Add files using upload-large-folder tool
Browse files- .gitattributes +3 -0
- diffusion_anubis_fold_towel/checkpoints/100000/pretrained_model/config.json +92 -0
- diffusion_anubis_fold_towel/checkpoints/100000/pretrained_model/model.safetensors +3 -0
- diffusion_anubis_fold_towel/checkpoints/100000/pretrained_model/train_config.json +202 -0
- diffusion_anubis_fold_towel/wandb/debug-internal.log +15 -0
- diffusion_anubis_fold_towel/wandb/debug.log +23 -0
- diffusion_anubis_fold_towel/wandb/run-20251118_013752-9jmkckoo/files/config.yaml +184 -0
- diffusion_anubis_fold_towel/wandb/run-20251118_013752-9jmkckoo/files/output.log +518 -0
- diffusion_anubis_fold_towel/wandb/run-20251118_013752-9jmkckoo/files/requirements.txt +264 -0
- diffusion_anubis_fold_towel/wandb/run-20251118_013752-9jmkckoo/files/wandb-metadata.json +98 -0
- diffusion_anubis_fold_towel/wandb/run-20251118_013752-9jmkckoo/files/wandb-summary.json +1 -0
- diffusion_anubis_fold_towel/wandb/run-20251118_013752-9jmkckoo/logs/debug-core.log +13 -0
- diffusion_anubis_fold_towel/wandb/run-20251118_013752-9jmkckoo/logs/debug-internal.log +15 -0
- diffusion_anubis_fold_towel/wandb/run-20251118_013752-9jmkckoo/logs/debug.log +23 -0
- diffusion_anubis_fold_towel/wandb/run-20251118_013752-9jmkckoo/run-9jmkckoo.wandb +3 -0
- diffusion_anubis_pullout_wrench/checkpoints/100000/pretrained_model/config.json +92 -0
- diffusion_anubis_pullout_wrench/checkpoints/100000/pretrained_model/model.safetensors +3 -0
- diffusion_anubis_pullout_wrench/checkpoints/100000/pretrained_model/train_config.json +202 -0
- diffusion_anubis_pullout_wrench/wandb/debug-internal.log +15 -0
- diffusion_anubis_pullout_wrench/wandb/debug.log +23 -0
- diffusion_anubis_pullout_wrench/wandb/run-20251118_013623-flrqqt58/files/config.yaml +184 -0
- diffusion_anubis_pullout_wrench/wandb/run-20251118_013623-flrqqt58/files/output.log +518 -0
- diffusion_anubis_pullout_wrench/wandb/run-20251118_013623-flrqqt58/files/requirements.txt +264 -0
- diffusion_anubis_pullout_wrench/wandb/run-20251118_013623-flrqqt58/files/wandb-metadata.json +98 -0
- diffusion_anubis_pullout_wrench/wandb/run-20251118_013623-flrqqt58/files/wandb-summary.json +1 -0
- diffusion_anubis_pullout_wrench/wandb/run-20251118_013623-flrqqt58/logs/debug-core.log +13 -0
- diffusion_anubis_pullout_wrench/wandb/run-20251118_013623-flrqqt58/logs/debug-internal.log +15 -0
- diffusion_anubis_pullout_wrench/wandb/run-20251118_013623-flrqqt58/logs/debug.log +23 -0
- diffusion_anubis_pullout_wrench/wandb/run-20251118_013623-flrqqt58/run-flrqqt58.wandb +3 -0
- diffusion_anubis_put_into_pot/checkpoints/100000/pretrained_model/config.json +92 -0
- diffusion_anubis_put_into_pot/checkpoints/100000/pretrained_model/model.safetensors +3 -0
- diffusion_anubis_put_into_pot/checkpoints/100000/pretrained_model/train_config.json +202 -0
- diffusion_anubis_put_into_pot/wandb/debug-internal.log +15 -0
- diffusion_anubis_put_into_pot/wandb/debug.log +23 -0
- diffusion_anubis_put_into_pot/wandb/run-20251118_013827-yx7en6s6/files/config.yaml +184 -0
- diffusion_anubis_put_into_pot/wandb/run-20251118_013827-yx7en6s6/files/output.log +518 -0
- diffusion_anubis_put_into_pot/wandb/run-20251118_013827-yx7en6s6/files/requirements.txt +264 -0
- diffusion_anubis_put_into_pot/wandb/run-20251118_013827-yx7en6s6/files/wandb-metadata.json +98 -0
- diffusion_anubis_put_into_pot/wandb/run-20251118_013827-yx7en6s6/files/wandb-summary.json +1 -0
- diffusion_anubis_put_into_pot/wandb/run-20251118_013827-yx7en6s6/logs/debug-core.log +13 -0
- diffusion_anubis_put_into_pot/wandb/run-20251118_013827-yx7en6s6/logs/debug-internal.log +15 -0
- diffusion_anubis_put_into_pot/wandb/run-20251118_013827-yx7en6s6/logs/debug.log +23 -0
- diffusion_anubis_put_into_pot/wandb/run-20251118_013827-yx7en6s6/run-yx7en6s6.wandb +3 -0
.gitattributes
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diffusion_anubis_fold_towel/checkpoints/100000/pretrained_model/config.json
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diffusion_anubis_fold_towel/checkpoints/100000/pretrained_model/train_config.json
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"normalization_mapping": {
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| 72 |
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"VISUAL": "MEAN_STD",
|
| 73 |
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"STATE": "MIN_MAX",
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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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| 80 |
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| 81 |
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| 82 |
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320
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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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320
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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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240,
|
| 98 |
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320
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| 99 |
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|
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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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|
| 111 |
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|
| 114 |
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| 115 |
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"device": "cuda",
|
| 117 |
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|
| 118 |
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|
| 119 |
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|
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|
| 121 |
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|
| 122 |
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| 123 |
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84,
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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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|
| 129 |
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|
| 130 |
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|
| 131 |
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512,
|
| 133 |
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1024,
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| 134 |
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2048
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| 136 |
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|
| 137 |
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|
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|
| 139 |
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|
| 140 |
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|
| 141 |
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|
| 142 |
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|
| 143 |
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|
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|
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|
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|
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|
| 151 |
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|
| 152 |
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0.95,
|
| 153 |
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0.999
|
| 154 |
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],
|
| 155 |
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"optimizer_eps": 1e-08,
|
| 156 |
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"optimizer_weight_decay": 1e-06,
|
| 157 |
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"scheduler_name": "cosine",
|
| 158 |
+
"scheduler_warmup_steps": 500
|
| 159 |
+
},
|
| 160 |
+
"output_dir": "outputs/train/2025-11-18/01-37-50_diffusion",
|
| 161 |
+
"job_name": "diffusion",
|
| 162 |
+
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|
| 163 |
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|
| 164 |
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|
| 165 |
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|
| 166 |
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|
| 167 |
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|
| 168 |
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"log_freq": 200,
|
| 169 |
+
"save_checkpoint": true,
|
| 170 |
+
"save_freq": 20000,
|
| 171 |
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"use_policy_training_preset": true,
|
| 172 |
+
"optimizer": {
|
| 173 |
+
"type": "adam",
|
| 174 |
+
"lr": 0.0001,
|
| 175 |
+
"weight_decay": 1e-06,
|
| 176 |
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"grad_clip_norm": 10.0,
|
| 177 |
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"betas": [
|
| 178 |
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0.95,
|
| 179 |
+
0.999
|
| 180 |
+
],
|
| 181 |
+
"eps": 1e-08
|
| 182 |
+
},
|
| 183 |
+
"scheduler": {
|
| 184 |
+
"type": "diffuser",
|
| 185 |
+
"num_warmup_steps": 500,
|
| 186 |
+
"name": "cosine"
|
| 187 |
+
},
|
| 188 |
+
"eval": {
|
| 189 |
+
"n_episodes": 50,
|
| 190 |
+
"batch_size": 50,
|
| 191 |
+
"use_async_envs": false
|
| 192 |
+
},
|
| 193 |
+
"wandb": {
|
| 194 |
+
"enable": true,
|
| 195 |
+
"disable_artifact": true,
|
| 196 |
+
"project": "lerobot",
|
| 197 |
+
"entity": null,
|
| 198 |
+
"notes": null,
|
| 199 |
+
"run_id": null,
|
| 200 |
+
"mode": null
|
| 201 |
+
}
|
| 202 |
+
}
|
diffusion_anubis_fold_towel/wandb/debug-internal.log
ADDED
|
@@ -0,0 +1,15 @@
|
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|
|
|
|
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|
|
|
|
|
|
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|
|
|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{"time":"2025-11-18T01:37:52.45738267+09:00","level":"INFO","msg":"stream: starting","core version":"0.19.9","symlink path":"outputs/train/2025-11-18/01-37-50_diffusion/wandb/run-20251118_013752-9jmkckoo/logs/debug-core.log"}
|
| 2 |
+
{"time":"2025-11-18T01:37:52.767747172+09:00","level":"INFO","msg":"created new stream","id":"9jmkckoo"}
|
| 3 |
+
{"time":"2025-11-18T01:37:52.767782145+09:00","level":"INFO","msg":"stream: started","id":"9jmkckoo"}
|
| 4 |
+
{"time":"2025-11-18T01:37:52.768509524+09:00","level":"INFO","msg":"handler: started","stream_id":"9jmkckoo"}
|
| 5 |
+
{"time":"2025-11-18T01:37:52.768527652+09:00","level":"INFO","msg":"writer: Do: started","stream_id":"9jmkckoo"}
|
| 6 |
+
{"time":"2025-11-18T01:37:52.768556525+09:00","level":"INFO","msg":"sender: started","stream_id":"9jmkckoo"}
|
| 7 |
+
{"time":"2025-11-18T01:37:54.252097273+09:00","level":"INFO","msg":"Starting system monitor"}
|
| 8 |
+
{"time":"2025-11-18T04:15:04.374330289+09:00","level":"INFO","msg":"stream: closing","id":"9jmkckoo"}
|
| 9 |
+
{"time":"2025-11-18T04:15:04.374406914+09:00","level":"INFO","msg":"Stopping system monitor"}
|
| 10 |
+
{"time":"2025-11-18T04:15:04.380827613+09:00","level":"INFO","msg":"Stopped system monitor"}
|
| 11 |
+
{"time":"2025-11-18T04:15:05.488452567+09:00","level":"INFO","msg":"fileTransfer: Close: file transfer manager closed"}
|
| 12 |
+
{"time":"2025-11-18T04:15:05.827001228+09:00","level":"INFO","msg":"handler: closed","stream_id":"9jmkckoo"}
|
| 13 |
+
{"time":"2025-11-18T04:15:05.827041618+09:00","level":"INFO","msg":"writer: Close: closed","stream_id":"9jmkckoo"}
|
| 14 |
+
{"time":"2025-11-18T04:15:05.827065124+09:00","level":"INFO","msg":"sender: closed","stream_id":"9jmkckoo"}
|
| 15 |
+
{"time":"2025-11-18T04:15:05.827656319+09:00","level":"INFO","msg":"stream: closed","id":"9jmkckoo"}
|
diffusion_anubis_fold_towel/wandb/debug.log
ADDED
|
@@ -0,0 +1,23 @@
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|
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|
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|
|
|
| 1 |
+
2025-11-18 01:37:52,447 INFO MainThread:2405445 [wandb_setup.py:_flush():67] Current SDK version is 0.19.9
|
| 2 |
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2025-11-18 01:37:52,447 INFO MainThread:2405445 [wandb_setup.py:_flush():67] Configure stats pid to 2405445
|
| 3 |
+
2025-11-18 01:37:52,447 INFO MainThread:2405445 [wandb_setup.py:_flush():67] Loading settings from /home/euijinrnd/.config/wandb/settings
|
| 4 |
+
2025-11-18 01:37:52,447 INFO MainThread:2405445 [wandb_setup.py:_flush():67] Loading settings from /home/euijinrnd/workspace/lerobot/wandb/settings
|
| 5 |
+
2025-11-18 01:37:52,447 INFO MainThread:2405445 [wandb_setup.py:_flush():67] Loading settings from environment variables
|
| 6 |
+
2025-11-18 01:37:52,447 INFO MainThread:2405445 [wandb_init.py:setup_run_log_directory():662] Logging user logs to outputs/train/2025-11-18/01-37-50_diffusion/wandb/run-20251118_013752-9jmkckoo/logs/debug.log
|
| 7 |
+
2025-11-18 01:37:52,447 INFO MainThread:2405445 [wandb_init.py:setup_run_log_directory():663] Logging internal logs to outputs/train/2025-11-18/01-37-50_diffusion/wandb/run-20251118_013752-9jmkckoo/logs/debug-internal.log
|
| 8 |
+
2025-11-18 01:37:52,448 INFO MainThread:2405445 [wandb_init.py:init():781] calling init triggers
|
| 9 |
+
2025-11-18 01:37:52,448 INFO MainThread:2405445 [wandb_init.py:init():786] wandb.init called with sweep_config: {}
|
| 10 |
+
config: {'dataset': {'repo_id': 'anubis_fold_towel__lerobot', 'root': '/data1/euijinrnd/hf_home_euijin/lerobot/lerobot/anubis_fold_towel__lerobot', 'episodes': None, 'image_transforms': {'enable': False, 'max_num_transforms': 3, 'random_order': False, 'tfs': {'brightness': {'weight': 1.0, 'type': 'ColorJitter', 'kwargs': {'brightness': [0.8, 1.2]}}, 'contrast': {'weight': 1.0, 'type': 'ColorJitter', 'kwargs': {'contrast': [0.8, 1.2]}}, 'saturation': {'weight': 1.0, 'type': 'ColorJitter', 'kwargs': {'saturation': [0.5, 1.5]}}, 'hue': {'weight': 1.0, 'type': 'ColorJitter', 'kwargs': {'hue': [-0.05, 0.05]}}, 'sharpness': {'weight': 1.0, 'type': 'SharpnessJitter', 'kwargs': {'sharpness': [0.5, 1.5]}}}}, 'revision': None, 'use_imagenet_stats': True, 'video_backend': 'torchcodec'}, 'env': None, 'policy': {'type': 'diffusion', 'n_obs_steps': 2, 'normalization_mapping': {'VISUAL': <NormalizationMode.MEAN_STD: 'MEAN_STD'>, 'STATE': <NormalizationMode.MIN_MAX: 'MIN_MAX'>, 'ACTION': <NormalizationMode.MIN_MAX: 'MIN_MAX'>}, 'input_features': {}, 'output_features': {}, 'device': 'cuda', 'use_amp': False, 'horizon': 16, 'n_action_steps': 8, 'drop_n_last_frames': 7, 'vision_backbone': 'resnet18', 'crop_shape': [84, 84], 'crop_is_random': True, 'pretrained_backbone_weights': None, 'use_group_norm': True, 'spatial_softmax_num_keypoints': 32, 'use_separate_rgb_encoder_per_camera': False, 'down_dims': [512, 1024, 2048], 'kernel_size': 5, 'n_groups': 8, 'diffusion_step_embed_dim': 128, 'use_film_scale_modulation': True, 'noise_scheduler_type': 'DDPM', 'num_train_timesteps': 100, 'beta_schedule': 'squaredcos_cap_v2', 'beta_start': 0.0001, 'beta_end': 0.02, 'prediction_type': 'epsilon', 'clip_sample': True, 'clip_sample_range': 1.0, 'num_inference_steps': None, 'do_mask_loss_for_padding': False, 'optimizer_lr': 0.0001, 'optimizer_betas': [0.95, 0.999], 'optimizer_eps': 1e-08, 'optimizer_weight_decay': 1e-06, 'scheduler_name': 'cosine', 'scheduler_warmup_steps': 500}, 'output_dir': 'outputs/train/2025-11-18/01-37-50_diffusion', 'job_name': 'diffusion', 'resume': False, 'seed': 1000, 'num_workers': 2, 'batch_size': 8, 'steps': 100000, 'eval_freq': 20000, 'log_freq': 200, 'save_checkpoint': True, 'save_freq': 20000, 'use_policy_training_preset': True, 'optimizer': {'type': 'adam', 'lr': 0.0001, 'weight_decay': 1e-06, 'grad_clip_norm': 10.0, 'betas': [0.95, 0.999], 'eps': 1e-08}, 'scheduler': {'type': 'diffuser', 'num_warmup_steps': 500, 'name': 'cosine'}, 'eval': {'n_episodes': 50, 'batch_size': 50, 'use_async_envs': False}, 'wandb': {'enable': True, 'disable_artifact': True, 'project': 'lerobot', 'entity': None, 'notes': None, 'run_id': None, 'mode': None}, '_wandb': {}}
|
| 11 |
+
2025-11-18 01:37:52,448 INFO MainThread:2405445 [wandb_init.py:init():809] starting backend
|
| 12 |
+
2025-11-18 01:37:52,448 INFO MainThread:2405445 [wandb_init.py:init():813] sending inform_init request
|
| 13 |
+
2025-11-18 01:37:52,451 INFO MainThread:2405445 [backend.py:_multiprocessing_setup():101] multiprocessing start_methods=fork,spawn,forkserver, using: spawn
|
| 14 |
+
2025-11-18 01:37:52,451 INFO MainThread:2405445 [wandb_init.py:init():823] backend started and connected
|
| 15 |
+
2025-11-18 01:37:52,453 INFO MainThread:2405445 [wandb_init.py:init():915] updated telemetry
|
| 16 |
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2025-11-18 01:37:52,597 INFO MainThread:2405445 [wandb_init.py:init():939] communicating run to backend with 90.0 second timeout
|
| 17 |
+
2025-11-18 01:37:54,207 INFO MainThread:2405445 [wandb_init.py:init():1014] starting run threads in backend
|
| 18 |
+
2025-11-18 01:37:55,209 INFO MainThread:2405445 [wandb_run.py:_console_start():2454] atexit reg
|
| 19 |
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2025-11-18 01:37:55,210 INFO MainThread:2405445 [wandb_run.py:_redirect():2306] redirect: wrap_raw
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| 20 |
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2025-11-18 01:37:55,210 INFO MainThread:2405445 [wandb_run.py:_redirect():2371] Wrapping output streams.
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| 21 |
+
2025-11-18 01:37:55,210 INFO MainThread:2405445 [wandb_run.py:_redirect():2394] Redirects installed.
|
| 22 |
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2025-11-18 01:37:55,222 INFO MainThread:2405445 [wandb_init.py:init():1056] run started, returning control to user process
|
| 23 |
+
2025-11-18 04:15:04,361 INFO MsgRouterThr:2405445 [mailbox.py:close():129] [no run ID] Closing mailbox, abandoning 1 handles.
|
diffusion_anubis_fold_towel/wandb/run-20251118_013752-9jmkckoo/files/config.yaml
ADDED
|
@@ -0,0 +1,184 @@
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|
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|
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|
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|
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|
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|
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|
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|
|
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|
|
|
|
|
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|
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|
|
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|
|
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|
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|
|
|
|
|
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|
|
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|
|
| 1 |
+
_wandb:
|
| 2 |
+
value:
|
| 3 |
+
cli_version: 0.19.9
|
| 4 |
+
m: []
|
| 5 |
+
python_version: 3.10.17
|
| 6 |
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t:
|
| 7 |
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"1":
|
| 8 |
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- 1
|
| 9 |
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- 41
|
| 10 |
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- 49
|
| 11 |
+
- 51
|
| 12 |
+
- 55
|
| 13 |
+
"2":
|
| 14 |
+
- 1
|
| 15 |
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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noise_scheduler_type: DDPM
|
| 136 |
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normalization_mapping:
|
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ACTION: MIN_MAX
|
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STATE: MIN_MAX
|
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|
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|
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|
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optimizer_lr: 0.0001
|
| 147 |
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optimizer_weight_decay: 1e-06
|
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|
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|
| 150 |
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|
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|
| 152 |
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|
| 153 |
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|
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|
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|
| 156 |
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|
| 157 |
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|
| 158 |
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|
| 159 |
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|
| 160 |
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|
| 161 |
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|
| 162 |
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|
| 163 |
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|
| 164 |
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|
| 165 |
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|
| 166 |
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|
| 167 |
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|
| 168 |
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|
| 169 |
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|
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|
| 171 |
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|
| 172 |
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|
| 173 |
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|
| 174 |
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|
| 175 |
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|
| 176 |
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|
| 177 |
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|
| 178 |
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|
| 179 |
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|
| 180 |
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|
| 181 |
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|
| 182 |
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notes: null
|
| 183 |
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project: lerobot
|
| 184 |
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run_id: null
|
diffusion_anubis_fold_towel/wandb/run-20251118_013752-9jmkckoo/files/output.log
ADDED
|
@@ -0,0 +1,518 @@
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|
| 1 |
+
Logs will be synced with wandb.
|
| 2 |
+
INFO 2025-11-18 01:37:55 ndb_utils.py:96 Track this run --> https://wandb.ai/jinprelude/lerobot/runs/9jmkckoo
|
| 3 |
+
INFO 2025-11-18 01:37:55 ts/train.py:127 Creating dataset
|
| 4 |
+
INFO 2025-11-18 01:37:57 ts/train.py:138 Creating policy
|
| 5 |
+
INFO 2025-11-18 01:37:59 ts/train.py:144 Creating optimizer and scheduler
|
| 6 |
+
INFO 2025-11-18 01:37:59 ts/train.py:156 Output dir: outputs/train/2025-11-18/01-37-50_diffusion
|
| 7 |
+
INFO 2025-11-18 01:37:59 ts/train.py:159 cfg.steps=100000 (100K)
|
| 8 |
+
INFO 2025-11-18 01:37:59 ts/train.py:160 dataset.num_frames=34022 (34K)
|
| 9 |
+
INFO 2025-11-18 01:37:59 ts/train.py:161 dataset.num_episodes=50
|
| 10 |
+
INFO 2025-11-18 01:37:59 ts/train.py:162 num_learnable_params=271145780 (271M)
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INFO 2025-11-18 01:37:59 ts/train.py:163 num_total_params=271145918 (271M)
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INFO 2025-11-18 01:37:59 ts/train.py:202 Start offline training on a fixed dataset
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INFO 2025-11-18 01:38:19 ts/train.py:232 step:200 smpl:2K ep:2 epch:0.05 loss:0.996 grdn:2.591 lr:2.0e-05 updt_s:0.071 data_s:0.030
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INFO 2025-11-18 01:38:38 ts/train.py:232 step:400 smpl:3K ep:5 epch:0.09 loss:0.400 grdn:2.943 lr:6.0e-05 updt_s:0.065 data_s:0.026
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INFO 2025-11-18 01:38:56 ts/train.py:232 step:600 smpl:5K ep:7 epch:0.14 loss:0.195 grdn:1.758 lr:9.5e-05 updt_s:0.065 data_s:0.027
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INFO 2025-11-18 01:39:15 ts/train.py:232 step:800 smpl:6K ep:9 epch:0.19 loss:0.132 grdn:1.248 lr:1.0e-04 updt_s:0.065 data_s:0.028
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INFO 2025-11-18 01:39:33 ts/train.py:232 step:1K smpl:8K ep:12 epch:0.24 loss:0.108 grdn:1.054 lr:1.0e-04 updt_s:0.065 data_s:0.025
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| 18 |
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INFO 2025-11-18 01:39:52 ts/train.py:232 step:1K smpl:10K ep:14 epch:0.28 loss:0.099 grdn:0.970 lr:1.0e-04 updt_s:0.064 data_s:0.027
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INFO 2025-11-18 01:40:09 ts/train.py:232 step:1K smpl:11K ep:16 epch:0.33 loss:0.088 grdn:0.848 lr:1.0e-04 updt_s:0.064 data_s:0.023
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INFO 2025-11-18 01:40:27 ts/train.py:232 step:2K smpl:13K ep:19 epch:0.38 loss:0.074 grdn:0.718 lr:1.0e-04 updt_s:0.065 data_s:0.023
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INFO 2025-11-18 01:40:44 ts/train.py:232 step:2K smpl:14K ep:21 epch:0.42 loss:0.072 grdn:0.705 lr:1.0e-04 updt_s:0.065 data_s:0.022
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INFO 2025-11-18 01:41:02 ts/train.py:232 step:2K smpl:16K ep:24 epch:0.47 loss:0.066 grdn:0.637 lr:1.0e-04 updt_s:0.065 data_s:0.022
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INFO 2025-11-18 01:41:19 ts/train.py:232 step:2K smpl:18K ep:26 epch:0.52 loss:0.068 grdn:0.643 lr:1.0e-04 updt_s:0.065 data_s:0.022
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INFO 2025-11-18 01:41:37 ts/train.py:232 step:2K smpl:19K ep:28 epch:0.56 loss:0.070 grdn:0.626 lr:1.0e-04 updt_s:0.065 data_s:0.023
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| 25 |
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INFO 2025-11-18 01:41:55 ts/train.py:232 step:3K smpl:21K ep:31 epch:0.61 loss:0.064 grdn:0.591 lr:1.0e-04 updt_s:0.065 data_s:0.023
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INFO 2025-11-18 01:42:12 ts/train.py:232 step:3K smpl:22K ep:33 epch:0.66 loss:0.057 grdn:0.546 lr:1.0e-04 updt_s:0.065 data_s:0.022
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INFO 2025-11-18 01:42:29 ts/train.py:232 step:3K smpl:24K ep:35 epch:0.71 loss:0.056 grdn:0.529 lr:1.0e-04 updt_s:0.065 data_s:0.021
|
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INFO 2025-11-18 01:42:48 ts/train.py:232 step:3K smpl:26K ep:38 epch:0.75 loss:0.056 grdn:0.524 lr:1.0e-04 updt_s:0.066 data_s:0.024
|
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INFO 2025-11-18 01:43:05 ts/train.py:232 step:3K smpl:27K ep:40 epch:0.80 loss:0.056 grdn:0.529 lr:1.0e-04 updt_s:0.066 data_s:0.023
|
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INFO 2025-11-18 01:43:23 ts/train.py:232 step:4K smpl:29K ep:42 epch:0.85 loss:0.053 grdn:0.492 lr:1.0e-04 updt_s:0.065 data_s:0.022
|
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INFO 2025-11-18 01:43:40 ts/train.py:232 step:4K smpl:30K ep:45 epch:0.89 loss:0.053 grdn:0.489 lr:1.0e-04 updt_s:0.065 data_s:0.022
|
| 32 |
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INFO 2025-11-18 01:43:59 ts/train.py:232 step:4K smpl:32K ep:47 epch:0.94 loss:0.051 grdn:0.468 lr:1.0e-04 updt_s:0.065 data_s:0.025
|
| 33 |
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INFO 2025-11-18 01:44:17 ts/train.py:232 step:4K smpl:34K ep:49 epch:0.99 loss:0.047 grdn:0.440 lr:1.0e-04 updt_s:0.065 data_s:0.024
|
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INFO 2025-11-18 01:44:37 ts/train.py:232 step:4K smpl:35K ep:52 epch:1.03 loss:0.048 grdn:0.440 lr:1.0e-04 updt_s:0.066 data_s:0.035
|
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INFO 2025-11-18 01:44:56 ts/train.py:232 step:5K smpl:37K ep:54 epch:1.08 loss:0.048 grdn:0.429 lr:1.0e-04 updt_s:0.066 data_s:0.030
|
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INFO 2025-11-18 01:45:16 ts/train.py:232 step:5K smpl:38K ep:56 epch:1.13 loss:0.050 grdn:0.447 lr:1.0e-04 updt_s:0.065 data_s:0.031
|
| 37 |
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INFO 2025-11-18 01:45:35 ts/train.py:232 step:5K smpl:40K ep:59 epch:1.18 loss:0.046 grdn:0.406 lr:1.0e-04 updt_s:0.066 data_s:0.031
|
| 38 |
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INFO 2025-11-18 01:45:54 ts/train.py:232 step:5K smpl:42K ep:61 epch:1.22 loss:0.046 grdn:0.406 lr:9.9e-05 updt_s:0.066 data_s:0.031
|
| 39 |
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INFO 2025-11-18 01:46:14 ts/train.py:232 step:5K smpl:43K ep:63 epch:1.27 loss:0.046 grdn:0.403 lr:9.9e-05 updt_s:0.066 data_s:0.031
|
| 40 |
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INFO 2025-11-18 01:46:36 ts/train.py:232 step:6K smpl:45K ep:66 epch:1.32 loss:0.045 grdn:0.391 lr:9.9e-05 updt_s:0.066 data_s:0.046
|
| 41 |
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INFO 2025-11-18 01:46:55 ts/train.py:232 step:6K smpl:46K ep:68 epch:1.36 loss:0.047 grdn:0.388 lr:9.9e-05 updt_s:0.066 data_s:0.027
|
| 42 |
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INFO 2025-11-18 01:47:14 ts/train.py:232 step:6K smpl:48K ep:71 epch:1.41 loss:0.044 grdn:0.373 lr:9.9e-05 updt_s:0.066 data_s:0.028
|
| 43 |
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INFO 2025-11-18 01:47:33 ts/train.py:232 step:6K smpl:50K ep:73 epch:1.46 loss:0.039 grdn:0.355 lr:9.9e-05 updt_s:0.066 data_s:0.026
|
| 44 |
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INFO 2025-11-18 01:47:51 ts/train.py:232 step:6K smpl:51K ep:75 epch:1.50 loss:0.046 grdn:0.383 lr:9.9e-05 updt_s:0.066 data_s:0.028
|
| 45 |
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INFO 2025-11-18 01:48:11 ts/train.py:232 step:7K smpl:53K ep:78 epch:1.55 loss:0.042 grdn:0.354 lr:9.9e-05 updt_s:0.066 data_s:0.030
|
| 46 |
+
INFO 2025-11-18 01:48:29 ts/train.py:232 step:7K smpl:54K ep:80 epch:1.60 loss:0.042 grdn:0.359 lr:9.9e-05 updt_s:0.066 data_s:0.026
|
| 47 |
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INFO 2025-11-18 01:48:48 ts/train.py:232 step:7K smpl:56K ep:82 epch:1.65 loss:0.041 grdn:0.354 lr:9.9e-05 updt_s:0.066 data_s:0.027
|
| 48 |
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INFO 2025-11-18 01:49:07 ts/train.py:232 step:7K smpl:58K ep:85 epch:1.69 loss:0.043 grdn:0.351 lr:9.9e-05 updt_s:0.066 data_s:0.027
|
| 49 |
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INFO 2025-11-18 01:49:26 ts/train.py:232 step:7K smpl:59K ep:87 epch:1.74 loss:0.042 grdn:0.342 lr:9.9e-05 updt_s:0.066 data_s:0.030
|
| 50 |
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INFO 2025-11-18 01:49:44 ts/train.py:232 step:8K smpl:61K ep:89 epch:1.79 loss:0.041 grdn:0.329 lr:9.9e-05 updt_s:0.065 data_s:0.026
|
| 51 |
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INFO 2025-11-18 01:50:03 ts/train.py:232 step:8K smpl:62K ep:92 epch:1.83 loss:0.036 grdn:0.307 lr:9.9e-05 updt_s:0.066 data_s:0.025
|
| 52 |
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INFO 2025-11-18 01:50:21 ts/train.py:232 step:8K smpl:64K ep:94 epch:1.88 loss:0.042 grdn:0.342 lr:9.9e-05 updt_s:0.065 data_s:0.028
|
| 53 |
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INFO 2025-11-18 01:50:40 ts/train.py:232 step:8K smpl:66K ep:96 epch:1.93 loss:0.038 grdn:0.311 lr:9.9e-05 updt_s:0.066 data_s:0.027
|
| 54 |
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INFO 2025-11-18 01:50:59 ts/train.py:232 step:8K smpl:67K ep:99 epch:1.98 loss:0.042 grdn:0.322 lr:9.8e-05 updt_s:0.065 data_s:0.027
|
| 55 |
+
INFO 2025-11-18 01:51:18 ts/train.py:232 step:9K smpl:69K ep:101 epch:2.02 loss:0.041 grdn:0.322 lr:9.8e-05 updt_s:0.066 data_s:0.031
|
| 56 |
+
INFO 2025-11-18 01:51:36 ts/train.py:232 step:9K smpl:70K ep:103 epch:2.07 loss:0.041 grdn:0.323 lr:9.8e-05 updt_s:0.067 data_s:0.022
|
| 57 |
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INFO 2025-11-18 01:51:54 ts/train.py:232 step:9K smpl:72K ep:106 epch:2.12 loss:0.037 grdn:0.293 lr:9.8e-05 updt_s:0.066 data_s:0.025
|
| 58 |
+
INFO 2025-11-18 01:52:12 ts/train.py:232 step:9K smpl:74K ep:108 epch:2.16 loss:0.037 grdn:0.296 lr:9.8e-05 updt_s:0.067 data_s:0.023
|
| 59 |
+
INFO 2025-11-18 01:52:30 ts/train.py:232 step:9K smpl:75K ep:111 epch:2.21 loss:0.037 grdn:0.296 lr:9.8e-05 updt_s:0.066 data_s:0.023
|
| 60 |
+
INFO 2025-11-18 01:52:48 ts/train.py:232 step:10K smpl:77K ep:113 epch:2.26 loss:0.038 grdn:0.303 lr:9.8e-05 updt_s:0.066 data_s:0.022
|
| 61 |
+
INFO 2025-11-18 01:53:06 ts/train.py:232 step:10K smpl:78K ep:115 epch:2.30 loss:0.038 grdn:0.300 lr:9.8e-05 updt_s:0.066 data_s:0.023
|
| 62 |
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INFO 2025-11-18 01:53:25 ts/train.py:232 step:10K smpl:80K ep:118 epch:2.35 loss:0.038 grdn:0.294 lr:9.8e-05 updt_s:0.066 data_s:0.030
|
| 63 |
+
INFO 2025-11-18 01:53:44 ts/train.py:232 step:10K smpl:82K ep:120 epch:2.40 loss:0.038 grdn:0.297 lr:9.8e-05 updt_s:0.066 data_s:0.029
|
| 64 |
+
INFO 2025-11-18 01:54:03 ts/train.py:232 step:10K smpl:83K ep:122 epch:2.45 loss:0.035 grdn:0.280 lr:9.8e-05 updt_s:0.066 data_s:0.028
|
| 65 |
+
INFO 2025-11-18 01:54:22 ts/train.py:232 step:11K smpl:85K ep:125 epch:2.49 loss:0.035 grdn:0.274 lr:9.8e-05 updt_s:0.066 data_s:0.027
|
| 66 |
+
INFO 2025-11-18 01:54:41 ts/train.py:232 step:11K smpl:86K ep:127 epch:2.54 loss:0.034 grdn:0.280 lr:9.7e-05 updt_s:0.067 data_s:0.028
|
| 67 |
+
INFO 2025-11-18 01:55:00 ts/train.py:232 step:11K smpl:88K ep:129 epch:2.59 loss:0.039 grdn:0.298 lr:9.7e-05 updt_s:0.067 data_s:0.026
|
| 68 |
+
INFO 2025-11-18 01:55:18 ts/train.py:232 step:11K smpl:90K ep:132 epch:2.63 loss:0.038 grdn:0.288 lr:9.7e-05 updt_s:0.066 data_s:0.027
|
| 69 |
+
INFO 2025-11-18 01:55:38 ts/train.py:232 step:11K smpl:91K ep:134 epch:2.68 loss:0.038 grdn:0.288 lr:9.7e-05 updt_s:0.067 data_s:0.031
|
| 70 |
+
INFO 2025-11-18 01:55:57 ts/train.py:232 step:12K smpl:93K ep:136 epch:2.73 loss:0.037 grdn:0.286 lr:9.7e-05 updt_s:0.066 data_s:0.032
|
| 71 |
+
INFO 2025-11-18 01:56:16 ts/train.py:232 step:12K smpl:94K ep:139 epch:2.77 loss:0.034 grdn:0.271 lr:9.7e-05 updt_s:0.066 data_s:0.026
|
| 72 |
+
INFO 2025-11-18 01:56:38 ts/train.py:232 step:12K smpl:96K ep:141 epch:2.82 loss:0.034 grdn:0.273 lr:9.7e-05 updt_s:0.066 data_s:0.041
|
| 73 |
+
INFO 2025-11-18 01:56:57 ts/train.py:232 step:12K smpl:98K ep:143 epch:2.87 loss:0.034 grdn:0.278 lr:9.7e-05 updt_s:0.066 data_s:0.031
|
| 74 |
+
INFO 2025-11-18 01:57:16 ts/train.py:232 step:12K smpl:99K ep:146 epch:2.92 loss:0.036 grdn:0.283 lr:9.7e-05 updt_s:0.067 data_s:0.027
|
| 75 |
+
INFO 2025-11-18 01:57:35 ts/train.py:232 step:13K smpl:101K ep:148 epch:2.96 loss:0.034 grdn:0.271 lr:9.6e-05 updt_s:0.066 data_s:0.028
|
| 76 |
+
INFO 2025-11-18 01:57:54 ts/train.py:232 step:13K smpl:102K ep:150 epch:3.01 loss:0.032 grdn:0.261 lr:9.6e-05 updt_s:0.066 data_s:0.031
|
| 77 |
+
INFO 2025-11-18 01:58:13 ts/train.py:232 step:13K smpl:104K ep:153 epch:3.06 loss:0.034 grdn:0.270 lr:9.6e-05 updt_s:0.066 data_s:0.028
|
| 78 |
+
INFO 2025-11-18 01:58:32 ts/train.py:232 step:13K smpl:106K ep:155 epch:3.10 loss:0.037 grdn:0.277 lr:9.6e-05 updt_s:0.066 data_s:0.029
|
| 79 |
+
INFO 2025-11-18 01:58:51 ts/train.py:232 step:13K smpl:107K ep:158 epch:3.15 loss:0.036 grdn:0.276 lr:9.6e-05 updt_s:0.066 data_s:0.029
|
| 80 |
+
INFO 2025-11-18 01:59:10 ts/train.py:232 step:14K smpl:109K ep:160 epch:3.20 loss:0.033 grdn:0.260 lr:9.6e-05 updt_s:0.067 data_s:0.028
|
| 81 |
+
INFO 2025-11-18 01:59:30 ts/train.py:232 step:14K smpl:110K ep:162 epch:3.24 loss:0.033 grdn:0.264 lr:9.6e-05 updt_s:0.066 data_s:0.030
|
| 82 |
+
INFO 2025-11-18 01:59:48 ts/train.py:232 step:14K smpl:112K ep:165 epch:3.29 loss:0.033 grdn:0.260 lr:9.6e-05 updt_s:0.065 data_s:0.025
|
| 83 |
+
INFO 2025-11-18 02:00:06 ts/train.py:232 step:14K smpl:114K ep:167 epch:3.34 loss:0.035 grdn:0.272 lr:9.5e-05 updt_s:0.065 data_s:0.026
|
| 84 |
+
INFO 2025-11-18 02:00:25 ts/train.py:232 step:14K smpl:115K ep:169 epch:3.39 loss:0.033 grdn:0.265 lr:9.5e-05 updt_s:0.066 data_s:0.028
|
| 85 |
+
INFO 2025-11-18 02:00:44 ts/train.py:232 step:15K smpl:117K ep:172 epch:3.43 loss:0.030 grdn:0.252 lr:9.5e-05 updt_s:0.066 data_s:0.028
|
| 86 |
+
INFO 2025-11-18 02:01:03 ts/train.py:232 step:15K smpl:118K ep:174 epch:3.48 loss:0.031 grdn:0.253 lr:9.5e-05 updt_s:0.066 data_s:0.028
|
| 87 |
+
INFO 2025-11-18 02:01:22 ts/train.py:232 step:15K smpl:120K ep:176 epch:3.53 loss:0.031 grdn:0.251 lr:9.5e-05 updt_s:0.066 data_s:0.028
|
| 88 |
+
INFO 2025-11-18 02:01:41 ts/train.py:232 step:15K smpl:122K ep:179 epch:3.57 loss:0.032 grdn:0.259 lr:9.5e-05 updt_s:0.066 data_s:0.029
|
| 89 |
+
INFO 2025-11-18 02:01:59 ts/train.py:232 step:15K smpl:123K ep:181 epch:3.62 loss:0.033 grdn:0.264 lr:9.5e-05 updt_s:0.066 data_s:0.028
|
| 90 |
+
INFO 2025-11-18 02:02:18 ts/train.py:232 step:16K smpl:125K ep:183 epch:3.67 loss:0.036 grdn:0.275 lr:9.4e-05 updt_s:0.066 data_s:0.027
|
| 91 |
+
INFO 2025-11-18 02:02:37 ts/train.py:232 step:16K smpl:126K ep:186 epch:3.72 loss:0.030 grdn:0.250 lr:9.4e-05 updt_s:0.067 data_s:0.028
|
| 92 |
+
INFO 2025-11-18 02:02:57 ts/train.py:232 step:16K smpl:128K ep:188 epch:3.76 loss:0.034 grdn:0.273 lr:9.4e-05 updt_s:0.067 data_s:0.029
|
| 93 |
+
INFO 2025-11-18 02:03:15 ts/train.py:232 step:16K smpl:130K ep:190 epch:3.81 loss:0.032 grdn:0.259 lr:9.4e-05 updt_s:0.066 data_s:0.027
|
| 94 |
+
INFO 2025-11-18 02:03:34 ts/train.py:232 step:16K smpl:131K ep:193 epch:3.86 loss:0.032 grdn:0.261 lr:9.4e-05 updt_s:0.066 data_s:0.028
|
| 95 |
+
INFO 2025-11-18 02:03:53 ts/train.py:232 step:17K smpl:133K ep:195 epch:3.90 loss:0.032 grdn:0.265 lr:9.4e-05 updt_s:0.066 data_s:0.030
|
| 96 |
+
INFO 2025-11-18 02:04:13 ts/train.py:232 step:17K smpl:134K ep:198 epch:3.95 loss:0.035 grdn:0.280 lr:9.4e-05 updt_s:0.066 data_s:0.031
|
| 97 |
+
INFO 2025-11-18 02:04:33 ts/train.py:232 step:17K smpl:136K ep:200 epch:4.00 loss:0.029 grdn:0.251 lr:9.3e-05 updt_s:0.066 data_s:0.032
|
| 98 |
+
INFO 2025-11-18 02:04:53 ts/train.py:232 step:17K smpl:138K ep:202 epch:4.04 loss:0.032 grdn:0.267 lr:9.3e-05 updt_s:0.067 data_s:0.035
|
| 99 |
+
INFO 2025-11-18 02:05:13 ts/train.py:232 step:17K smpl:139K ep:205 epch:4.09 loss:0.030 grdn:0.261 lr:9.3e-05 updt_s:0.066 data_s:0.031
|
| 100 |
+
INFO 2025-11-18 02:05:32 ts/train.py:232 step:18K smpl:141K ep:207 epch:4.14 loss:0.029 grdn:0.245 lr:9.3e-05 updt_s:0.066 data_s:0.031
|
| 101 |
+
INFO 2025-11-18 02:05:52 ts/train.py:232 step:18K smpl:142K ep:209 epch:4.19 loss:0.029 grdn:0.250 lr:9.3e-05 updt_s:0.065 data_s:0.033
|
| 102 |
+
INFO 2025-11-18 02:06:12 ts/train.py:232 step:18K smpl:144K ep:212 epch:4.23 loss:0.035 grdn:0.282 lr:9.3e-05 updt_s:0.066 data_s:0.032
|
| 103 |
+
INFO 2025-11-18 02:06:32 ts/train.py:232 step:18K smpl:146K ep:214 epch:4.28 loss:0.031 grdn:0.261 lr:9.2e-05 updt_s:0.066 data_s:0.032
|
| 104 |
+
INFO 2025-11-18 02:06:54 ts/train.py:232 step:18K smpl:147K ep:216 epch:4.33 loss:0.032 grdn:0.264 lr:9.2e-05 updt_s:0.065 data_s:0.045
|
| 105 |
+
INFO 2025-11-18 02:07:13 ts/train.py:232 step:19K smpl:149K ep:219 epch:4.37 loss:0.032 grdn:0.262 lr:9.2e-05 updt_s:0.066 data_s:0.029
|
| 106 |
+
