.191 data_s:0.001 +INFO 2025-05-02 08:42:22 ts/train.py:232 step:293K smpl:2M ep:8K epch:40.29 loss:0.005 grdn:0.157 lr:3.3e-05 updt_s:0.191 data_s:0.000 +INFO 2025-05-02 08:43:01 ts/train.py:232 step:293K smpl:2M ep:8K epch:40.32 loss:0.005 grdn:0.185 lr:3.3e-05 updt_s:0.191 data_s:0.000 +INFO 2025-05-02 08:43:39 ts/train.py:232 step:294K smpl:2M ep:8K epch:40.35 loss:0.005 grdn:0.173 lr:3.3e-05 updt_s:0.191 data_s:0.000 +INFO 2025-05-02 08:44:17 ts/train.py:232 step:294K smpl:2M ep:8K epch:40.38 loss:0.004 grdn:0.169 lr:3.3e-05 updt_s:0.191 data_s:0.000 +INFO 2025-05-02 08:44:56 ts/train.py:232 step:294K smpl:2M ep:8K epch:40.40 loss:0.005 grdn:0.170 lr:3.3e-05 updt_s:0.191 data_s:0.000 +INFO 2025-05-02 08:45:34 ts/train.py:232 step:294K smpl:2M ep:8K epch:40.43 loss:0.004 grdn:0.157 lr:3.3e-05 updt_s:0.191 data_s:0.000 +INFO 2025-05-02 08:46:13 ts/train.py:232 step:294K smpl:2M ep:8K epch:40.46 loss:0.004 grdn:0.166 lr:3.3e-05 updt_s:0.191 data_s:0.000 +INFO 2025-05-02 08:46:51 ts/train.py:232 step:295K smpl:2M ep:8K epch:40.49 loss:0.004 grdn:0.157 lr:3.3e-05 updt_s:0.191 data_s:0.000 +INFO 2025-05-02 08:47:29 ts/train.py:232 step:295K smpl:2M ep:8K epch:40.51 loss:0.004 grdn:0.162 lr:3.3e-05 updt_s:0.191 data_s:0.000 +INFO 2025-05-02 08:48:08 ts/train.py:232 step:295K smpl:2M ep:8K epch:40.54 loss:0.005 grdn:0.171 lr:3.2e-05 updt_s:0.191 data_s:0.000 +INFO 2025-05-02 08:48:46 ts/train.py:232 step:295K smpl:2M ep:8K epch:40.57 loss:0.004 grdn:0.143 lr:3.2e-05 updt_s:0.191 data_s:0.001 +INFO 2025-05-02 08:49:24 ts/train.py:232 step:295K smpl:2M ep:8K epch:40.60 loss:0.004 grdn:0.159 lr:3.2e-05 updt_s:0.191 data_s:0.000 diff --git a/DP_cube_downDims1_cropNo_freeze1_32_32_ema0_1e-4/wandb/run-20250501_164722-qj0kf3mh/files/requirements.txt b/DP_cube_downDims1_cropNo_freeze1_32_32_ema0_1e-4/wandb/run-20250501_164722-qj0kf3mh/files/requirements.txt new file mode 100644 index 0000000000000000000000000000000000000000..8fc771efb7757d31b751b471861a827f2ce353fc --- /dev/null +++ b/DP_cube_downDims1_cropNo_freeze1_32_32_ema0_1e-4/wandb/run-20250501_164722-qj0kf3mh/files/requirements.txt @@ -0,0 +1,146 @@ +sympy==1.13.1 +torch==2.6.0 +nvidia-cuda-cupti-cu12==12.4.127 +gitdb==4.0.12 +nvidia-cusolver-cu12==11.6.1.9 +packaging==24.2 +numba==0.61.2 +safetensors==0.5.3 +nvidia-cusparselt-cu12==0.6.2 +pynput==1.8.1 +fsspec==2024.12.0 +filelock==3.18.0 +pydantic==2.11.3 +cloudpickle==3.1.1 +pillow==11.2.1 +lerobot==0.1.0 +inquirerpy==0.3.4 +charset-normalizer==3.4.1 +PySocks==1.7.1 +pycparser==2.22 +nvidia-cublas-cu12==12.4.5.8 +propcache==0.3.1 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ts/train.py:161 dataset.num_episodes=200 +INFO 2025-05-02 09:40:32 ts/train.py:162 num_learnable_params=83699686 (84M) +INFO 2025-05-02 09:40:32 ts/train.py:163 num_total_params=92243036 (92M) +INFO 2025-05-02 09:40:32 ts/train.py:202 Start offline training on a fixed dataset +INFO 2025-05-02 09:41:19 ts/train.py:232 step:290K smpl:2M ep:8K epch:39.88 loss:0.005 grdn:0.174 lr:3.4e-05 updt_s:0.226 data_s:0.012 +INFO 2025-05-02 09:41:57 ts/train.py:232 step:290K smpl:2M ep:8K epch:39.91 loss:0.004 grdn:0.154 lr:3.4e-05 updt_s:0.188 data_s:0.000 +INFO 2025-05-02 09:42:35 ts/train.py:232 step:291K smpl:2M ep:8K epch:39.94 loss:0.005 grdn:0.159 lr:3.4e-05 updt_s:0.189 data_s:0.000 +INFO 2025-05-02 09:43:13 ts/train.py:232 step:291K smpl:2M ep:8K epch:39.96 loss:0.005 grdn:0.172 lr:3.4e-05 updt_s:0.189 data_s:0.001 +INFO 2025-05-02 09:43:51 ts/train.py:232 step:291K smpl:2M ep:8K epch:39.99 loss:0.005 grdn:0.171 lr:3.4e-05 updt_s:0.190 data_s:0.000 +INFO 2025-05-02 09:44:30 ts/train.py:232 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