INFO 2025-11-18 02:07:32 ts/train.py:232 step:19K smpl:150K ep:221 epch:4.42 loss:0.030 grdn:0.256 lr:9.2e-05 updt_s:0.066 data_s:0.029
|
| 107 |
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INFO 2025-11-18 02:07:51 ts/train.py:232 step:19K smpl:152K ep:223 epch:4.47 loss:0.032 grdn:0.263 lr:9.2e-05 updt_s:0.065 data_s:0.030
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INFO 2025-11-18 02:08:10 ts/train.py:232 step:19K smpl:154K ep:226 epch:4.51 loss:0.029 grdn:0.253 lr:9.2e-05 updt_s:0.065 data_s:0.027
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INFO 2025-11-18 02:08:28 ts/train.py:232 step:19K smpl:155K ep:228 epch:4.56 loss:0.029 grdn:0.254 lr:9.1e-05 updt_s:0.066 data_s:0.027
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INFO 2025-11-18 02:08:48 ts/train.py:232 step:20K smpl:157K ep:230 epch:4.61 loss:0.029 grdn:0.249 lr:9.1e-05 updt_s:0.065 data_s:0.030
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INFO 2025-11-18 02:09:06 ts/train.py:232 step:20K smpl:158K ep:233 epch:4.66 loss:0.028 grdn:0.245 lr:9.1e-05 updt_s:0.066 data_s:0.026
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| 112 |
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INFO 2025-11-18 02:09:25 ts/train.py:232 step:20K smpl:160K ep:235 epch:4.70 loss:0.031 grdn:0.264 lr:9.1e-05 updt_s:0.065 data_s:0.030
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| 113 |
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INFO 2025-11-18 02:09:25 ts/train.py:241 Checkpoint policy after step 20000
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INFO 2025-11-18 02:10:19 ts/train.py:232 step:20K smpl:162K ep:237 epch:4.75 loss:0.033 grdn:0.270 lr:9.1e-05 updt_s:0.065 data_s:0.026
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| 115 |
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INFO 2025-11-18 02:10:37 ts/train.py:232 step:20K smpl:163K ep:240 epch:4.80 loss:0.028 grdn:0.248 lr:9.1e-05 updt_s:0.065 data_s:0.027
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| 116 |
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INFO 2025-11-18 02:10:57 ts/train.py:232 step:21K smpl:165K ep:242 epch:4.84 loss:0.029 grdn:0.254 lr:9.0e-05 updt_s:0.066 data_s:0.030
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| 117 |
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INFO 2025-11-18 02:11:16 ts/train.py:232 step:21K smpl:166K ep:245 epch:4.89 loss:0.029 grdn:0.253 lr:9.0e-05 updt_s:0.066 data_s:0.029
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| 118 |
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INFO 2025-11-18 02:11:35 ts/train.py:232 step:21K smpl:168K ep:247 epch:4.94 loss:0.029 grdn:0.252 lr:9.0e-05 updt_s:0.066 data_s:0.029
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| 119 |
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INFO 2025-11-18 02:11:55 ts/train.py:232 step:21K smpl:170K ep:249 epch:4.99 loss:0.028 grdn:0.257 lr:9.0e-05 updt_s:0.068 data_s:0.033
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| 120 |
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INFO 2025-11-18 02:12:15 ts/train.py:232 step:21K smpl:171K ep:252 epch:5.03 loss:0.028 grdn:0.249 lr:9.0e-05 updt_s:0.066 data_s:0.032
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INFO 2025-11-18 02:12:35 ts/train.py:232 step:22K smpl:173K ep:254 epch:5.08 loss:0.029 grdn:0.261 lr:8.9e-05 updt_s:0.065 data_s:0.033
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INFO 2025-11-18 02:12:54 ts/train.py:232 step:22K smpl:174K ep:256 epch:5.13 loss:0.029 grdn:0.258 lr:8.9e-05 updt_s:0.066 data_s:0.031
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INFO 2025-11-18 02:13:14 ts/train.py:232 step:22K smpl:176K ep:259 epch:5.17 loss:0.029 grdn:0.256 lr:8.9e-05 updt_s:0.067 data_s:0.033
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INFO 2025-11-18 02:13:34 ts/train.py:232 step:22K smpl:178K ep:261 epch:5.22 loss:0.030 grdn:0.266 lr:8.9e-05 updt_s:0.067 data_s:0.033
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| 125 |
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INFO 2025-11-18 02:13:54 ts/train.py:232 step:22K smpl:179K ep:263 epch:5.27 loss:0.029 grdn:0.256 lr:8.9e-05 updt_s:0.066 data_s:0.033
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| 126 |
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INFO 2025-11-18 02:14:12 ts/train.py:232 step:23K smpl:181K ep:266 epch:5.31 loss:0.026 grdn:0.245 lr:8.8e-05 updt_s:0.065 data_s:0.026
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INFO 2025-11-18 02:14:30 ts/train.py:232 step:23K smpl:182K ep:268 epch:5.36 loss:0.028 grdn:0.255 lr:8.8e-05 updt_s:0.066 data_s:0.023
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| 128 |
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INFO 2025-11-18 02:14:48 ts/train.py:232 step:23K smpl:184K ep:270 epch:5.41 loss:0.027 grdn:0.249 lr:8.8e-05 updt_s:0.065 data_s:0.025
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INFO 2025-11-18 02:15:06 ts/train.py:232 step:23K smpl:186K ep:273 epch:5.46 loss:0.026 grdn:0.242 lr:8.8e-05 updt_s:0.067 data_s:0.023
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INFO 2025-11-18 02:15:24 ts/train.py:232 step:23K smpl:187K ep:275 epch:5.50 loss:0.027 grdn:0.249 lr:8.8e-05 updt_s:0.066 data_s:0.022
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INFO 2025-11-18 02:15:42 ts/train.py:232 step:24K smpl:189K ep:277 epch:5.55 loss:0.027 grdn:0.243 lr:8.7e-05 updt_s:0.066 data_s:0.024
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INFO 2025-11-18 02:16:00 ts/train.py:232 step:24K smpl:190K ep:280 epch:5.60 loss:0.027 grdn:0.251 lr:8.7e-05 updt_s:0.066 data_s:0.022
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INFO 2025-11-18 02:16:18 ts/train.py:232 step:24K smpl:192K ep:282 epch:5.64 loss:0.028 grdn:0.250 lr:8.7e-05 updt_s:0.067 data_s:0.022
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INFO 2025-11-18 02:16:36 ts/train.py:232 step:24K smpl:194K ep:285 epch:5.69 loss:0.026 grdn:0.248 lr:8.7e-05 updt_s:0.066 data_s:0.023
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INFO 2025-11-18 02:16:54 ts/train.py:232 step:24K smpl:195K ep:287 epch:5.74 loss:0.027 grdn:0.254 lr:8.7e-05 updt_s:0.067 data_s:0.024
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INFO 2025-11-18 02:17:15 ts/train.py:232 step:25K smpl:197K ep:289 epch:5.78 loss:0.026 grdn:0.248 lr:8.6e-05 updt_s:0.067 data_s:0.037
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INFO 2025-11-18 02:17:33 ts/train.py:232 step:25K smpl:198K ep:292 epch:5.83 loss:0.027 grdn:0.252 lr:8.6e-05 updt_s:0.066 data_s:0.022
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| 138 |
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INFO 2025-11-18 02:17:51 ts/train.py:232 step:25K smpl:200K ep:294 epch:5.88 loss:0.026 grdn:0.248 lr:8.6e-05 updt_s:0.067 data_s:0.024
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| 139 |
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INFO 2025-11-18 02:18:09 ts/train.py:232 step:25K smpl:202K ep:296 epch:5.93 loss:0.026 grdn:0.239 lr:8.6e-05 updt_s:0.067 data_s:0.022
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INFO 2025-11-18 02:18:28 ts/train.py:232 step:25K smpl:203K ep:299 epch:5.97 loss:0.029 grdn:0.263 lr:8.5e-05 updt_s:0.066 data_s:0.029
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INFO 2025-11-18 02:18:47 ts/train.py:232 step:26K smpl:205K ep:301 epch:6.02 loss:0.029 grdn:0.254 lr:8.5e-05 updt_s:0.067 data_s:0.028
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INFO 2025-11-18 02:19:06 ts/train.py:232 step:26K smpl:206K ep:303 epch:6.07 loss:0.025 grdn:0.235 lr:8.5e-05 updt_s:0.067 data_s:0.027
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| 143 |
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INFO 2025-11-18 02:19:25 ts/train.py:232 step:26K smpl:208K ep:306 epch:6.11 loss:0.025 grdn:0.242 lr:8.5e-05 updt_s:0.066 data_s:0.029
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| 144 |
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INFO 2025-11-18 02:19:43 ts/train.py:232 step:26K smpl:210K ep:308 epch:6.16 loss:0.025 grdn:0.236 lr:8.5e-05 updt_s:0.066 data_s:0.025
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INFO 2025-11-18 02:20:02 ts/train.py:232 step:26K smpl:211K ep:310 epch:6.21 loss:0.025 grdn:0.245 lr:8.4e-05 updt_s:0.066 data_s:0.027
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INFO 2025-11-18 02:20:21 ts/train.py:232 step:27K smpl:213K ep:313 epch:6.25 loss:0.026 grdn:0.246 lr:8.4e-05 updt_s:0.066 data_s:0.028
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| 147 |
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INFO 2025-11-18 02:20:38 ts/train.py:232 step:27K smpl:214K ep:315 epch:6.30 loss:0.028 grdn:0.259 lr:8.4e-05 updt_s:0.066 data_s:0.021
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| 148 |
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INFO 2025-11-18 02:20:56 ts/train.py:232 step:27K smpl:216K ep:317 epch:6.35 loss:0.025 grdn:0.238 lr:8.4e-05 updt_s:0.067 data_s:0.020
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| 149 |
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INFO 2025-11-18 02:21:14 ts/train.py:232 step:27K smpl:218K ep:320 epch:6.40 loss:0.029 grdn:0.259 lr:8.3e-05 updt_s:0.067 data_s:0.022
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| 150 |
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INFO 2025-11-18 02:21:31 ts/train.py:232 step:27K smpl:219K ep:322 epch:6.44 loss:0.026 grdn:0.252 lr:8.3e-05 updt_s:0.065 data_s:0.023
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INFO 2025-11-18 02:21:49 ts/train.py:232 step:28K smpl:221K ep:324 epch:6.49 loss:0.028 grdn:0.253 lr:8.3e-05 updt_s:0.065 data_s:0.024
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INFO 2025-11-18 02:22:07 ts/train.py:232 step:28K smpl:222K ep:327 epch:6.54 loss:0.027 grdn:0.253 lr:8.3e-05 updt_s:0.066 data_s:0.024
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INFO 2025-11-18 02:22:25 ts/train.py:232 step:28K smpl:224K ep:329 epch:6.58 loss:0.025 grdn:0.237 lr:8.2e-05 updt_s:0.066 data_s:0.023
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INFO 2025-11-18 02:22:43 ts/train.py:232 step:28K smpl:226K ep:332 epch:6.63 loss:0.026 grdn:0.244 lr:8.2e-05 updt_s:0.067 data_s:0.023
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INFO 2025-11-18 02:23:01 ts/train.py:232 step:28K smpl:227K ep:334 epch:6.68 loss:0.026 grdn:0.246 lr:8.2e-05 updt_s:0.066 data_s:0.023
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| 156 |
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INFO 2025-11-18 02:23:19 ts/train.py:232 step:29K smpl:229K ep:336 epch:6.73 loss:0.026 grdn:0.243 lr:8.2e-05 updt_s:0.066 data_s:0.023
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INFO 2025-11-18 02:23:37 ts/train.py:232 step:29K smpl:230K ep:339 epch:6.77 loss:0.027 grdn:0.264 lr:8.1e-05 updt_s:0.066 data_s:0.022
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INFO 2025-11-18 02:23:55 ts/train.py:232 step:29K smpl:232K ep:341 epch:6.82 loss:0.029 grdn:0.260 lr:8.1e-05 updt_s:0.064 data_s:0.023
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INFO 2025-11-18 02:24:12 ts/train.py:232 step:29K smpl:234K ep:343 epch:6.87 loss:0.027 grdn:0.251 lr:8.1e-05 updt_s:0.064 data_s:0.024
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INFO 2025-11-18 02:24:30 ts/train.py:232 step:29K smpl:235K ep:346 epch:6.91 loss:0.025 grdn:0.240 lr:8.1e-05 updt_s:0.065 data_s:0.024
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INFO 2025-11-18 02:24:53 ts/train.py:232 step:30K smpl:237K ep:348 epch:6.96 loss:0.027 grdn:0.252 lr:8.0e-05 updt_s:0.066 data_s:0.048
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INFO 2025-11-18 02:25:12 ts/train.py:232 step:30K smpl:238K ep:350 epch:7.01 loss:0.024 grdn:0.237 lr:8.0e-05 updt_s:0.066 data_s:0.026
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INFO 2025-11-18 02:25:31 ts/train.py:232 step:30K smpl:240K ep:353 epch:7.05 loss:0.024 grdn:0.236 lr:8.0e-05 updt_s:0.066 data_s:0.030
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INFO 2025-11-18 02:25:51 ts/train.py:232 step:30K smpl:242K ep:355 epch:7.10 loss:0.025 grdn:0.240 lr:8.0e-05 updt_s:0.066 data_s:0.029
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INFO 2025-11-18 02:26:10 ts/train.py:232 step:30K smpl:243K ep:357 epch:7.15 loss:0.025 grdn:0.237 lr:7.9e-05 updt_s:0.067 data_s:0.029
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INFO 2025-11-18 02:26:29 ts/train.py:232 step:31K smpl:245K ep:360 epch:7.20 loss:0.023 grdn:0.239 lr:7.9e-05 updt_s:0.067 data_s:0.030
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INFO 2025-11-18 02:26:48 ts/train.py:232 step:31K smpl:246K ep:362 epch:7.24 loss:0.024 grdn:0.229 lr:7.9e-05 updt_s:0.066 data_s:0.029
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| 168 |
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INFO 2025-11-18 02:27:06 ts/train.py:232 step:31K smpl:248K ep:364 epch:7.29 loss:0.023 grdn:0.230 lr:7.9e-05 updt_s:0.067 data_s:0.023
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INFO 2025-11-18 02:27:24 ts/train.py:232 step:31K smpl:250K ep:367 epch:7.34 loss:0.026 grdn:0.250 lr:7.8e-05 updt_s:0.066 data_s:0.023
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INFO 2025-11-18 02:27:45 ts/train.py:232 step:31K smpl:251K ep:369 epch:7.38 loss:0.026 grdn:0.255 lr:7.8e-05 updt_s:0.066 data_s:0.037
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INFO 2025-11-18 02:28:03 ts/train.py:232 step:32K smpl:253K ep:372 epch:7.43 loss:0.023 grdn:0.235 lr:7.8e-05 updt_s:0.066 data_s:0.024
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INFO 2025-11-18 02:28:21 ts/train.py:232 step:32K smpl:254K ep:374 epch:7.48 loss:0.027 grdn:0.250 lr:7.8e-05 updt_s:0.066 data_s:0.024
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INFO 2025-11-18 02:28:39 ts/train.py:232 step:32K smpl:256K ep:376 epch:7.52 loss:0.026 grdn:0.243 lr:7.7e-05 updt_s:0.065 data_s:0.023
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INFO 2025-11-18 02:28:56 ts/train.py:232 step:32K smpl:258K ep:379 epch:7.57 loss:0.025 grdn:0.240 lr:7.7e-05 updt_s:0.066 data_s:0.023
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| 175 |
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INFO 2025-11-18 02:29:14 ts/train.py:232 step:32K smpl:259K ep:381 epch:7.62 loss:0.026 grdn:0.240 lr:7.7e-05 updt_s:0.065 data_s:0.023
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INFO 2025-11-18 02:29:31 ts/train.py:232 step:33K smpl:261K ep:383 epch:7.67 loss:0.026 grdn:0.247 lr:7.7e-05 updt_s:0.066 data_s:0.021
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INFO 2025-11-18 02:29:49 ts/train.py:232 step:33K smpl:262K ep:386 epch:7.71 loss:0.024 grdn:0.238 lr:7.6e-05 updt_s:0.066 data_s:0.023
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INFO 2025-11-18 02:30:07 ts/train.py:232 step:33K smpl:264K ep:388 epch:7.76 loss:0.025 grdn:0.238 lr:7.6e-05 updt_s:0.066 data_s:0.021
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INFO 2025-11-18 02:30:25 ts/train.py:232 step:33K smpl:266K ep:390 epch:7.81 loss:0.026 grdn:0.251 lr:7.6e-05 updt_s:0.066 data_s:0.022
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INFO 2025-11-18 02:30:42 ts/train.py:232 step:33K smpl:267K ep:393 epch:7.85 loss:0.022 grdn:0.228 lr:7.5e-05 updt_s:0.066 data_s:0.022
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INFO 2025-11-18 02:31:00 ts/train.py:232 step:34K smpl:269K ep:395 epch:7.90 loss:0.026 grdn:0.249 lr:7.5e-05 updt_s:0.066 data_s:0.023
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INFO 2025-11-18 02:31:22 ts/train.py:232 step:34K smpl:270K ep:397 epch:7.95 loss:0.025 grdn:0.242 lr:7.5e-05 updt_s:0.065 data_s:0.044
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INFO 2025-11-18 02:31:41 ts/train.py:232 step:34K smpl:272K ep:400 epch:7.99 loss:0.025 grdn:0.240 lr:7.5e-05 updt_s:0.067 data_s:0.028
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INFO 2025-11-18 02:32:01 ts/train.py:232 step:34K smpl:274K ep:402 epch:8.04 loss:0.025 grdn:0.233 lr:7.4e-05 updt_s:0.067 data_s:0.030
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INFO 2025-11-18 02:32:20 ts/train.py:232 step:34K smpl:275K ep:404 epch:8.09 loss:0.025 grdn:0.242 lr:7.4e-05 updt_s:0.066 data_s:0.029
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INFO 2025-11-18 02:32:39 ts/train.py:232 step:35K smpl:277K ep:407 epch:8.14 loss:0.024 grdn:0.236 lr:7.4e-05 updt_s:0.066 data_s:0.031
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INFO 2025-11-18 02:32:59 ts/train.py:232 step:35K smpl:278K ep:409 epch:8.18 loss:0.027 grdn:0.247 lr:7.4e-05 updt_s:0.067 data_s:0.029
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| 188 |
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INFO 2025-11-18 02:33:18 ts/train.py:232 step:35K smpl:280K ep:411 epch:8.23 loss:0.023 grdn:0.227 lr:7.3e-05 updt_s:0.067 data_s:0.030
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INFO 2025-11-18 02:33:36 ts/train.py:232 step:35K smpl:282K ep:414 epch:8.28 loss:0.023 grdn:0.227 lr:7.3e-05 updt_s:0.067 data_s:0.023
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INFO 2025-11-18 02:33:54 ts/train.py:232 step:35K smpl:283K ep:416 epch:8.32 loss:0.025 grdn:0.246 lr:7.3e-05 updt_s:0.067 data_s:0.022
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INFO 2025-11-18 02:34:12 ts/train.py:232 step:36K smpl:285K ep:419 epch:8.37 loss:0.023 grdn:0.226 lr:7.2e-05 updt_s:0.066 data_s:0.023
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INFO 2025-11-18 02:34:30 ts/train.py:232 step:36K smpl:286K ep:421 epch:8.42 loss:0.023 grdn:0.235 lr:7.2e-05 updt_s:0.066 data_s:0.023
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INFO 2025-11-18 02:34:48 ts/train.py:232 step:36K smpl:288K ep:423 epch:8.47 loss:0.022 grdn:0.224 lr:7.2e-05 updt_s:0.066 data_s:0.025
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INFO 2025-11-18 02:35:07 ts/train.py:232 step:36K smpl:290K ep:426 epch:8.51 loss:0.023 grdn:0.227 lr:7.2e-05 updt_s:0.066 data_s:0.024
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INFO 2025-11-18 02:35:25 ts/train.py:232 step:36K smpl:291K ep:428 epch:8.56 loss:0.023 grdn:0.231 lr:7.1e-05 updt_s:0.067 data_s:0.023
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INFO 2025-11-18 02:35:43 ts/train.py:232 step:37K smpl:293K ep:430 epch:8.61 loss:0.023 grdn:0.237 lr:7.1e-05 updt_s:0.066 data_s:0.024
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INFO 2025-11-18 02:36:01 ts/train.py:232 step:37K smpl:294K ep:433 epch:8.65 loss:0.023 grdn:0.234 lr:7.1e-05 updt_s:0.065 data_s:0.024
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INFO 2025-11-18 02:36:19 ts/train.py:232 step:37K smpl:296K ep:435 epch:8.70 loss:0.024 grdn:0.250 lr:7.0e-05 updt_s:0.065 data_s:0.024
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INFO 2025-11-18 02:36:36 ts/train.py:232 step:37K smpl:298K ep:437 epch:8.75 loss:0.024 grdn:0.242 lr:7.0e-05 updt_s:0.066 data_s:0.021
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INFO 2025-11-18 02:36:54 ts/train.py:232 step:37K smpl:299K ep:440 epch:8.79 loss:0.022 grdn:0.223 lr:7.0e-05 updt_s:0.067 data_s:0.022
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INFO 2025-11-18 02:37:12 ts/train.py:232 step:38K smpl:301K ep:442 epch:8.84 loss:0.020 grdn:0.222 lr:7.0e-05 updt_s:0.066 data_s:0.022
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INFO 2025-11-18 02:37:30 ts/train.py:232 step:38K smpl:302K ep:444 epch:8.89 loss:0.022 grdn:0.230 lr:6.9e-05 updt_s:0.066 data_s:0.023
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INFO 2025-11-18 02:37:53 ts/train.py:232 step:38K smpl:304K ep:447 epch:8.94 loss:0.023 grdn:0.226 lr:6.9e-05 updt_s:0.065 data_s:0.049
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INFO 2025-11-18 02:38:15 ts/train.py:232 step:38K smpl:306K ep:449 epch:8.98 loss:0.023 grdn:0.231 lr:6.9e-05 updt_s:0.066 data_s:0.045
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INFO 2025-11-18 02:38:35 ts/train.py:232 step:38K smpl:307K ep:451 epch:9.03 loss:0.023 grdn:0.236 lr:6.8e-05 updt_s:0.066 data_s:0.033
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INFO 2025-11-18 02:38:54 ts/train.py:232 step:39K smpl:309K ep:454 epch:9.08 loss:0.023 grdn:0.228 lr:6.8e-05 updt_s:0.066 data_s:0.029
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INFO 2025-11-18 02:39:13 ts/train.py:232 step:39K smpl:310K ep:456 epch:9.12 loss:0.023 grdn:0.234 lr:6.8e-05 updt_s:0.066 data_s:0.029
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INFO 2025-11-18 02:39:32 ts/train.py:232 step:39K smpl:312K ep:459 epch:9.17 loss:0.024 grdn:0.237 lr:6.8e-05 updt_s:0.066 data_s:0.030
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INFO 2025-11-18 02:39:51 ts/train.py:232 step:39K smpl:314K ep:461 epch:9.22 loss:0.023 grdn:0.229 lr:6.7e-05 updt_s:0.066 data_s:0.026
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INFO 2025-11-18 02:40:08 ts/train.py:232 step:39K smpl:315K ep:463 epch:9.26 loss:0.025 grdn:0.244 lr:6.7e-05 updt_s:0.065 data_s:0.021
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INFO 2025-11-18 02:40:25 ts/train.py:232 step:40K smpl:317K ep:466 epch:9.31 loss:0.021 grdn:0.223 lr:6.7e-05 updt_s:0.065 data_s:0.020
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INFO 2025-11-18 02:40:42 ts/train.py:232 step:40K smpl:318K ep:468 epch:9.36 loss:0.022 grdn:0.235 lr:6.6e-05 updt_s:0.065 data_s:0.021
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INFO 2025-11-18 02:40:59 ts/train.py:232 step:40K smpl:320K ep:470 epch:9.41 loss:0.024 grdn:0.238 lr:6.6e-05 updt_s:0.064 data_s:0.021
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INFO 2025-11-18 02:40:59 ts/train.py:241 Checkpoint policy after step 40000
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INFO 2025-11-18 02:42:10 ts/train.py:232 step:40K smpl:322K ep:473 epch:9.45 loss:0.023 grdn:0.237 lr:6.6e-05 updt_s:0.067 data_s:0.020
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INFO 2025-11-18 02:42:28 ts/train.py:232 step:40K smpl:323K ep:475 epch:9.50 loss:0.023 grdn:0.240 lr:6.5e-05 updt_s:0.066 data_s:0.024
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INFO 2025-11-18 02:42:46 ts/train.py:232 step:41K smpl:325K ep:477 epch:9.55 loss:0.022 grdn:0.227 lr:6.5e-05 updt_s:0.066 data_s:0.022
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INFO 2025-11-18 02:43:03 ts/train.py:232 step:41K smpl:326K ep:480 epch:9.59 loss:0.024 grdn:0.238 lr:6.5e-05 updt_s:0.066 data_s:0.021
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INFO 2025-11-18 02:43:21 ts/train.py:232 step:41K smpl:328K ep:482 epch:9.64 loss:0.024 grdn:0.236 lr:6.5e-05 updt_s:0.066 data_s:0.023
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INFO 2025-11-18 02:43:39 ts/train.py:232 step:41K smpl:330K ep:484 epch:9.69 loss:0.022 grdn:0.230 lr:6.4e-05 updt_s:0.066 data_s:0.023
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INFO 2025-11-18 02:43:57 ts/train.py:232 step:41K smpl:331K ep:487 epch:9.73 loss:0.022 grdn:0.238 lr:6.4e-05 updt_s:0.066 data_s:0.022
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INFO 2025-11-18 02:44:15 ts/train.py:232 step:42K smpl:333K ep:489 epch:9.78 loss:0.024 grdn:0.243 lr:6.4e-05 updt_s:0.066 data_s:0.023
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INFO 2025-11-18 02:44:32 ts/train.py:232 step:42K smpl:334K ep:491 epch:9.83 loss:0.023 grdn:0.234 lr:6.3e-05 updt_s:0.065 data_s:0.022
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INFO 2025-11-18 02:44:50 ts/train.py:232 step:42K smpl:336K ep:494 epch:9.88 loss:0.022 grdn:0.232 lr:6.3e-05 updt_s:0.067 data_s:0.022
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INFO 2025-11-18 02:45:09 ts/train.py:232 step:42K smpl:338K ep:496 epch:9.92 loss:0.021 grdn:0.218 lr:6.3e-05 updt_s:0.066 data_s:0.028
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INFO 2025-11-18 02:45:28 ts/train.py:232 step:42K smpl:339K ep:499 epch:9.97 loss:0.022 grdn:0.230 lr:6.2e-05 updt_s:0.066 data_s:0.028
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INFO 2025-11-18 02:45:47 ts/train.py:232 step:43K smpl:341K ep:501 epch:10.02 loss:0.024 grdn:0.244 lr:6.2e-05 updt_s:0.066 data_s:0.028
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INFO 2025-11-18 02:46:06 ts/train.py:232 step:43K smpl:342K ep:503 epch:10.06 loss:0.024 grdn:0.244 lr:6.2e-05 updt_s:0.066 data_s:0.026
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INFO 2025-11-18 02:46:24 ts/train.py:232 step:43K smpl:344K ep:506 epch:10.11 loss:0.023 grdn:0.232 lr:6.1e-05 updt_s:0.066 data_s:0.023
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INFO 2025-11-18 02:46:43 ts/train.py:232 step:43K smpl:346K ep:508 epch:10.16 loss:0.023 grdn:0.225 lr:6.1e-05 updt_s:0.066 data_s:0.029
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INFO 2025-11-18 02:47:02 ts/train.py:232 step:43K smpl:347K ep:510 epch:10.21 loss:0.021 grdn:0.221 lr:6.1e-05 updt_s:0.066 data_s:0.030
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INFO 2025-11-18 02:47:20 ts/train.py:232 step:44K smpl:349K ep:513 epch:10.25 loss:0.020 grdn:0.223 lr:6.1e-05 updt_s:0.066 data_s:0.022
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INFO 2025-11-18 02:47:37 ts/train.py:232 step:44K smpl:350K ep:515 epch:10.30 loss:0.021 grdn:0.223 lr:6.0e-05 updt_s:0.065 data_s:0.020
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INFO 2025-11-18 02:47:58 ts/train.py:232 step:44K smpl:352K ep:517 epch:10.35 loss:0.022 grdn:0.238 lr:6.0e-05 updt_s:0.066 data_s:0.037
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INFO 2025-11-18 02:48:16 ts/train.py:232 step:44K smpl:354K ep:520 epch:10.39 loss:0.022 grdn:0.233 lr:6.0e-05 updt_s:0.066 data_s:0.025
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INFO 2025-11-18 02:48:34 ts/train.py:232 step:44K smpl:355K ep:522 epch:10.44 loss:0.024 grdn:0.249 lr:5.9e-05 updt_s:0.066 data_s:0.022
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INFO 2025-11-18 02:48:52 ts/train.py:232 step:45K smpl:357K ep:524 epch:10.49 loss:0.020 grdn:0.222 lr:5.9e-05 updt_s:0.066 data_s:0.023
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INFO 2025-11-18 02:49:09 ts/train.py:232 step:45K smpl:358K ep:527 epch:10.53 loss:0.022 grdn:0.234 lr:5.9e-05 updt_s:0.066 data_s:0.020
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INFO 2025-11-18 02:49:27 ts/train.py:232 step:45K smpl:360K ep:529 epch:10.58 loss:0.026 grdn:0.255 lr:5.8e-05 updt_s:0.066 data_s:0.021
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INFO 2025-11-18 02:49:44 ts/train.py:232 step:45K smpl:362K ep:531 epch:10.63 loss:0.023 grdn:0.235 lr:5.8e-05 updt_s:0.066 data_s:0.021
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INFO 2025-11-18 02:50:02 ts/train.py:232 step:45K smpl:363K ep:534 epch:10.68 loss:0.022 grdn:0.234 lr:5.8e-05 updt_s:0.065 data_s:0.022
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INFO 2025-11-18 02:50:19 ts/train.py:232 step:46K smpl:365K ep:536 epch:10.72 loss:0.022 grdn:0.234 lr:5.7e-05 updt_s:0.066 data_s:0.021
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INFO 2025-11-18 02:50:37 ts/train.py:232 step:46K smpl:366K ep:538 epch:10.77 loss:0.022 grdn:0.231 lr:5.7e-05 updt_s:0.066 data_s:0.022
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INFO 2025-11-18 02:50:55 ts/train.py:232 step:46K smpl:368K ep:541 epch:10.82 loss:0.023 grdn:0.233 lr:5.7e-05 updt_s:0.066 data_s:0.025
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INFO 2025-11-18 02:51:13 ts/train.py:232 step:46K smpl:370K ep:543 epch:10.86 loss:0.022 grdn:0.234 lr:5.7e-05 updt_s:0.065 data_s:0.021
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INFO 2025-11-18 02:51:32 ts/train.py:232 step:46K smpl:371K ep:546 epch:10.91 loss:0.021 grdn:0.217 lr:5.6e-05 updt_s:0.066 data_s:0.028
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INFO 2025-11-18 02:51:51 ts/train.py:232 step:47K smpl:373K ep:548 epch:10.96 loss:0.021 grdn:0.223 lr:5.6e-05 updt_s:0.066 data_s:0.028
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INFO 2025-11-18 02:52:10 ts/train.py:232 step:47K smpl:374K ep:550 epch:11.00 loss:0.021 grdn:0.222 lr:5.6e-05 updt_s:0.067 data_s:0.031
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INFO 2025-11-18 02:52:30 ts/train.py:232 step:47K smpl:376K ep:553 epch:11.05 loss:0.021 grdn:0.234 lr:5.5e-05 updt_s:0.066 data_s:0.029
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INFO 2025-11-18 02:52:50 ts/train.py:232 step:47K smpl:378K ep:555 epch:11.10 loss:0.021 grdn:0.222 lr:5.5e-05 updt_s:0.066 data_s:0.033
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INFO 2025-11-18 02:53:09 ts/train.py:232 step:47K smpl:379K ep:557 epch:11.15 loss:0.021 grdn:0.231 lr:5.5e-05 updt_s:0.066 data_s:0.031
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INFO 2025-11-18 02:53:29 ts/train.py:232 step:48K smpl:381K ep:560 epch:11.19 loss:0.022 grdn:0.235 lr:5.4e-05 updt_s:0.066 data_s:0.030
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INFO 2025-11-18 02:53:47 ts/train.py:232 step:48K smpl:382K ep:562 epch:11.24 loss:0.021 grdn:0.229 lr:5.4e-05 updt_s:0.066 data_s:0.024
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INFO 2025-11-18 02:54:05 ts/train.py:232 step:48K smpl:384K ep:564 epch:11.29 loss:0.022 grdn:0.228 lr:5.4e-05 updt_s:0.066 data_s:0.024
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INFO 2025-11-18 02:54:23 ts/train.py:232 step:48K smpl:386K ep:567 epch:11.33 loss:0.020 grdn:0.222 lr:5.3e-05 updt_s:0.066 data_s:0.024
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INFO 2025-11-18 02:54:41 ts/train.py:232 step:48K smpl:387K ep:569 epch:11.38 loss:0.021 grdn:0.227 lr:5.3e-05 updt_s:0.066 data_s:0.023
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INFO 2025-11-18 02:54:59 ts/train.py:232 step:49K smpl:389K ep:571 epch:11.43 loss:0.021 grdn:0.228 lr:5.3e-05 updt_s:0.066 data_s:0.025
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INFO 2025-11-18 02:55:17 ts/train.py:232 step:49K smpl:390K ep:574 epch:11.47 loss:0.020 grdn:0.217 lr:5.2e-05 updt_s:0.066 data_s:0.022
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INFO 2025-11-18 02:55:35 ts/train.py:232 step:49K smpl:392K ep:576 epch:11.52 loss:0.023 grdn:0.242 lr:5.2e-05 updt_s:0.066 data_s:0.023
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INFO 2025-11-18 02:55:53 ts/train.py:232 step:49K smpl:394K ep:578 epch:11.57 loss:0.020 grdn:0.221 lr:5.2e-05 updt_s:0.066 data_s:0.024
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INFO 2025-11-18 02:56:11 ts/train.py:232 step:49K smpl:395K ep:581 epch:11.62 loss:0.021 grdn:0.220 lr:5.1e-05 updt_s:0.067 data_s:0.023
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INFO 2025-11-18 02:56:29 ts/train.py:232 step:50K smpl:397K ep:583 epch:11.66 loss:0.020 grdn:0.215 lr:5.1e-05 updt_s:0.065 data_s:0.025
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INFO 2025-11-18 02:56:47 ts/train.py:232 step:50K smpl:398K ep:586 epch:11.71 loss:0.021 grdn:0.220 lr:5.1e-05 updt_s:0.066 data_s:0.024
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INFO 2025-11-18 02:57:05 ts/train.py:232 step:50K smpl:400K ep:588 epch:11.76 loss:0.021 grdn:0.234 lr:5.1e-05 updt_s:0.066 data_s:0.022
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INFO 2025-11-18 02:57:23 ts/train.py:232 step:50K smpl:402K ep:590 epch:11.80 loss:0.021 grdn:0.230 lr:5.0e-05 updt_s:0.067 data_s:0.023
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INFO 2025-11-18 02:57:41 ts/train.py:232 step:50K smpl:403K ep:593 epch:11.85 loss:0.019 grdn:0.208 lr:5.0e-05 updt_s:0.065 data_s:0.025
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INFO 2025-11-18 02:58:02 ts/train.py:232 step:51K smpl:405K ep:595 epch:11.90 loss:0.021 grdn:0.222 lr:5.0e-05 updt_s:0.065 data_s:0.041
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INFO 2025-11-18 02:58:25 ts/train.py:232 step:51K smpl:406K ep:597 epch:11.95 loss:0.018 grdn:0.208 lr:4.9e-05 updt_s:0.066 data_s:0.046
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INFO 2025-11-18 02:58:44 ts/train.py:232 step:51K smpl:408K ep:600 epch:11.99 loss:0.021 grdn:0.231 lr:4.9e-05 updt_s:0.066 data_s:0.028
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INFO 2025-11-18 02:59:03 ts/train.py:232 step:51K smpl:410K ep:602 epch:12.04 loss:0.020 grdn:0.219 lr:4.9e-05 updt_s:0.067 data_s:0.031
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INFO 2025-11-18 02:59:23 ts/train.py:232 step:51K smpl:411K ep:604 epch:12.09 loss:0.019 grdn:0.218 lr:4.8e-05 updt_s:0.065 data_s:0.031
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INFO 2025-11-18 02:59:42 ts/train.py:232 step:52K smpl:413K ep:607 epch:12.13 loss:0.021 grdn:0.225 lr:4.8e-05 updt_s:0.066 data_s:0.028
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INFO 2025-11-18 03:00:01 ts/train.py:232 step:52K smpl:414K ep:609 epch:12.18 loss:0.021 grdn:0.227 lr:4.8e-05 updt_s:0.066 data_s:0.029
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INFO 2025-11-18 03:00:18 ts/train.py:232 step:52K smpl:416K ep:611 epch:12.23 loss:0.021 grdn:0.224 lr:4.7e-05 updt_s:0.066 data_s:0.022
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INFO 2025-11-18 03:00:36 ts/train.py:232 step:52K smpl:418K ep:614 epch:12.27 loss:0.022 grdn:0.236 lr:4.7e-05 updt_s:0.066 data_s:0.022
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INFO 2025-11-18 03:00:54 ts/train.py:232 step:52K smpl:419K ep:616 epch:12.32 loss:0.020 grdn:0.224 lr:4.7e-05 updt_s:0.066 data_s:0.023
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INFO 2025-11-18 03:01:11 ts/train.py:232 step:53K smpl:421K ep:618 epch:12.37 loss:0.020 grdn:0.225 lr:4.6e-05 updt_s:0.065 data_s:0.021
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INFO 2025-11-18 03:01:29 ts/train.py:232 step:53K smpl:422K ep:621 epch:12.42 loss:0.020 grdn:0.218 lr:4.6e-05 updt_s:0.065 data_s:0.021
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INFO 2025-11-18 03:01:46 ts/train.py:232 step:53K smpl:424K ep:623 epch:12.46 loss:0.021 grdn:0.223 lr:4.6e-05 updt_s:0.066 data_s:0.021
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INFO 2025-11-18 03:02:03 ts/train.py:232 step:53K smpl:426K ep:625 epch:12.51 loss:0.019 grdn:0.212 lr:4.6e-05 updt_s:0.065 data_s:0.021
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INFO 2025-11-18 03:02:21 ts/train.py:232 step:53K smpl:427K ep:628 epch:12.56 loss:0.021 grdn:0.230 lr:4.5e-05 updt_s:0.066 data_s:0.023
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INFO 2025-11-18 03:02:39 ts/train.py:232 step:54K smpl:429K ep:630 epch:12.60 loss:0.020 grdn:0.215 lr:4.5e-05 updt_s:0.065 data_s:0.024
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INFO 2025-11-18 03:02:58 ts/train.py:232 step:54K smpl:430K ep:633 epch:12.65 loss:0.020 grdn:0.220 lr:4.5e-05 updt_s:0.067 data_s:0.024
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INFO 2025-11-18 03:03:15 ts/train.py:232 step:54K smpl:432K ep:635 epch:12.70 loss:0.022 grdn:0.231 lr:4.4e-05 updt_s:0.066 data_s:0.022
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INFO 2025-11-18 03:03:33 ts/train.py:232 step:54K smpl:434K ep:637 epch:12.74 loss:0.018 grdn:0.210 lr:4.4e-05 updt_s:0.066 data_s:0.023
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INFO 2025-11-18 03:03:51 ts/train.py:232 step:54K smpl:435K ep:640 epch:12.79 loss:0.018 grdn:0.205 lr:4.4e-05 updt_s:0.066 data_s:0.023
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INFO 2025-11-18 03:04:09 ts/train.py:232 step:55K smpl:437K ep:642 epch:12.84 loss:0.019 grdn:0.224 lr:4.3e-05 updt_s:0.066 data_s:0.024
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INFO 2025-11-18 03:04:29 ts/train.py:232 step:55K smpl:438K ep:644 epch:12.89 loss:0.021 grdn:0.231 lr:4.3e-05 updt_s:0.066 data_s:0.032
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INFO 2025-11-18 03:04:47 ts/train.py:232 step:55K smpl:440K ep:647 epch:12.93 loss:0.021 grdn:0.228 lr:4.3e-05 updt_s:0.066 data_s:0.026
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INFO 2025-11-18 03:05:06 ts/train.py:232 step:55K smpl:442K ep:649 epch:12.98 loss:0.020 grdn:0.220 lr:4.2e-05 updt_s:0.067 data_s:0.025
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INFO 2025-11-18 03:05:23 ts/train.py:232 step:55K smpl:443K ep:651 epch:13.03 loss:0.020 grdn:0.228 lr:4.2e-05 updt_s:0.066 data_s:0.022
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INFO 2025-11-18 03:05:41 ts/train.py:232 step:56K smpl:445K ep:654 epch:13.07 loss:0.020 grdn:0.225 lr:4.2e-05 updt_s:0.066 data_s:0.024
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INFO 2025-11-18 03:06:00 ts/train.py:232 step:56K smpl:446K ep:656 epch:13.12 loss:0.020 grdn:0.226 lr:4.1e-05 updt_s:0.066 data_s:0.024
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INFO 2025-11-18 03:06:18 ts/train.py:232 step:56K smpl:448K ep:658 epch:13.17 loss:0.021 grdn:0.232 lr:4.1e-05 updt_s:0.066 data_s:0.025
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INFO 2025-11-18 03:06:36 ts/train.py:232 step:56K smpl:450K ep:661 epch:13.21 loss:0.021 grdn:0.234 lr:4.1e-05 updt_s:0.066 data_s:0.023
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INFO 2025-11-18 03:06:54 ts/train.py:232 step:56K smpl:451K ep:663 epch:13.26 loss:0.020 grdn:0.218 lr:4.1e-05 updt_s:0.066 data_s:0.023
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INFO 2025-11-18 03:07:12 ts/train.py:232 step:57K smpl:453K ep:665 epch:13.31 loss:0.020 grdn:0.221 lr:4.0e-05 updt_s:0.067 data_s:0.023
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INFO 2025-11-18 03:07:29 ts/train.py:232 step:57K smpl:454K ep:668 epch:13.36 loss:0.020 grdn:0.229 lr:4.0e-05 updt_s:0.066 data_s:0.023
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INFO 2025-11-18 03:07:47 ts/train.py:232 step:57K smpl:456K ep:670 epch:13.40 loss:0.019 grdn:0.221 lr:4.0e-05 updt_s:0.066 data_s:0.022
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INFO 2025-11-18 03:08:05 ts/train.py:232 step:57K smpl:458K ep:673 epch:13.45 loss:0.019 grdn:0.218 lr:3.9e-05 updt_s:0.066 data_s:0.023
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INFO 2025-11-18 03:08:23 ts/train.py:232 step:57K smpl:459K ep:675 epch:13.50 loss:0.019 grdn:0.216 lr:3.9e-05 updt_s:0.065 data_s:0.023
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INFO 2025-11-18 03:08:44 ts/train.py:232 step:58K smpl:461K ep:677 epch:13.54 loss:0.021 grdn:0.232 lr:3.9e-05 updt_s:0.065 data_s:0.038
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INFO 2025-11-18 03:09:01 ts/train.py:232 step:58K smpl:462K ep:680 epch:13.59 loss:0.020 grdn:0.222 lr:3.8e-05 updt_s:0.065 data_s:0.024
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INFO 2025-11-18 03:09:19 ts/train.py:232 step:58K smpl:464K ep:682 epch:13.64 loss:0.020 grdn:0.223 lr:3.8e-05 updt_s:0.066 data_s:0.022
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INFO 2025-11-18 03:09:37 ts/train.py:232 step:58K smpl:466K ep:684 epch:13.69 loss:0.018 grdn:0.205 lr:3.8e-05 updt_s:0.066 data_s:0.021
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INFO 2025-11-18 03:09:54 ts/train.py:232 step:58K smpl:467K ep:687 epch:13.73 loss:0.019 grdn:0.216 lr:3.7e-05 updt_s:0.066 data_s:0.021
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INFO 2025-11-18 03:10:12 ts/train.py:232 step:59K smpl:469K ep:689 epch:13.78 loss:0.019 grdn:0.220 lr:3.7e-05 updt_s:0.066 data_s:0.021
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INFO 2025-11-18 03:10:30 ts/train.py:232 step:59K smpl:470K ep:691 epch:13.83 loss:0.019 grdn:0.218 lr:3.7e-05 updt_s:0.066 data_s:0.023
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INFO 2025-11-18 03:10:49 ts/train.py:232 step:59K smpl:472K ep:694 epch:13.87 loss:0.019 grdn:0.221 lr:3.7e-05 updt_s:0.066 data_s:0.027
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INFO 2025-11-18 03:11:08 ts/train.py:232 step:59K smpl:474K ep:696 epch:13.92 loss:0.019 grdn:0.211 lr:3.6e-05 updt_s:0.066 data_s:0.029
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INFO 2025-11-18 03:11:27 ts/train.py:232 step:59K smpl:475K ep:698 epch:13.97 loss:0.020 grdn:0.222 lr:3.6e-05 updt_s:0.066 data_s:0.030
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INFO 2025-11-18 03:11:46 ts/train.py:232 step:60K smpl:477K ep:701 epch:14.01 loss:0.019 grdn:0.217 lr:3.6e-05 updt_s:0.066 data_s:0.030
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INFO 2025-11-18 03:12:06 ts/train.py:232 step:60K smpl:478K ep:703 epch:14.06 loss:0.020 grdn:0.225 lr:3.5e-05 updt_s:0.066 data_s:0.029
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INFO 2025-11-18 03:12:23 ts/train.py:232 step:60K smpl:480K ep:705 epch:14.11 loss:0.018 grdn:0.212 lr:3.5e-05 updt_s:0.064 data_s:0.025
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INFO 2025-11-18 03:12:23 ts/train.py:241 Checkpoint policy after step 60000
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INFO 2025-11-18 03:13:02 ts/train.py:232 step:60K smpl:482K ep:708 epch:14.16 loss:0.021 grdn:0.235 lr:3.5e-05 updt_s:0.066 data_s:0.029
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INFO 2025-11-18 03:13:20 ts/train.py:232 step:60K smpl:483K ep:710 epch:14.20 loss:0.019 grdn:0.216 lr:3.4e-05 updt_s:0.067 data_s:0.026
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INFO 2025-11-18 03:13:39 ts/train.py:232 step:61K smpl:485K ep:712 epch:14.25 loss:0.018 grdn:0.217 lr:3.4e-05 updt_s:0.066 data_s:0.024
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INFO 2025-11-18 03:13:57 ts/train.py:232 step:61K smpl:486K ep:715 epch:14.30 loss:0.020 grdn:0.226 lr:3.4e-05 updt_s:0.066 data_s:0.023
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INFO 2025-11-18 03:14:14 ts/train.py:232 step:61K smpl:488K ep:717 epch:14.34 loss:0.018 grdn:0.208 lr:3.4e-05 updt_s:0.067 data_s:0.022
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INFO 2025-11-18 03:14:32 ts/train.py:232 step:61K smpl:490K ep:720 epch:14.39 loss:0.020 grdn:0.214 lr:3.3e-05 updt_s:0.066 data_s:0.022
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INFO 2025-11-18 03:14:50 ts/train.py:232 step:61K smpl:491K ep:722 epch:14.44 loss:0.018 grdn:0.215 lr:3.3e-05 updt_s:0.066 data_s:0.023
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INFO 2025-11-18 03:15:08 ts/train.py:232 step:62K smpl:493K ep:724 epch:14.48 loss:0.018 grdn:0.214 lr:3.3e-05 updt_s:0.067 data_s:0.022
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INFO 2025-11-18 03:15:26 ts/train.py:232 step:62K smpl:494K ep:727 epch:14.53 loss:0.019 grdn:0.215 lr:3.2e-05 updt_s:0.065 data_s:0.023
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INFO 2025-11-18 03:15:43 ts/train.py:232 step:62K smpl:496K ep:729 epch:14.58 loss:0.018 grdn:0.215 lr:3.2e-05 updt_s:0.065 data_s:0.023
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INFO 2025-11-18 03:16:01 ts/train.py:232 step:62K smpl:498K ep:731 epch:14.63 loss:0.017 grdn:0.207 lr:3.2e-05 updt_s:0.066 data_s:0.023
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INFO 2025-11-18 03:16:19 ts/train.py:232 step:62K smpl:499K ep:734 epch:14.67 loss:0.018 grdn:0.215 lr:3.1e-05 updt_s:0.066 data_s:0.022
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INFO 2025-11-18 03:16:37 ts/train.py:232 step:63K smpl:501K ep:736 epch:14.72 loss:0.017 grdn:0.205 lr:3.1e-05 updt_s:0.066 data_s:0.023
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INFO 2025-11-18 03:16:55 ts/train.py:232 step:63K smpl:502K ep:738 epch:14.77 loss:0.017 grdn:0.212 lr:3.1e-05 updt_s:0.067 data_s:0.023
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INFO 2025-11-18 03:17:13 ts/train.py:232 step:63K smpl:504K ep:741 epch:14.81 loss:0.018 grdn:0.214 lr:3.1e-05 updt_s:0.065 data_s:0.024
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INFO 2025-11-18 03:17:32 ts/train.py:232 step:63K smpl:506K ep:743 epch:14.86 loss:0.018 grdn:0.208 lr:3.0e-05 updt_s:0.066 data_s:0.028
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INFO 2025-11-18 03:17:52 ts/train.py:232 step:63K smpl:507K ep:745 epch:14.91 loss:0.019 grdn:0.220 lr:3.0e-05 updt_s:0.066 data_s:0.032
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INFO 2025-11-18 03:18:11 ts/train.py:232 step:64K smpl:509K ep:748 epch:14.96 loss:0.019 grdn:0.221 lr:3.0e-05 updt_s:0.066 data_s:0.030
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INFO 2025-11-18 03:18:30 ts/train.py:232 step:64K smpl:510K ep:750 epch:15.00 loss:0.020 grdn:0.222 lr:2.9e-05 updt_s:0.066 data_s:0.027
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INFO 2025-11-18 03:18:52 ts/train.py:232 step:64K smpl:512K ep:752 epch:15.05 loss:0.018 grdn:0.215 lr:2.9e-05 updt_s:0.066 data_s:0.045
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INFO 2025-11-18 03:19:11 ts/train.py:232 step:64K smpl:514K ep:755 epch:15.10 loss:0.018 grdn:0.214 lr:2.9e-05 updt_s:0.066 data_s:0.029
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INFO 2025-11-18 03:19:31 ts/train.py:232 step:64K smpl:515K ep:757 epch:15.14 loss:0.016 grdn:0.197 lr:2.9e-05 updt_s:0.067 data_s:0.032
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INFO 2025-11-18 03:19:49 ts/train.py:232 step:65K smpl:517K ep:760 epch:15.19 loss:0.017 grdn:0.201 lr:2.8e-05 updt_s:0.066 data_s:0.025
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INFO 2025-11-18 03:20:07 ts/train.py:232 step:65K smpl:518K ep:762 epch:15.24 loss:0.017 grdn:0.204 lr:2.8e-05 updt_s:0.066 data_s:0.023
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INFO 2025-11-18 03:20:25 ts/train.py:232 step:65K smpl:520K ep:764 epch:15.28 loss:0.018 grdn:0.216 lr:2.8e-05 updt_s:0.065 data_s:0.023
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INFO 2025-11-18 03:20:43 ts/train.py:232 step:65K smpl:522K ep:767 epch:15.33 loss:0.018 grdn:0.212 lr:2.7e-05 updt_s:0.065 data_s:0.024
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INFO 2025-11-18 03:21:01 ts/train.py:232 step:65K smpl:523K ep:769 epch:15.38 loss:0.018 grdn:0.220 lr:2.7e-05 updt_s:0.065 data_s:0.024
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INFO 2025-11-18 03:21:18 ts/train.py:232 step:66K smpl:525K ep:771 epch:15.43 loss:0.019 grdn:0.220 lr:2.7e-05 updt_s:0.066 data_s:0.021
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INFO 2025-11-18 03:21:36 ts/train.py:232 step:66K smpl:526K ep:774 epch:15.47 loss:0.018 grdn:0.217 lr:2.7e-05 updt_s:0.066 data_s:0.023
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INFO 2025-11-18 03:21:54 ts/train.py:232 step:66K smpl:528K ep:776 epch:15.52 loss:0.018 grdn:0.212 lr:2.6e-05 updt_s:0.066 data_s:0.021
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INFO 2025-11-18 03:22:11 ts/train.py:232 step:66K smpl:530K ep:778 epch:15.57 loss:0.017 grdn:0.206 lr:2.6e-05 updt_s:0.066 data_s:0.022
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INFO 2025-11-18 03:22:29 ts/train.py:232 step:66K smpl:531K ep:781 epch:15.61 loss:0.018 grdn:0.221 lr:2.6e-05 updt_s:0.066 data_s:0.021
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INFO 2025-11-18 03:22:47 ts/train.py:232 step:67K smpl:533K ep:783 epch:15.66 loss:0.018 grdn:0.214 lr:2.5e-05 updt_s:0.066 data_s:0.022
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INFO 2025-11-18 03:23:05 ts/train.py:232 step:67K smpl:534K ep:785 epch:15.71 loss:0.019 grdn:0.221 lr:2.5e-05 updt_s:0.066 data_s:0.024
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INFO 2025-11-18 03:23:23 ts/train.py:232 step:67K smpl:536K ep:788 epch:15.75 loss:0.017 grdn:0.205 lr:2.5e-05 updt_s:0.067 data_s:0.023
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INFO 2025-11-18 03:23:41 ts/train.py:232 step:67K smpl:538K ep:790 epch:15.80 loss:0.016 grdn:0.199 lr:2.5e-05 updt_s:0.066 data_s:0.022
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INFO 2025-11-18 03:24:00 ts/train.py:232 step:67K smpl:539K ep:792 epch:15.85 loss:0.019 grdn:0.227 lr:2.4e-05 updt_s:0.066 data_s:0.029
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INFO 2025-11-18 03:24:18 ts/train.py:232 step:68K smpl:541K ep:795 epch:15.90 loss:0.017 grdn:0.212 lr:2.4e-05 updt_s:0.066 data_s:0.027
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INFO 2025-11-18 03:24:38 ts/train.py:232 step:68K smpl:542K ep:797 epch:15.94 loss:0.018 grdn:0.220 lr:2.4e-05 updt_s:0.066 data_s:0.031
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INFO 2025-11-18 03:24:57 ts/train.py:232 step:68K smpl:544K ep:799 epch:15.99 loss:0.018 grdn:0.219 lr:2.4e-05 updt_s:0.066 data_s:0.030
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INFO 2025-11-18 03:25:16 ts/train.py:232 step:68K smpl:546K ep:802 epch:16.04 loss:0.018 grdn:0.217 lr:2.3e-05 updt_s:0.066 data_s:0.029
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INFO 2025-11-18 03:25:36 ts/train.py:232 step:68K smpl:547K ep:804 epch:16.08 loss:0.017 grdn:0.211 lr:2.3e-05 updt_s:0.067 data_s:0.032
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INFO 2025-11-18 03:25:55 ts/train.py:232 step:69K smpl:549K ep:807 epch:16.13 loss:0.018 grdn:0.218 lr:2.3e-05 updt_s:0.066 data_s:0.029
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INFO 2025-11-18 03:26:14 ts/train.py:232 step:69K smpl:550K ep:809 epch:16.18 loss:0.018 grdn:0.219 lr:2.2e-05 updt_s:0.066 data_s:0.028
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INFO 2025-11-18 03:26:32 ts/train.py:232 step:69K smpl:552K ep:811 epch:16.22 loss:0.018 grdn:0.224 lr:2.2e-05 updt_s:0.066 data_s:0.023
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INFO 2025-11-18 03:26:50 ts/train.py:232 step:69K smpl:554K ep:814 epch:16.27 loss:0.018 grdn:0.223 lr:2.2e-05 updt_s:0.067 data_s:0.023
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INFO 2025-11-18 03:27:08 ts/train.py:232 step:69K smpl:555K ep:816 epch:16.32 loss:0.016 grdn:0.200 lr:2.2e-05 updt_s:0.066 data_s:0.024
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INFO 2025-11-18 03:27:26 ts/train.py:232 step:70K smpl:557K ep:818 epch:16.37 loss:0.017 grdn:0.205 lr:2.1e-05 updt_s:0.066 data_s:0.025
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| 364 |
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INFO 2025-11-18 03:27:45 ts/train.py:232 step:70K smpl:558K ep:821 epch:16.41 loss:0.017 grdn:0.213 lr:2.1e-05 updt_s:0.066 data_s:0.025
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| 365 |
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INFO 2025-11-18 03:28:03 ts/train.py:232 step:70K smpl:560K ep:823 epch:16.46 loss:0.017 grdn:0.213 lr:2.1e-05 updt_s:0.066 data_s:0.026
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INFO 2025-11-18 03:28:21 ts/train.py:232 step:70K smpl:562K ep:825 epch:16.51 loss:0.018 grdn:0.211 lr:2.1e-05 updt_s:0.066 data_s:0.023
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INFO 2025-11-18 03:28:40 ts/train.py:232 step:70K smpl:563K ep:828 epch:16.55 loss:0.019 grdn:0.222 lr:2.0e-05 updt_s:0.066 data_s:0.027
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| 368 |
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INFO 2025-11-18 03:29:01 ts/train.py:232 step:71K smpl:565K ep:830 epch:16.60 loss:0.017 grdn:0.205 lr:2.0e-05 updt_s:0.066 data_s:0.039
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| 369 |
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INFO 2025-11-18 03:29:20 ts/train.py:232 step:71K smpl:566K ep:832 epch:16.65 loss:0.017 grdn:0.205 lr:2.0e-05 updt_s:0.066 data_s:0.026
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| 370 |
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INFO 2025-11-18 03:29:38 ts/train.py:232 step:71K smpl:568K ep:835 epch:16.70 loss:0.016 grdn:0.200 lr:2.0e-05 updt_s:0.066 data_s:0.026
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| 371 |
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INFO 2025-11-18 03:29:56 ts/train.py:232 step:71K smpl:570K ep:837 epch:16.74 loss:0.018 grdn:0.211 lr:1.9e-05 updt_s:0.066 data_s:0.023
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| 372 |
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INFO 2025-11-18 03:30:14 ts/train.py:232 step:71K smpl:571K ep:839 epch:16.79 loss:0.017 grdn:0.209 lr:1.9e-05 updt_s:0.067 data_s:0.024
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INFO 2025-11-18 03:30:33 ts/train.py:232 step:72K smpl:573K ep:842 epch:16.84 loss:0.016 grdn:0.201 lr:1.9e-05 updt_s:0.066 data_s:0.026
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| 374 |
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INFO 2025-11-18 03:30:51 ts/train.py:232 step:72K smpl:574K ep:844 epch:16.88 loss:0.018 grdn:0.215 lr:1.9e-05 updt_s:0.065 data_s:0.026
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INFO 2025-11-18 03:31:10 ts/train.py:232 step:72K smpl:576K ep:847 epch:16.93 loss:0.017 grdn:0.206 lr:1.8e-05 updt_s:0.066 data_s:0.028
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INFO 2025-11-18 03:31:29 ts/train.py:232 step:72K smpl:578K ep:849 epch:16.98 loss:0.016 grdn:0.204 lr:1.8e-05 updt_s:0.066 data_s:0.026
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| 377 |
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INFO 2025-11-18 03:31:47 ts/train.py:232 step:72K smpl:579K ep:851 epch:17.02 loss:0.017 grdn:0.216 lr:1.8e-05 updt_s:0.065 data_s:0.027
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| 378 |
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INFO 2025-11-18 03:32:06 ts/train.py:232 step:73K smpl:581K ep:854 epch:17.07 loss:0.018 grdn:0.220 lr:1.8e-05 updt_s:0.066 data_s:0.028
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INFO 2025-11-18 03:32:25 ts/train.py:232 step:73K smpl:582K ep:856 epch:17.12 loss:0.017 grdn:0.209 lr:1.7e-05 updt_s:0.067 data_s:0.026
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| 380 |
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INFO 2025-11-18 03:32:43 ts/train.py:232 step:73K smpl:584K ep:858 epch:17.17 loss:0.017 grdn:0.201 lr:1.7e-05 updt_s:0.066 data_s:0.025
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INFO 2025-11-18 03:33:01 ts/train.py:232 step:73K smpl:586K ep:861 epch:17.21 loss:0.016 grdn:0.206 lr:1.7e-05 updt_s:0.066 data_s:0.023
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INFO 2025-11-18 03:33:19 ts/train.py:232 step:73K smpl:587K ep:863 epch:17.26 loss:0.016 grdn:0.196 lr:1.7e-05 updt_s:0.066 data_s:0.023
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INFO 2025-11-18 03:33:37 ts/train.py:232 step:74K smpl:589K ep:865 epch:17.31 loss:0.017 grdn:0.204 lr:1.7e-05 updt_s:0.066 data_s:0.022
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INFO 2025-11-18 03:33:55 ts/train.py:232 step:74K smpl:590K ep:868 epch:17.35 loss:0.016 grdn:0.201 lr:1.6e-05 updt_s:0.066 data_s:0.024
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INFO 2025-11-18 03:34:13 ts/train.py:232 step:74K smpl:592K ep:870 epch:17.40 loss:0.016 grdn:0.206 lr:1.6e-05 updt_s:0.065 data_s:0.024
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| 386 |
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INFO 2025-11-18 03:34:30 ts/train.py:232 step:74K smpl:594K ep:872 epch:17.45 loss:0.016 grdn:0.201 lr:1.6e-05 updt_s:0.066 data_s:0.022
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| 387 |
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INFO 2025-11-18 03:34:48 ts/train.py:232 step:74K smpl:595K ep:875 epch:17.49 loss:0.016 grdn:0.199 lr:1.6e-05 updt_s:0.066 data_s:0.023
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| 388 |
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INFO 2025-11-18 03:35:06 ts/train.py:232 step:75K smpl:597K ep:877 epch:17.54 loss:0.017 grdn:0.206 lr:1.5e-05 updt_s:0.066 data_s:0.023
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| 389 |
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INFO 2025-11-18 03:35:24 ts/train.py:232 step:75K smpl:598K ep:879 epch:17.59 loss:0.016 grdn:0.204 lr:1.5e-05 updt_s:0.067 data_s:0.023
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| 390 |
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INFO 2025-11-18 03:35:42 ts/train.py:232 step:75K smpl:600K ep:882 epch:17.64 loss:0.016 grdn:0.206 lr:1.5e-05 updt_s:0.066 data_s:0.024
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INFO 2025-11-18 03:36:00 ts/train.py:232 step:75K smpl:602K ep:884 epch:17.68 loss:0.016 grdn:0.199 lr:1.5e-05 updt_s:0.066 data_s:0.023
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INFO 2025-11-18 03:36:18 ts/train.py:232 step:75K smpl:603K ep:886 epch:17.73 loss:0.018 grdn:0.217 lr:1.4e-05 updt_s:0.066 data_s:0.022
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INFO 2025-11-18 03:36:36 ts/train.py:232 step:76K smpl:605K ep:889 epch:17.78 loss:0.017 grdn:0.213 lr:1.4e-05 updt_s:0.066 data_s:0.023
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INFO 2025-11-18 03:36:54 ts/train.py:232 step:76K smpl:606K ep:891 epch:17.82 loss:0.016 grdn:0.205 lr:1.4e-05 updt_s:0.066 data_s:0.028
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INFO 2025-11-18 03:37:14 ts/train.py:232 step:76K smpl:608K ep:894 epch:17.87 loss:0.017 grdn:0.218 lr:1.4e-05 updt_s:0.066 data_s:0.033
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| 396 |
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INFO 2025-11-18 03:37:34 ts/train.py:232 step:76K smpl:610K ep:896 epch:17.92 loss:0.016 grdn:0.206 lr:1.4e-05 updt_s:0.066 data_s:0.033
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| 397 |
+
INFO 2025-11-18 03:37:54 ts/train.py:232 step:76K smpl:611K ep:898 epch:17.96 loss:0.016 grdn:0.219 lr:1.3e-05 updt_s:0.066 data_s:0.033
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| 398 |
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INFO 2025-11-18 03:38:14 ts/train.py:232 step:77K smpl:613K ep:901 epch:18.01 loss:0.017 grdn:0.219 lr:1.3e-05 updt_s:0.066 data_s:0.032
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| 399 |
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INFO 2025-11-18 03:38:34 ts/train.py:232 step:77K smpl:614K ep:903 epch:18.06 loss:0.017 grdn:0.202 lr:1.3e-05 updt_s:0.066 data_s:0.032
|
| 400 |
+
INFO 2025-11-18 03:38:56 ts/train.py:232 step:77K smpl:616K ep:905 epch:18.11 loss:0.015 grdn:0.185 lr:1.3e-05 updt_s:0.067 data_s:0.046
|
| 401 |
+
INFO 2025-11-18 03:39:15 ts/train.py:232 step:77K smpl:618K ep:908 epch:18.15 loss:0.016 grdn:0.201 lr:1.3e-05 updt_s:0.066 data_s:0.025
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| 402 |
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INFO 2025-11-18 03:39:33 ts/train.py:232 step:77K smpl:619K ep:910 epch:18.20 loss:0.016 grdn:0.201 lr:1.2e-05 updt_s:0.066 data_s:0.025
|
| 403 |
+
INFO 2025-11-18 03:39:51 ts/train.py:232 step:78K smpl:621K ep:912 epch:18.25 loss:0.017 grdn:0.210 lr:1.2e-05 updt_s:0.066 data_s:0.024
|
| 404 |
+
INFO 2025-11-18 03:40:09 ts/train.py:232 step:78K smpl:622K ep:915 epch:18.29 loss:0.016 grdn:0.213 lr:1.2e-05 updt_s:0.066 data_s:0.022
|
| 405 |
+
INFO 2025-11-18 03:40:27 ts/train.py:232 step:78K smpl:624K ep:917 epch:18.34 loss:0.016 grdn:0.206 lr:1.2e-05 updt_s:0.066 data_s:0.023
|
| 406 |
+
INFO 2025-11-18 03:40:45 ts/train.py:232 step:78K smpl:626K ep:919 epch:18.39 loss:0.017 grdn:0.214 lr:1.1e-05 updt_s:0.065 data_s:0.024
|
| 407 |
+
INFO 2025-11-18 03:41:03 ts/train.py:232 step:78K smpl:627K ep:922 epch:18.44 loss:0.016 grdn:0.199 lr:1.1e-05 updt_s:0.066 data_s:0.024
|
| 408 |
+
INFO 2025-11-18 03:41:21 ts/train.py:232 step:79K smpl:629K ep:924 epch:18.48 loss:0.016 grdn:0.205 lr:1.1e-05 updt_s:0.066 data_s:0.023
|
| 409 |
+
INFO 2025-11-18 03:41:38 ts/train.py:232 step:79K smpl:630K ep:926 epch:18.53 loss:0.016 grdn:0.202 lr:1.1e-05 updt_s:0.066 data_s:0.022
|
| 410 |
+
INFO 2025-11-18 03:41:56 ts/train.py:232 step:79K smpl:632K ep:929 epch:18.58 loss:0.016 grdn:0.207 lr:1.1e-05 updt_s:0.066 data_s:0.023
|
| 411 |
+
INFO 2025-11-18 03:42:14 ts/train.py:232 step:79K smpl:634K ep:931 epch:18.62 loss:0.017 grdn:0.212 lr:1.0e-05 updt_s:0.066 data_s:0.023
|
| 412 |
+
INFO 2025-11-18 03:42:32 ts/train.py:232 step:79K smpl:635K ep:934 epch:18.67 loss:0.016 grdn:0.202 lr:1.0e-05 updt_s:0.066 data_s:0.022
|
| 413 |
+
INFO 2025-11-18 03:42:50 ts/train.py:232 step:80K smpl:637K ep:936 epch:18.72 loss:0.016 grdn:0.200 lr:1.0e-05 updt_s:0.066 data_s:0.022
|
| 414 |
+
INFO 2025-11-18 03:43:08 ts/train.py:232 step:80K smpl:638K ep:938 epch:18.76 loss:0.017 grdn:0.214 lr:9.9e-06 updt_s:0.065 data_s:0.024
|
| 415 |
+
INFO 2025-11-18 03:43:27 ts/train.py:232 step:80K smpl:640K ep:941 epch:18.81 loss:0.018 grdn:0.217 lr:9.7e-06 updt_s:0.065 data_s:0.029
|
| 416 |
+
INFO 2025-11-18 03:43:27 ts/train.py:241 Checkpoint policy after step 80000
|
| 417 |
+
INFO 2025-11-18 03:44:05 ts/train.py:232 step:80K smpl:642K ep:943 epch:18.86 loss:0.016 grdn:0.208 lr:9.5e-06 updt_s:0.066 data_s:0.033
|
| 418 |
+
INFO 2025-11-18 03:44:25 ts/train.py:232 step:80K smpl:643K ep:945 epch:18.91 loss:0.016 grdn:0.205 lr:9.4e-06 updt_s:0.065 data_s:0.033
|
| 419 |
+
INFO 2025-11-18 03:44:44 ts/train.py:232 step:81K smpl:645K ep:948 epch:18.95 loss:0.015 grdn:0.193 lr:9.2e-06 updt_s:0.066 data_s:0.032
|
| 420 |
+
INFO 2025-11-18 03:45:04 ts/train.py:232 step:81K smpl:646K ep:950 epch:19.00 loss:0.016 grdn:0.204 lr:9.0e-06 updt_s:0.067 data_s:0.032
|
| 421 |
+
INFO 2025-11-18 03:45:24 ts/train.py:232 step:81K smpl:648K ep:952 epch:19.05 loss:0.016 grdn:0.203 lr:8.8e-06 updt_s:0.066 data_s:0.034
|
| 422 |
+
INFO 2025-11-18 03:45:44 ts/train.py:232 step:81K smpl:650K ep:955 epch:19.09 loss:0.016 grdn:0.202 lr:8.6e-06 updt_s:0.066 data_s:0.032
|
| 423 |
+
INFO 2025-11-18 03:46:03 ts/train.py:232 step:81K smpl:651K ep:957 epch:19.14 loss:0.016 grdn:0.202 lr:8.5e-06 updt_s:0.066 data_s:0.028
|
| 424 |
+
INFO 2025-11-18 03:46:21 ts/train.py:232 step:82K smpl:653K ep:959 epch:19.19 loss:0.017 grdn:0.216 lr:8.3e-06 updt_s:0.066 data_s:0.024
|
| 425 |
+
INFO 2025-11-18 03:46:39 ts/train.py:232 step:82K smpl:654K ep:962 epch:19.23 loss:0.016 grdn:0.205 lr:8.1e-06 updt_s:0.066 data_s:0.023
|
| 426 |
+
INFO 2025-11-18 03:46:57 ts/train.py:232 step:82K smpl:656K ep:964 epch:19.28 loss:0.014 grdn:0.185 lr:7.9e-06 updt_s:0.067 data_s:0.024
|
| 427 |
+
INFO 2025-11-18 03:47:15 ts/train.py:232 step:82K smpl:658K ep:966 epch:19.33 loss:0.015 grdn:0.196 lr:7.8e-06 updt_s:0.066 data_s:0.024
|
| 428 |
+
INFO 2025-11-18 03:47:33 ts/train.py:232 step:82K smpl:659K ep:969 epch:19.38 loss:0.016 grdn:0.201 lr:7.6e-06 updt_s:0.065 data_s:0.024
|
| 429 |
+
INFO 2025-11-18 03:47:52 ts/train.py:232 step:83K smpl:661K ep:971 epch:19.42 loss:0.017 grdn:0.200 lr:7.4e-06 updt_s:0.066 data_s:0.026
|
| 430 |
+
INFO 2025-11-18 03:48:10 ts/train.py:232 step:83K smpl:662K ep:973 epch:19.47 loss:0.016 grdn:0.207 lr:7.3e-06 updt_s:0.066 data_s:0.023
|
| 431 |
+
INFO 2025-11-18 03:48:28 ts/train.py:232 step:83K smpl:664K ep:976 epch:19.52 loss:0.016 grdn:0.205 lr:7.1e-06 updt_s:0.066 data_s:0.027
|
| 432 |
+
INFO 2025-11-18 03:48:47 ts/train.py:232 step:83K smpl:666K ep:978 epch:19.56 loss:0.016 grdn:0.206 lr:7.0e-06 updt_s:0.066 data_s:0.027
|
| 433 |
+
INFO 2025-11-18 03:49:05 ts/train.py:232 step:83K smpl:667K ep:981 epch:19.61 loss:0.016 grdn:0.196 lr:6.8e-06 updt_s:0.066 data_s:0.026
|
| 434 |
+
INFO 2025-11-18 03:49:24 ts/train.py:232 step:84K smpl:669K ep:983 epch:19.66 loss:0.016 grdn:0.206 lr:6.6e-06 updt_s:0.066 data_s:0.025
|
| 435 |
+
INFO 2025-11-18 03:49:45 ts/train.py:232 step:84K smpl:670K ep:985 epch:19.70 loss:0.016 grdn:0.207 lr:6.5e-06 updt_s:0.066 data_s:0.041
|
| 436 |
+
INFO 2025-11-18 03:50:03 ts/train.py:232 step:84K smpl:672K ep:988 epch:19.75 loss:0.017 grdn:0.217 lr:6.3e-06 updt_s:0.066 data_s:0.022
|
| 437 |
+
INFO 2025-11-18 03:50:22 ts/train.py:232 step:84K smpl:674K ep:990 epch:19.80 loss:0.016 grdn:0.204 lr:6.2e-06 updt_s:0.065 data_s:0.028
|
| 438 |
+
INFO 2025-11-18 03:50:41 ts/train.py:232 step:84K smpl:675K ep:992 epch:19.85 loss:0.015 grdn:0.198 lr:6.0e-06 updt_s:0.066 data_s:0.030
|
| 439 |
+
INFO 2025-11-18 03:51:00 ts/train.py:232 step:85K smpl:677K ep:995 epch:19.89 loss:0.016 grdn:0.197 lr:5.9e-06 updt_s:0.065 data_s:0.027
|
| 440 |
+
INFO 2025-11-18 03:51:19 ts/train.py:232 step:85K smpl:678K ep:997 epch:19.94 loss:0.015 grdn:0.196 lr:5.7e-06 updt_s:0.066 data_s:0.028
|
| 441 |
+
INFO 2025-11-18 03:51:37 ts/train.py:232 step:85K smpl:680K ep:999 epch:19.99 loss:0.016 grdn:0.200 lr:5.6e-06 updt_s:0.066 data_s:0.028
|
| 442 |
+
INFO 2025-11-18 03:51:56 ts/train.py:232 step:85K smpl:682K ep:1K epch:20.03 loss:0.016 grdn:0.202 lr:5.4e-06 updt_s:0.065 data_s:0.029
|
| 443 |
+
INFO 2025-11-18 03:52:15 ts/train.py:232 step:85K smpl:683K ep:1K epch:20.08 loss:0.016 grdn:0.206 lr:5.3e-06 updt_s:0.066 data_s:0.027
|
| 444 |
+
INFO 2025-11-18 03:52:33 ts/train.py:232 step:86K smpl:685K ep:1K epch:20.13 loss:0.015 grdn:0.198 lr:5.1e-06 updt_s:0.066 data_s:0.025
|
| 445 |
+
INFO 2025-11-18 03:52:51 ts/train.py:232 step:86K smpl:686K ep:1K epch:20.18 loss:0.018 grdn:0.217 lr:5.0e-06 updt_s:0.066 data_s:0.022
|
| 446 |
+
INFO 2025-11-18 03:53:09 ts/train.py:232 step:86K smpl:688K ep:1K epch:20.22 loss:0.016 grdn:0.200 lr:4.9e-06 updt_s:0.066 data_s:0.023
|
| 447 |
+
INFO 2025-11-18 03:53:26 ts/train.py:232 step:86K smpl:690K ep:1K epch:20.27 loss:0.017 grdn:0.209 lr:4.7e-06 updt_s:0.066 data_s:0.021
|
| 448 |
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INFO 2025-11-18 03:53:44 ts/train.py:232 step:86K smpl:691K ep:1K epch:20.32 loss:0.016 grdn:0.205 lr:4.6e-06 updt_s:0.066 data_s:0.024
|
| 449 |
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INFO 2025-11-18 03:54:03 ts/train.py:232 step:87K smpl:693K ep:1K epch:20.36 loss:0.015 grdn:0.192 lr:4.5e-06 updt_s:0.065 data_s:0.025
|
| 450 |
+
INFO 2025-11-18 03:54:21 ts/train.py:232 step:87K smpl:694K ep:1K epch:20.41 loss:0.015 grdn:0.192 lr:4.3e-06 updt_s:0.067 data_s:0.022
|
| 451 |
+
INFO 2025-11-18 03:54:39 ts/train.py:232 step:87K smpl:696K ep:1K epch:20.46 loss:0.017 grdn:0.207 lr:4.2e-06 updt_s:0.066 data_s:0.024
|
| 452 |
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INFO 2025-11-18 03:54:57 ts/train.py:232 step:87K smpl:698K ep:1K epch:20.50 loss:0.015 grdn:0.191 lr:4.1e-06 updt_s:0.067 data_s:0.024
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| 453 |
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INFO 2025-11-18 03:55:15 ts/train.py:232 step:87K smpl:699K ep:1K epch:20.55 loss:0.016 grdn:0.202 lr:4.0e-06 updt_s:0.066 data_s:0.025
|
| 454 |
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INFO 2025-11-18 03:55:34 ts/train.py:232 step:88K smpl:701K ep:1K epch:20.60 loss:0.015 grdn:0.197 lr:3.8e-06 updt_s:0.066 data_s:0.025
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| 455 |
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INFO 2025-11-18 03:55:51 ts/train.py:232 step:88K smpl:702K ep:1K epch:20.65 loss:0.017 grdn:0.211 lr:3.7e-06 updt_s:0.066 data_s:0.023
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| 456 |
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INFO 2025-11-18 03:56:10 ts/train.py:232 step:88K smpl:704K ep:1K epch:20.69 loss:0.014 grdn:0.191 lr:3.6e-06 updt_s:0.067 data_s:0.024
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| 457 |
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INFO 2025-11-18 03:56:27 ts/train.py:232 step:88K smpl:706K ep:1K epch:20.74 loss:0.017 grdn:0.208 lr:3.5e-06 updt_s:0.066 data_s:0.022
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| 458 |
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INFO 2025-11-18 03:56:46 ts/train.py:232 step:88K smpl:707K ep:1K epch:20.79 loss:0.015 grdn:0.197 lr:3.4e-06 updt_s:0.066 data_s:0.028
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| 459 |
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INFO 2025-11-18 03:57:06 ts/train.py:232 step:89K smpl:709K ep:1K epch:20.83 loss:0.016 grdn:0.201 lr:3.3e-06 updt_s:0.066 data_s:0.032
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| 460 |
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INFO 2025-11-18 03:57:26 ts/train.py:232 step:89K smpl:710K ep:1K epch:20.88 loss:0.014 grdn:0.191 lr:3.1e-06 updt_s:0.066 data_s:0.033
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| 461 |
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INFO 2025-11-18 03:57:45 ts/train.py:232 step:89K smpl:712K ep:1K epch:20.93 loss:0.016 grdn:0.207 lr:3.0e-06 updt_s:0.066 data_s:0.030
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| 462 |
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INFO 2025-11-18 03:58:06 ts/train.py:232 step:89K smpl:714K ep:1K epch:20.97 loss:0.015 grdn:0.193 lr:2.9e-06 updt_s:0.067 data_s:0.033
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| 463 |
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INFO 2025-11-18 03:58:25 ts/train.py:232 step:89K smpl:715K ep:1K epch:21.02 loss:0.015 grdn:0.193 lr:2.8e-06 updt_s:0.067 data_s:0.028
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| 464 |
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INFO 2025-11-18 03:58:44 ts/train.py:232 step:90K smpl:717K ep:1K epch:21.07 loss:0.016 grdn:0.208 lr:2.7e-06 updt_s:0.066 data_s:0.030
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| 465 |
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INFO 2025-11-18 03:59:03 ts/train.py:232 step:90K smpl:718K ep:1K epch:21.12 loss:0.015 grdn:0.193 lr:2.6e-06 updt_s:0.066 data_s:0.028
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| 466 |
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INFO 2025-11-18 03:59:22 ts/train.py:232 step:90K smpl:720K ep:1K epch:21.16 loss:0.016 grdn:0.202 lr:2.5e-06 updt_s:0.066 data_s:0.026
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| 467 |
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INFO 2025-11-18 03:59:40 ts/train.py:232 step:90K smpl:722K ep:1K epch:21.21 loss:0.016 grdn:0.206 lr:2.4e-06 updt_s:0.066 data_s:0.026
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| 468 |
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INFO 2025-11-18 03:59:58 ts/train.py:232 step:90K smpl:723K ep:1K epch:21.26 loss:0.016 grdn:0.197 lr:2.3e-06 updt_s:0.065 data_s:0.024
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| 469 |
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INFO 2025-11-18 04:00:17 ts/train.py:232 step:91K smpl:725K ep:1K epch:21.30 loss:0.016 grdn:0.204 lr:2.2e-06 updt_s:0.066 data_s:0.027
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| 470 |
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INFO 2025-11-18 04:00:38 ts/train.py:232 step:91K smpl:726K ep:1K epch:21.35 loss:0.015 grdn:0.194 lr:2.1e-06 updt_s:0.066 data_s:0.039
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| 471 |
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INFO 2025-11-18 04:00:57 ts/train.py:232 step:91K smpl:728K ep:1K epch:21.40 loss:0.016 grdn:0.198 lr:2.0e-06 updt_s:0.066 data_s:0.027
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| 472 |
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INFO 2025-11-18 04:01:15 ts/train.py:232 step:91K smpl:730K ep:1K epch:21.44 loss:0.015 grdn:0.196 lr:2.0e-06 updt_s:0.066 data_s:0.024
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| 473 |
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INFO 2025-11-18 04:01:33 ts/train.py:232 step:91K smpl:731K ep:1K epch:21.49 loss:0.016 grdn:0.203 lr:1.9e-06 updt_s:0.067 data_s:0.022
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| 474 |
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INFO 2025-11-18 04:01:51 ts/train.py:232 step:92K smpl:733K ep:1K epch:21.54 loss:0.016 grdn:0.202 lr:1.8e-06 updt_s:0.067 data_s:0.023
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| 475 |
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INFO 2025-11-18 04:02:09 ts/train.py:232 step:92K smpl:734K ep:1K epch:21.59 loss:0.016 grdn:0.206 lr:1.7e-06 updt_s:0.066 data_s:0.024
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| 476 |
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INFO 2025-11-18 04:02:27 ts/train.py:232 step:92K smpl:736K ep:1K epch:21.63 loss:0.016 grdn:0.199 lr:1.6e-06 updt_s:0.066 data_s:0.026
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| 477 |
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INFO 2025-11-18 04:02:46 ts/train.py:232 step:92K smpl:738K ep:1K epch:21.68 loss:0.015 grdn:0.200 lr:1.5e-06 updt_s:0.065 data_s:0.025
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| 478 |
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INFO 2025-11-18 04:03:04 ts/train.py:232 step:92K smpl:739K ep:1K epch:21.73 loss:0.015 grdn:0.190 lr:1.5e-06 updt_s:0.066 data_s:0.026
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| 479 |
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INFO 2025-11-18 04:03:23 ts/train.py:232 step:93K smpl:741K ep:1K epch:21.77 loss:0.016 grdn:0.201 lr:1.4e-06 updt_s:0.065 data_s:0.026
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| 480 |
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INFO 2025-11-18 04:03:42 ts/train.py:232 step:93K smpl:742K ep:1K epch:21.82 loss:0.015 grdn:0.191 lr:1.3e-06 updt_s:0.066 data_s:0.028
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| 481 |
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INFO 2025-11-18 04:04:00 ts/train.py:232 step:93K smpl:744K ep:1K epch:21.87 loss:0.016 grdn:0.207 lr:1.3e-06 updt_s:0.066 data_s:0.026
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| 482 |
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INFO 2025-11-18 04:04:19 ts/train.py:232 step:93K smpl:746K ep:1K epch:21.92 loss:0.015 grdn:0.194 lr:1.2e-06 updt_s:0.066 data_s:0.026
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| 483 |
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INFO 2025-11-18 04:04:38 ts/train.py:232 step:93K smpl:747K ep:1K epch:21.96 loss:0.014 grdn:0.188 lr:1.1e-06 updt_s:0.067 data_s:0.029
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| 484 |
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INFO 2025-11-18 04:04:57 ts/train.py:232 step:94K smpl:749K ep:1K epch:22.01 loss:0.015 grdn:0.193 lr:1.0e-06 updt_s:0.066 data_s:0.029
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| 485 |
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INFO 2025-11-18 04:05:16 ts/train.py:232 step:94K smpl:750K ep:1K epch:22.06 loss:0.015 grdn:0.191 lr:9.9e-07 updt_s:0.067 data_s:0.027
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| 486 |
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INFO 2025-11-18 04:05:35 ts/train.py:232 step:94K smpl:752K ep:1K epch:22.10 loss:0.015 grdn:0.203 lr:9.2e-07 updt_s:0.067 data_s:0.027
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| 487 |
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INFO 2025-11-18 04:05:53 ts/train.py:232 step:94K smpl:754K ep:1K epch:22.15 loss:0.015 grdn:0.201 lr:8.6e-07 updt_s:0.067 data_s:0.024
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| 488 |
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INFO 2025-11-18 04:06:11 ts/train.py:232 step:94K smpl:755K ep:1K epch:22.20 loss:0.015 grdn:0.199 lr:8.1e-07 updt_s:0.067 data_s:0.023
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| 489 |
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INFO 2025-11-18 04:06:30 ts/train.py:232 step:95K smpl:757K ep:1K epch:22.24 loss:0.015 grdn:0.198 lr:7.5e-07 updt_s:0.067 data_s:0.024
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| 490 |
+
INFO 2025-11-18 04:06:48 ts/train.py:232 step:95K smpl:758K ep:1K epch:22.29 loss:0.015 grdn:0.194 lr:7.0e-07 updt_s:0.066 data_s:0.023
|
| 491 |
+
INFO 2025-11-18 04:07:05 ts/train.py:232 step:95K smpl:760K ep:1K epch:22.34 loss:0.016 grdn:0.200 lr:6.5e-07 updt_s:0.067 data_s:0.022
|
| 492 |
+
INFO 2025-11-18 04:07:23 ts/train.py:232 step:95K smpl:762K ep:1K epch:22.39 loss:0.015 grdn:0.197 lr:6.0e-07 updt_s:0.066 data_s:0.024
|
| 493 |
+
INFO 2025-11-18 04:07:42 ts/train.py:232 step:95K smpl:763K ep:1K epch:22.43 loss:0.015 grdn:0.189 lr:5.5e-07 updt_s:0.066 data_s:0.025
|
| 494 |
+
INFO 2025-11-18 04:08:00 ts/train.py:232 step:96K smpl:765K ep:1K epch:22.48 loss:0.016 grdn:0.202 lr:5.0e-07 updt_s:0.066 data_s:0.023
|
| 495 |
+
INFO 2025-11-18 04:08:18 ts/train.py:232 step:96K smpl:766K ep:1K epch:22.53 loss:0.016 grdn:0.204 lr:4.6e-07 updt_s:0.067 data_s:0.023
|
| 496 |
+
INFO 2025-11-18 04:08:36 ts/train.py:232 step:96K smpl:768K ep:1K epch:22.57 loss:0.014 grdn:0.193 lr:4.2e-07 updt_s:0.066 data_s:0.025
|
| 497 |
+
INFO 2025-11-18 04:08:54 ts/train.py:232 step:96K smpl:770K ep:1K epch:22.62 loss:0.016 grdn:0.198 lr:3.8e-07 updt_s:0.066 data_s:0.025
|
| 498 |
+
INFO 2025-11-18 04:09:12 ts/train.py:232 step:96K smpl:771K ep:1K epch:22.67 loss:0.016 grdn:0.195 lr:3.4e-07 updt_s:0.066 data_s:0.023
|
| 499 |
+
INFO 2025-11-18 04:09:30 ts/train.py:232 step:97K smpl:773K ep:1K epch:22.71 loss:0.015 grdn:0.190 lr:3.0e-07 updt_s:0.066 data_s:0.023
|
| 500 |
+
INFO 2025-11-18 04:09:48 ts/train.py:232 step:97K smpl:774K ep:1K epch:22.76 loss:0.015 grdn:0.198 lr:2.7e-07 updt_s:0.067 data_s:0.023
|
| 501 |
+
INFO 2025-11-18 04:10:08 ts/train.py:232 step:97K smpl:776K ep:1K epch:22.81 loss:0.015 grdn:0.196 lr:2.4e-07 updt_s:0.065 data_s:0.035
|
| 502 |
+
INFO 2025-11-18 04:10:28 ts/train.py:232 step:97K smpl:778K ep:1K epch:22.86 loss:0.015 grdn:0.194 lr:2.1e-07 updt_s:0.066 data_s:0.032
|
| 503 |
+
INFO 2025-11-18 04:10:48 ts/train.py:232 step:97K smpl:779K ep:1K epch:22.90 loss:0.015 grdn:0.201 lr:1.8e-07 updt_s:0.066 data_s:0.032
|
| 504 |
+
INFO 2025-11-18 04:11:08 ts/train.py:232 step:98K smpl:781K ep:1K epch:22.95 loss:0.016 grdn:0.207 lr:1.6e-07 updt_s:0.066 data_s:0.033
|
| 505 |
+
INFO 2025-11-18 04:11:30 ts/train.py:232 step:98K smpl:782K ep:1K epch:23.00 loss:0.014 grdn:0.194 lr:1.3e-07 updt_s:0.066 data_s:0.042
|
| 506 |
+
INFO 2025-11-18 04:11:49 ts/train.py:232 step:98K smpl:784K ep:1K epch:23.04 loss:0.016 grdn:0.200 lr:1.1e-07 updt_s:0.066 data_s:0.032
|
| 507 |
+
INFO 2025-11-18 04:12:08 ts/train.py:232 step:98K smpl:786K ep:1K epch:23.09 loss:0.015 grdn:0.194 lr:9.0e-08 updt_s:0.066 data_s:0.028
|
| 508 |
+
INFO 2025-11-18 04:12:26 ts/train.py:232 step:98K smpl:787K ep:1K epch:23.14 loss:0.016 grdn:0.200 lr:7.2e-08 updt_s:0.065 data_s:0.023
|
| 509 |
+
INFO 2025-11-18 04:12:44 ts/train.py:232 step:99K smpl:789K ep:1K epch:23.18 loss:0.016 grdn:0.201 lr:5.6e-08 updt_s:0.065 data_s:0.024
|
| 510 |
+
INFO 2025-11-18 04:13:02 ts/train.py:232 step:99K smpl:790K ep:1K epch:23.23 loss:0.016 grdn:0.206 lr:4.2e-08 updt_s:0.066 data_s:0.025
|
| 511 |
+
INFO 2025-11-18 04:13:20 ts/train.py:232 step:99K smpl:792K ep:1K epch:23.28 loss:0.016 grdn:0.201 lr:3.0e-08 updt_s:0.066 data_s:0.025
|
| 512 |
+
INFO 2025-11-18 04:13:38 ts/train.py:232 step:99K smpl:794K ep:1K epch:23.33 loss:0.015 grdn:0.188 lr:2.0e-08 updt_s:0.065 data_s:0.025
|
| 513 |
+
INFO 2025-11-18 04:13:56 ts/train.py:232 step:99K smpl:795K ep:1K epch:23.37 loss:0.016 grdn:0.200 lr:1.2e-08 updt_s:0.066 data_s:0.022
|
| 514 |
+
INFO 2025-11-18 04:14:14 ts/train.py:232 step:100K smpl:797K ep:1K epch:23.42 loss:0.015 grdn:0.196 lr:6.3e-09 updt_s:0.066 data_s:0.022
|
| 515 |
+
INFO 2025-11-18 04:14:32 ts/train.py:232 step:100K smpl:798K ep:1K epch:23.47 loss:0.016 grdn:0.207 lr:2.3e-09 updt_s:0.064 data_s:0.023
|
| 516 |
+
INFO 2025-11-18 04:14:49 ts/train.py:232 step:100K smpl:800K ep:1K epch:23.51 loss:0.016 grdn:0.196 lr:3.3e-10 updt_s:0.065 data_s:0.021
|
| 517 |
+
INFO 2025-11-18 04:14:49 ts/train.py:241 Checkpoint policy after step 100000
|
| 518 |
+
INFO 2025-11-18 04:15:04 ts/train.py:283 End of training
|
diffusion_anubis_fold_towel/wandb/run-20251118_013752-9jmkckoo/files/requirements.txt
ADDED
|
@@ -0,0 +1,264 @@
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|
|
|
|
|
|
|
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|
|
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|
|
|
|
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|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
| 1 |
+
setuptools==79.0.0
|
| 2 |
+
wheel==0.45.1
|
| 3 |
+
pip==25.0.1
|
| 4 |
+
wcwidth==0.2.13
|
| 5 |
+
triton==3.2.0
|
| 6 |
+
pytz==2025.2
|
| 7 |
+
nvidia-cusparselt-cu12==0.6.2
|
| 8 |
+
mpmath==1.3.0
|
| 9 |
+
Farama-Notifications==0.0.4
|
| 10 |
+
asciitree==0.3.3
|
| 11 |
+
antlr4-python3-runtime==4.9.3
|
| 12 |
+
zipp==3.21.0
|
| 13 |
+
xxhash==3.5.0
|
| 14 |
+
urllib3==2.4.0
|
| 15 |
+
tzdata==2025.2
|
| 16 |
+
typing_extensions==4.13.2
|
| 17 |
+
tqdm==4.67.1
|
| 18 |
+
uv==0.7.3
|
| 19 |
+
toml==0.10.2
|
| 20 |
+
termcolor==3.0.1
|
| 21 |
+
sympy==1.13.1
|
| 22 |
+
soupsieve==2.7
|
| 23 |
+
smmap==5.0.2
|
| 24 |
+
six==1.17.0
|
| 25 |
+
setproctitle==1.3.5
|
| 26 |
+
safetensors==0.5.3
|
| 27 |
+
regex==2024.11.6
|
| 28 |
+
pyzmq==26.4.0
|
| 29 |
+
PyYAML==6.0.2
|
| 30 |
+
PySocks==1.7.1
|
| 31 |
+
pycparser==2.22
|
| 32 |
+
pyarrow==19.0.1
|
| 33 |
+
pyarrow==19.0.1
|
| 34 |
+
psutil==7.0.0
|
| 35 |
+
protobuf==4.21.12
|
| 36 |
+
propcache==0.3.1
|
| 37 |
+
prompt_toolkit==3.0.51
|
| 38 |
+
platformdirs==4.3.7
|
| 39 |
+
pillow==11.2.1
|
| 40 |
+
pillow==11.1.0
|
| 41 |
+
pfzy==0.3.4
|
| 42 |
+
packaging==25.0
|
| 43 |
+
orderly-set==5.4.0
|
| 44 |
+
nvidia-nvtx-cu12==12.4.127
|
| 45 |
+
nvidia-nvjitlink-cu12==12.4.127
|
| 46 |
+
nvidia-nccl-cu12==2.21.5
|
| 47 |
+
nvidia-curand-cu12==10.3.5.147
|
| 48 |
+
nvidia-cufft-cu12==11.2.1.3
|
| 49 |
+
nvidia-cuda-runtime-cu12==12.4.127
|
| 50 |
+
nvidia-cuda-nvrtc-cu12==12.4.127
|
| 51 |
+
nvidia-cuda-cupti-cu12==12.4.127
|
| 52 |
+
nvidia-cublas-cu12==12.4.5.8
|
| 53 |
+
networkx==3.4.2
|
| 54 |
+
mypy-extensions==1.0.0
|
| 55 |
+
mergedeep==1.3.4
|
| 56 |
+
MarkupSafe==3.0.2
|
| 57 |
+
llvmlite==0.44.0
|
| 58 |
+
itsdangerous==2.2.0
|
| 59 |
+
imageio-ffmpeg==0.6.0
|
| 60 |
+
idna==3.10
|
| 61 |
+
hf_transfer==0.1.9
|
| 62 |
+
fsspec==2024.12.0
|
| 63 |
+
frozenlist==1.6.0
|
| 64 |
+
filelock==3.18.0
|
| 65 |
+
fasteners==0.19
|
| 66 |
+
evdev==1.9.1
|
| 67 |
+
einops==0.8.1
|
| 68 |
+
dill==0.3.8
|
| 69 |
+
cmake==4.0.0
|
| 70 |
+
cloudpickle==3.1.1
|
| 71 |
+
click==8.1.8
|
| 72 |
+
charset-normalizer==3.4.1
|
| 73 |
+
certifi==2025.1.31
|
| 74 |
+
blinker==1.9.0
|
| 75 |
+
av==14.3.0
|
| 76 |
+
attrs==25.3.0
|
| 77 |
+
async-timeout==5.0.1
|
| 78 |
+
annotated-types==0.7.0
|
| 79 |
+
aiohappyeyeballs==2.6.1
|
| 80 |
+
Werkzeug==3.1.3
|
| 81 |
+
typing-inspection==0.4.0
|
| 82 |
+
typing-inspect==0.9.0
|
| 83 |
+
sentry-sdk==2.26.1
|
| 84 |
+
requests==2.32.3
|
| 85 |
+
pyyaml-include==1.4.1
|
| 86 |
+
python-xlib==0.33
|
| 87 |
+
python-dateutil==2.9.0.post0
|
| 88 |
+
pydantic_core==2.33.1
|
| 89 |
+
opencv-python-headless==4.11.0.86
|
| 90 |
+
omegaconf==2.3.0
|
| 91 |
+
nvidia-cusparse-cu12==12.3.1.170
|
| 92 |
+
nvidia-cudnn-cu12==9.1.0.70
|
| 93 |
+
numcodecs==0.13.1
|
| 94 |
+
numba==0.61.2
|
| 95 |
+
multiprocess==0.70.16
|
| 96 |
+
multidict==6.4.3
|
| 97 |
+
jsonlines==4.0.0
|
| 98 |
+
Jinja2==3.1.6
|
| 99 |
+
inquirerpy==0.3.4
|
| 100 |
+
importlib_metadata==8.6.1
|
| 101 |
+
imageio==2.37.0
|
| 102 |
+
h5py==3.13.0
|
| 103 |
+
gymnasium==0.29.1
|
| 104 |
+
gitdb==4.0.12
|
| 105 |
+
docker-pycreds==0.4.0
|
| 106 |
+
deepdiff==8.4.2
|
| 107 |
+
cffi==1.17.1
|
| 108 |
+
beautifulsoup4==4.13.4
|
| 109 |
+
aiosignal==1.3.2
|
| 110 |
+
zarr==2.18.3
|
| 111 |
+
yarl==1.20.0
|
| 112 |
+
pynput==1.8.1
|
| 113 |
+
pymunk==6.11.1
|
| 114 |
+
pydantic==2.11.3
|
| 115 |
+
pandas==2.2.3
|
| 116 |
+
nvidia-cusolver-cu12==11.6.1.9
|
| 117 |
+
GitPython==3.1.44
|
| 118 |
+
Flask==3.1.0
|
| 119 |
+
tomli==2.2.1
|
| 120 |
+
wandb==0.19.9
|
| 121 |
+
torch==2.6.0
|
| 122 |
+
diffusers==0.33.1
|
| 123 |
+
aiohttp==3.11.18
|
| 124 |
+
torchvision==0.21.0
|
| 125 |
+
datasets==3.5.0
|
| 126 |
+
PyOpenGL==3.1.9
|
| 127 |
+
glfw==2.9.0
|
| 128 |
+
wrapt==1.17.2
|
| 129 |
+
scipy==1.15.2
|
| 130 |
+
pyparsing==3.2.3
|
| 131 |
+
lxml==5.3.2
|
| 132 |
+
absl-py==2.2.2
|
| 133 |
+
labmaze==1.0.6
|
| 134 |
+
dm-tree==0.1.9
|
| 135 |
+
dm-env==1.6
|
| 136 |
+
gym-aloha==0.1.1
|
| 137 |
+
argcomplete==3.6.2
|
| 138 |
+
tokenizers==0.21.1
|
| 139 |
+
asttokens==3.0.0
|
| 140 |
+
decorator==5.2.1
|
| 141 |
+
exceptiongroup==1.2.2
|
| 142 |
+
executing==2.1.0
|
| 143 |
+
jupyterlab_widgets==3.0.14
|
| 144 |
+
parso==0.8.4
|
| 145 |
+
pickleshare==0.7.5
|
| 146 |
+
ptyprocess==0.7.0
|
| 147 |
+
pure_eval==0.2.3
|
| 148 |
+
Pygments==2.19.1
|
| 149 |
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opencv-python==4.11.0.86
|
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lazy_loader==0.4
|
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scikit-image==0.25.2
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gdown==5.2.0
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pluggy==1.5.0
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|
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|
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|
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future==1.0.0
|
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pyserial==3.5
|
| 227 |
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draccus==0.10.0
|
| 228 |
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transformers==4.51.3
|
| 229 |
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lerobot==0.1.0
|
| 230 |
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bottle==0.12.25
|
| 231 |
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waitress==3.0.2
|
| 232 |
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accelerate==1.6.0
|
| 233 |
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TorchCodec==0.2.1
|
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kiwisolver==1.4.9
|
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|
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|
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|
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|
| 239 |
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typer-slim==0.20.0
|
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sniffio==1.3.1
|
| 241 |
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shellingham==1.5.4
|
| 242 |
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hf-xet==1.2.0
|
| 243 |
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h11==0.16.0
|
| 244 |
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httpcore==1.0.9
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anyio==4.11.0
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| 246 |
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httpx==0.28.1
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huggingface-hub==0.36.0
|
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tabletop_sim==0.0.0
|
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|
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backports.tarfile==1.2.0
|
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importlib_metadata==8.0.0
|
| 252 |
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inflect==7.3.1
|
| 253 |
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jaraco.collections==5.1.0
|
| 254 |
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jaraco.context==5.3.0
|
| 255 |
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jaraco.functools==4.0.1
|
| 256 |
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jaraco.text==3.12.1
|
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|
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|
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|
| 260 |
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tomli==2.0.1
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| 261 |
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typeguard==4.3.0
|
| 262 |
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typing_extensions==4.12.2
|
| 263 |
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wheel==0.45.1
|
| 264 |
+
zipp==3.19.2
|
diffusion_anubis_fold_towel/wandb/run-20251118_013752-9jmkckoo/files/wandb-metadata.json
ADDED
|
@@ -0,0 +1,98 @@
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|
|
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|
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|
|
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|
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|
| 1 |
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{
|
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| 9 |
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| 11 |
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|
| 12 |
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],
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| 18 |
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| 19 |
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| 22 |
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},
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| 25 |
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| 27 |
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| 51 |
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| 52 |
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| 53 |
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"cluster_name": "cluster",
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| 54 |
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| 63 |
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| 64 |
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| 65 |
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| 66 |
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"job_user": "euijinrnd",
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"jobid": "16532",
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| 69 |
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| 70 |
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| 71 |
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"prio_process": "0",
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"step_tasks_per_node": "1",
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"stepid": "0",
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"submit_dir": "/home/euijinrnd/workspace/lerobot",
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},
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}
|
diffusion_anubis_fold_towel/wandb/run-20251118_013752-9jmkckoo/files/wandb-summary.json
ADDED
|
@@ -0,0 +1 @@
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|
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|
| 1 |
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{"train/epochs":23.514196696255365,"_wandb":{"runtime":9431},"train/lr":3.298127591122574e-10,"_step":100000,"train/update_s":0.06529190188797657,"_runtime":9431.922480348,"_timestamp":1.7634068894828126e+09,"train/episodes":1175.7098348127681,"train/grad_norm":0.19627147464081646,"train/steps":100000,"train/loss":0.015586143255932257,"train/dataloading_s":0.021492825771565548,"train/samples":800000}
|
diffusion_anubis_fold_towel/wandb/run-20251118_013752-9jmkckoo/logs/debug-core.log
ADDED
|
@@ -0,0 +1,13 @@
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|
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|
| 1 |
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{"time":"2025-11-18T01:37:52.215397636+09:00","level":"INFO","msg":"main: starting server","port-filename":"/tmp/tmpj8l1ey4o/port-2405445.txt","pid":2405445,"log-level":0,"disable-analytics":false,"shutdown-on-parent-exit":false}
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{"time":"2025-11-18T01:37:52.216040589+09:00","level":"INFO","msg":"server is running","addr":{"IP":"127.0.0.1","Port":40557,"Zone":""}}
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{"time":"2025-11-18T01:37:52.216125927+09:00","level":"INFO","msg":"Will exit if parent process dies.","ppid":2405445}
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{"time":"2025-11-18T01:37:52.409360218+09:00","level":"INFO","msg":"connection: ManageConnectionData: new connection created","id":"127.0.0.1:42150"}
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| 5 |
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{"time":"2025-11-18T01:37:52.456407279+09:00","level":"INFO","msg":"handleInformInit: received","streamId":"9jmkckoo","id":"127.0.0.1:42150"}
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| 6 |
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{"time":"2025-11-18T01:37:52.767786331+09:00","level":"INFO","msg":"handleInformInit: stream started","streamId":"9jmkckoo","id":"127.0.0.1:42150"}
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| 7 |
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{"time":"2025-11-18T04:15:04.367921498+09:00","level":"INFO","msg":"handleInformTeardown: server teardown initiated","id":"127.0.0.1:42150"}
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| 8 |
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{"time":"2025-11-18T04:15:04.374288977+09:00","level":"INFO","msg":"connection: closing","id":"127.0.0.1:42150"}
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| 9 |
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{"time":"2025-11-18T04:15:04.374375747+09:00","level":"INFO","msg":"connection: closed successfully","id":"127.0.0.1:42150"}
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| 10 |
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{"time":"2025-11-18T04:15:04.374381486+09:00","level":"INFO","msg":"server is shutting down"}
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| 11 |
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{"time":"2025-11-18T04:15:05.827985693+09:00","level":"INFO","msg":"handleInformTeardown: server shutdown complete","id":"127.0.0.1:42150"}
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| 12 |
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{"time":"2025-11-18T04:15:05.82800358+09:00","level":"INFO","msg":"connection: ManageConnectionData: connection closed","id":"127.0.0.1:42150"}
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| 13 |
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{"time":"2025-11-18T04:15:05.828013895+09:00","level":"INFO","msg":"server is closed"}
|
diffusion_anubis_fold_towel/wandb/run-20251118_013752-9jmkckoo/logs/debug-internal.log
ADDED
|
@@ -0,0 +1,15 @@
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|
|
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|
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|
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|
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|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
| 1 |
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{"time":"2025-11-18T01:37:52.45738267+09:00","level":"INFO","msg":"stream: starting","core version":"0.19.9","symlink path":"outputs/train/2025-11-18/01-37-50_diffusion/wandb/run-20251118_013752-9jmkckoo/logs/debug-core.log"}
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| 2 |
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{"time":"2025-11-18T01:37:52.767747172+09:00","level":"INFO","msg":"created new stream","id":"9jmkckoo"}
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| 3 |
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{"time":"2025-11-18T01:37:52.767782145+09:00","level":"INFO","msg":"stream: started","id":"9jmkckoo"}
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| 4 |
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{"time":"2025-11-18T01:37:52.768509524+09:00","level":"INFO","msg":"handler: started","stream_id":"9jmkckoo"}
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| 5 |
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| 6 |
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| 7 |
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| 8 |
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{"time":"2025-11-18T04:15:04.374330289+09:00","level":"INFO","msg":"stream: closing","id":"9jmkckoo"}
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| 9 |
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{"time":"2025-11-18T04:15:04.374406914+09:00","level":"INFO","msg":"Stopping system monitor"}
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| 10 |
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{"time":"2025-11-18T04:15:04.380827613+09:00","level":"INFO","msg":"Stopped system monitor"}
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| 11 |
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{"time":"2025-11-18T04:15:05.488452567+09:00","level":"INFO","msg":"fileTransfer: Close: file transfer manager closed"}
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| 12 |
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{"time":"2025-11-18T04:15:05.827001228+09:00","level":"INFO","msg":"handler: closed","stream_id":"9jmkckoo"}
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| 13 |
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{"time":"2025-11-18T04:15:05.827041618+09:00","level":"INFO","msg":"writer: Close: closed","stream_id":"9jmkckoo"}
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| 14 |
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{"time":"2025-11-18T04:15:05.827065124+09:00","level":"INFO","msg":"sender: closed","stream_id":"9jmkckoo"}
|
| 15 |
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|
diffusion_anubis_fold_towel/wandb/run-20251118_013752-9jmkckoo/logs/debug.log
ADDED
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2025-11-18 01:37:52,447 INFO MainThread:2405445 [wandb_setup.py:_flush():67] Current SDK version is 0.19.9
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2025-11-18 01:37:52,447 INFO MainThread:2405445 [wandb_setup.py:_flush():67] Loading settings from /home/euijinrnd/workspace/lerobot/wandb/settings
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2025-11-18 01:37:52,448 INFO MainThread:2405445 [wandb_init.py:init():786] wandb.init called with sweep_config: {}
|
| 10 |
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config: {'dataset': {'repo_id': 'anubis_fold_towel__lerobot', 'root': '/data1/euijinrnd/hf_home_euijin/lerobot/lerobot/anubis_fold_towel__lerobot', 'episodes': None, 'image_transforms': {'enable': False, 'max_num_transforms': 3, 'random_order': False, 'tfs': {'brightness': {'weight': 1.0, 'type': 'ColorJitter', 'kwargs': {'brightness': [0.8, 1.2]}}, 'contrast': {'weight': 1.0, 'type': 'ColorJitter', 'kwargs': {'contrast': [0.8, 1.2]}}, 'saturation': {'weight': 1.0, 'type': 'ColorJitter', 'kwargs': {'saturation': [0.5, 1.5]}}, 'hue': {'weight': 1.0, 'type': 'ColorJitter', 'kwargs': {'hue': [-0.05, 0.05]}}, 'sharpness': {'weight': 1.0, 'type': 'SharpnessJitter', 'kwargs': {'sharpness': [0.5, 1.5]}}}}, 'revision': None, 'use_imagenet_stats': True, 'video_backend': 'torchcodec'}, 'env': None, 'policy': {'type': 'diffusion', 'n_obs_steps': 2, 'normalization_mapping': {'VISUAL': <NormalizationMode.MEAN_STD: 'MEAN_STD'>, 'STATE': <NormalizationMode.MIN_MAX: 'MIN_MAX'>, 'ACTION': <NormalizationMode.MIN_MAX: 'MIN_MAX'>}, 'input_features': {}, 'output_features': {}, 'device': 'cuda', 'use_amp': False, 'horizon': 16, 'n_action_steps': 8, 'drop_n_last_frames': 7, 'vision_backbone': 'resnet18', 'crop_shape': [84, 84], 'crop_is_random': True, 'pretrained_backbone_weights': None, 'use_group_norm': True, 'spatial_softmax_num_keypoints': 32, 'use_separate_rgb_encoder_per_camera': False, 'down_dims': [512, 1024, 2048], 'kernel_size': 5, 'n_groups': 8, 'diffusion_step_embed_dim': 128, 'use_film_scale_modulation': True, 'noise_scheduler_type': 'DDPM', 'num_train_timesteps': 100, 'beta_schedule': 'squaredcos_cap_v2', 'beta_start': 0.0001, 'beta_end': 0.02, 'prediction_type': 'epsilon', 'clip_sample': True, 'clip_sample_range': 1.0, 'num_inference_steps': None, 'do_mask_loss_for_padding': False, 'optimizer_lr': 0.0001, 'optimizer_betas': [0.95, 0.999], 'optimizer_eps': 1e-08, 'optimizer_weight_decay': 1e-06, 'scheduler_name': 'cosine', 'scheduler_warmup_steps': 500}, 'output_dir': 'outputs/train/2025-11-18/01-37-50_diffusion', 'job_name': 'diffusion', 'resume': False, 'seed': 1000, 'num_workers': 2, 'batch_size': 8, 'steps': 100000, 'eval_freq': 20000, 'log_freq': 200, 'save_checkpoint': True, 'save_freq': 20000, 'use_policy_training_preset': True, 'optimizer': {'type': 'adam', 'lr': 0.0001, 'weight_decay': 1e-06, 'grad_clip_norm': 10.0, 'betas': [0.95, 0.999], 'eps': 1e-08}, 'scheduler': {'type': 'diffuser', 'num_warmup_steps': 500, 'name': 'cosine'}, 'eval': {'n_episodes': 50, 'batch_size': 50, 'use_async_envs': False}, 'wandb': {'enable': True, 'disable_artifact': True, 'project': 'lerobot', 'entity': None, 'notes': None, 'run_id': None, 'mode': None}, '_wandb': {}}
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diffusion_anubis_fold_towel/wandb/run-20251118_013752-9jmkckoo/run-9jmkckoo.wandb
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size 1059449
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diffusion_anubis_pullout_wrench/checkpoints/100000/pretrained_model/config.json
ADDED
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| 19 |
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| 21 |
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| 22 |
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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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],
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|
| 90 |
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|
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|
| 92 |
+
}
|
diffusion_anubis_pullout_wrench/checkpoints/100000/pretrained_model/model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
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size 1084610496
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diffusion_anubis_pullout_wrench/checkpoints/100000/pretrained_model/train_config.json
ADDED
|
@@ -0,0 +1,202 @@
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| 1 |
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{
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| 2 |
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| 3 |
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|
| 4 |
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"root": "/data1/euijinrnd/hf_home_euijin/lerobot/lerobot/anubis_pullout_wrench_v2__lerobot",
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| 18 |
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]
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| 21 |
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|
| 22 |
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| 28 |
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]
|
| 29 |
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}
|
| 30 |
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},
|
| 31 |
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"saturation": {
|
| 32 |
+
"weight": 1.0,
|
| 33 |
+
"type": "ColorJitter",
|
| 34 |
+
"kwargs": {
|
| 35 |
+
"saturation": [
|
| 36 |
+
0.5,
|
| 37 |
+
1.5
|
| 38 |
+
]
|
| 39 |
+
}
|
| 40 |
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},
|
| 41 |
+
"hue": {
|
| 42 |
+
"weight": 1.0,
|
| 43 |
+
"type": "ColorJitter",
|
| 44 |
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"kwargs": {
|
| 45 |
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"hue": [
|
| 46 |
+
-0.05,
|
| 47 |
+
0.05
|
| 48 |
+
]
|
| 49 |
+
}
|
| 50 |
+
},
|
| 51 |
+
"sharpness": {
|
| 52 |
+
"weight": 1.0,
|
| 53 |
+
"type": "SharpnessJitter",
|
| 54 |
+
"kwargs": {
|
| 55 |
+
"sharpness": [
|
| 56 |
+
0.5,
|
| 57 |
+
1.5
|
| 58 |
+
]
|
| 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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"revision": null,
|
| 64 |
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"use_imagenet_stats": true,
|
| 65 |
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"video_backend": "torchcodec"
|
| 66 |
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},
|
| 67 |
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"env": null,
|
| 68 |
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"policy": {
|
| 69 |
+
"type": "diffusion",
|
| 70 |
+
"n_obs_steps": 2,
|
| 71 |
+
"normalization_mapping": {
|
| 72 |
+
"VISUAL": "MEAN_STD",
|
| 73 |
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"STATE": "MIN_MAX",
|
| 74 |
+
"ACTION": "MIN_MAX"
|
| 75 |
+
},
|
| 76 |
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"input_features": {
|
| 77 |
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"observation.images.left_wrist_image": {
|
| 78 |
+
"type": "VISUAL",
|
| 79 |
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"shape": [
|
| 80 |
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3,
|
| 81 |
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240,
|
| 82 |
+
320
|
| 83 |
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]
|
| 84 |
+
},
|
| 85 |
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"observation.images.image": {
|
| 86 |
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"type": "VISUAL",
|
| 87 |
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"shape": [
|
| 88 |
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3,
|
| 89 |
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240,
|
| 90 |
+
320
|
| 91 |
+
]
|
| 92 |
+
},
|
| 93 |
+
"observation.images.right_wrist_image": {
|
| 94 |
+
"type": "VISUAL",
|
| 95 |
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"shape": [
|
| 96 |
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3,
|
| 97 |
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240,
|
| 98 |
+
320
|
| 99 |
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]
|
| 100 |
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},
|
| 101 |
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"observation.state": {
|
| 102 |
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"type": "STATE",
|
| 103 |
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"shape": [
|
| 104 |
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20
|
| 105 |
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]
|
| 106 |
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}
|
| 107 |
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},
|
| 108 |
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"output_features": {
|
| 109 |
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"action": {
|
| 110 |
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"type": "ACTION",
|
| 111 |
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"shape": [
|
| 112 |
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20
|
| 113 |
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]
|
| 114 |
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}
|
| 115 |
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},
|
| 116 |
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"device": "cuda",
|
| 117 |
+
"use_amp": false,
|
| 118 |
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"horizon": 16,
|
| 119 |
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"n_action_steps": 8,
|
| 120 |
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"drop_n_last_frames": 7,
|
| 121 |
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"vision_backbone": "resnet18",
|
| 122 |
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"crop_shape": [
|
| 123 |
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84,
|
| 124 |
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84
|
| 125 |
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],
|
| 126 |
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"crop_is_random": true,
|
| 127 |
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"pretrained_backbone_weights": null,
|
| 128 |
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"use_group_norm": true,
|
| 129 |
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"spatial_softmax_num_keypoints": 32,
|
| 130 |
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"use_separate_rgb_encoder_per_camera": false,
|
| 131 |
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"down_dims": [
|
| 132 |
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512,
|
| 133 |
+
1024,
|
| 134 |
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2048
|
| 135 |
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],
|
| 136 |
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"kernel_size": 5,
|
| 137 |
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"n_groups": 8,
|
| 138 |
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"diffusion_step_embed_dim": 128,
|
| 139 |
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"use_film_scale_modulation": true,
|
| 140 |
+
"noise_scheduler_type": "DDPM",
|
| 141 |
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"num_train_timesteps": 100,
|
| 142 |
+
"beta_schedule": "squaredcos_cap_v2",
|
| 143 |
+
"beta_start": 0.0001,
|
| 144 |
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"beta_end": 0.02,
|
| 145 |
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"prediction_type": "epsilon",
|
| 146 |
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"clip_sample": true,
|
| 147 |
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|
| 148 |
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|
| 149 |
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"do_mask_loss_for_padding": false,
|
| 150 |
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"optimizer_lr": 0.0001,
|
| 151 |
+
"optimizer_betas": [
|
| 152 |
+
0.95,
|
| 153 |
+
0.999
|
| 154 |
+
],
|
| 155 |
+
"optimizer_eps": 1e-08,
|
| 156 |
+
"optimizer_weight_decay": 1e-06,
|
| 157 |
+
"scheduler_name": "cosine",
|
| 158 |
+
"scheduler_warmup_steps": 500
|
| 159 |
+
},
|
| 160 |
+
"output_dir": "outputs/train/2025-11-18/01-36-18_diffusion",
|
| 161 |
+
"job_name": "diffusion",
|
| 162 |
+
"resume": false,
|
| 163 |
+
"seed": 1000,
|
| 164 |
+
"num_workers": 2,
|
| 165 |
+
"batch_size": 8,
|
| 166 |
+
"steps": 100000,
|
| 167 |
+
"eval_freq": 20000,
|
| 168 |
+
"log_freq": 200,
|
| 169 |
+
"save_checkpoint": true,
|
| 170 |
+
"save_freq": 20000,
|
| 171 |
+
"use_policy_training_preset": true,
|
| 172 |
+
"optimizer": {
|
| 173 |
+
"type": "adam",
|
| 174 |
+
"lr": 0.0001,
|
| 175 |
+
"weight_decay": 1e-06,
|
| 176 |
+
"grad_clip_norm": 10.0,
|
| 177 |
+
"betas": [
|
| 178 |
+
0.95,
|
| 179 |
+
0.999
|
| 180 |
+
],
|
| 181 |
+
"eps": 1e-08
|
| 182 |
+
},
|
| 183 |
+
"scheduler": {
|
| 184 |
+
"type": "diffuser",
|
| 185 |
+
"num_warmup_steps": 500,
|
| 186 |
+
"name": "cosine"
|
| 187 |
+
},
|
| 188 |
+
"eval": {
|
| 189 |
+
"n_episodes": 50,
|
| 190 |
+
"batch_size": 50,
|
| 191 |
+
"use_async_envs": false
|
| 192 |
+
},
|
| 193 |
+
"wandb": {
|
| 194 |
+
"enable": true,
|
| 195 |
+
"disable_artifact": true,
|
| 196 |
+
"project": "lerobot",
|
| 197 |
+
"entity": null,
|
| 198 |
+
"notes": null,
|
| 199 |
+
"run_id": null,
|
| 200 |
+
"mode": null
|
| 201 |
+
}
|
| 202 |
+
}
|
diffusion_anubis_pullout_wrench/wandb/debug-internal.log
ADDED
|
@@ -0,0 +1,15 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{"time":"2025-11-18T01:36:23.35076218+09:00","level":"INFO","msg":"stream: starting","core version":"0.19.9","symlink path":"outputs/train/2025-11-18/01-36-18_diffusion/wandb/run-20251118_013623-flrqqt58/logs/debug-core.log"}
|
| 2 |
+
{"time":"2025-11-18T01:36:23.660911217+09:00","level":"INFO","msg":"created new stream","id":"flrqqt58"}
|
| 3 |
+
{"time":"2025-11-18T01:36:23.660947201+09:00","level":"INFO","msg":"stream: started","id":"flrqqt58"}
|
| 4 |
+
{"time":"2025-11-18T01:36:23.660958247+09:00","level":"INFO","msg":"sender: started","stream_id":"flrqqt58"}
|
| 5 |
+
{"time":"2025-11-18T01:36:23.66096688+09:00","level":"INFO","msg":"handler: started","stream_id":"flrqqt58"}
|
| 6 |
+
{"time":"2025-11-18T01:36:23.661121021+09:00","level":"INFO","msg":"writer: Do: started","stream_id":"flrqqt58"}
|
| 7 |
+
{"time":"2025-11-18T01:36:23.976562105+09:00","level":"INFO","msg":"Starting system monitor"}
|
| 8 |
+
{"time":"2025-11-18T04:16:59.78404243+09:00","level":"INFO","msg":"stream: closing","id":"flrqqt58"}
|
| 9 |
+
{"time":"2025-11-18T04:16:59.784073456+09:00","level":"INFO","msg":"Stopping system monitor"}
|
| 10 |
+
{"time":"2025-11-18T04:16:59.790432212+09:00","level":"INFO","msg":"Stopped system monitor"}
|
| 11 |
+
{"time":"2025-11-18T04:17:00.606052291+09:00","level":"INFO","msg":"fileTransfer: Close: file transfer manager closed"}
|
| 12 |
+
{"time":"2025-11-18T04:17:01.008649672+09:00","level":"INFO","msg":"handler: closed","stream_id":"flrqqt58"}
|
| 13 |
+
{"time":"2025-11-18T04:17:01.008680528+09:00","level":"INFO","msg":"writer: Close: closed","stream_id":"flrqqt58"}
|
| 14 |
+
{"time":"2025-11-18T04:17:01.008697914+09:00","level":"INFO","msg":"sender: closed","stream_id":"flrqqt58"}
|
| 15 |
+
{"time":"2025-11-18T04:17:01.009483381+09:00","level":"INFO","msg":"stream: closed","id":"flrqqt58"}
|
diffusion_anubis_pullout_wrench/wandb/debug.log
ADDED
|
@@ -0,0 +1,23 @@
|
|
|
|
|
|
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|
|
|
|
|
|
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|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
|
|
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|
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|
|
|
|
|
| 1 |
+
2025-11-18 01:36:23,330 INFO MainThread:2405166 [wandb_setup.py:_flush():67] Current SDK version is 0.19.9
|
| 2 |
+
2025-11-18 01:36:23,330 INFO MainThread:2405166 [wandb_setup.py:_flush():67] Configure stats pid to 2405166
|
| 3 |
+
2025-11-18 01:36:23,330 INFO MainThread:2405166 [wandb_setup.py:_flush():67] Loading settings from /home/euijinrnd/.config/wandb/settings
|
| 4 |
+
2025-11-18 01:36:23,330 INFO MainThread:2405166 [wandb_setup.py:_flush():67] Loading settings from /home/euijinrnd/workspace/lerobot/wandb/settings
|
| 5 |
+
2025-11-18 01:36:23,330 INFO MainThread:2405166 [wandb_setup.py:_flush():67] Loading settings from environment variables
|
| 6 |
+
2025-11-18 01:36:23,330 INFO MainThread:2405166 [wandb_init.py:setup_run_log_directory():662] Logging user logs to outputs/train/2025-11-18/01-36-18_diffusion/wandb/run-20251118_013623-flrqqt58/logs/debug.log
|
| 7 |
+
2025-11-18 01:36:23,330 INFO MainThread:2405166 [wandb_init.py:setup_run_log_directory():663] Logging internal logs to outputs/train/2025-11-18/01-36-18_diffusion/wandb/run-20251118_013623-flrqqt58/logs/debug-internal.log
|
| 8 |
+
2025-11-18 01:36:23,330 INFO MainThread:2405166 [wandb_init.py:init():781] calling init triggers
|
| 9 |
+
2025-11-18 01:36:23,330 INFO MainThread:2405166 [wandb_init.py:init():786] wandb.init called with sweep_config: {}
|
| 10 |
+
config: {'dataset': {'repo_id': 'anubis_pullout_wrench_v2__lerobot', 'root': '/data1/euijinrnd/hf_home_euijin/lerobot/lerobot/anubis_pullout_wrench_v2__lerobot', 'episodes': None, 'image_transforms': {'enable': False, 'max_num_transforms': 3, 'random_order': False, 'tfs': {'brightness': {'weight': 1.0, 'type': 'ColorJitter', 'kwargs': {'brightness': [0.8, 1.2]}}, 'contrast': {'weight': 1.0, 'type': 'ColorJitter', 'kwargs': {'contrast': [0.8, 1.2]}}, 'saturation': {'weight': 1.0, 'type': 'ColorJitter', 'kwargs': {'saturation': [0.5, 1.5]}}, 'hue': {'weight': 1.0, 'type': 'ColorJitter', 'kwargs': {'hue': [-0.05, 0.05]}}, 'sharpness': {'weight': 1.0, 'type': 'SharpnessJitter', 'kwargs': {'sharpness': [0.5, 1.5]}}}}, 'revision': None, 'use_imagenet_stats': True, 'video_backend': 'torchcodec'}, 'env': None, 'policy': {'type': 'diffusion', 'n_obs_steps': 2, 'normalization_mapping': {'VISUAL': <NormalizationMode.MEAN_STD: 'MEAN_STD'>, 'STATE': <NormalizationMode.MIN_MAX: 'MIN_MAX'>, 'ACTION': <NormalizationMode.MIN_MAX: 'MIN_MAX'>}, 'input_features': {}, 'output_features': {}, 'device': 'cuda', 'use_amp': False, 'horizon': 16, 'n_action_steps': 8, 'drop_n_last_frames': 7, 'vision_backbone': 'resnet18', 'crop_shape': [84, 84], 'crop_is_random': True, 'pretrained_backbone_weights': None, 'use_group_norm': True, 'spatial_softmax_num_keypoints': 32, 'use_separate_rgb_encoder_per_camera': False, 'down_dims': [512, 1024, 2048], 'kernel_size': 5, 'n_groups': 8, 'diffusion_step_embed_dim': 128, 'use_film_scale_modulation': True, 'noise_scheduler_type': 'DDPM', 'num_train_timesteps': 100, 'beta_schedule': 'squaredcos_cap_v2', 'beta_start': 0.0001, 'beta_end': 0.02, 'prediction_type': 'epsilon', 'clip_sample': True, 'clip_sample_range': 1.0, 'num_inference_steps': None, 'do_mask_loss_for_padding': False, 'optimizer_lr': 0.0001, 'optimizer_betas': [0.95, 0.999], 'optimizer_eps': 1e-08, 'optimizer_weight_decay': 1e-06, 'scheduler_name': 'cosine', 'scheduler_warmup_steps': 500}, 'output_dir': 'outputs/train/2025-11-18/01-36-18_diffusion', 'job_name': 'diffusion', 'resume': False, 'seed': 1000, 'num_workers': 2, 'batch_size': 8, 'steps': 100000, 'eval_freq': 20000, 'log_freq': 200, 'save_checkpoint': True, 'save_freq': 20000, 'use_policy_training_preset': True, 'optimizer': {'type': 'adam', 'lr': 0.0001, 'weight_decay': 1e-06, 'grad_clip_norm': 10.0, 'betas': [0.95, 0.999], 'eps': 1e-08}, 'scheduler': {'type': 'diffuser', 'num_warmup_steps': 500, 'name': 'cosine'}, 'eval': {'n_episodes': 50, 'batch_size': 50, 'use_async_envs': False}, 'wandb': {'enable': True, 'disable_artifact': True, 'project': 'lerobot', 'entity': None, 'notes': None, 'run_id': None, 'mode': None}, '_wandb': {}}
|
| 11 |
+
2025-11-18 01:36:23,330 INFO MainThread:2405166 [wandb_init.py:init():809] starting backend
|
| 12 |
+
2025-11-18 01:36:23,330 INFO MainThread:2405166 [wandb_init.py:init():813] sending inform_init request
|
| 13 |
+
2025-11-18 01:36:23,342 INFO MainThread:2405166 [backend.py:_multiprocessing_setup():101] multiprocessing start_methods=fork,spawn,forkserver, using: spawn
|
| 14 |
+
2025-11-18 01:36:23,343 INFO MainThread:2405166 [wandb_init.py:init():823] backend started and connected
|
| 15 |
+
2025-11-18 01:36:23,344 INFO MainThread:2405166 [wandb_init.py:init():915] updated telemetry
|
| 16 |
+
2025-11-18 01:36:23,398 INFO MainThread:2405166 [wandb_init.py:init():939] communicating run to backend with 90.0 second timeout
|
| 17 |
+
2025-11-18 01:36:23,974 INFO MainThread:2405166 [wandb_init.py:init():1014] starting run threads in backend
|
| 18 |
+
2025-11-18 01:36:24,364 INFO MainThread:2405166 [wandb_run.py:_console_start():2454] atexit reg
|
| 19 |
+
2025-11-18 01:36:24,364 INFO MainThread:2405166 [wandb_run.py:_redirect():2306] redirect: wrap_raw
|
| 20 |
+
2025-11-18 01:36:24,364 INFO MainThread:2405166 [wandb_run.py:_redirect():2371] Wrapping output streams.
|
| 21 |
+
2025-11-18 01:36:24,364 INFO MainThread:2405166 [wandb_run.py:_redirect():2394] Redirects installed.
|
| 22 |
+
2025-11-18 01:36:24,366 INFO MainThread:2405166 [wandb_init.py:init():1056] run started, returning control to user process
|
| 23 |
+
2025-11-18 04:16:59,770 INFO MsgRouterThr:2405166 [mailbox.py:close():129] [no run ID] Closing mailbox, abandoning 1 handles.
|
diffusion_anubis_pullout_wrench/wandb/run-20251118_013623-flrqqt58/files/config.yaml
ADDED
|
@@ -0,0 +1,184 @@
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|
|
|
|
|
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|
|
|
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|
|
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|
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|
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|
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|
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|
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|
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|
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|
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| 80 |
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|
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|
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|
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| 108 |
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|
| 112 |
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| 113 |
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| 117 |
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| 119 |
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|
| 120 |
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| 121 |
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|
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|
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|
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|
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|
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|
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|
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| 144 |
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|
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|
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|
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|
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| 156 |
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|
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|
| 159 |
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|
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|
| 161 |
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| 162 |
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|
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|
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|
| 166 |
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|
| 167 |
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|
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|
| 169 |
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|
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|
| 171 |
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|
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|
| 173 |
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|
| 174 |
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|
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| 177 |
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|
| 178 |
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| 179 |
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|
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|
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project: lerobot
|
| 184 |
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run_id: null
|
diffusion_anubis_pullout_wrench/wandb/run-20251118_013623-flrqqt58/files/output.log
ADDED
|
@@ -0,0 +1,518 @@
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| 1 |
+
Logs will be synced with wandb.
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| 2 |
+
INFO 2025-11-18 01:36:24 ndb_utils.py:96 Track this run --> https://wandb.ai/jinprelude/lerobot/runs/flrqqt58
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| 3 |
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INFO 2025-11-18 01:36:24 ts/train.py:127 Creating dataset
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| 4 |
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INFO 2025-11-18 01:36:25 ts/train.py:138 Creating policy
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| 5 |
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INFO 2025-11-18 01:36:27 ts/train.py:144 Creating optimizer and scheduler
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| 6 |
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INFO 2025-11-18 01:36:27 ts/train.py:156 Output dir: outputs/train/2025-11-18/01-36-18_diffusion
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INFO 2025-11-18 01:36:27 ts/train.py:159 cfg.steps=100000 (100K)
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INFO 2025-11-18 01:36:27 ts/train.py:160 dataset.num_frames=16910 (17K)
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INFO 2025-11-18 01:36:27 ts/train.py:161 dataset.num_episodes=50
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INFO 2025-11-18 01:36:27 ts/train.py:162 num_learnable_params=271145780 (271M)
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INFO 2025-11-18 01:36:27 ts/train.py:163 num_total_params=271145918 (271M)
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INFO 2025-11-18 01:36:27 ts/train.py:202 Start offline training on a fixed dataset
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INFO 2025-11-18 01:36:48 ts/train.py:232 step:200 smpl:2K ep:5 epch:0.09 loss:1.001 grdn:2.523 lr:2.0e-05 updt_s:0.070 data_s:0.034
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| 14 |
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INFO 2025-11-18 01:37:07 ts/train.py:232 step:400 smpl:3K ep:9 epch:0.19 loss:0.415 grdn:2.967 lr:6.0e-05 updt_s:0.064 data_s:0.030
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| 15 |
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INFO 2025-11-18 01:37:25 ts/train.py:232 step:600 smpl:5K ep:14 epch:0.28 loss:0.186 grdn:1.756 lr:9.5e-05 updt_s:0.064 data_s:0.029
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| 16 |
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INFO 2025-11-18 01:37:44 ts/train.py:232 step:800 smpl:6K ep:19 epch:0.38 loss:0.125 grdn:1.241 lr:1.0e-04 updt_s:0.064 data_s:0.027
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| 17 |
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INFO 2025-11-18 01:38:01 ts/train.py:232 step:1K smpl:8K ep:24 epch:0.47 loss:0.098 grdn:1.049 lr:1.0e-04 updt_s:0.064 data_s:0.023
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| 18 |
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INFO 2025-11-18 01:38:20 ts/train.py:232 step:1K smpl:10K ep:28 epch:0.57 loss:0.089 grdn:0.928 lr:1.0e-04 updt_s:0.065 data_s:0.029
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| 19 |
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INFO 2025-11-18 01:38:38 ts/train.py:232 step:1K smpl:11K ep:33 epch:0.66 loss:0.079 grdn:0.835 lr:1.0e-04 updt_s:0.065 data_s:0.024
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| 20 |
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INFO 2025-11-18 01:38:56 ts/train.py:232 step:2K smpl:13K ep:38 epch:0.76 loss:0.065 grdn:0.726 lr:1.0e-04 updt_s:0.065 data_s:0.025
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| 21 |
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INFO 2025-11-18 01:39:14 ts/train.py:232 step:2K smpl:14K ep:43 epch:0.85 loss:0.063 grdn:0.696 lr:1.0e-04 updt_s:0.065 data_s:0.024
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| 22 |
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INFO 2025-11-18 01:39:32 ts/train.py:232 step:2K smpl:16K ep:47 epch:0.95 loss:0.059 grdn:0.648 lr:1.0e-04 updt_s:0.065 data_s:0.023
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| 23 |
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INFO 2025-11-18 01:39:53 ts/train.py:232 step:2K smpl:18K ep:52 epch:1.04 loss:0.058 grdn:0.636 lr:1.0e-04 updt_s:0.066 data_s:0.039
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| 24 |
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INFO 2025-11-18 01:40:12 ts/train.py:232 step:2K smpl:19K ep:57 epch:1.14 loss:0.061 grdn:0.623 lr:1.0e-04 updt_s:0.066 data_s:0.032
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| 25 |
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INFO 2025-11-18 01:40:32 ts/train.py:232 step:3K smpl:21K ep:62 epch:1.23 loss:0.056 grdn:0.580 lr:1.0e-04 updt_s:0.067 data_s:0.029
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| 26 |
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INFO 2025-11-18 01:40:51 ts/train.py:232 step:3K smpl:22K ep:66 epch:1.32 loss:0.049 grdn:0.525 lr:1.0e-04 updt_s:0.067 data_s:0.030
|
| 27 |
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INFO 2025-11-18 01:41:11 ts/train.py:232 step:3K smpl:24K ep:71 epch:1.42 loss:0.050 grdn:0.532 lr:1.0e-04 updt_s:0.067 data_s:0.030
|
| 28 |
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INFO 2025-11-18 01:41:30 ts/train.py:232 step:3K smpl:26K ep:76 epch:1.51 loss:0.051 grdn:0.525 lr:1.0e-04 updt_s:0.066 data_s:0.031
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| 29 |
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INFO 2025-11-18 01:41:49 ts/train.py:232 step:3K smpl:27K ep:80 epch:1.61 loss:0.048 grdn:0.496 lr:1.0e-04 updt_s:0.067 data_s:0.030
|
| 30 |
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INFO 2025-11-18 01:42:08 ts/train.py:232 step:4K smpl:29K ep:85 epch:1.70 loss:0.045 grdn:0.474 lr:1.0e-04 updt_s:0.066 data_s:0.024
|
| 31 |
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INFO 2025-11-18 01:42:26 ts/train.py:232 step:4K smpl:30K ep:90 epch:1.80 loss:0.045 grdn:0.467 lr:1.0e-04 updt_s:0.066 data_s:0.025
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| 32 |
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INFO 2025-11-18 01:42:45 ts/train.py:232 step:4K smpl:32K ep:95 epch:1.89 loss:0.043 grdn:0.450 lr:1.0e-04 updt_s:0.067 data_s:0.026
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| 33 |
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INFO 2025-11-18 01:43:05 ts/train.py:232 step:4K smpl:34K ep:99 epch:1.99 loss:0.042 grdn:0.440 lr:1.0e-04 updt_s:0.067 data_s:0.031
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| 34 |
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INFO 2025-11-18 01:43:24 ts/train.py:232 step:4K smpl:35K ep:104 epch:2.08 loss:0.041 grdn:0.433 lr:1.0e-04 updt_s:0.066 data_s:0.029
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| 35 |
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INFO 2025-11-18 01:43:43 ts/train.py:232 step:5K smpl:37K ep:109 epch:2.18 loss:0.041 grdn:0.424 lr:1.0e-04 updt_s:0.066 data_s:0.030
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| 36 |
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INFO 2025-11-18 01:44:02 ts/train.py:232 step:5K smpl:38K ep:114 epch:2.27 loss:0.043 grdn:0.428 lr:1.0e-04 updt_s:0.066 data_s:0.028
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| 37 |
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INFO 2025-11-18 01:44:21 ts/train.py:232 step:5K smpl:40K ep:118 epch:2.37 loss:0.041 grdn:0.399 lr:1.0e-04 updt_s:0.066 data_s:0.028
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| 38 |
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INFO 2025-11-18 01:44:40 ts/train.py:232 step:5K smpl:42K ep:123 epch:2.46 loss:0.041 grdn:0.403 lr:9.9e-05 updt_s:0.066 data_s:0.028
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| 39 |
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INFO 2025-11-18 01:44:59 ts/train.py:232 step:5K smpl:43K ep:128 epch:2.55 loss:0.040 grdn:0.401 lr:9.9e-05 updt_s:0.067 data_s:0.030
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| 40 |
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INFO 2025-11-18 01:45:18 ts/train.py:232 step:6K smpl:45K ep:132 epch:2.65 loss:0.038 grdn:0.377 lr:9.9e-05 updt_s:0.067 data_s:0.023
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| 41 |
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INFO 2025-11-18 01:45:35 ts/train.py:232 step:6K smpl:46K ep:137 epch:2.74 loss:0.043 grdn:0.401 lr:9.9e-05 updt_s:0.067 data_s:0.021
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| 42 |
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INFO 2025-11-18 01:45:53 ts/train.py:232 step:6K smpl:48K ep:142 epch:2.84 loss:0.038 grdn:0.366 lr:9.9e-05 updt_s:0.066 data_s:0.021
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| 43 |
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INFO 2025-11-18 01:46:11 ts/train.py:232 step:6K smpl:50K ep:147 epch:2.93 loss:0.033 grdn:0.342 lr:9.9e-05 updt_s:0.066 data_s:0.022
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INFO 2025-11-18 01:46:34 ts/train.py:232 step:6K smpl:51K ep:151 epch:3.03 loss:0.040 grdn:0.373 lr:9.9e-05 updt_s:0.066 data_s:0.049
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INFO 2025-11-18 01:46:53 ts/train.py:232 step:7K smpl:53K ep:156 epch:3.12 loss:0.035 grdn:0.342 lr:9.9e-05 updt_s:0.067 data_s:0.031
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| 46 |
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INFO 2025-11-18 01:47:13 ts/train.py:232 step:7K smpl:54K ep:161 epch:3.22 loss:0.038 grdn:0.360 lr:9.9e-05 updt_s:0.067 data_s:0.030
|
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INFO 2025-11-18 01:47:32 ts/train.py:232 step:7K smpl:56K ep:166 epch:3.31 loss:0.035 grdn:0.332 lr:9.9e-05 updt_s:0.066 data_s:0.030
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| 48 |
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INFO 2025-11-18 01:47:51 ts/train.py:232 step:7K smpl:58K ep:170 epch:3.41 loss:0.037 grdn:0.345 lr:9.9e-05 updt_s:0.066 data_s:0.029
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| 49 |
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INFO 2025-11-18 01:48:11 ts/train.py:232 step:7K smpl:59K ep:175 epch:3.50 loss:0.036 grdn:0.347 lr:9.9e-05 updt_s:0.067 data_s:0.029
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| 50 |
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INFO 2025-11-18 01:48:29 ts/train.py:232 step:8K smpl:61K ep:180 epch:3.60 loss:0.035 grdn:0.332 lr:9.9e-05 updt_s:0.066 data_s:0.027
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| 51 |
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INFO 2025-11-18 01:48:47 ts/train.py:232 step:8K smpl:62K ep:185 epch:3.69 loss:0.029 grdn:0.302 lr:9.9e-05 updt_s:0.066 data_s:0.021
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| 52 |
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INFO 2025-11-18 01:49:04 ts/train.py:232 step:8K smpl:64K ep:189 epch:3.78 loss:0.035 grdn:0.328 lr:9.9e-05 updt_s:0.066 data_s:0.021
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| 53 |
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INFO 2025-11-18 01:49:22 ts/train.py:232 step:8K smpl:66K ep:194 epch:3.88 loss:0.033 grdn:0.312 lr:9.9e-05 updt_s:0.066 data_s:0.020
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| 54 |
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INFO 2025-11-18 01:49:41 ts/train.py:232 step:8K smpl:67K ep:199 epch:3.97 loss:0.035 grdn:0.324 lr:9.8e-05 updt_s:0.066 data_s:0.029
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| 55 |
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INFO 2025-11-18 01:50:00 ts/train.py:232 step:9K smpl:69K ep:203 epch:4.07 loss:0.035 grdn:0.330 lr:9.8e-05 updt_s:0.066 data_s:0.029
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| 56 |
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INFO 2025-11-18 01:50:19 ts/train.py:232 step:9K smpl:70K ep:208 epch:4.16 loss:0.035 grdn:0.320 lr:9.8e-05 updt_s:0.066 data_s:0.030
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| 57 |
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INFO 2025-11-18 01:50:39 ts/train.py:232 step:9K smpl:72K ep:213 epch:4.26 loss:0.032 grdn:0.307 lr:9.8e-05 updt_s:0.067 data_s:0.030
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INFO 2025-11-18 01:50:58 ts/train.py:232 step:9K smpl:74K ep:218 epch:4.35 loss:0.032 grdn:0.302 lr:9.8e-05 updt_s:0.066 data_s:0.031
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INFO 2025-11-18 01:51:18 ts/train.py:232 step:9K smpl:75K ep:222 epch:4.45 loss:0.031 grdn:0.294 lr:9.8e-05 updt_s:0.066 data_s:0.031
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INFO 2025-11-18 01:51:37 ts/train.py:232 step:10K smpl:77K ep:227 epch:4.54 loss:0.031 grdn:0.293 lr:9.8e-05 updt_s:0.067 data_s:0.030
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INFO 2025-11-18 01:51:56 ts/train.py:232 step:10K smpl:78K ep:232 epch:4.64 loss:0.033 grdn:0.301 lr:9.8e-05 updt_s:0.067 data_s:0.023
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INFO 2025-11-18 01:52:13 ts/train.py:232 step:10K smpl:80K ep:237 epch:4.73 loss:0.032 grdn:0.297 lr:9.8e-05 updt_s:0.066 data_s:0.022
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INFO 2025-11-18 01:52:31 ts/train.py:232 step:10K smpl:82K ep:241 epch:4.83 loss:0.031 grdn:0.290 lr:9.8e-05 updt_s:0.066 data_s:0.022
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| 64 |
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INFO 2025-11-18 01:52:50 ts/train.py:232 step:10K smpl:83K ep:246 epch:4.92 loss:0.029 grdn:0.271 lr:9.8e-05 updt_s:0.067 data_s:0.026
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| 65 |
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INFO 2025-11-18 01:53:09 ts/train.py:232 step:11K smpl:85K ep:251 epch:5.01 loss:0.028 grdn:0.275 lr:9.8e-05 updt_s:0.066 data_s:0.031
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INFO 2025-11-18 01:53:29 ts/train.py:232 step:11K smpl:86K ep:255 epch:5.11 loss:0.028 grdn:0.278 lr:9.7e-05 updt_s:0.066 data_s:0.030
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INFO 2025-11-18 01:53:48 ts/train.py:232 step:11K smpl:88K ep:260 epch:5.20 loss:0.033 grdn:0.298 lr:9.7e-05 updt_s:0.066 data_s:0.030
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| 68 |
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INFO 2025-11-18 01:54:08 ts/train.py:232 step:11K smpl:90K ep:265 epch:5.30 loss:0.032 grdn:0.290 lr:9.7e-05 updt_s:0.066 data_s:0.030
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| 69 |
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INFO 2025-11-18 01:54:27 ts/train.py:232 step:11K smpl:91K ep:270 epch:5.39 loss:0.032 grdn:0.289 lr:9.7e-05 updt_s:0.066 data_s:0.031
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INFO 2025-11-18 01:54:46 ts/train.py:232 step:12K smpl:93K ep:274 epch:5.49 loss:0.030 grdn:0.286 lr:9.7e-05 updt_s:0.066 data_s:0.030
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INFO 2025-11-18 01:55:05 ts/train.py:232 step:12K smpl:94K ep:279 epch:5.58 loss:0.029 grdn:0.281 lr:9.7e-05 updt_s:0.066 data_s:0.025
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INFO 2025-11-18 01:55:23 ts/train.py:232 step:12K smpl:96K ep:284 epch:5.68 loss:0.029 grdn:0.285 lr:9.7e-05 updt_s:0.066 data_s:0.022
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INFO 2025-11-18 01:55:40 ts/train.py:232 step:12K smpl:98K ep:289 epch:5.77 loss:0.029 grdn:0.268 lr:9.7e-05 updt_s:0.066 data_s:0.022
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INFO 2025-11-18 01:55:58 ts/train.py:232 step:12K smpl:99K ep:293 epch:5.87 loss:0.030 grdn:0.285 lr:9.7e-05 updt_s:0.066 data_s:0.022
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INFO 2025-11-18 01:56:16 ts/train.py:232 step:13K smpl:101K ep:298 epch:5.96 loss:0.029 grdn:0.280 lr:9.6e-05 updt_s:0.066 data_s:0.026
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INFO 2025-11-18 01:56:38 ts/train.py:232 step:13K smpl:102K ep:303 epch:6.06 loss:0.027 grdn:0.266 lr:9.6e-05 updt_s:0.066 data_s:0.039
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INFO 2025-11-18 01:56:56 ts/train.py:232 step:13K smpl:104K ep:308 epch:6.15 loss:0.028 grdn:0.268 lr:9.6e-05 updt_s:0.067 data_s:0.023
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INFO 2025-11-18 01:57:14 ts/train.py:232 step:13K smpl:106K ep:312 epch:6.24 loss:0.030 grdn:0.285 lr:9.6e-05 updt_s:0.066 data_s:0.022
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INFO 2025-11-18 01:57:31 ts/train.py:232 step:13K smpl:107K ep:317 epch:6.34 loss:0.028 grdn:0.276 lr:9.6e-05 updt_s:0.066 data_s:0.021
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INFO 2025-11-18 01:57:49 ts/train.py:232 step:14K smpl:109K ep:322 epch:6.43 loss:0.027 grdn:0.266 lr:9.6e-05 updt_s:0.066 data_s:0.021
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INFO 2025-11-18 01:58:06 ts/train.py:232 step:14K smpl:110K ep:326 epch:6.53 loss:0.026 grdn:0.259 lr:9.6e-05 updt_s:0.066 data_s:0.021
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INFO 2025-11-18 01:58:24 ts/train.py:232 step:14K smpl:112K ep:331 epch:6.62 loss:0.028 grdn:0.275 lr:9.6e-05 updt_s:0.067 data_s:0.022
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| 83 |
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INFO 2025-11-18 01:58:42 ts/train.py:232 step:14K smpl:114K ep:336 epch:6.72 loss:0.028 grdn:0.275 lr:9.5e-05 updt_s:0.067 data_s:0.021
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INFO 2025-11-18 01:58:59 ts/train.py:232 step:14K smpl:115K ep:341 epch:6.81 loss:0.027 grdn:0.274 lr:9.5e-05 updt_s:0.066 data_s:0.022
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INFO 2025-11-18 01:59:18 ts/train.py:232 step:15K smpl:117K ep:345 epch:6.91 loss:0.025 grdn:0.249 lr:9.5e-05 updt_s:0.066 data_s:0.030
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INFO 2025-11-18 01:59:38 ts/train.py:232 step:15K smpl:118K ep:350 epch:7.00 loss:0.025 grdn:0.261 lr:9.5e-05 updt_s:0.066 data_s:0.031
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INFO 2025-11-18 01:59:57 ts/train.py:232 step:15K smpl:120K ep:355 epch:7.10 loss:0.026 grdn:0.259 lr:9.5e-05 updt_s:0.066 data_s:0.030
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INFO 2025-11-18 02:00:16 ts/train.py:232 step:15K smpl:122K ep:360 epch:7.19 loss:0.026 grdn:0.261 lr:9.5e-05 updt_s:0.066 data_s:0.029
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INFO 2025-11-18 02:00:36 ts/train.py:232 step:15K smpl:123K ep:364 epch:7.29 loss:0.027 grdn:0.272 lr:9.5e-05 updt_s:0.066 data_s:0.032
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INFO 2025-11-18 02:00:56 ts/train.py:232 step:16K smpl:125K ep:369 epch:7.38 loss:0.030 grdn:0.277 lr:9.4e-05 updt_s:0.067 data_s:0.032
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INFO 2025-11-18 02:01:15 ts/train.py:232 step:16K smpl:126K ep:374 epch:7.47 loss:0.025 grdn:0.256 lr:9.4e-05 updt_s:0.066 data_s:0.032
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INFO 2025-11-18 02:01:34 ts/train.py:232 step:16K smpl:128K ep:378 epch:7.57 loss:0.029 grdn:0.273 lr:9.4e-05 updt_s:0.066 data_s:0.024
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INFO 2025-11-18 02:01:52 ts/train.py:232 step:16K smpl:130K ep:383 epch:7.66 loss:0.026 grdn:0.271 lr:9.4e-05 updt_s:0.067 data_s:0.023
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INFO 2025-11-18 02:02:10 ts/train.py:232 step:16K smpl:131K ep:388 epch:7.76 loss:0.026 grdn:0.262 lr:9.4e-05 updt_s:0.066 data_s:0.025
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INFO 2025-11-18 02:02:29 ts/train.py:232 step:17K smpl:133K ep:393 epch:7.85 loss:0.026 grdn:0.275 lr:9.4e-05 updt_s:0.067 data_s:0.028
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| 96 |
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INFO 2025-11-18 02:02:49 ts/train.py:232 step:17K smpl:134K ep:397 epch:7.95 loss:0.028 grdn:0.279 lr:9.4e-05 updt_s:0.067 data_s:0.031
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INFO 2025-11-18 02:03:09 ts/train.py:232 step:17K smpl:136K ep:402 epch:8.04 loss:0.023 grdn:0.251 lr:9.3e-05 updt_s:0.067 data_s:0.032
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INFO 2025-11-18 02:03:29 ts/train.py:232 step:17K smpl:138K ep:407 epch:8.14 loss:0.025 grdn:0.269 lr:9.3e-05 updt_s:0.066 data_s:0.032
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INFO 2025-11-18 02:03:48 ts/train.py:232 step:17K smpl:139K ep:412 epch:8.23 loss:0.024 grdn:0.257 lr:9.3e-05 updt_s:0.066 data_s:0.032
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| 100 |
+
INFO 2025-11-18 02:04:08 ts/train.py:232 step:18K smpl:141K ep:416 epch:8.33 loss:0.023 grdn:0.254 lr:9.3e-05 updt_s:0.066 data_s:0.031
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| 101 |
+
INFO 2025-11-18 02:04:28 ts/train.py:232 step:18K smpl:142K ep:421 epch:8.42 loss:0.023 grdn:0.254 lr:9.3e-05 updt_s:0.066 data_s:0.031
|
| 102 |
+
INFO 2025-11-18 02:04:46 ts/train.py:232 step:18K smpl:144K ep:426 epch:8.52 loss:0.028 grdn:0.283 lr:9.3e-05 updt_s:0.067 data_s:0.026
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| 103 |
+
INFO 2025-11-18 02:05:04 ts/train.py:232 step:18K smpl:146K ep:431 epch:8.61 loss:0.026 grdn:0.265 lr:9.2e-05 updt_s:0.066 data_s:0.023
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| 104 |
+
INFO 2025-11-18 02:05:22 ts/train.py:232 step:18K smpl:147K ep:435 epch:8.70 loss:0.027 grdn:0.271 lr:9.2e-05 updt_s:0.067 data_s:0.023
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| 105 |
+
INFO 2025-11-18 02:05:40 ts/train.py:232 step:19K smpl:149K ep:440 epch:8.80 loss:0.026 grdn:0.271 lr:9.2e-05 updt_s:0.067 data_s:0.024
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| 106 |
+
INFO 2025-11-18 02:05:59 ts/train.py:232 step:19K smpl:150K ep:445 epch:8.89 loss:0.025 grdn:0.265 lr:9.2e-05 updt_s:0.066 data_s:0.026
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| 107 |
+
INFO 2025-11-18 02:06:17 ts/train.py:232 step:19K smpl:152K ep:449 epch:8.99 loss:0.027 grdn:0.276 lr:9.2e-05 updt_s:0.067 data_s:0.023
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| 108 |
+
INFO 2025-11-18 02:06:35 ts/train.py:232 step:19K smpl:154K ep:454 epch:9.08 loss:0.024 grdn:0.263 lr:9.2e-05 updt_s:0.067 data_s:0.023
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| 109 |
+
INFO 2025-11-18 02:06:56 ts/train.py:232 step:19K smpl:155K ep:459 epch:9.18 loss:0.023 grdn:0.249 lr:9.1e-05 updt_s:0.066 data_s:0.038
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| 110 |
+
INFO 2025-11-18 02:07:14 ts/train.py:232 step:20K smpl:157K ep:464 epch:9.27 loss:0.023 grdn:0.273 lr:9.1e-05 updt_s:0.066 data_s:0.024
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| 111 |
+
INFO 2025-11-18 02:07:32 ts/train.py:232 step:20K smpl:158K ep:468 epch:9.37 loss:0.023 grdn:0.247 lr:9.1e-05 updt_s:0.066 data_s:0.023
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| 112 |
+
INFO 2025-11-18 02:07:50 ts/train.py:232 step:20K smpl:160K ep:473 epch:9.46 loss:0.026 grdn:0.274 lr:9.1e-05 updt_s:0.066 data_s:0.023
|
| 113 |
+
INFO 2025-11-18 02:07:50 ts/train.py:241 Checkpoint policy after step 20000
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| 114 |
+
INFO 2025-11-18 02:08:21 ts/train.py:232 step:20K smpl:162K ep:478 epch:9.56 loss:0.026 grdn:0.272 lr:9.1e-05 updt_s:0.066 data_s:0.021
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| 115 |
+
INFO 2025-11-18 02:08:39 ts/train.py:232 step:20K smpl:163K ep:483 epch:9.65 loss:0.023 grdn:0.257 lr:9.1e-05 updt_s:0.066 data_s:0.021
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| 116 |
+
INFO 2025-11-18 02:08:56 ts/train.py:232 step:21K smpl:165K ep:487 epch:9.75 loss:0.023 grdn:0.259 lr:9.0e-05 updt_s:0.066 data_s:0.022
|
| 117 |
+
INFO 2025-11-18 02:09:15 ts/train.py:232 step:21K smpl:166K ep:492 epch:9.84 loss:0.024 grdn:0.256 lr:9.0e-05 updt_s:0.067 data_s:0.027
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| 118 |
+
INFO 2025-11-18 02:09:34 ts/train.py:232 step:21K smpl:168K ep:497 epch:9.93 loss:0.023 grdn:0.260 lr:9.0e-05 updt_s:0.066 data_s:0.027
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| 119 |
+
INFO 2025-11-18 02:09:52 ts/train.py:232 step:21K smpl:170K ep:501 epch:10.03 loss:0.022 grdn:0.257 lr:9.0e-05 updt_s:0.065 data_s:0.023
|
| 120 |
+
INFO 2025-11-18 02:10:10 ts/train.py:232 step:21K smpl:171K ep:506 epch:10.12 loss:0.023 grdn:0.256 lr:9.0e-05 updt_s:0.066 data_s:0.025
|
| 121 |
+
INFO 2025-11-18 02:10:29 ts/train.py:232 step:22K smpl:173K ep:511 epch:10.22 loss:0.024 grdn:0.278 lr:8.9e-05 updt_s:0.066 data_s:0.027
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| 122 |
+
INFO 2025-11-18 02:10:48 ts/train.py:232 step:22K smpl:174K ep:516 epch:10.31 loss:0.024 grdn:0.267 lr:8.9e-05 updt_s:0.066 data_s:0.029
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| 123 |
+
INFO 2025-11-18 02:11:07 ts/train.py:232 step:22K smpl:176K ep:520 epch:10.41 loss:0.024 grdn:0.264 lr:8.9e-05 updt_s:0.066 data_s:0.030
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| 124 |
+
INFO 2025-11-18 02:11:26 ts/train.py:232 step:22K smpl:178K ep:525 epch:10.50 loss:0.024 grdn:0.257 lr:8.9e-05 updt_s:0.067 data_s:0.026
|
| 125 |
+
INFO 2025-11-18 02:11:44 ts/train.py:232 step:22K smpl:179K ep:530 epch:10.60 loss:0.023 grdn:0.255 lr:8.9e-05 updt_s:0.067 data_s:0.026
|
| 126 |
+
INFO 2025-11-18 02:12:03 ts/train.py:232 step:23K smpl:181K ep:535 epch:10.69 loss:0.021 grdn:0.249 lr:8.8e-05 updt_s:0.067 data_s:0.025
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| 127 |
+
INFO 2025-11-18 02:12:22 ts/train.py:232 step:23K smpl:182K ep:539 epch:10.79 loss:0.022 grdn:0.256 lr:8.8e-05 updt_s:0.067 data_s:0.028
|
| 128 |
+
INFO 2025-11-18 02:12:41 ts/train.py:232 step:23K smpl:184K ep:544 epch:10.88 loss:0.022 grdn:0.253 lr:8.8e-05 updt_s:0.066 data_s:0.030
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| 129 |
+
INFO 2025-11-18 02:13:00 ts/train.py:232 step:23K smpl:186K ep:549 epch:10.98 loss:0.020 grdn:0.244 lr:8.8e-05 updt_s:0.066 data_s:0.030
|
| 130 |
+
INFO 2025-11-18 02:13:20 ts/train.py:232 step:23K smpl:187K ep:554 epch:11.07 loss:0.022 grdn:0.250 lr:8.8e-05 updt_s:0.066 data_s:0.029
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| 131 |
+
INFO 2025-11-18 02:13:39 ts/train.py:232 step:24K smpl:189K ep:558 epch:11.16 loss:0.021 grdn:0.242 lr:8.7e-05 updt_s:0.066 data_s:0.031
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| 132 |
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INFO 2025-11-18 02:13:58 ts/train.py:232 step:24K smpl:190K ep:563 epch:11.26 loss:0.021 grdn:0.258 lr:8.7e-05 updt_s:0.066 data_s:0.030
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| 133 |
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INFO 2025-11-18 02:14:18 ts/train.py:232 step:24K smpl:192K ep:568 epch:11.35 loss:0.024 grdn:0.271 lr:8.7e-05 updt_s:0.067 data_s:0.030
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| 134 |
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INFO 2025-11-18 02:14:37 ts/train.py:232 step:24K smpl:194K ep:572 epch:11.45 loss:0.023 grdn:0.261 lr:8.7e-05 updt_s:0.066 data_s:0.027
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| 135 |
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INFO 2025-11-18 02:14:55 ts/train.py:232 step:24K smpl:195K ep:577 epch:11.54 loss:0.021 grdn:0.249 lr:8.7e-05 updt_s:0.067 data_s:0.023
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| 136 |
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INFO 2025-11-18 02:15:13 ts/train.py:232 step:25K smpl:197K ep:582 epch:11.64 loss:0.020 grdn:0.248 lr:8.6e-05 updt_s:0.067 data_s:0.022
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| 137 |
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INFO 2025-11-18 02:15:31 ts/train.py:232 step:25K smpl:198K ep:587 epch:11.73 loss:0.022 grdn:0.246 lr:8.6e-05 updt_s:0.066 data_s:0.023
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| 138 |
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INFO 2025-11-18 02:15:50 ts/train.py:232 step:25K smpl:200K ep:591 epch:11.83 loss:0.021 grdn:0.251 lr:8.6e-05 updt_s:0.066 data_s:0.030
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| 139 |
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INFO 2025-11-18 02:16:09 ts/train.py:232 step:25K smpl:202K ep:596 epch:11.92 loss:0.021 grdn:0.245 lr:8.6e-05 updt_s:0.067 data_s:0.029
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| 140 |
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INFO 2025-11-18 02:16:29 ts/train.py:232 step:25K smpl:203K ep:601 epch:12.02 loss:0.023 grdn:0.256 lr:8.5e-05 updt_s:0.067 data_s:0.029
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| 141 |
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INFO 2025-11-18 02:16:48 ts/train.py:232 step:26K smpl:205K ep:606 epch:12.11 loss:0.024 grdn:0.265 lr:8.5e-05 updt_s:0.066 data_s:0.028
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| 142 |
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INFO 2025-11-18 02:17:07 ts/train.py:232 step:26K smpl:206K ep:610 epch:12.21 loss:0.020 grdn:0.235 lr:8.5e-05 updt_s:0.067 data_s:0.028
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| 143 |
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INFO 2025-11-18 02:17:29 ts/train.py:232 step:26K smpl:208K ep:615 epch:12.30 loss:0.021 grdn:0.238 lr:8.5e-05 updt_s:0.066 data_s:0.044
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| 144 |
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INFO 2025-11-18 02:17:48 ts/train.py:232 step:26K smpl:210K ep:620 epch:12.40 loss:0.020 grdn:0.233 lr:8.5e-05 updt_s:0.066 data_s:0.027
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| 145 |
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INFO 2025-11-18 02:18:06 ts/train.py:232 step:26K smpl:211K ep:624 epch:12.49 loss:0.020 grdn:0.251 lr:8.4e-05 updt_s:0.066 data_s:0.022
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| 146 |
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INFO 2025-11-18 02:18:23 ts/train.py:232 step:27K smpl:213K ep:629 epch:12.58 loss:0.021 grdn:0.259 lr:8.4e-05 updt_s:0.066 data_s:0.020
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| 147 |
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INFO 2025-11-18 02:18:41 ts/train.py:232 step:27K smpl:214K ep:634 epch:12.68 loss:0.023 grdn:0.260 lr:8.4e-05 updt_s:0.066 data_s:0.021
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| 148 |
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INFO 2025-11-18 02:18:59 ts/train.py:232 step:27K smpl:216K ep:639 epch:12.77 loss:0.020 grdn:0.248 lr:8.4e-05 updt_s:0.066 data_s:0.026
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| 149 |
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INFO 2025-11-18 02:19:18 ts/train.py:232 step:27K smpl:218K ep:643 epch:12.87 loss:0.024 grdn:0.270 lr:8.3e-05 updt_s:0.067 data_s:0.027
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| 150 |
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INFO 2025-11-18 02:19:37 ts/train.py:232 step:27K smpl:219K ep:648 epch:12.96 loss:0.021 grdn:0.247 lr:8.3e-05 updt_s:0.066 data_s:0.027
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| 151 |
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INFO 2025-11-18 02:19:56 ts/train.py:232 step:28K smpl:221K ep:653 epch:13.06 loss:0.023 grdn:0.260 lr:8.3e-05 updt_s:0.066 data_s:0.028
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| 152 |
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INFO 2025-11-18 02:20:15 ts/train.py:232 step:28K smpl:222K ep:658 epch:13.15 loss:0.022 grdn:0.263 lr:8.3e-05 updt_s:0.066 data_s:0.028
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| 153 |
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INFO 2025-11-18 02:20:33 ts/train.py:232 step:28K smpl:224K ep:662 epch:13.25 loss:0.020 grdn:0.239 lr:8.2e-05 updt_s:0.066 data_s:0.026
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| 154 |
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INFO 2025-11-18 02:20:52 ts/train.py:232 step:28K smpl:226K ep:667 epch:13.34 loss:0.021 grdn:0.251 lr:8.2e-05 updt_s:0.067 data_s:0.026
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INFO 2025-11-18 02:21:10 ts/train.py:232 step:28K smpl:227K ep:672 epch:13.44 loss:0.020 grdn:0.248 lr:8.2e-05 updt_s:0.066 data_s:0.023
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| 156 |
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INFO 2025-11-18 02:21:28 ts/train.py:232 step:29K smpl:229K ep:677 epch:13.53 loss:0.021 grdn:0.259 lr:8.2e-05 updt_s:0.067 data_s:0.023
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| 157 |
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INFO 2025-11-18 02:21:46 ts/train.py:232 step:29K smpl:230K ep:681 epch:13.63 loss:0.022 grdn:0.269 lr:8.1e-05 updt_s:0.067 data_s:0.023
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| 158 |
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INFO 2025-11-18 02:22:05 ts/train.py:232 step:29K smpl:232K ep:686 epch:13.72 loss:0.023 grdn:0.263 lr:8.1e-05 updt_s:0.067 data_s:0.026
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| 159 |
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INFO 2025-11-18 02:22:24 ts/train.py:232 step:29K smpl:234K ep:691 epch:13.81 loss:0.022 grdn:0.262 lr:8.1e-05 updt_s:0.066 data_s:0.029
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| 160 |
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INFO 2025-11-18 02:22:43 ts/train.py:232 step:29K smpl:235K ep:695 epch:13.91 loss:0.020 grdn:0.254 lr:8.1e-05 updt_s:0.066 data_s:0.029
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| 161 |
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INFO 2025-11-18 02:23:02 ts/train.py:232 step:30K smpl:237K ep:700 epch:14.00 loss:0.021 grdn:0.257 lr:8.0e-05 updt_s:0.067 data_s:0.030
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| 162 |
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INFO 2025-11-18 02:23:22 ts/train.py:232 step:30K smpl:238K ep:705 epch:14.10 loss:0.019 grdn:0.237 lr:8.0e-05 updt_s:0.066 data_s:0.031
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| 163 |
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INFO 2025-11-18 02:23:41 ts/train.py:232 step:30K smpl:240K ep:710 epch:14.19 loss:0.020 grdn:0.246 lr:8.0e-05 updt_s:0.067 data_s:0.028
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| 164 |
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INFO 2025-11-18 02:24:00 ts/train.py:232 step:30K smpl:242K ep:714 epch:14.29 loss:0.020 grdn:0.244 lr:8.0e-05 updt_s:0.067 data_s:0.031
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| 165 |
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INFO 2025-11-18 02:24:19 ts/train.py:232 step:30K smpl:243K ep:719 epch:14.38 loss:0.020 grdn:0.266 lr:7.9e-05 updt_s:0.066 data_s:0.027
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| 166 |
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INFO 2025-11-18 02:24:37 ts/train.py:232 step:31K smpl:245K ep:724 epch:14.48 loss:0.018 grdn:0.237 lr:7.9e-05 updt_s:0.066 data_s:0.023
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| 167 |
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INFO 2025-11-18 02:24:55 ts/train.py:232 step:31K smpl:246K ep:729 epch:14.57 loss:0.019 grdn:0.240 lr:7.9e-05 updt_s:0.067 data_s:0.022
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| 168 |
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INFO 2025-11-18 02:25:13 ts/train.py:232 step:31K smpl:248K ep:733 epch:14.67 loss:0.019 grdn:0.240 lr:7.9e-05 updt_s:0.066 data_s:0.024
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| 169 |
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INFO 2025-11-18 02:25:33 ts/train.py:232 step:31K smpl:250K ep:738 epch:14.76 loss:0.021 grdn:0.255 lr:7.8e-05 updt_s:0.067 data_s:0.033
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| 170 |
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INFO 2025-11-18 02:25:53 ts/train.py:232 step:31K smpl:251K ep:743 epch:14.86 loss:0.022 grdn:0.251 lr:7.8e-05 updt_s:0.066 data_s:0.031
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| 171 |
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INFO 2025-11-18 02:26:12 ts/train.py:232 step:32K smpl:253K ep:747 epch:14.95 loss:0.019 grdn:0.237 lr:7.8e-05 updt_s:0.067 data_s:0.030
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| 172 |
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INFO 2025-11-18 02:26:32 ts/train.py:232 step:32K smpl:254K ep:752 epch:15.04 loss:0.021 grdn:0.246 lr:7.8e-05 updt_s:0.067 data_s:0.030
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| 173 |
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INFO 2025-11-18 02:26:51 ts/train.py:232 step:32K smpl:256K ep:757 epch:15.14 loss:0.021 grdn:0.247 lr:7.7e-05 updt_s:0.066 data_s:0.031
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| 174 |
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INFO 2025-11-18 02:27:10 ts/train.py:232 step:32K smpl:258K ep:762 epch:15.23 loss:0.020 grdn:0.245 lr:7.7e-05 updt_s:0.067 data_s:0.029
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| 175 |
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INFO 2025-11-18 02:27:30 ts/train.py:232 step:32K smpl:259K ep:766 epch:15.33 loss:0.020 grdn:0.252 lr:7.7e-05 updt_s:0.067 data_s:0.029
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| 176 |
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INFO 2025-11-18 02:27:51 ts/train.py:232 step:33K smpl:261K ep:771 epch:15.42 loss:0.020 grdn:0.254 lr:7.7e-05 updt_s:0.066 data_s:0.038
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| 177 |
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INFO 2025-11-18 02:28:09 ts/train.py:232 step:33K smpl:262K ep:776 epch:15.52 loss:0.019 grdn:0.245 lr:7.6e-05 updt_s:0.066 data_s:0.025
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| 178 |
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INFO 2025-11-18 02:28:27 ts/train.py:232 step:33K smpl:264K ep:781 epch:15.61 loss:0.020 grdn:0.250 lr:7.6e-05 updt_s:0.066 data_s:0.024
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| 179 |
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INFO 2025-11-18 02:28:47 ts/train.py:232 step:33K smpl:266K ep:785 epch:15.71 loss:0.021 grdn:0.250 lr:7.6e-05 updt_s:0.067 data_s:0.032
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| 180 |
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INFO 2025-11-18 02:29:06 ts/train.py:232 step:33K smpl:267K ep:790 epch:15.80 loss:0.018 grdn:0.227 lr:7.5e-05 updt_s:0.066 data_s:0.028
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| 181 |
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INFO 2025-11-18 02:29:25 ts/train.py:232 step:34K smpl:269K ep:795 epch:15.90 loss:0.021 grdn:0.261 lr:7.5e-05 updt_s:0.067 data_s:0.028
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| 182 |
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INFO 2025-11-18 02:29:44 ts/train.py:232 step:34K smpl:270K ep:800 epch:15.99 loss:0.020 grdn:0.252 lr:7.5e-05 updt_s:0.066 data_s:0.029
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| 183 |
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INFO 2025-11-18 02:30:03 ts/train.py:232 step:34K smpl:272K ep:804 epch:16.09 loss:0.020 grdn:0.244 lr:7.5e-05 updt_s:0.066 data_s:0.029
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| 184 |
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INFO 2025-11-18 02:30:22 ts/train.py:232 step:34K smpl:274K ep:809 epch:16.18 loss:0.019 grdn:0.235 lr:7.4e-05 updt_s:0.066 data_s:0.029
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| 185 |
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INFO 2025-11-18 02:30:41 ts/train.py:232 step:34K smpl:275K ep:814 epch:16.27 loss:0.019 grdn:0.237 lr:7.4e-05 updt_s:0.066 data_s:0.028
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| 186 |
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INFO 2025-11-18 02:30:59 ts/train.py:232 step:35K smpl:277K ep:818 epch:16.37 loss:0.019 grdn:0.248 lr:7.4e-05 updt_s:0.066 data_s:0.024
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| 187 |
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INFO 2025-11-18 02:31:17 ts/train.py:232 step:35K smpl:278K ep:823 epch:16.46 loss:0.021 grdn:0.259 lr:7.4e-05 updt_s:0.066 data_s:0.022
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| 188 |
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INFO 2025-11-18 02:31:35 ts/train.py:232 step:35K smpl:280K ep:828 epch:16.56 loss:0.019 grdn:0.234 lr:7.3e-05 updt_s:0.066 data_s:0.023
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| 189 |
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INFO 2025-11-18 02:31:53 ts/train.py:232 step:35K smpl:282K ep:833 epch:16.65 loss:0.018 grdn:0.235 lr:7.3e-05 updt_s:0.066 data_s:0.026
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| 190 |
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INFO 2025-11-18 02:32:13 ts/train.py:232 step:35K smpl:283K ep:837 epch:16.75 loss:0.019 grdn:0.249 lr:7.3e-05 updt_s:0.066 data_s:0.031
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INFO 2025-11-18 02:32:33 ts/train.py:232 step:36K smpl:285K ep:842 epch:16.84 loss:0.017 grdn:0.238 lr:7.2e-05 updt_s:0.066 data_s:0.031
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INFO 2025-11-18 02:32:52 ts/train.py:232 step:36K smpl:286K ep:847 epch:16.94 loss:0.018 grdn:0.238 lr:7.2e-05 updt_s:0.067 data_s:0.031
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INFO 2025-11-18 02:33:12 ts/train.py:232 step:36K smpl:288K ep:852 epch:17.03 loss:0.018 grdn:0.233 lr:7.2e-05 updt_s:0.066 data_s:0.030
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| 194 |
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INFO 2025-11-18 02:33:31 ts/train.py:232 step:36K smpl:290K ep:856 epch:17.13 loss:0.019 grdn:0.245 lr:7.2e-05 updt_s:0.066 data_s:0.031
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INFO 2025-11-18 02:33:51 ts/train.py:232 step:36K smpl:291K ep:861 epch:17.22 loss:0.018 grdn:0.228 lr:7.1e-05 updt_s:0.067 data_s:0.030
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INFO 2025-11-18 02:34:09 ts/train.py:232 step:37K smpl:293K ep:866 epch:17.32 loss:0.019 grdn:0.230 lr:7.1e-05 updt_s:0.066 data_s:0.026
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INFO 2025-11-18 02:34:28 ts/train.py:232 step:37K smpl:294K ep:870 epch:17.41 loss:0.019 grdn:0.243 lr:7.1e-05 updt_s:0.067 data_s:0.025
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INFO 2025-11-18 02:34:46 ts/train.py:232 step:37K smpl:296K ep:875 epch:17.50 loss:0.019 grdn:0.247 lr:7.0e-05 updt_s:0.067 data_s:0.024
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INFO 2025-11-18 02:35:04 ts/train.py:232 step:37K smpl:298K ep:880 epch:17.60 loss:0.019 grdn:0.236 lr:7.0e-05 updt_s:0.066 data_s:0.025
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INFO 2025-11-18 02:35:28 ts/train.py:232 step:37K smpl:299K ep:885 epch:17.69 loss:0.017 grdn:0.229 lr:7.0e-05 updt_s:0.066 data_s:0.055
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INFO 2025-11-18 02:35:48 ts/train.py:232 step:38K smpl:301K ep:889 epch:17.79 loss:0.016 grdn:0.236 lr:7.0e-05 updt_s:0.067 data_s:0.031
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INFO 2025-11-18 02:36:08 ts/train.py:232 step:38K smpl:302K ep:894 epch:17.88 loss:0.017 grdn:0.229 lr:6.9e-05 updt_s:0.067 data_s:0.031
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INFO 2025-11-18 02:36:28 ts/train.py:232 step:38K smpl:304K ep:899 epch:17.98 loss:0.018 grdn:0.238 lr:6.9e-05 updt_s:0.067 data_s:0.032
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INFO 2025-11-18 02:36:48 ts/train.py:232 step:38K smpl:306K ep:904 epch:18.07 loss:0.018 grdn:0.239 lr:6.9e-05 updt_s:0.067 data_s:0.032
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INFO 2025-11-18 02:37:08 ts/train.py:232 step:38K smpl:307K ep:908 epch:18.17 loss:0.018 grdn:0.234 lr:6.8e-05 updt_s:0.067 data_s:0.033
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INFO 2025-11-18 02:37:27 ts/train.py:232 step:39K smpl:309K ep:913 epch:18.26 loss:0.018 grdn:0.241 lr:6.8e-05 updt_s:0.066 data_s:0.031
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INFO 2025-11-18 02:37:46 ts/train.py:232 step:39K smpl:310K ep:918 epch:18.36 loss:0.019 grdn:0.250 lr:6.8e-05 updt_s:0.067 data_s:0.024
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INFO 2025-11-18 02:38:06 ts/train.py:232 step:39K smpl:312K ep:923 epch:18.45 loss:0.019 grdn:0.247 lr:6.8e-05 updt_s:0.067 data_s:0.037
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INFO 2025-11-18 02:38:25 ts/train.py:232 step:39K smpl:314K ep:927 epch:18.55 loss:0.018 grdn:0.236 lr:6.7e-05 updt_s:0.066 data_s:0.025
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INFO 2025-11-18 02:38:44 ts/train.py:232 step:39K smpl:315K ep:932 epch:18.64 loss:0.019 grdn:0.258 lr:6.7e-05 updt_s:0.067 data_s:0.028
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INFO 2025-11-18 02:39:03 ts/train.py:232 step:40K smpl:317K ep:937 epch:18.73 loss:0.017 grdn:0.223 lr:6.7e-05 updt_s:0.066 data_s:0.028
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INFO 2025-11-18 02:39:22 ts/train.py:232 step:40K smpl:318K ep:941 epch:18.83 loss:0.017 grdn:0.242 lr:6.6e-05 updt_s:0.066 data_s:0.028
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INFO 2025-11-18 02:39:40 ts/train.py:232 step:40K smpl:320K ep:946 epch:18.92 loss:0.019 grdn:0.243 lr:6.6e-05 updt_s:0.066 data_s:0.027
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INFO 2025-11-18 02:39:40 ts/train.py:241 Checkpoint policy after step 40000
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INFO 2025-11-18 02:40:38 ts/train.py:232 step:40K smpl:322K ep:951 epch:19.02 loss:0.018 grdn:0.239 lr:6.6e-05 updt_s:0.067 data_s:0.026
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INFO 2025-11-18 02:40:57 ts/train.py:232 step:40K smpl:323K ep:956 epch:19.11 loss:0.018 grdn:0.240 lr:6.5e-05 updt_s:0.066 data_s:0.027
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INFO 2025-11-18 02:41:14 ts/train.py:232 step:41K smpl:325K ep:960 epch:19.21 loss:0.017 grdn:0.234 lr:6.5e-05 updt_s:0.065 data_s:0.021
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INFO 2025-11-18 02:41:31 ts/train.py:232 step:41K smpl:326K ep:965 epch:19.30 loss:0.018 grdn:0.246 lr:6.5e-05 updt_s:0.065 data_s:0.018
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INFO 2025-11-18 02:41:48 ts/train.py:232 step:41K smpl:328K ep:970 epch:19.40 loss:0.018 grdn:0.242 lr:6.5e-05 updt_s:0.065 data_s:0.019
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INFO 2025-11-18 02:42:06 ts/train.py:232 step:41K smpl:330K ep:975 epch:19.49 loss:0.018 grdn:0.247 lr:6.4e-05 updt_s:0.066 data_s:0.023
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INFO 2025-11-18 02:42:24 ts/train.py:232 step:41K smpl:331K ep:979 epch:19.59 loss:0.017 grdn:0.231 lr:6.4e-05 updt_s:0.066 data_s:0.024
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INFO 2025-11-18 02:42:44 ts/train.py:232 step:42K smpl:333K ep:984 epch:19.68 loss:0.018 grdn:0.241 lr:6.4e-05 updt_s:0.066 data_s:0.033
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INFO 2025-11-18 02:43:04 ts/train.py:232 step:42K smpl:334K ep:989 epch:19.78 loss:0.017 grdn:0.230 lr:6.3e-05 updt_s:0.066 data_s:0.030
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INFO 2025-11-18 02:43:23 ts/train.py:232 step:42K smpl:336K ep:993 epch:19.87 loss:0.017 grdn:0.232 lr:6.3e-05 updt_s:0.066 data_s:0.030
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INFO 2025-11-18 02:43:42 ts/train.py:232 step:42K smpl:338K ep:998 epch:19.96 loss:0.016 grdn:0.225 lr:6.3e-05 updt_s:0.067 data_s:0.030
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INFO 2025-11-18 02:44:02 ts/train.py:232 step:42K smpl:339K ep:1K epch:20.06 loss:0.017 grdn:0.242 lr:6.2e-05 updt_s:0.066 data_s:0.030
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INFO 2025-11-18 02:44:21 ts/train.py:232 step:43K smpl:341K ep:1K epch:20.15 loss:0.019 grdn:0.256 lr:6.2e-05 updt_s:0.066 data_s:0.031
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INFO 2025-11-18 02:44:40 ts/train.py:232 step:43K smpl:342K ep:1K epch:20.25 loss:0.017 grdn:0.239 lr:6.2e-05 updt_s:0.066 data_s:0.028
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INFO 2025-11-18 02:44:58 ts/train.py:232 step:43K smpl:344K ep:1K epch:20.34 loss:0.017 grdn:0.231 lr:6.1e-05 updt_s:0.066 data_s:0.024
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INFO 2025-11-18 02:45:17 ts/train.py:232 step:43K smpl:346K ep:1K epch:20.44 loss:0.017 grdn:0.240 lr:6.1e-05 updt_s:0.067 data_s:0.024
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INFO 2025-11-18 02:45:35 ts/train.py:232 step:43K smpl:347K ep:1K epch:20.53 loss:0.016 grdn:0.225 lr:6.1e-05 updt_s:0.067 data_s:0.023
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INFO 2025-11-18 02:45:56 ts/train.py:232 step:44K smpl:349K ep:1K epch:20.63 loss:0.016 grdn:0.229 lr:6.1e-05 updt_s:0.067 data_s:0.041
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INFO 2025-11-18 02:46:16 ts/train.py:232 step:44K smpl:350K ep:1K epch:20.72 loss:0.017 grdn:0.233 lr:6.0e-05 updt_s:0.067 data_s:0.031
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INFO 2025-11-18 02:46:36 ts/train.py:232 step:44K smpl:352K ep:1K epch:20.82 loss:0.017 grdn:0.231 lr:6.0e-05 updt_s:0.067 data_s:0.031
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INFO 2025-11-18 02:46:55 ts/train.py:232 step:44K smpl:354K ep:1K epch:20.91 loss:0.017 grdn:0.244 lr:6.0e-05 updt_s:0.067 data_s:0.030
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INFO 2025-11-18 02:47:14 ts/train.py:232 step:44K smpl:355K ep:1K epch:21.01 loss:0.018 grdn:0.249 lr:5.9e-05 updt_s:0.066 data_s:0.030
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INFO 2025-11-18 02:47:34 ts/train.py:232 step:45K smpl:357K ep:1K epch:21.10 loss:0.015 grdn:0.226 lr:5.9e-05 updt_s:0.067 data_s:0.030
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INFO 2025-11-18 02:47:53 ts/train.py:232 step:45K smpl:358K ep:1K epch:21.19 loss:0.017 grdn:0.238 lr:5.9e-05 updt_s:0.066 data_s:0.030
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INFO 2025-11-18 02:48:14 ts/train.py:232 step:45K smpl:360K ep:1K epch:21.29 loss:0.020 grdn:0.250 lr:5.8e-05 updt_s:0.066 data_s:0.039
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INFO 2025-11-18 02:48:33 ts/train.py:232 step:45K smpl:362K ep:1K epch:21.38 loss:0.019 grdn:0.250 lr:5.8e-05 updt_s:0.067 data_s:0.024
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INFO 2025-11-18 02:48:51 ts/train.py:232 step:45K smpl:363K ep:1K epch:21.48 loss:0.017 grdn:0.234 lr:5.8e-05 updt_s:0.066 data_s:0.024
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INFO 2025-11-18 02:49:10 ts/train.py:232 step:46K smpl:365K ep:1K epch:21.57 loss:0.017 grdn:0.233 lr:5.7e-05 updt_s:0.066 data_s:0.029
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INFO 2025-11-18 02:49:29 ts/train.py:232 step:46K smpl:366K ep:1K epch:21.67 loss:0.018 grdn:0.236 lr:5.7e-05 updt_s:0.066 data_s:0.030
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INFO 2025-11-18 02:49:49 ts/train.py:232 step:46K smpl:368K ep:1K epch:21.76 loss:0.017 grdn:0.245 lr:5.7e-05 updt_s:0.066 data_s:0.029
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INFO 2025-11-18 02:50:08 ts/train.py:232 step:46K smpl:370K ep:1K epch:21.86 loss:0.017 grdn:0.237 lr:5.7e-05 updt_s:0.066 data_s:0.029
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INFO 2025-11-18 02:50:27 ts/train.py:232 step:46K smpl:371K ep:1K epch:21.95 loss:0.015 grdn:0.224 lr:5.6e-05 updt_s:0.066 data_s:0.029
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INFO 2025-11-18 02:50:46 ts/train.py:232 step:47K smpl:373K ep:1K epch:22.05 loss:0.016 grdn:0.224 lr:5.6e-05 updt_s:0.066 data_s:0.030
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INFO 2025-11-18 02:51:05 ts/train.py:232 step:47K smpl:374K ep:1K epch:22.14 loss:0.016 grdn:0.222 lr:5.6e-05 updt_s:0.066 data_s:0.028
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INFO 2025-11-18 02:51:23 ts/train.py:232 step:47K smpl:376K ep:1K epch:22.24 loss:0.016 grdn:0.232 lr:5.5e-05 updt_s:0.066 data_s:0.024
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INFO 2025-11-18 02:51:41 ts/train.py:232 step:47K smpl:378K ep:1K epch:22.33 loss:0.016 grdn:0.232 lr:5.5e-05 updt_s:0.066 data_s:0.023
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INFO 2025-11-18 02:51:59 ts/train.py:232 step:47K smpl:379K ep:1K epch:22.42 loss:0.016 grdn:0.242 lr:5.5e-05 updt_s:0.066 data_s:0.024
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INFO 2025-11-18 02:52:17 ts/train.py:232 step:48K smpl:381K ep:1K epch:22.52 loss:0.017 grdn:0.245 lr:5.4e-05 updt_s:0.066 data_s:0.023
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INFO 2025-11-18 02:52:39 ts/train.py:232 step:48K smpl:382K ep:1K epch:22.61 loss:0.016 grdn:0.238 lr:5.4e-05 updt_s:0.066 data_s:0.042
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INFO 2025-11-18 02:52:58 ts/train.py:232 step:48K smpl:384K ep:1K epch:22.71 loss:0.016 grdn:0.239 lr:5.4e-05 updt_s:0.067 data_s:0.029
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INFO 2025-11-18 02:53:18 ts/train.py:232 step:48K smpl:386K ep:1K epch:22.80 loss:0.016 grdn:0.233 lr:5.3e-05 updt_s:0.066 data_s:0.030
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INFO 2025-11-18 02:53:37 ts/train.py:232 step:48K smpl:387K ep:1K epch:22.90 loss:0.016 grdn:0.244 lr:5.3e-05 updt_s:0.067 data_s:0.029
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INFO 2025-11-18 02:53:56 ts/train.py:232 step:49K smpl:389K ep:1K epch:22.99 loss:0.016 grdn:0.238 lr:5.3e-05 updt_s:0.066 data_s:0.030
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INFO 2025-11-18 02:54:15 ts/train.py:232 step:49K smpl:390K ep:1K epch:23.09 loss:0.016 grdn:0.226 lr:5.2e-05 updt_s:0.066 data_s:0.029
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INFO 2025-11-18 02:54:34 ts/train.py:232 step:49K smpl:392K ep:1K epch:23.18 loss:0.018 grdn:0.250 lr:5.2e-05 updt_s:0.066 data_s:0.028
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INFO 2025-11-18 02:54:52 ts/train.py:232 step:49K smpl:394K ep:1K epch:23.28 loss:0.015 grdn:0.223 lr:5.2e-05 updt_s:0.067 data_s:0.023
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INFO 2025-11-18 02:55:10 ts/train.py:232 step:49K smpl:395K ep:1K epch:23.37 loss:0.016 grdn:0.228 lr:5.1e-05 updt_s:0.067 data_s:0.023
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INFO 2025-11-18 02:55:28 ts/train.py:232 step:50K smpl:397K ep:1K epch:23.47 loss:0.015 grdn:0.228 lr:5.1e-05 updt_s:0.067 data_s:0.024
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INFO 2025-11-18 02:55:50 ts/train.py:232 step:50K smpl:398K ep:1K epch:23.56 loss:0.015 grdn:0.232 lr:5.1e-05 updt_s:0.066 data_s:0.041
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INFO 2025-11-18 02:56:09 ts/train.py:232 step:50K smpl:400K ep:1K epch:23.65 loss:0.016 grdn:0.244 lr:5.1e-05 updt_s:0.066 data_s:0.031
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INFO 2025-11-18 02:56:29 ts/train.py:232 step:50K smpl:402K ep:1K epch:23.75 loss:0.017 grdn:0.241 lr:5.0e-05 updt_s:0.067 data_s:0.031
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INFO 2025-11-18 02:56:48 ts/train.py:232 step:50K smpl:403K ep:1K epch:23.84 loss:0.015 grdn:0.207 lr:5.0e-05 updt_s:0.066 data_s:0.030
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INFO 2025-11-18 02:57:08 ts/train.py:232 step:51K smpl:405K ep:1K epch:23.94 loss:0.015 grdn:0.228 lr:5.0e-05 updt_s:0.067 data_s:0.030
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INFO 2025-11-18 02:57:27 ts/train.py:232 step:51K smpl:406K ep:1K epch:24.03 loss:0.014 grdn:0.222 lr:4.9e-05 updt_s:0.067 data_s:0.030
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INFO 2025-11-18 02:57:47 ts/train.py:232 step:51K smpl:408K ep:1K epch:24.13 loss:0.016 grdn:0.238 lr:4.9e-05 updt_s:0.066 data_s:0.031
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INFO 2025-11-18 02:58:05 ts/train.py:232 step:51K smpl:410K ep:1K epch:24.22 loss:0.015 grdn:0.223 lr:4.9e-05 updt_s:0.066 data_s:0.024
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INFO 2025-11-18 02:58:26 ts/train.py:232 step:51K smpl:411K ep:1K epch:24.32 loss:0.015 grdn:0.222 lr:4.8e-05 updt_s:0.066 data_s:0.040
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INFO 2025-11-18 02:58:44 ts/train.py:232 step:52K smpl:413K ep:1K epch:24.41 loss:0.016 grdn:0.237 lr:4.8e-05 updt_s:0.066 data_s:0.024
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INFO 2025-11-18 02:59:06 ts/train.py:232 step:52K smpl:414K ep:1K epch:24.51 loss:0.016 grdn:0.241 lr:4.8e-05 updt_s:0.066 data_s:0.043
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INFO 2025-11-18 02:59:25 ts/train.py:232 step:52K smpl:416K ep:1K epch:24.60 loss:0.016 grdn:0.223 lr:4.7e-05 updt_s:0.066 data_s:0.030
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INFO 2025-11-18 02:59:45 ts/train.py:232 step:52K smpl:418K ep:1K epch:24.70 loss:0.017 grdn:0.244 lr:4.7e-05 updt_s:0.067 data_s:0.029
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INFO 2025-11-18 03:00:04 ts/train.py:232 step:52K smpl:419K ep:1K epch:24.79 loss:0.015 grdn:0.231 lr:4.7e-05 updt_s:0.066 data_s:0.030
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INFO 2025-11-18 03:00:23 ts/train.py:232 step:53K smpl:421K ep:1K epch:24.88 loss:0.016 grdn:0.231 lr:4.6e-05 updt_s:0.066 data_s:0.030
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INFO 2025-11-18 03:00:42 ts/train.py:232 step:53K smpl:422K ep:1K epch:24.98 loss:0.015 grdn:0.224 lr:4.6e-05 updt_s:0.066 data_s:0.030
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INFO 2025-11-18 03:01:02 ts/train.py:232 step:53K smpl:424K ep:1K epch:25.07 loss:0.016 grdn:0.243 lr:4.6e-05 updt_s:0.067 data_s:0.030
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INFO 2025-11-18 03:01:21 ts/train.py:232 step:53K smpl:426K ep:1K epch:25.17 loss:0.015 grdn:0.211 lr:4.6e-05 updt_s:0.066 data_s:0.027
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INFO 2025-11-18 03:01:39 ts/train.py:232 step:53K smpl:427K ep:1K epch:25.26 loss:0.016 grdn:0.236 lr:4.5e-05 updt_s:0.066 data_s:0.025
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INFO 2025-11-18 03:01:57 ts/train.py:232 step:54K smpl:429K ep:1K epch:25.36 loss:0.015 grdn:0.230 lr:4.5e-05 updt_s:0.066 data_s:0.023
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INFO 2025-11-18 03:02:15 ts/train.py:232 step:54K smpl:430K ep:1K epch:25.45 loss:0.016 grdn:0.237 lr:4.5e-05 updt_s:0.066 data_s:0.023
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INFO 2025-11-18 03:02:38 ts/train.py:232 step:54K smpl:432K ep:1K epch:25.55 loss:0.015 grdn:0.233 lr:4.4e-05 updt_s:0.066 data_s:0.048
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INFO 2025-11-18 03:02:57 ts/train.py:232 step:54K smpl:434K ep:1K epch:25.64 loss:0.013 grdn:0.208 lr:4.4e-05 updt_s:0.066 data_s:0.032
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INFO 2025-11-18 03:03:17 ts/train.py:232 step:54K smpl:435K ep:1K epch:25.74 loss:0.013 grdn:0.213 lr:4.4e-05 updt_s:0.066 data_s:0.030
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INFO 2025-11-18 03:03:36 ts/train.py:232 step:55K smpl:437K ep:1K epch:25.83 loss:0.016 grdn:0.228 lr:4.3e-05 updt_s:0.066 data_s:0.030
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INFO 2025-11-18 03:03:55 ts/train.py:232 step:55K smpl:438K ep:1K epch:25.93 loss:0.016 grdn:0.233 lr:4.3e-05 updt_s:0.067 data_s:0.029
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INFO 2025-11-18 03:04:15 ts/train.py:232 step:55K smpl:440K ep:1K epch:26.02 loss:0.016 grdn:0.235 lr:4.3e-05 updt_s:0.066 data_s:0.031
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INFO 2025-11-18 03:04:33 ts/train.py:232 step:55K smpl:442K ep:1K epch:26.11 loss:0.015 grdn:0.224 lr:4.2e-05 updt_s:0.066 data_s:0.028
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INFO 2025-11-18 03:04:52 ts/train.py:232 step:55K smpl:443K ep:1K epch:26.21 loss:0.015 grdn:0.226 lr:4.2e-05 updt_s:0.066 data_s:0.026
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INFO 2025-11-18 03:05:11 ts/train.py:232 step:56K smpl:445K ep:1K epch:26.30 loss:0.015 grdn:0.222 lr:4.2e-05 updt_s:0.066 data_s:0.028
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INFO 2025-11-18 03:05:30 ts/train.py:232 step:56K smpl:446K ep:1K epch:26.40 loss:0.015 grdn:0.222 lr:4.1e-05 updt_s:0.066 data_s:0.027
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INFO 2025-11-18 03:05:50 ts/train.py:232 step:56K smpl:448K ep:1K epch:26.49 loss:0.015 grdn:0.231 lr:4.1e-05 updt_s:0.066 data_s:0.036
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INFO 2025-11-18 03:06:09 ts/train.py:232 step:56K smpl:450K ep:1K epch:26.59 loss:0.016 grdn:0.244 lr:4.1e-05 updt_s:0.066 data_s:0.029
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INFO 2025-11-18 03:06:28 ts/train.py:232 step:56K smpl:451K ep:1K epch:26.68 loss:0.015 grdn:0.225 lr:4.1e-05 updt_s:0.066 data_s:0.029
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INFO 2025-11-18 03:06:47 ts/train.py:232 step:57K smpl:453K ep:1K epch:26.78 loss:0.014 grdn:0.223 lr:4.0e-05 updt_s:0.066 data_s:0.029
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INFO 2025-11-18 03:07:07 ts/train.py:232 step:57K smpl:454K ep:1K epch:26.87 loss:0.015 grdn:0.232 lr:4.0e-05 updt_s:0.066 data_s:0.029
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INFO 2025-11-18 03:07:26 ts/train.py:232 step:57K smpl:456K ep:1K epch:26.97 loss:0.014 grdn:0.224 lr:4.0e-05 updt_s:0.066 data_s:0.030
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INFO 2025-11-18 03:07:45 ts/train.py:232 step:57K smpl:458K ep:1K epch:27.06 loss:0.014 grdn:0.217 lr:3.9e-05 updt_s:0.066 data_s:0.029
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INFO 2025-11-18 03:08:03 ts/train.py:232 step:57K smpl:459K ep:1K epch:27.16 loss:0.014 grdn:0.223 lr:3.9e-05 updt_s:0.066 data_s:0.022
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INFO 2025-11-18 03:08:21 ts/train.py:232 step:58K smpl:461K ep:1K epch:27.25 loss:0.015 grdn:0.236 lr:3.9e-05 updt_s:0.066 data_s:0.022
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INFO 2025-11-18 03:08:41 ts/train.py:232 step:58K smpl:462K ep:1K epch:27.34 loss:0.014 grdn:0.225 lr:3.8e-05 updt_s:0.066 data_s:0.036
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INFO 2025-11-18 03:09:00 ts/train.py:232 step:58K smpl:464K ep:1K epch:27.44 loss:0.015 grdn:0.232 lr:3.8e-05 updt_s:0.067 data_s:0.026
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INFO 2025-11-18 03:09:19 ts/train.py:232 step:58K smpl:466K ep:1K epch:27.53 loss:0.014 grdn:0.212 lr:3.8e-05 updt_s:0.067 data_s:0.028
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INFO 2025-11-18 03:09:38 ts/train.py:232 step:58K smpl:467K ep:1K epch:27.63 loss:0.014 grdn:0.225 lr:3.7e-05 updt_s:0.067 data_s:0.026
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INFO 2025-11-18 03:09:56 ts/train.py:232 step:59K smpl:469K ep:1K epch:27.72 loss:0.015 grdn:0.233 lr:3.7e-05 updt_s:0.066 data_s:0.026
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INFO 2025-11-18 03:10:15 ts/train.py:232 step:59K smpl:470K ep:1K epch:27.82 loss:0.014 grdn:0.220 lr:3.7e-05 updt_s:0.067 data_s:0.028
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INFO 2025-11-18 03:10:34 ts/train.py:232 step:59K smpl:472K ep:1K epch:27.91 loss:0.014 grdn:0.216 lr:3.7e-05 updt_s:0.066 data_s:0.027
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INFO 2025-11-18 03:10:53 ts/train.py:232 step:59K smpl:474K ep:1K epch:28.01 loss:0.014 grdn:0.213 lr:3.6e-05 updt_s:0.067 data_s:0.027
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INFO 2025-11-18 03:11:11 ts/train.py:232 step:59K smpl:475K ep:1K epch:28.10 loss:0.015 grdn:0.240 lr:3.6e-05 updt_s:0.066 data_s:0.024
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INFO 2025-11-18 03:11:29 ts/train.py:232 step:60K smpl:477K ep:1K epch:28.20 loss:0.015 grdn:0.236 lr:3.6e-05 updt_s:0.066 data_s:0.022
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INFO 2025-11-18 03:11:46 ts/train.py:232 step:60K smpl:478K ep:1K epch:28.29 loss:0.015 grdn:0.244 lr:3.5e-05 updt_s:0.066 data_s:0.022
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INFO 2025-11-18 03:12:04 ts/train.py:232 step:60K smpl:480K ep:1K epch:28.39 loss:0.013 grdn:0.207 lr:3.5e-05 updt_s:0.066 data_s:0.021
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INFO 2025-11-18 03:12:04 ts/train.py:241 Checkpoint policy after step 60000
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INFO 2025-11-18 03:12:44 ts/train.py:232 step:60K smpl:482K ep:1K epch:28.48 loss:0.016 grdn:0.245 lr:3.5e-05 updt_s:0.065 data_s:0.032
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INFO 2025-11-18 03:13:04 ts/train.py:232 step:60K smpl:483K ep:1K epch:28.57 loss:0.013 grdn:0.217 lr:3.4e-05 updt_s:0.066 data_s:0.033
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INFO 2025-11-18 03:13:24 ts/train.py:232 step:61K smpl:485K ep:1K epch:28.67 loss:0.013 grdn:0.227 lr:3.4e-05 updt_s:0.067 data_s:0.034
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INFO 2025-11-18 03:13:44 ts/train.py:232 step:61K smpl:486K ep:1K epch:28.76 loss:0.014 grdn:0.233 lr:3.4e-05 updt_s:0.066 data_s:0.033
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INFO 2025-11-18 03:14:04 ts/train.py:232 step:61K smpl:488K ep:1K epch:28.86 loss:0.013 grdn:0.213 lr:3.4e-05 updt_s:0.066 data_s:0.034
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INFO 2025-11-18 03:14:24 ts/train.py:232 step:61K smpl:490K ep:1K epch:28.95 loss:0.014 grdn:0.224 lr:3.3e-05 updt_s:0.066 data_s:0.034
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INFO 2025-11-18 03:14:44 ts/train.py:232 step:61K smpl:491K ep:1K epch:29.05 loss:0.013 grdn:0.217 lr:3.3e-05 updt_s:0.066 data_s:0.032
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INFO 2025-11-18 03:15:03 ts/train.py:232 step:62K smpl:493K ep:1K epch:29.14 loss:0.013 grdn:0.218 lr:3.3e-05 updt_s:0.067 data_s:0.028
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INFO 2025-11-18 03:15:22 ts/train.py:232 step:62K smpl:494K ep:1K epch:29.24 loss:0.014 grdn:0.225 lr:3.2e-05 updt_s:0.067 data_s:0.027
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INFO 2025-11-18 03:15:41 ts/train.py:232 step:62K smpl:496K ep:1K epch:29.33 loss:0.013 grdn:0.214 lr:3.2e-05 updt_s:0.067 data_s:0.029
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INFO 2025-11-18 03:16:01 ts/train.py:232 step:62K smpl:498K ep:1K epch:29.43 loss:0.013 grdn:0.219 lr:3.2e-05 updt_s:0.067 data_s:0.032
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INFO 2025-11-18 03:16:21 ts/train.py:232 step:62K smpl:499K ep:1K epch:29.52 loss:0.013 grdn:0.227 lr:3.1e-05 updt_s:0.067 data_s:0.031
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INFO 2025-11-18 03:16:40 ts/train.py:232 step:63K smpl:501K ep:1K epch:29.62 loss:0.012 grdn:0.213 lr:3.1e-05 updt_s:0.066 data_s:0.030
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INFO 2025-11-18 03:17:00 ts/train.py:232 step:63K smpl:502K ep:1K epch:29.71 loss:0.012 grdn:0.208 lr:3.1e-05 updt_s:0.067 data_s:0.030
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INFO 2025-11-18 03:17:19 ts/train.py:232 step:63K smpl:504K ep:1K epch:29.80 loss:0.014 grdn:0.216 lr:3.1e-05 updt_s:0.067 data_s:0.030
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INFO 2025-11-18 03:17:39 ts/train.py:232 step:63K smpl:506K ep:1K epch:29.90 loss:0.013 grdn:0.214 lr:3.0e-05 updt_s:0.067 data_s:0.030
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INFO 2025-11-18 03:17:58 ts/train.py:232 step:63K smpl:507K ep:1K epch:29.99 loss:0.013 grdn:0.218 lr:3.0e-05 updt_s:0.066 data_s:0.029
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INFO 2025-11-18 03:18:16 ts/train.py:232 step:64K smpl:509K ep:2K epch:30.09 loss:0.014 grdn:0.238 lr:3.0e-05 updt_s:0.066 data_s:0.024
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INFO 2025-11-18 03:18:37 ts/train.py:232 step:64K smpl:510K ep:2K epch:30.18 loss:0.014 grdn:0.225 lr:2.9e-05 updt_s:0.066 data_s:0.040
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INFO 2025-11-18 03:18:56 ts/train.py:232 step:64K smpl:512K ep:2K epch:30.28 loss:0.013 grdn:0.229 lr:2.9e-05 updt_s:0.067 data_s:0.025
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INFO 2025-11-18 03:19:15 ts/train.py:232 step:64K smpl:514K ep:2K epch:30.37 loss:0.013 grdn:0.226 lr:2.9e-05 updt_s:0.066 data_s:0.027
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INFO 2025-11-18 03:19:34 ts/train.py:232 step:64K smpl:515K ep:2K epch:30.47 loss:0.011 grdn:0.195 lr:2.9e-05 updt_s:0.067 data_s:0.029
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INFO 2025-11-18 03:19:53 ts/train.py:232 step:65K smpl:517K ep:2K epch:30.56 loss:0.012 grdn:0.209 lr:2.8e-05 updt_s:0.066 data_s:0.029
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INFO 2025-11-18 03:20:12 ts/train.py:232 step:65K smpl:518K ep:2K epch:30.66 loss:0.013 grdn:0.222 lr:2.8e-05 updt_s:0.066 data_s:0.028
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INFO 2025-11-18 03:20:31 ts/train.py:232 step:65K smpl:520K ep:2K epch:30.75 loss:0.013 grdn:0.219 lr:2.8e-05 updt_s:0.067 data_s:0.029
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INFO 2025-11-18 03:20:50 ts/train.py:232 step:65K smpl:522K ep:2K epch:30.85 loss:0.013 grdn:0.224 lr:2.7e-05 updt_s:0.066 data_s:0.030
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INFO 2025-11-18 03:21:09 ts/train.py:232 step:65K smpl:523K ep:2K epch:30.94 loss:0.014 grdn:0.217 lr:2.7e-05 updt_s:0.067 data_s:0.028
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INFO 2025-11-18 03:21:28 ts/train.py:232 step:66K smpl:525K ep:2K epch:31.03 loss:0.014 grdn:0.226 lr:2.7e-05 updt_s:0.066 data_s:0.026
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INFO 2025-11-18 03:21:46 ts/train.py:232 step:66K smpl:526K ep:2K epch:31.13 loss:0.013 grdn:0.216 lr:2.7e-05 updt_s:0.066 data_s:0.024
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INFO 2025-11-18 03:22:04 ts/train.py:232 step:66K smpl:528K ep:2K epch:31.22 loss:0.013 grdn:0.222 lr:2.6e-05 updt_s:0.066 data_s:0.024
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INFO 2025-11-18 03:22:22 ts/train.py:232 step:66K smpl:530K ep:2K epch:31.32 loss:0.012 grdn:0.215 lr:2.6e-05 updt_s:0.065 data_s:0.022
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INFO 2025-11-18 03:22:42 ts/train.py:232 step:66K smpl:531K ep:2K epch:31.41 loss:0.013 grdn:0.217 lr:2.6e-05 updt_s:0.066 data_s:0.032
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INFO 2025-11-18 03:23:01 ts/train.py:232 step:67K smpl:533K ep:2K epch:31.51 loss:0.013 grdn:0.224 lr:2.5e-05 updt_s:0.066 data_s:0.032
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INFO 2025-11-18 03:23:21 ts/train.py:232 step:67K smpl:534K ep:2K epch:31.60 loss:0.014 grdn:0.226 lr:2.5e-05 updt_s:0.066 data_s:0.032
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INFO 2025-11-18 03:23:40 ts/train.py:232 step:67K smpl:536K ep:2K epch:31.70 loss:0.012 grdn:0.207 lr:2.5e-05 updt_s:0.066 data_s:0.031
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INFO 2025-11-18 03:24:00 ts/train.py:232 step:67K smpl:538K ep:2K epch:31.79 loss:0.012 grdn:0.206 lr:2.5e-05 updt_s:0.066 data_s:0.031
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INFO 2025-11-18 03:24:20 ts/train.py:232 step:67K smpl:539K ep:2K epch:31.89 loss:0.014 grdn:0.225 lr:2.4e-05 updt_s:0.066 data_s:0.032
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INFO 2025-11-18 03:24:39 ts/train.py:232 step:68K smpl:541K ep:2K epch:31.98 loss:0.013 grdn:0.212 lr:2.4e-05 updt_s:0.066 data_s:0.031
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INFO 2025-11-18 03:24:58 ts/train.py:232 step:68K smpl:542K ep:2K epch:32.08 loss:0.013 grdn:0.224 lr:2.4e-05 updt_s:0.066 data_s:0.028
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INFO 2025-11-18 03:25:17 ts/train.py:232 step:68K smpl:544K ep:2K epch:32.17 loss:0.013 grdn:0.224 lr:2.4e-05 updt_s:0.067 data_s:0.027
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INFO 2025-11-18 03:25:36 ts/train.py:232 step:68K smpl:546K ep:2K epch:32.26 loss:0.013 grdn:0.224 lr:2.3e-05 updt_s:0.066 data_s:0.027
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INFO 2025-11-18 03:25:56 ts/train.py:232 step:68K smpl:547K ep:2K epch:32.36 loss:0.012 grdn:0.218 lr:2.3e-05 updt_s:0.066 data_s:0.032
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INFO 2025-11-18 03:26:16 ts/train.py:232 step:69K smpl:549K ep:2K epch:32.45 loss:0.013 grdn:0.221 lr:2.3e-05 updt_s:0.066 data_s:0.032
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INFO 2025-11-18 03:26:35 ts/train.py:232 step:69K smpl:550K ep:2K epch:32.55 loss:0.013 grdn:0.220 lr:2.2e-05 updt_s:0.067 data_s:0.032
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INFO 2025-11-18 03:26:55 ts/train.py:232 step:69K smpl:552K ep:2K epch:32.64 loss:0.014 grdn:0.243 lr:2.2e-05 updt_s:0.066 data_s:0.032
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INFO 2025-11-18 03:27:15 ts/train.py:232 step:69K smpl:554K ep:2K epch:32.74 loss:0.013 grdn:0.231 lr:2.2e-05 updt_s:0.067 data_s:0.032
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INFO 2025-11-18 03:27:35 ts/train.py:232 step:69K smpl:555K ep:2K epch:32.83 loss:0.012 grdn:0.204 lr:2.2e-05 updt_s:0.066 data_s:0.031
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INFO 2025-11-18 03:27:54 ts/train.py:232 step:70K smpl:557K ep:2K epch:32.93 loss:0.013 grdn:0.219 lr:2.1e-05 updt_s:0.066 data_s:0.031
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INFO 2025-11-18 03:28:13 ts/train.py:232 step:70K smpl:558K ep:2K epch:33.02 loss:0.012 grdn:0.215 lr:2.1e-05 updt_s:0.067 data_s:0.028
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INFO 2025-11-18 03:28:32 ts/train.py:232 step:70K smpl:560K ep:2K epch:33.12 loss:0.012 grdn:0.219 lr:2.1e-05 updt_s:0.067 data_s:0.028
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INFO 2025-11-18 03:28:54 ts/train.py:232 step:70K smpl:562K ep:2K epch:33.21 loss:0.013 grdn:0.215 lr:2.1e-05 updt_s:0.067 data_s:0.043
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INFO 2025-11-18 03:29:14 ts/train.py:232 step:70K smpl:563K ep:2K epch:33.31 loss:0.013 grdn:0.223 lr:2.0e-05 updt_s:0.067 data_s:0.029
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| 368 |
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INFO 2025-11-18 03:29:33 ts/train.py:232 step:71K smpl:565K ep:2K epch:33.40 loss:0.012 grdn:0.206 lr:2.0e-05 updt_s:0.067 data_s:0.031
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INFO 2025-11-18 03:29:52 ts/train.py:232 step:71K smpl:566K ep:2K epch:33.49 loss:0.012 grdn:0.212 lr:2.0e-05 updt_s:0.066 data_s:0.029
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INFO 2025-11-18 03:30:11 ts/train.py:232 step:71K smpl:568K ep:2K epch:33.59 loss:0.011 grdn:0.200 lr:2.0e-05 updt_s:0.066 data_s:0.028
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INFO 2025-11-18 03:30:31 ts/train.py:232 step:71K smpl:570K ep:2K epch:33.68 loss:0.012 grdn:0.220 lr:1.9e-05 updt_s:0.066 data_s:0.028
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INFO 2025-11-18 03:30:50 ts/train.py:232 step:71K smpl:571K ep:2K epch:33.78 loss:0.012 grdn:0.222 lr:1.9e-05 updt_s:0.067 data_s:0.029
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INFO 2025-11-18 03:31:09 ts/train.py:232 step:72K smpl:573K ep:2K epch:33.87 loss:0.012 grdn:0.209 lr:1.9e-05 updt_s:0.067 data_s:0.030
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INFO 2025-11-18 03:31:28 ts/train.py:232 step:72K smpl:574K ep:2K epch:33.97 loss:0.013 grdn:0.226 lr:1.9e-05 updt_s:0.067 data_s:0.028
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INFO 2025-11-18 03:31:47 ts/train.py:232 step:72K smpl:576K ep:2K epch:34.06 loss:0.012 grdn:0.213 lr:1.8e-05 updt_s:0.067 data_s:0.026
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INFO 2025-11-18 03:32:06 ts/train.py:232 step:72K smpl:578K ep:2K epch:34.16 loss:0.011 grdn:0.216 lr:1.8e-05 updt_s:0.066 data_s:0.026
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INFO 2025-11-18 03:32:24 ts/train.py:232 step:72K smpl:579K ep:2K epch:34.25 loss:0.012 grdn:0.213 lr:1.8e-05 updt_s:0.067 data_s:0.025
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INFO 2025-11-18 03:32:43 ts/train.py:232 step:73K smpl:581K ep:2K epch:34.35 loss:0.012 grdn:0.225 lr:1.8e-05 updt_s:0.066 data_s:0.030
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INFO 2025-11-18 03:33:03 ts/train.py:232 step:73K smpl:582K ep:2K epch:34.44 loss:0.012 grdn:0.220 lr:1.7e-05 updt_s:0.067 data_s:0.031
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INFO 2025-11-18 03:33:23 ts/train.py:232 step:73K smpl:584K ep:2K epch:34.54 loss:0.012 grdn:0.212 lr:1.7e-05 updt_s:0.067 data_s:0.030
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INFO 2025-11-18 03:33:42 ts/train.py:232 step:73K smpl:586K ep:2K epch:34.63 loss:0.011 grdn:0.201 lr:1.7e-05 updt_s:0.067 data_s:0.030
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INFO 2025-11-18 03:34:01 ts/train.py:232 step:73K smpl:587K ep:2K epch:34.73 loss:0.011 grdn:0.193 lr:1.7e-05 updt_s:0.066 data_s:0.030
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INFO 2025-11-18 03:34:21 ts/train.py:232 step:74K smpl:589K ep:2K epch:34.82 loss:0.012 grdn:0.203 lr:1.7e-05 updt_s:0.067 data_s:0.030
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INFO 2025-11-18 03:34:40 ts/train.py:232 step:74K smpl:590K ep:2K epch:34.91 loss:0.011 grdn:0.206 lr:1.6e-05 updt_s:0.067 data_s:0.030
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INFO 2025-11-18 03:34:58 ts/train.py:232 step:74K smpl:592K ep:2K epch:35.01 loss:0.011 grdn:0.212 lr:1.6e-05 updt_s:0.066 data_s:0.024
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| 386 |
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INFO 2025-11-18 03:35:17 ts/train.py:232 step:74K smpl:594K ep:2K epch:35.10 loss:0.011 grdn:0.206 lr:1.6e-05 updt_s:0.066 data_s:0.024
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| 387 |
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INFO 2025-11-18 03:35:35 ts/train.py:232 step:74K smpl:595K ep:2K epch:35.20 loss:0.011 grdn:0.202 lr:1.6e-05 updt_s:0.066 data_s:0.023
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| 388 |
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INFO 2025-11-18 03:35:54 ts/train.py:232 step:75K smpl:597K ep:2K epch:35.29 loss:0.012 grdn:0.214 lr:1.5e-05 updt_s:0.066 data_s:0.029
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| 389 |
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INFO 2025-11-18 03:36:13 ts/train.py:232 step:75K smpl:598K ep:2K epch:35.39 loss:0.011 grdn:0.208 lr:1.5e-05 updt_s:0.067 data_s:0.030
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| 390 |
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INFO 2025-11-18 03:36:33 ts/train.py:232 step:75K smpl:600K ep:2K epch:35.48 loss:0.011 grdn:0.217 lr:1.5e-05 updt_s:0.067 data_s:0.033
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| 391 |
+
INFO 2025-11-18 03:36:53 ts/train.py:232 step:75K smpl:602K ep:2K epch:35.58 loss:0.011 grdn:0.205 lr:1.5e-05 updt_s:0.066 data_s:0.030
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| 392 |
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INFO 2025-11-18 03:37:12 ts/train.py:232 step:75K smpl:603K ep:2K epch:35.67 loss:0.013 grdn:0.238 lr:1.4e-05 updt_s:0.067 data_s:0.030
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| 393 |
+
INFO 2025-11-18 03:37:32 ts/train.py:232 step:76K smpl:605K ep:2K epch:35.77 loss:0.011 grdn:0.210 lr:1.4e-05 updt_s:0.066 data_s:0.031
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| 394 |
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INFO 2025-11-18 03:37:51 ts/train.py:232 step:76K smpl:606K ep:2K epch:35.86 loss:0.011 grdn:0.208 lr:1.4e-05 updt_s:0.067 data_s:0.029
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| 395 |
+
INFO 2025-11-18 03:38:10 ts/train.py:232 step:76K smpl:608K ep:2K epch:35.96 loss:0.012 grdn:0.218 lr:1.4e-05 updt_s:0.067 data_s:0.028
|
| 396 |
+
INFO 2025-11-18 03:38:29 ts/train.py:232 step:76K smpl:610K ep:2K epch:36.05 loss:0.012 grdn:0.210 lr:1.4e-05 updt_s:0.066 data_s:0.027
|
| 397 |
+
INFO 2025-11-18 03:38:48 ts/train.py:232 step:76K smpl:611K ep:2K epch:36.14 loss:0.011 grdn:0.222 lr:1.3e-05 updt_s:0.066 data_s:0.027
|
| 398 |
+
INFO 2025-11-18 03:39:10 ts/train.py:232 step:77K smpl:613K ep:2K epch:36.24 loss:0.012 grdn:0.221 lr:1.3e-05 updt_s:0.066 data_s:0.044
|
| 399 |
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INFO 2025-11-18 03:39:29 ts/train.py:232 step:77K smpl:614K ep:2K epch:36.33 loss:0.012 grdn:0.208 lr:1.3e-05 updt_s:0.067 data_s:0.030
|
| 400 |
+
INFO 2025-11-18 03:39:48 ts/train.py:232 step:77K smpl:616K ep:2K epch:36.43 loss:0.010 grdn:0.188 lr:1.3e-05 updt_s:0.066 data_s:0.029
|
| 401 |
+
INFO 2025-11-18 03:40:07 ts/train.py:232 step:77K smpl:618K ep:2K epch:36.52 loss:0.011 grdn:0.207 lr:1.3e-05 updt_s:0.066 data_s:0.028
|
| 402 |
+
INFO 2025-11-18 03:40:26 ts/train.py:232 step:77K smpl:619K ep:2K epch:36.62 loss:0.011 grdn:0.210 lr:1.2e-05 updt_s:0.066 data_s:0.029
|
| 403 |
+
INFO 2025-11-18 03:40:45 ts/train.py:232 step:78K smpl:621K ep:2K epch:36.71 loss:0.012 grdn:0.223 lr:1.2e-05 updt_s:0.066 data_s:0.027
|
| 404 |
+
INFO 2025-11-18 03:41:04 ts/train.py:232 step:78K smpl:622K ep:2K epch:36.81 loss:0.011 grdn:0.210 lr:1.2e-05 updt_s:0.066 data_s:0.028
|
| 405 |
+
INFO 2025-11-18 03:41:23 ts/train.py:232 step:78K smpl:624K ep:2K epch:36.90 loss:0.011 grdn:0.217 lr:1.2e-05 updt_s:0.066 data_s:0.028
|
| 406 |
+
INFO 2025-11-18 03:41:41 ts/train.py:232 step:78K smpl:626K ep:2K epch:37.00 loss:0.012 grdn:0.229 lr:1.1e-05 updt_s:0.066 data_s:0.024
|
| 407 |
+
INFO 2025-11-18 03:41:59 ts/train.py:232 step:78K smpl:627K ep:2K epch:37.09 loss:0.010 grdn:0.200 lr:1.1e-05 updt_s:0.066 data_s:0.024
|
| 408 |
+
INFO 2025-11-18 03:42:17 ts/train.py:232 step:79K smpl:629K ep:2K epch:37.19 loss:0.011 grdn:0.205 lr:1.1e-05 updt_s:0.066 data_s:0.023
|
| 409 |
+
INFO 2025-11-18 03:42:36 ts/train.py:232 step:79K smpl:630K ep:2K epch:37.28 loss:0.011 grdn:0.201 lr:1.1e-05 updt_s:0.066 data_s:0.030
|
| 410 |
+
INFO 2025-11-18 03:42:56 ts/train.py:232 step:79K smpl:632K ep:2K epch:37.37 loss:0.011 grdn:0.228 lr:1.1e-05 updt_s:0.066 data_s:0.031
|
| 411 |
+
INFO 2025-11-18 03:43:15 ts/train.py:232 step:79K smpl:634K ep:2K epch:37.47 loss:0.011 grdn:0.218 lr:1.0e-05 updt_s:0.066 data_s:0.031
|
| 412 |
+
INFO 2025-11-18 03:43:35 ts/train.py:232 step:79K smpl:635K ep:2K epch:37.56 loss:0.011 grdn:0.211 lr:1.0e-05 updt_s:0.066 data_s:0.030
|
| 413 |
+
INFO 2025-11-18 03:43:54 ts/train.py:232 step:80K smpl:637K ep:2K epch:37.66 loss:0.010 grdn:0.198 lr:1.0e-05 updt_s:0.066 data_s:0.029
|
| 414 |
+
INFO 2025-11-18 03:44:13 ts/train.py:232 step:80K smpl:638K ep:2K epch:37.75 loss:0.012 grdn:0.221 lr:9.9e-06 updt_s:0.066 data_s:0.031
|
| 415 |
+
INFO 2025-11-18 03:44:33 ts/train.py:232 step:80K smpl:640K ep:2K epch:37.85 loss:0.012 grdn:0.216 lr:9.7e-06 updt_s:0.066 data_s:0.030
|
| 416 |
+
INFO 2025-11-18 03:44:33 ts/train.py:241 Checkpoint policy after step 80000
|
| 417 |
+
INFO 2025-11-18 03:45:06 ts/train.py:232 step:80K smpl:642K ep:2K epch:37.94 loss:0.011 grdn:0.218 lr:9.5e-06 updt_s:0.066 data_s:0.027
|
| 418 |
+
INFO 2025-11-18 03:45:24 ts/train.py:232 step:80K smpl:643K ep:2K epch:38.04 loss:0.011 grdn:0.216 lr:9.4e-06 updt_s:0.067 data_s:0.026
|
| 419 |
+
INFO 2025-11-18 03:45:43 ts/train.py:232 step:81K smpl:645K ep:2K epch:38.13 loss:0.010 grdn:0.198 lr:9.2e-06 updt_s:0.066 data_s:0.028
|
| 420 |
+
INFO 2025-11-18 03:46:03 ts/train.py:232 step:81K smpl:646K ep:2K epch:38.23 loss:0.011 grdn:0.204 lr:9.0e-06 updt_s:0.066 data_s:0.031
|
| 421 |
+
INFO 2025-11-18 03:46:23 ts/train.py:232 step:81K smpl:648K ep:2K epch:38.32 loss:0.011 grdn:0.208 lr:8.8e-06 updt_s:0.067 data_s:0.032
|
| 422 |
+
INFO 2025-11-18 03:46:43 ts/train.py:232 step:81K smpl:650K ep:2K epch:38.42 loss:0.011 grdn:0.212 lr:8.6e-06 updt_s:0.066 data_s:0.033
|
| 423 |
+
INFO 2025-11-18 03:47:02 ts/train.py:232 step:81K smpl:651K ep:2K epch:38.51 loss:0.011 grdn:0.209 lr:8.5e-06 updt_s:0.066 data_s:0.031
|
| 424 |
+
INFO 2025-11-18 03:47:22 ts/train.py:232 step:82K smpl:653K ep:2K epch:38.60 loss:0.012 grdn:0.223 lr:8.3e-06 updt_s:0.067 data_s:0.032
|
| 425 |
+
INFO 2025-11-18 03:47:42 ts/train.py:232 step:82K smpl:654K ep:2K epch:38.70 loss:0.011 grdn:0.212 lr:8.1e-06 updt_s:0.066 data_s:0.031
|
| 426 |
+
INFO 2025-11-18 03:48:02 ts/train.py:232 step:82K smpl:656K ep:2K epch:38.79 loss:0.010 grdn:0.185 lr:7.9e-06 updt_s:0.066 data_s:0.032
|
| 427 |
+
INFO 2025-11-18 03:48:21 ts/train.py:232 step:82K smpl:658K ep:2K epch:38.89 loss:0.010 grdn:0.197 lr:7.8e-06 updt_s:0.067 data_s:0.029
|
| 428 |
+
INFO 2025-11-18 03:48:40 ts/train.py:232 step:82K smpl:659K ep:2K epch:38.98 loss:0.012 grdn:0.217 lr:7.6e-06 updt_s:0.066 data_s:0.029
|
| 429 |
+
INFO 2025-11-18 03:48:59 ts/train.py:232 step:83K smpl:661K ep:2K epch:39.08 loss:0.011 grdn:0.205 lr:7.4e-06 updt_s:0.066 data_s:0.029
|
| 430 |
+
INFO 2025-11-18 03:49:18 ts/train.py:232 step:83K smpl:662K ep:2K epch:39.17 loss:0.011 grdn:0.213 lr:7.3e-06 updt_s:0.066 data_s:0.028
|
| 431 |
+
INFO 2025-11-18 03:49:41 ts/train.py:232 step:83K smpl:664K ep:2K epch:39.27 loss:0.011 grdn:0.209 lr:7.1e-06 updt_s:0.066 data_s:0.050
|
| 432 |
+
INFO 2025-11-18 03:50:01 ts/train.py:232 step:83K smpl:666K ep:2K epch:39.36 loss:0.012 grdn:0.209 lr:7.0e-06 updt_s:0.066 data_s:0.032
|
| 433 |
+
INFO 2025-11-18 03:50:21 ts/train.py:232 step:83K smpl:667K ep:2K epch:39.46 loss:0.010 grdn:0.201 lr:6.8e-06 updt_s:0.066 data_s:0.031
|
| 434 |
+
INFO 2025-11-18 03:50:40 ts/train.py:232 step:84K smpl:669K ep:2K epch:39.55 loss:0.011 grdn:0.221 lr:6.6e-06 updt_s:0.066 data_s:0.030
|
| 435 |
+
INFO 2025-11-18 03:50:59 ts/train.py:232 step:84K smpl:670K ep:2K epch:39.65 loss:0.011 grdn:0.203 lr:6.5e-06 updt_s:0.066 data_s:0.030
|
| 436 |
+
INFO 2025-11-18 03:51:18 ts/train.py:232 step:84K smpl:672K ep:2K epch:39.74 loss:0.012 grdn:0.219 lr:6.3e-06 updt_s:0.066 data_s:0.029
|
| 437 |
+
INFO 2025-11-18 03:51:38 ts/train.py:232 step:84K smpl:674K ep:2K epch:39.83 loss:0.011 grdn:0.210 lr:6.2e-06 updt_s:0.066 data_s:0.030
|
| 438 |
+
INFO 2025-11-18 03:51:56 ts/train.py:232 step:84K smpl:675K ep:2K epch:39.93 loss:0.011 grdn:0.210 lr:6.0e-06 updt_s:0.066 data_s:0.027
|
| 439 |
+
INFO 2025-11-18 03:52:15 ts/train.py:232 step:85K smpl:677K ep:2K epch:40.02 loss:0.010 grdn:0.208 lr:5.9e-06 updt_s:0.066 data_s:0.027
|
| 440 |
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INFO 2025-11-18 03:52:34 ts/train.py:232 step:85K smpl:678K ep:2K epch:40.12 loss:0.010 grdn:0.194 lr:5.7e-06 updt_s:0.066 data_s:0.027
|
| 441 |
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INFO 2025-11-18 03:52:53 ts/train.py:232 step:85K smpl:680K ep:2K epch:40.21 loss:0.011 grdn:0.205 lr:5.6e-06 updt_s:0.066 data_s:0.029
|
| 442 |
+
INFO 2025-11-18 03:53:12 ts/train.py:232 step:85K smpl:682K ep:2K epch:40.31 loss:0.011 grdn:0.212 lr:5.4e-06 updt_s:0.066 data_s:0.027
|
| 443 |
+
INFO 2025-11-18 03:53:31 ts/train.py:232 step:85K smpl:683K ep:2K epch:40.40 loss:0.011 grdn:0.219 lr:5.3e-06 updt_s:0.066 data_s:0.030
|
| 444 |
+
INFO 2025-11-18 03:53:51 ts/train.py:232 step:86K smpl:685K ep:2K epch:40.50 loss:0.010 grdn:0.198 lr:5.1e-06 updt_s:0.067 data_s:0.031
|
| 445 |
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INFO 2025-11-18 03:54:10 ts/train.py:232 step:86K smpl:686K ep:2K epch:40.59 loss:0.011 grdn:0.219 lr:5.0e-06 updt_s:0.066 data_s:0.031
|
| 446 |
+
INFO 2025-11-18 03:54:30 ts/train.py:232 step:86K smpl:688K ep:2K epch:40.69 loss:0.011 grdn:0.208 lr:4.9e-06 updt_s:0.067 data_s:0.030
|
| 447 |
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INFO 2025-11-18 03:54:49 ts/train.py:232 step:86K smpl:690K ep:2K epch:40.78 loss:0.011 grdn:0.211 lr:4.7e-06 updt_s:0.066 data_s:0.031
|
| 448 |
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INFO 2025-11-18 03:55:08 ts/train.py:232 step:86K smpl:691K ep:2K epch:40.88 loss:0.011 grdn:0.211 lr:4.6e-06 updt_s:0.066 data_s:0.026
|
| 449 |
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INFO 2025-11-18 03:55:27 ts/train.py:232 step:87K smpl:693K ep:2K epch:40.97 loss:0.010 grdn:0.198 lr:4.5e-06 updt_s:0.066 data_s:0.027
|
| 450 |
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INFO 2025-11-18 03:55:46 ts/train.py:232 step:87K smpl:694K ep:2K epch:41.06 loss:0.010 grdn:0.194 lr:4.3e-06 updt_s:0.066 data_s:0.028
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| 451 |
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INFO 2025-11-18 03:56:05 ts/train.py:232 step:87K smpl:696K ep:2K epch:41.16 loss:0.012 grdn:0.212 lr:4.2e-06 updt_s:0.067 data_s:0.030
|
| 452 |
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INFO 2025-11-18 03:56:25 ts/train.py:232 step:87K smpl:698K ep:2K epch:41.25 loss:0.010 grdn:0.199 lr:4.1e-06 updt_s:0.066 data_s:0.031
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| 453 |
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INFO 2025-11-18 03:56:45 ts/train.py:232 step:87K smpl:699K ep:2K epch:41.35 loss:0.011 grdn:0.207 lr:4.0e-06 updt_s:0.067 data_s:0.033
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| 454 |
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INFO 2025-11-18 03:57:04 ts/train.py:232 step:88K smpl:701K ep:2K epch:41.44 loss:0.010 grdn:0.195 lr:3.8e-06 updt_s:0.067 data_s:0.031
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| 455 |
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INFO 2025-11-18 03:57:24 ts/train.py:232 step:88K smpl:702K ep:2K epch:41.54 loss:0.011 grdn:0.219 lr:3.7e-06 updt_s:0.067 data_s:0.031
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| 456 |
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INFO 2025-11-18 03:57:43 ts/train.py:232 step:88K smpl:704K ep:2K epch:41.63 loss:0.010 grdn:0.196 lr:3.6e-06 updt_s:0.067 data_s:0.031
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| 457 |
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INFO 2025-11-18 03:58:03 ts/train.py:232 step:88K smpl:706K ep:2K epch:41.73 loss:0.011 grdn:0.220 lr:3.5e-06 updt_s:0.067 data_s:0.031
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| 458 |
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INFO 2025-11-18 03:58:22 ts/train.py:232 step:88K smpl:707K ep:2K epch:41.82 loss:0.010 grdn:0.211 lr:3.4e-06 updt_s:0.067 data_s:0.027
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| 459 |
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INFO 2025-11-18 03:58:41 ts/train.py:232 step:89K smpl:709K ep:2K epch:41.92 loss:0.011 grdn:0.209 lr:3.3e-06 updt_s:0.066 data_s:0.026
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| 460 |
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INFO 2025-11-18 03:58:59 ts/train.py:232 step:89K smpl:710K ep:2K epch:42.01 loss:0.010 grdn:0.195 lr:3.1e-06 updt_s:0.067 data_s:0.026
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| 461 |
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INFO 2025-11-18 03:59:18 ts/train.py:232 step:89K smpl:712K ep:2K epch:42.11 loss:0.011 grdn:0.212 lr:3.0e-06 updt_s:0.067 data_s:0.026
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| 462 |
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INFO 2025-11-18 03:59:39 ts/train.py:232 step:89K smpl:714K ep:2K epch:42.20 loss:0.010 grdn:0.197 lr:2.9e-06 updt_s:0.067 data_s:0.036
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| 463 |
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INFO 2025-11-18 03:59:58 ts/train.py:232 step:89K smpl:715K ep:2K epch:42.29 loss:0.010 grdn:0.198 lr:2.8e-06 updt_s:0.067 data_s:0.030
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| 464 |
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INFO 2025-11-18 04:00:18 ts/train.py:232 step:90K smpl:717K ep:2K epch:42.39 loss:0.011 grdn:0.216 lr:2.7e-06 updt_s:0.066 data_s:0.031
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| 465 |
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INFO 2025-11-18 04:00:40 ts/train.py:232 step:90K smpl:718K ep:2K epch:42.48 loss:0.010 grdn:0.190 lr:2.6e-06 updt_s:0.066 data_s:0.043
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| 466 |
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INFO 2025-11-18 04:01:00 ts/train.py:232 step:90K smpl:720K ep:2K epch:42.58 loss:0.011 grdn:0.210 lr:2.5e-06 updt_s:0.066 data_s:0.031
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| 467 |
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INFO 2025-11-18 04:01:19 ts/train.py:232 step:90K smpl:722K ep:2K epch:42.67 loss:0.011 grdn:0.215 lr:2.4e-06 updt_s:0.066 data_s:0.029
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| 468 |
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INFO 2025-11-18 04:01:37 ts/train.py:232 step:90K smpl:723K ep:2K epch:42.77 loss:0.011 grdn:0.202 lr:2.3e-06 updt_s:0.066 data_s:0.026
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| 469 |
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INFO 2025-11-18 04:01:55 ts/train.py:232 step:91K smpl:725K ep:2K epch:42.86 loss:0.011 grdn:0.220 lr:2.2e-06 updt_s:0.066 data_s:0.022
|
| 470 |
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INFO 2025-11-18 04:02:12 ts/train.py:232 step:91K smpl:726K ep:2K epch:42.96 loss:0.010 grdn:0.204 lr:2.1e-06 updt_s:0.066 data_s:0.021
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| 471 |
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INFO 2025-11-18 04:02:30 ts/train.py:232 step:91K smpl:728K ep:2K epch:43.05 loss:0.011 grdn:0.203 lr:2.0e-06 updt_s:0.066 data_s:0.020
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| 472 |
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INFO 2025-11-18 04:02:49 ts/train.py:232 step:91K smpl:730K ep:2K epch:43.15 loss:0.010 grdn:0.195 lr:2.0e-06 updt_s:0.067 data_s:0.030
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| 473 |
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INFO 2025-11-18 04:03:09 ts/train.py:232 step:91K smpl:731K ep:2K epch:43.24 loss:0.011 grdn:0.211 lr:1.9e-06 updt_s:0.067 data_s:0.030
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| 474 |
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INFO 2025-11-18 04:03:28 ts/train.py:232 step:92K smpl:733K ep:2K epch:43.34 loss:0.010 grdn:0.202 lr:1.8e-06 updt_s:0.066 data_s:0.030
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| 475 |
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INFO 2025-11-18 04:03:47 ts/train.py:232 step:92K smpl:734K ep:2K epch:43.43 loss:0.011 grdn:0.211 lr:1.7e-06 updt_s:0.066 data_s:0.029
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| 476 |
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INFO 2025-11-18 04:04:06 ts/train.py:232 step:92K smpl:736K ep:2K epch:43.52 loss:0.011 grdn:0.199 lr:1.6e-06 updt_s:0.066 data_s:0.027
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| 477 |
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INFO 2025-11-18 04:04:25 ts/train.py:232 step:92K smpl:738K ep:2K epch:43.62 loss:0.011 grdn:0.200 lr:1.5e-06 updt_s:0.066 data_s:0.028
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| 478 |
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INFO 2025-11-18 04:04:44 ts/train.py:232 step:92K smpl:739K ep:2K epch:43.71 loss:0.010 grdn:0.202 lr:1.5e-06 updt_s:0.067 data_s:0.030
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| 479 |
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INFO 2025-11-18 04:05:03 ts/train.py:232 step:93K smpl:741K ep:2K epch:43.81 loss:0.011 grdn:0.202 lr:1.4e-06 updt_s:0.067 data_s:0.028
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| 480 |
+
INFO 2025-11-18 04:05:22 ts/train.py:232 step:93K smpl:742K ep:2K epch:43.90 loss:0.010 grdn:0.195 lr:1.3e-06 updt_s:0.067 data_s:0.027
|
| 481 |
+
INFO 2025-11-18 04:05:41 ts/train.py:232 step:93K smpl:744K ep:2K epch:44.00 loss:0.011 grdn:0.214 lr:1.3e-06 updt_s:0.067 data_s:0.026
|
| 482 |
+
INFO 2025-11-18 04:06:00 ts/train.py:232 step:93K smpl:746K ep:2K epch:44.09 loss:0.010 grdn:0.197 lr:1.2e-06 updt_s:0.066 data_s:0.030
|
| 483 |
+
INFO 2025-11-18 04:06:20 ts/train.py:232 step:93K smpl:747K ep:2K epch:44.19 loss:0.009 grdn:0.189 lr:1.1e-06 updt_s:0.066 data_s:0.030
|
| 484 |
+
INFO 2025-11-18 04:06:39 ts/train.py:232 step:94K smpl:749K ep:2K epch:44.28 loss:0.010 grdn:0.195 lr:1.0e-06 updt_s:0.067 data_s:0.028
|
| 485 |
+
INFO 2025-11-18 04:06:58 ts/train.py:232 step:94K smpl:750K ep:2K epch:44.38 loss:0.010 grdn:0.200 lr:9.9e-07 updt_s:0.067 data_s:0.028
|
| 486 |
+
INFO 2025-11-18 04:07:17 ts/train.py:232 step:94K smpl:752K ep:2K epch:44.47 loss:0.010 grdn:0.196 lr:9.2e-07 updt_s:0.067 data_s:0.029
|
| 487 |
+
INFO 2025-11-18 04:07:37 ts/train.py:232 step:94K smpl:754K ep:2K epch:44.57 loss:0.011 grdn:0.200 lr:8.6e-07 updt_s:0.067 data_s:0.030
|
| 488 |
+
INFO 2025-11-18 04:07:56 ts/train.py:232 step:94K smpl:755K ep:2K epch:44.66 loss:0.011 grdn:0.204 lr:8.1e-07 updt_s:0.067 data_s:0.029
|
| 489 |
+
INFO 2025-11-18 04:08:14 ts/train.py:232 step:95K smpl:757K ep:2K epch:44.75 loss:0.011 grdn:0.199 lr:7.5e-07 updt_s:0.066 data_s:0.026
|
| 490 |
+
INFO 2025-11-18 04:08:33 ts/train.py:232 step:95K smpl:758K ep:2K epch:44.85 loss:0.010 grdn:0.199 lr:7.0e-07 updt_s:0.067 data_s:0.025
|
| 491 |
+
INFO 2025-11-18 04:08:51 ts/train.py:232 step:95K smpl:760K ep:2K epch:44.94 loss:0.010 grdn:0.201 lr:6.5e-07 updt_s:0.067 data_s:0.023
|
| 492 |
+
INFO 2025-11-18 04:09:09 ts/train.py:232 step:95K smpl:762K ep:2K epch:45.04 loss:0.011 grdn:0.193 lr:6.0e-07 updt_s:0.067 data_s:0.024
|
| 493 |
+
INFO 2025-11-18 04:09:29 ts/train.py:232 step:95K smpl:763K ep:2K epch:45.13 loss:0.010 grdn:0.195 lr:5.5e-07 updt_s:0.066 data_s:0.033
|
| 494 |
+
INFO 2025-11-18 04:09:49 ts/train.py:232 step:96K smpl:765K ep:2K epch:45.23 loss:0.011 grdn:0.207 lr:5.0e-07 updt_s:0.066 data_s:0.031
|
| 495 |
+
INFO 2025-11-18 04:10:08 ts/train.py:232 step:96K smpl:766K ep:2K epch:45.32 loss:0.011 grdn:0.204 lr:4.6e-07 updt_s:0.066 data_s:0.031
|
| 496 |
+
INFO 2025-11-18 04:10:27 ts/train.py:232 step:96K smpl:768K ep:2K epch:45.42 loss:0.010 grdn:0.192 lr:4.2e-07 updt_s:0.067 data_s:0.029
|
| 497 |
+
INFO 2025-11-18 04:10:47 ts/train.py:232 step:96K smpl:770K ep:2K epch:45.51 loss:0.011 grdn:0.203 lr:3.8e-07 updt_s:0.066 data_s:0.030
|
| 498 |
+
INFO 2025-11-18 04:11:06 ts/train.py:232 step:96K smpl:771K ep:2K epch:45.61 loss:0.010 grdn:0.201 lr:3.4e-07 updt_s:0.066 data_s:0.031
|
| 499 |
+
INFO 2025-11-18 04:11:28 ts/train.py:232 step:97K smpl:773K ep:2K epch:45.70 loss:0.010 grdn:0.191 lr:3.0e-07 updt_s:0.066 data_s:0.043
|
| 500 |
+
INFO 2025-11-18 04:11:47 ts/train.py:232 step:97K smpl:774K ep:2K epch:45.80 loss:0.011 grdn:0.198 lr:2.7e-07 updt_s:0.067 data_s:0.026
|
| 501 |
+
INFO 2025-11-18 04:12:05 ts/train.py:232 step:97K smpl:776K ep:2K epch:45.89 loss:0.011 grdn:0.201 lr:2.4e-07 updt_s:0.067 data_s:0.026
|
| 502 |
+
INFO 2025-11-18 04:12:24 ts/train.py:232 step:97K smpl:778K ep:2K epch:45.98 loss:0.010 grdn:0.192 lr:2.1e-07 updt_s:0.066 data_s:0.026
|
| 503 |
+
INFO 2025-11-18 04:12:43 ts/train.py:232 step:97K smpl:779K ep:2K epch:46.08 loss:0.010 grdn:0.209 lr:1.8e-07 updt_s:0.066 data_s:0.028
|
| 504 |
+
INFO 2025-11-18 04:13:02 ts/train.py:232 step:98K smpl:781K ep:2K epch:46.17 loss:0.010 grdn:0.203 lr:1.6e-07 updt_s:0.066 data_s:0.028
|
| 505 |
+
INFO 2025-11-18 04:13:21 ts/train.py:232 step:98K smpl:782K ep:2K epch:46.27 loss:0.010 grdn:0.195 lr:1.3e-07 updt_s:0.066 data_s:0.028
|
| 506 |
+
INFO 2025-11-18 04:13:40 ts/train.py:232 step:98K smpl:784K ep:2K epch:46.36 loss:0.010 grdn:0.199 lr:1.1e-07 updt_s:0.066 data_s:0.028
|
| 507 |
+
INFO 2025-11-18 04:13:59 ts/train.py:232 step:98K smpl:786K ep:2K epch:46.46 loss:0.010 grdn:0.194 lr:9.0e-08 updt_s:0.066 data_s:0.028
|
| 508 |
+
INFO 2025-11-18 04:14:18 ts/train.py:232 step:98K smpl:787K ep:2K epch:46.55 loss:0.011 grdn:0.206 lr:7.2e-08 updt_s:0.066 data_s:0.028
|
| 509 |
+
INFO 2025-11-18 04:14:37 ts/train.py:232 step:99K smpl:789K ep:2K epch:46.65 loss:0.010 grdn:0.195 lr:5.6e-08 updt_s:0.066 data_s:0.029
|
| 510 |
+
INFO 2025-11-18 04:14:55 ts/train.py:232 step:99K smpl:790K ep:2K epch:46.74 loss:0.011 grdn:0.212 lr:4.2e-08 updt_s:0.066 data_s:0.023
|
| 511 |
+
INFO 2025-11-18 04:15:12 ts/train.py:232 step:99K smpl:792K ep:2K epch:46.84 loss:0.010 grdn:0.205 lr:3.0e-08 updt_s:0.065 data_s:0.022
|
| 512 |
+
INFO 2025-11-18 04:15:30 ts/train.py:232 step:99K smpl:794K ep:2K epch:46.93 loss:0.010 grdn:0.193 lr:2.0e-08 updt_s:0.065 data_s:0.022
|
| 513 |
+
INFO 2025-11-18 04:15:48 ts/train.py:232 step:99K smpl:795K ep:2K epch:47.03 loss:0.010 grdn:0.201 lr:1.2e-08 updt_s:0.065 data_s:0.027
|
| 514 |
+
INFO 2025-11-18 04:16:07 ts/train.py:232 step:100K smpl:797K ep:2K epch:47.12 loss:0.010 grdn:0.194 lr:6.3e-09 updt_s:0.066 data_s:0.026
|
| 515 |
+
INFO 2025-11-18 04:16:25 ts/train.py:232 step:100K smpl:798K ep:2K epch:47.21 loss:0.011 grdn:0.209 lr:2.3e-09 updt_s:0.065 data_s:0.027
|
| 516 |
+
INFO 2025-11-18 04:16:44 ts/train.py:232 step:100K smpl:800K ep:2K epch:47.31 loss:0.010 grdn:0.198 lr:3.3e-10 updt_s:0.066 data_s:0.026
|
| 517 |
+
INFO 2025-11-18 04:16:44 ts/train.py:241 Checkpoint policy after step 100000
|
| 518 |
+
INFO 2025-11-18 04:16:59 ts/train.py:283 End of training
|
diffusion_anubis_pullout_wrench/wandb/run-20251118_013623-flrqqt58/files/requirements.txt
ADDED
|
@@ -0,0 +1,264 @@
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|
| 1 |
+
setuptools==79.0.0
|
| 2 |
+
wheel==0.45.1
|
| 3 |
+
pip==25.0.1
|
| 4 |
+
wcwidth==0.2.13
|
| 5 |
+
triton==3.2.0
|
| 6 |
+
pytz==2025.2
|
| 7 |
+
nvidia-cusparselt-cu12==0.6.2
|
| 8 |
+
mpmath==1.3.0
|
| 9 |
+
Farama-Notifications==0.0.4
|
| 10 |
+
asciitree==0.3.3
|
| 11 |
+
antlr4-python3-runtime==4.9.3
|
| 12 |
+
zipp==3.21.0
|
| 13 |
+
xxhash==3.5.0
|
| 14 |
+
urllib3==2.4.0
|
| 15 |
+
tzdata==2025.2
|
| 16 |
+
typing_extensions==4.13.2
|
| 17 |
+
tqdm==4.67.1
|
| 18 |
+
uv==0.7.3
|
| 19 |
+
toml==0.10.2
|
| 20 |
+
termcolor==3.0.1
|
| 21 |
+
sympy==1.13.1
|
| 22 |
+
soupsieve==2.7
|
| 23 |
+
smmap==5.0.2
|
| 24 |
+
six==1.17.0
|
| 25 |
+
setproctitle==1.3.5
|
| 26 |
+
safetensors==0.5.3
|
| 27 |
+
regex==2024.11.6
|
| 28 |
+
pyzmq==26.4.0
|
| 29 |
+
PyYAML==6.0.2
|
| 30 |
+
PySocks==1.7.1
|
| 31 |
+
pycparser==2.22
|
| 32 |
+
pyarrow==19.0.1
|
| 33 |
+
pyarrow==19.0.1
|
| 34 |
+
psutil==7.0.0
|
| 35 |
+
protobuf==4.21.12
|
| 36 |
+
propcache==0.3.1
|
| 37 |
+
prompt_toolkit==3.0.51
|
| 38 |
+
platformdirs==4.3.7
|
| 39 |
+
pillow==11.2.1
|
| 40 |
+
pillow==11.1.0
|
| 41 |
+
pfzy==0.3.4
|
| 42 |
+
packaging==25.0
|
| 43 |
+
orderly-set==5.4.0
|
| 44 |
+
nvidia-nvtx-cu12==12.4.127
|
| 45 |
+
nvidia-nvjitlink-cu12==12.4.127
|
| 46 |
+
nvidia-nccl-cu12==2.21.5
|
| 47 |
+
nvidia-curand-cu12==10.3.5.147
|
| 48 |
+
nvidia-cufft-cu12==11.2.1.3
|
| 49 |
+
nvidia-cuda-runtime-cu12==12.4.127
|
| 50 |
+
nvidia-cuda-nvrtc-cu12==12.4.127
|
| 51 |
+
nvidia-cuda-cupti-cu12==12.4.127
|
| 52 |
+
nvidia-cublas-cu12==12.4.5.8
|
| 53 |
+
networkx==3.4.2
|
| 54 |
+
mypy-extensions==1.0.0
|
| 55 |
+
mergedeep==1.3.4
|
| 56 |
+
MarkupSafe==3.0.2
|
| 57 |
+
llvmlite==0.44.0
|
| 58 |
+
itsdangerous==2.2.0
|
| 59 |
+
imageio-ffmpeg==0.6.0
|
| 60 |
+
idna==3.10
|
| 61 |
+
hf_transfer==0.1.9
|
| 62 |
+
fsspec==2024.12.0
|
| 63 |
+
frozenlist==1.6.0
|
| 64 |
+
filelock==3.18.0
|
| 65 |
+
fasteners==0.19
|
| 66 |
+
evdev==1.9.1
|
| 67 |
+
einops==0.8.1
|
| 68 |
+
dill==0.3.8
|
| 69 |
+
cmake==4.0.0
|
| 70 |
+
cloudpickle==3.1.1
|
| 71 |
+
click==8.1.8
|
| 72 |
+
charset-normalizer==3.4.1
|
| 73 |
+
certifi==2025.1.31
|
| 74 |
+
blinker==1.9.0
|
| 75 |
+
av==14.3.0
|
| 76 |
+
attrs==25.3.0
|
| 77 |
+
async-timeout==5.0.1
|
| 78 |
+
annotated-types==0.7.0
|
| 79 |
+
aiohappyeyeballs==2.6.1
|
| 80 |
+
Werkzeug==3.1.3
|
| 81 |
+
typing-inspection==0.4.0
|
| 82 |
+
typing-inspect==0.9.0
|
| 83 |
+
sentry-sdk==2.26.1
|
| 84 |
+
requests==2.32.3
|
| 85 |
+
pyyaml-include==1.4.1
|
| 86 |
+
python-xlib==0.33
|
| 87 |
+
python-dateutil==2.9.0.post0
|
| 88 |
+
pydantic_core==2.33.1
|
| 89 |
+
opencv-python-headless==4.11.0.86
|
| 90 |
+
omegaconf==2.3.0
|
| 91 |
+
nvidia-cusparse-cu12==12.3.1.170
|
| 92 |
+
nvidia-cudnn-cu12==9.1.0.70
|
| 93 |
+
numcodecs==0.13.1
|
| 94 |
+
numba==0.61.2
|
| 95 |
+
multiprocess==0.70.16
|
| 96 |
+
multidict==6.4.3
|
| 97 |
+
jsonlines==4.0.0
|
| 98 |
+
Jinja2==3.1.6
|
| 99 |
+
inquirerpy==0.3.4
|
| 100 |
+
importlib_metadata==8.6.1
|
| 101 |
+
imageio==2.37.0
|
| 102 |
+
h5py==3.13.0
|
| 103 |
+
gymnasium==0.29.1
|
| 104 |
+
gitdb==4.0.12
|
| 105 |
+
docker-pycreds==0.4.0
|
| 106 |
+
deepdiff==8.4.2
|
| 107 |
+
cffi==1.17.1
|
| 108 |
+
beautifulsoup4==4.13.4
|
| 109 |
+
aiosignal==1.3.2
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lazy_loader==0.4
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scikit-image==0.25.2
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gdown==5.2.0
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future==1.0.0
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draccus==0.10.0
|
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transformers==4.51.3
|
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lerobot==0.1.0
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bottle==0.12.25
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waitress==3.0.2
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accelerate==1.6.0
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TorchCodec==0.2.1
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| 241 |
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hf-xet==1.2.0
|
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h11==0.16.0
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| 244 |
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anyio==4.11.0
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| 253 |
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jaraco.collections==5.1.0
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| 254 |
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jaraco.context==5.3.0
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| 255 |
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jaraco.functools==4.0.1
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jaraco.text==3.12.1
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tomli==2.0.1
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typeguard==4.3.0
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typing_extensions==4.12.2
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| 263 |
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wheel==0.45.1
|
| 264 |
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zipp==3.19.2
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diffusion_anubis_pullout_wrench/wandb/run-20251118_013623-flrqqt58/files/wandb-metadata.json
ADDED
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|
| 1 |
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{
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diffusion_anubis_pullout_wrench/wandb/run-20251118_013623-flrqqt58/files/wandb-summary.json
ADDED
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@@ -0,0 +1 @@
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diffusion_anubis_pullout_wrench/wandb/run-20251118_013623-flrqqt58/logs/debug-core.log
ADDED
|
@@ -0,0 +1,13 @@
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| 1 |
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{"time":"2025-11-18T01:36:23.131060725+09:00","level":"INFO","msg":"main: starting server","port-filename":"/tmp/tmpade0upuo/port-2405166.txt","pid":2405166,"log-level":0,"disable-analytics":false,"shutdown-on-parent-exit":false}
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{"time":"2025-11-18T01:36:23.131740544+09:00","level":"INFO","msg":"Will exit if parent process dies.","ppid":2405166}
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{"time":"2025-11-18T01:36:23.131746192+09:00","level":"INFO","msg":"server is running","addr":{"IP":"127.0.0.1","Port":33545,"Zone":""}}
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{"time":"2025-11-18T01:36:23.324384466+09:00","level":"INFO","msg":"connection: ManageConnectionData: new connection created","id":"127.0.0.1:41272"}
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| 5 |
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{"time":"2025-11-18T01:36:23.344101192+09:00","level":"INFO","msg":"handleInformInit: received","streamId":"flrqqt58","id":"127.0.0.1:41272"}
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| 6 |
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{"time":"2025-11-18T01:36:23.660951698+09:00","level":"INFO","msg":"handleInformInit: stream started","streamId":"flrqqt58","id":"127.0.0.1:41272"}
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| 7 |
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{"time":"2025-11-18T04:16:59.777732927+09:00","level":"INFO","msg":"handleInformTeardown: server teardown initiated","id":"127.0.0.1:41272"}
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| 8 |
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{"time":"2025-11-18T04:16:59.784019245+09:00","level":"INFO","msg":"server is shutting down"}
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| 9 |
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{"time":"2025-11-18T04:16:59.784016471+09:00","level":"INFO","msg":"connection: closing","id":"127.0.0.1:41272"}
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| 10 |
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{"time":"2025-11-18T04:16:59.784079355+09:00","level":"INFO","msg":"connection: closed successfully","id":"127.0.0.1:41272"}
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| 11 |
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{"time":"2025-11-18T04:17:01.009788087+09:00","level":"INFO","msg":"handleInformTeardown: server shutdown complete","id":"127.0.0.1:41272"}
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| 12 |
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{"time":"2025-11-18T04:17:01.009811282+09:00","level":"INFO","msg":"connection: ManageConnectionData: connection closed","id":"127.0.0.1:41272"}
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| 13 |
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{"time":"2025-11-18T04:17:01.009817722+09:00","level":"INFO","msg":"server is closed"}
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diffusion_anubis_pullout_wrench/wandb/run-20251118_013623-flrqqt58/logs/debug-internal.log
ADDED
|
@@ -0,0 +1,15 @@
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|
|
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|
|
| 1 |
+
{"time":"2025-11-18T01:36:23.35076218+09:00","level":"INFO","msg":"stream: starting","core version":"0.19.9","symlink path":"outputs/train/2025-11-18/01-36-18_diffusion/wandb/run-20251118_013623-flrqqt58/logs/debug-core.log"}
|
| 2 |
+
{"time":"2025-11-18T01:36:23.660911217+09:00","level":"INFO","msg":"created new stream","id":"flrqqt58"}
|
| 3 |
+
{"time":"2025-11-18T01:36:23.660947201+09:00","level":"INFO","msg":"stream: started","id":"flrqqt58"}
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|
| 5 |
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|
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|
| 7 |
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|
| 8 |
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{"time":"2025-11-18T04:16:59.78404243+09:00","level":"INFO","msg":"stream: closing","id":"flrqqt58"}
|
| 9 |
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|
| 10 |
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|
| 11 |
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|
| 12 |
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{"time":"2025-11-18T04:17:01.008649672+09:00","level":"INFO","msg":"handler: closed","stream_id":"flrqqt58"}
|
| 13 |
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{"time":"2025-11-18T04:17:01.008680528+09:00","level":"INFO","msg":"writer: Close: closed","stream_id":"flrqqt58"}
|
| 14 |
+
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|
| 15 |
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{"time":"2025-11-18T04:17:01.009483381+09:00","level":"INFO","msg":"stream: closed","id":"flrqqt58"}
|
diffusion_anubis_pullout_wrench/wandb/run-20251118_013623-flrqqt58/logs/debug.log
ADDED
|
@@ -0,0 +1,23 @@
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|
| 1 |
+
2025-11-18 01:36:23,330 INFO MainThread:2405166 [wandb_setup.py:_flush():67] Current SDK version is 0.19.9
|
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2025-11-18 01:36:23,330 INFO MainThread:2405166 [wandb_setup.py:_flush():67] Configure stats pid to 2405166
|
| 3 |
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2025-11-18 01:36:23,330 INFO MainThread:2405166 [wandb_setup.py:_flush():67] Loading settings from /home/euijinrnd/.config/wandb/settings
|
| 4 |
+
2025-11-18 01:36:23,330 INFO MainThread:2405166 [wandb_setup.py:_flush():67] Loading settings from /home/euijinrnd/workspace/lerobot/wandb/settings
|
| 5 |
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2025-11-18 01:36:23,330 INFO MainThread:2405166 [wandb_setup.py:_flush():67] Loading settings from environment variables
|
| 6 |
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2025-11-18 01:36:23,330 INFO MainThread:2405166 [wandb_init.py:setup_run_log_directory():662] Logging user logs to outputs/train/2025-11-18/01-36-18_diffusion/wandb/run-20251118_013623-flrqqt58/logs/debug.log
|
| 7 |
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2025-11-18 01:36:23,330 INFO MainThread:2405166 [wandb_init.py:setup_run_log_directory():663] Logging internal logs to outputs/train/2025-11-18/01-36-18_diffusion/wandb/run-20251118_013623-flrqqt58/logs/debug-internal.log
|
| 8 |
+
2025-11-18 01:36:23,330 INFO MainThread:2405166 [wandb_init.py:init():781] calling init triggers
|
| 9 |
+
2025-11-18 01:36:23,330 INFO MainThread:2405166 [wandb_init.py:init():786] wandb.init called with sweep_config: {}
|
| 10 |
+
config: {'dataset': {'repo_id': 'anubis_pullout_wrench_v2__lerobot', 'root': '/data1/euijinrnd/hf_home_euijin/lerobot/lerobot/anubis_pullout_wrench_v2__lerobot', 'episodes': None, 'image_transforms': {'enable': False, 'max_num_transforms': 3, 'random_order': False, 'tfs': {'brightness': {'weight': 1.0, 'type': 'ColorJitter', 'kwargs': {'brightness': [0.8, 1.2]}}, 'contrast': {'weight': 1.0, 'type': 'ColorJitter', 'kwargs': {'contrast': [0.8, 1.2]}}, 'saturation': {'weight': 1.0, 'type': 'ColorJitter', 'kwargs': {'saturation': [0.5, 1.5]}}, 'hue': {'weight': 1.0, 'type': 'ColorJitter', 'kwargs': {'hue': [-0.05, 0.05]}}, 'sharpness': {'weight': 1.0, 'type': 'SharpnessJitter', 'kwargs': {'sharpness': [0.5, 1.5]}}}}, 'revision': None, 'use_imagenet_stats': True, 'video_backend': 'torchcodec'}, 'env': None, 'policy': {'type': 'diffusion', 'n_obs_steps': 2, 'normalization_mapping': {'VISUAL': <NormalizationMode.MEAN_STD: 'MEAN_STD'>, 'STATE': <NormalizationMode.MIN_MAX: 'MIN_MAX'>, 'ACTION': <NormalizationMode.MIN_MAX: 'MIN_MAX'>}, 'input_features': {}, 'output_features': {}, 'device': 'cuda', 'use_amp': False, 'horizon': 16, 'n_action_steps': 8, 'drop_n_last_frames': 7, 'vision_backbone': 'resnet18', 'crop_shape': [84, 84], 'crop_is_random': True, 'pretrained_backbone_weights': None, 'use_group_norm': True, 'spatial_softmax_num_keypoints': 32, 'use_separate_rgb_encoder_per_camera': False, 'down_dims': [512, 1024, 2048], 'kernel_size': 5, 'n_groups': 8, 'diffusion_step_embed_dim': 128, 'use_film_scale_modulation': True, 'noise_scheduler_type': 'DDPM', 'num_train_timesteps': 100, 'beta_schedule': 'squaredcos_cap_v2', 'beta_start': 0.0001, 'beta_end': 0.02, 'prediction_type': 'epsilon', 'clip_sample': True, 'clip_sample_range': 1.0, 'num_inference_steps': None, 'do_mask_loss_for_padding': False, 'optimizer_lr': 0.0001, 'optimizer_betas': [0.95, 0.999], 'optimizer_eps': 1e-08, 'optimizer_weight_decay': 1e-06, 'scheduler_name': 'cosine', 'scheduler_warmup_steps': 500}, 'output_dir': 'outputs/train/2025-11-18/01-36-18_diffusion', 'job_name': 'diffusion', 'resume': False, 'seed': 1000, 'num_workers': 2, 'batch_size': 8, 'steps': 100000, 'eval_freq': 20000, 'log_freq': 200, 'save_checkpoint': True, 'save_freq': 20000, 'use_policy_training_preset': True, 'optimizer': {'type': 'adam', 'lr': 0.0001, 'weight_decay': 1e-06, 'grad_clip_norm': 10.0, 'betas': [0.95, 0.999], 'eps': 1e-08}, 'scheduler': {'type': 'diffuser', 'num_warmup_steps': 500, 'name': 'cosine'}, 'eval': {'n_episodes': 50, 'batch_size': 50, 'use_async_envs': False}, 'wandb': {'enable': True, 'disable_artifact': True, 'project': 'lerobot', 'entity': None, 'notes': None, 'run_id': None, 'mode': None}, '_wandb': {}}
|
| 11 |
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2025-11-18 01:36:23,330 INFO MainThread:2405166 [wandb_init.py:init():809] starting backend
|
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2025-11-18 01:36:23,330 INFO MainThread:2405166 [wandb_init.py:init():813] sending inform_init request
|
| 13 |
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2025-11-18 01:36:23,342 INFO MainThread:2405166 [backend.py:_multiprocessing_setup():101] multiprocessing start_methods=fork,spawn,forkserver, using: spawn
|
| 14 |
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2025-11-18 01:36:23,343 INFO MainThread:2405166 [wandb_init.py:init():823] backend started and connected
|
| 15 |
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2025-11-18 01:36:23,344 INFO MainThread:2405166 [wandb_init.py:init():915] updated telemetry
|
| 16 |
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2025-11-18 01:36:23,398 INFO MainThread:2405166 [wandb_init.py:init():939] communicating run to backend with 90.0 second timeout
|
| 17 |
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2025-11-18 01:36:23,974 INFO MainThread:2405166 [wandb_init.py:init():1014] starting run threads in backend
|
| 18 |
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2025-11-18 01:36:24,364 INFO MainThread:2405166 [wandb_run.py:_console_start():2454] atexit reg
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| 19 |
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| 20 |
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2025-11-18 01:36:24,364 INFO MainThread:2405166 [wandb_run.py:_redirect():2371] Wrapping output streams.
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| 21 |
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2025-11-18 01:36:24,364 INFO MainThread:2405166 [wandb_run.py:_redirect():2394] Redirects installed.
|
| 22 |
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2025-11-18 01:36:24,366 INFO MainThread:2405166 [wandb_init.py:init():1056] run started, returning control to user process
|
| 23 |
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2025-11-18 04:16:59,770 INFO MsgRouterThr:2405166 [mailbox.py:close():129] [no run ID] Closing mailbox, abandoning 1 handles.
|
diffusion_anubis_pullout_wrench/wandb/run-20251118_013623-flrqqt58/run-flrqqt58.wandb
ADDED
|
@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:b8bcd7e6f2adc36631ebfe7b9d5897e887abbada7fe0c28dc42255de05dcc9ef
|
| 3 |
+
size 1071827
|
diffusion_anubis_put_into_pot/checkpoints/100000/pretrained_model/config.json
ADDED
|
@@ -0,0 +1,92 @@
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|
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|
|
|
|
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|
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|
|
|
|
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|
|
|
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|
|
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|
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|
|
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|
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|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
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|
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|
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|
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|
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|
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|
|
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|
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|
| 1 |
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{
|
| 2 |
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"type": "diffusion",
|
| 3 |
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"n_obs_steps": 2,
|
| 4 |
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"normalization_mapping": {
|
| 5 |
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"VISUAL": "MEAN_STD",
|
| 6 |
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"STATE": "MIN_MAX",
|
| 7 |
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"ACTION": "MIN_MAX"
|
| 8 |
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},
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| 9 |
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| 10 |
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|
| 11 |
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"type": "VISUAL",
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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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},
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| 18 |
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"observation.images.image": {
|
| 19 |
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"type": "VISUAL",
|
| 20 |
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"shape": [
|
| 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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},
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| 26 |
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"observation.images.right_wrist_image": {
|
| 27 |
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"type": "VISUAL",
|
| 28 |
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"shape": [
|
| 29 |
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|
| 30 |
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240,
|
| 31 |
+
320
|
| 32 |
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]
|
| 33 |
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},
|
| 34 |
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"observation.state": {
|
| 35 |
+
"type": "STATE",
|
| 36 |
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"shape": [
|
| 37 |
+
20
|
| 38 |
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]
|
| 39 |
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}
|
| 40 |
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},
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| 41 |
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"output_features": {
|
| 42 |
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"action": {
|
| 43 |
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"type": "ACTION",
|
| 44 |
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"shape": [
|
| 45 |
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20
|
| 46 |
+
]
|
| 47 |
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}
|
| 48 |
+
},
|
| 49 |
+
"device": "cuda",
|
| 50 |
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"use_amp": false,
|
| 51 |
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"horizon": 16,
|
| 52 |
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"n_action_steps": 8,
|
| 53 |
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"drop_n_last_frames": 7,
|
| 54 |
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"vision_backbone": "resnet18",
|
| 55 |
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"crop_shape": [
|
| 56 |
+
84,
|
| 57 |
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|
| 58 |
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],
|
| 59 |
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"crop_is_random": true,
|
| 60 |
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"pretrained_backbone_weights": null,
|
| 61 |
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"use_group_norm": true,
|
| 62 |
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"spatial_softmax_num_keypoints": 32,
|
| 63 |
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"use_separate_rgb_encoder_per_camera": false,
|
| 64 |
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"down_dims": [
|
| 65 |
+
512,
|
| 66 |
+
1024,
|
| 67 |
+
2048
|
| 68 |
+
],
|
| 69 |
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"kernel_size": 5,
|
| 70 |
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"n_groups": 8,
|
| 71 |
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"diffusion_step_embed_dim": 128,
|
| 72 |
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"use_film_scale_modulation": true,
|
| 73 |
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"noise_scheduler_type": "DDPM",
|
| 74 |
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"num_train_timesteps": 100,
|
| 75 |
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"beta_schedule": "squaredcos_cap_v2",
|
| 76 |
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"beta_start": 0.0001,
|
| 77 |
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"beta_end": 0.02,
|
| 78 |
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"prediction_type": "epsilon",
|
| 79 |
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"clip_sample": true,
|
| 80 |
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"clip_sample_range": 1.0,
|
| 81 |
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"num_inference_steps": null,
|
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|
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"optimizer_lr": 0.0001,
|
| 84 |
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"optimizer_betas": [
|
| 85 |
+
0.95,
|
| 86 |
+
0.999
|
| 87 |
+
],
|
| 88 |
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"optimizer_eps": 1e-08,
|
| 89 |
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"optimizer_weight_decay": 1e-06,
|
| 90 |
+
"scheduler_name": "cosine",
|
| 91 |
+
"scheduler_warmup_steps": 500
|
| 92 |
+
}
|
diffusion_anubis_put_into_pot/checkpoints/100000/pretrained_model/model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
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|
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| 1 |
+
version https://git-lfs.github.com/spec/v1
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oid sha256:8ff39ba2bd4baf65478d5c248f26079fde6e4311929fc2b552d7e6028aac0a2e
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| 3 |
+
size 1084610496
|
diffusion_anubis_put_into_pot/checkpoints/100000/pretrained_model/train_config.json
ADDED
|
@@ -0,0 +1,202 @@
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|
| 1 |
+
{
|
| 2 |
+
"dataset": {
|
| 3 |
+
"repo_id": "anubis_put_into_pot__lerobot",
|
| 4 |
+
"root": "/data1/euijinrnd/hf_home_euijin/lerobot/lerobot/anubis_put_into_pot__lerobot",
|
| 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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"type": "ColorJitter",
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| 14 |
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| 15 |
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| 16 |
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0.8,
|
| 17 |
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1.2
|
| 18 |
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]
|
| 19 |
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}
|
| 20 |
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| 21 |
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"contrast": {
|
| 22 |
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|
| 23 |
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"type": "ColorJitter",
|
| 24 |
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| 25 |
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|
| 26 |
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0.8,
|
| 27 |
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1.2
|
| 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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"weight": 1.0,
|
| 33 |
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"type": "ColorJitter",
|
| 34 |
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"kwargs": {
|
| 35 |
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"saturation": [
|
| 36 |
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0.5,
|
| 37 |
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1.5
|
| 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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"type": "ColorJitter",
|
| 44 |
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| 45 |
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"hue": [
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| 46 |
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-0.05,
|
| 47 |
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0.05
|
| 48 |
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]
|
| 49 |
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}
|
| 50 |
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|
| 51 |
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"sharpness": {
|
| 52 |
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"weight": 1.0,
|
| 53 |
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"type": "SharpnessJitter",
|
| 54 |
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| 55 |
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"sharpness": [
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| 56 |
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0.5,
|
| 57 |
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1.5
|
| 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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"type": "diffusion",
|
| 70 |
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"n_obs_steps": 2,
|
| 71 |
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"normalization_mapping": {
|
| 72 |
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"VISUAL": "MEAN_STD",
|
| 73 |
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"STATE": "MIN_MAX",
|
| 74 |
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"ACTION": "MIN_MAX"
|
| 75 |
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},
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| 76 |
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"input_features": {
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| 77 |
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"observation.images.left_wrist_image": {
|
| 78 |
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"type": "VISUAL",
|
| 79 |
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"shape": [
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| 80 |
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3,
|
| 81 |
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240,
|
| 82 |
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320
|
| 83 |
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]
|
| 84 |
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},
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| 85 |
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"observation.images.image": {
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| 86 |
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"type": "VISUAL",
|
| 87 |
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"shape": [
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| 88 |
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3,
|
| 89 |
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240,
|
| 90 |
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320
|
| 91 |
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]
|
| 92 |
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},
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| 93 |
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"observation.images.right_wrist_image": {
|
| 94 |
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"type": "VISUAL",
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| 95 |
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| 96 |
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3,
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| 97 |
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240,
|
| 98 |
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320
|
| 99 |
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]
|
| 100 |
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},
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| 101 |
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"observation.state": {
|
| 102 |
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"type": "STATE",
|
| 103 |
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| 104 |
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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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"type": "ACTION",
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| 113 |
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| 114 |
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| 115 |
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| 116 |
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"device": "cuda",
|
| 117 |
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|
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| 121 |
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|
| 122 |
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84,
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| 124 |
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| 125 |
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],
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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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512,
|
| 133 |
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1024,
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| 134 |
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2048
|
| 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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"noise_scheduler_type": "DDPM",
|
| 141 |
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|
| 142 |
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|
| 143 |
+
"beta_start": 0.0001,
|
| 144 |
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|
| 145 |
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|
| 146 |
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|
| 147 |
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|
| 148 |
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|
| 150 |
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|
| 151 |
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"optimizer_betas": [
|
| 152 |
+
0.95,
|
| 153 |
+
0.999
|
| 154 |
+
],
|
| 155 |
+
"optimizer_eps": 1e-08,
|
| 156 |
+
"optimizer_weight_decay": 1e-06,
|
| 157 |
+
"scheduler_name": "cosine",
|
| 158 |
+
"scheduler_warmup_steps": 500
|
| 159 |
+
},
|
| 160 |
+
"output_dir": "outputs/train/2025-11-18/01-38-26_diffusion",
|
| 161 |
+
"job_name": "diffusion",
|
| 162 |
+
"resume": false,
|
| 163 |
+
"seed": 1000,
|
| 164 |
+
"num_workers": 2,
|
| 165 |
+
"batch_size": 8,
|
| 166 |
+
"steps": 100000,
|
| 167 |
+
"eval_freq": 20000,
|
| 168 |
+
"log_freq": 200,
|
| 169 |
+
"save_checkpoint": true,
|
| 170 |
+
"save_freq": 20000,
|
| 171 |
+
"use_policy_training_preset": true,
|
| 172 |
+
"optimizer": {
|
| 173 |
+
"type": "adam",
|
| 174 |
+
"lr": 0.0001,
|
| 175 |
+
"weight_decay": 1e-06,
|
| 176 |
+
"grad_clip_norm": 10.0,
|
| 177 |
+
"betas": [
|
| 178 |
+
0.95,
|
| 179 |
+
0.999
|
| 180 |
+
],
|
| 181 |
+
"eps": 1e-08
|
| 182 |
+
},
|
| 183 |
+
"scheduler": {
|
| 184 |
+
"type": "diffuser",
|
| 185 |
+
"num_warmup_steps": 500,
|
| 186 |
+
"name": "cosine"
|
| 187 |
+
},
|
| 188 |
+
"eval": {
|
| 189 |
+
"n_episodes": 50,
|
| 190 |
+
"batch_size": 50,
|
| 191 |
+
"use_async_envs": false
|
| 192 |
+
},
|
| 193 |
+
"wandb": {
|
| 194 |
+
"enable": true,
|
| 195 |
+
"disable_artifact": true,
|
| 196 |
+
"project": "lerobot",
|
| 197 |
+
"entity": null,
|
| 198 |
+
"notes": null,
|
| 199 |
+
"run_id": null,
|
| 200 |
+
"mode": null
|
| 201 |
+
}
|
| 202 |
+
}
|
diffusion_anubis_put_into_pot/wandb/debug-internal.log
ADDED
|
@@ -0,0 +1,15 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{"time":"2025-11-18T01:38:27.86226386+09:00","level":"INFO","msg":"stream: starting","core version":"0.19.9","symlink path":"outputs/train/2025-11-18/01-38-26_diffusion/wandb/run-20251118_013827-yx7en6s6/logs/debug-core.log"}
|
| 2 |
+
{"time":"2025-11-18T01:38:28.164948557+09:00","level":"INFO","msg":"created new stream","id":"yx7en6s6"}
|
| 3 |
+
{"time":"2025-11-18T01:38:28.164982138+09:00","level":"INFO","msg":"stream: started","id":"yx7en6s6"}
|
| 4 |
+
{"time":"2025-11-18T01:38:28.164994967+09:00","level":"INFO","msg":"handler: started","stream_id":"yx7en6s6"}
|
| 5 |
+
{"time":"2025-11-18T01:38:28.165018842+09:00","level":"INFO","msg":"sender: started","stream_id":"yx7en6s6"}
|
| 6 |
+
{"time":"2025-11-18T01:38:28.165033154+09:00","level":"INFO","msg":"writer: Do: started","stream_id":"yx7en6s6"}
|
| 7 |
+
{"time":"2025-11-18T01:38:28.632818175+09:00","level":"INFO","msg":"Starting system monitor"}
|
| 8 |
+
{"time":"2025-11-18T04:13:54.475529708+09:00","level":"INFO","msg":"stream: closing","id":"yx7en6s6"}
|
| 9 |
+
{"time":"2025-11-18T04:13:54.47557102+09:00","level":"INFO","msg":"Stopping system monitor"}
|
| 10 |
+
{"time":"2025-11-18T04:13:54.475653333+09:00","level":"INFO","msg":"Stopped system monitor"}
|
| 11 |
+
{"time":"2025-11-18T04:13:55.330036373+09:00","level":"INFO","msg":"fileTransfer: Close: file transfer manager closed"}
|
| 12 |
+
{"time":"2025-11-18T04:13:55.650223156+09:00","level":"INFO","msg":"handler: closed","stream_id":"yx7en6s6"}
|
| 13 |
+
{"time":"2025-11-18T04:13:55.650251138+09:00","level":"INFO","msg":"writer: Close: closed","stream_id":"yx7en6s6"}
|
| 14 |
+
{"time":"2025-11-18T04:13:55.65025934+09:00","level":"INFO","msg":"sender: closed","stream_id":"yx7en6s6"}
|
| 15 |
+
{"time":"2025-11-18T04:13:55.650702114+09:00","level":"INFO","msg":"stream: closed","id":"yx7en6s6"}
|
diffusion_anubis_put_into_pot/wandb/debug.log
ADDED
|
@@ -0,0 +1,23 @@
|
|
|
|
|
|
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|
|
|
|
|
|
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|
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|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
|
| 1 |
+
2025-11-18 01:38:27,856 INFO MainThread:2405533 [wandb_setup.py:_flush():67] Current SDK version is 0.19.9
|
| 2 |
+
2025-11-18 01:38:27,857 INFO MainThread:2405533 [wandb_setup.py:_flush():67] Configure stats pid to 2405533
|
| 3 |
+
2025-11-18 01:38:27,857 INFO MainThread:2405533 [wandb_setup.py:_flush():67] Loading settings from /home/euijinrnd/.config/wandb/settings
|
| 4 |
+
2025-11-18 01:38:27,857 INFO MainThread:2405533 [wandb_setup.py:_flush():67] Loading settings from /home/euijinrnd/workspace/lerobot/wandb/settings
|
| 5 |
+
2025-11-18 01:38:27,857 INFO MainThread:2405533 [wandb_setup.py:_flush():67] Loading settings from environment variables
|
| 6 |
+
2025-11-18 01:38:27,857 INFO MainThread:2405533 [wandb_init.py:setup_run_log_directory():662] Logging user logs to outputs/train/2025-11-18/01-38-26_diffusion/wandb/run-20251118_013827-yx7en6s6/logs/debug.log
|
| 7 |
+
2025-11-18 01:38:27,857 INFO MainThread:2405533 [wandb_init.py:setup_run_log_directory():663] Logging internal logs to outputs/train/2025-11-18/01-38-26_diffusion/wandb/run-20251118_013827-yx7en6s6/logs/debug-internal.log
|
| 8 |
+
2025-11-18 01:38:27,857 INFO MainThread:2405533 [wandb_init.py:init():781] calling init triggers
|
| 9 |
+
2025-11-18 01:38:27,857 INFO MainThread:2405533 [wandb_init.py:init():786] wandb.init called with sweep_config: {}
|
| 10 |
+
config: {'dataset': {'repo_id': 'anubis_put_into_pot__lerobot', 'root': '/data1/euijinrnd/hf_home_euijin/lerobot/lerobot/anubis_put_into_pot__lerobot', 'episodes': None, 'image_transforms': {'enable': False, 'max_num_transforms': 3, 'random_order': False, 'tfs': {'brightness': {'weight': 1.0, 'type': 'ColorJitter', 'kwargs': {'brightness': [0.8, 1.2]}}, 'contrast': {'weight': 1.0, 'type': 'ColorJitter', 'kwargs': {'contrast': [0.8, 1.2]}}, 'saturation': {'weight': 1.0, 'type': 'ColorJitter', 'kwargs': {'saturation': [0.5, 1.5]}}, 'hue': {'weight': 1.0, 'type': 'ColorJitter', 'kwargs': {'hue': [-0.05, 0.05]}}, 'sharpness': {'weight': 1.0, 'type': 'SharpnessJitter', 'kwargs': {'sharpness': [0.5, 1.5]}}}}, 'revision': None, 'use_imagenet_stats': True, 'video_backend': 'torchcodec'}, 'env': None, 'policy': {'type': 'diffusion', 'n_obs_steps': 2, 'normalization_mapping': {'VISUAL': <NormalizationMode.MEAN_STD: 'MEAN_STD'>, 'STATE': <NormalizationMode.MIN_MAX: 'MIN_MAX'>, 'ACTION': <NormalizationMode.MIN_MAX: 'MIN_MAX'>}, 'input_features': {}, 'output_features': {}, 'device': 'cuda', 'use_amp': False, 'horizon': 16, 'n_action_steps': 8, 'drop_n_last_frames': 7, 'vision_backbone': 'resnet18', 'crop_shape': [84, 84], 'crop_is_random': True, 'pretrained_backbone_weights': None, 'use_group_norm': True, 'spatial_softmax_num_keypoints': 32, 'use_separate_rgb_encoder_per_camera': False, 'down_dims': [512, 1024, 2048], 'kernel_size': 5, 'n_groups': 8, 'diffusion_step_embed_dim': 128, 'use_film_scale_modulation': True, 'noise_scheduler_type': 'DDPM', 'num_train_timesteps': 100, 'beta_schedule': 'squaredcos_cap_v2', 'beta_start': 0.0001, 'beta_end': 0.02, 'prediction_type': 'epsilon', 'clip_sample': True, 'clip_sample_range': 1.0, 'num_inference_steps': None, 'do_mask_loss_for_padding': False, 'optimizer_lr': 0.0001, 'optimizer_betas': [0.95, 0.999], 'optimizer_eps': 1e-08, 'optimizer_weight_decay': 1e-06, 'scheduler_name': 'cosine', 'scheduler_warmup_steps': 500}, 'output_dir': 'outputs/train/2025-11-18/01-38-26_diffusion', 'job_name': 'diffusion', 'resume': False, 'seed': 1000, 'num_workers': 2, 'batch_size': 8, 'steps': 100000, 'eval_freq': 20000, 'log_freq': 200, 'save_checkpoint': True, 'save_freq': 20000, 'use_policy_training_preset': True, 'optimizer': {'type': 'adam', 'lr': 0.0001, 'weight_decay': 1e-06, 'grad_clip_norm': 10.0, 'betas': [0.95, 0.999], 'eps': 1e-08}, 'scheduler': {'type': 'diffuser', 'num_warmup_steps': 500, 'name': 'cosine'}, 'eval': {'n_episodes': 50, 'batch_size': 50, 'use_async_envs': False}, 'wandb': {'enable': True, 'disable_artifact': True, 'project': 'lerobot', 'entity': None, 'notes': None, 'run_id': None, 'mode': None}, '_wandb': {}}
|
| 11 |
+
2025-11-18 01:38:27,857 INFO MainThread:2405533 [wandb_init.py:init():809] starting backend
|
| 12 |
+
2025-11-18 01:38:27,857 INFO MainThread:2405533 [wandb_init.py:init():813] sending inform_init request
|
| 13 |
+
2025-11-18 01:38:27,860 INFO MainThread:2405533 [backend.py:_multiprocessing_setup():101] multiprocessing start_methods=fork,spawn,forkserver, using: spawn
|
| 14 |
+
2025-11-18 01:38:27,860 INFO MainThread:2405533 [wandb_init.py:init():823] backend started and connected
|
| 15 |
+
2025-11-18 01:38:27,863 INFO MainThread:2405533 [wandb_init.py:init():915] updated telemetry
|
| 16 |
+
2025-11-18 01:38:27,924 INFO MainThread:2405533 [wandb_init.py:init():939] communicating run to backend with 90.0 second timeout
|
| 17 |
+
2025-11-18 01:38:28,621 INFO MainThread:2405533 [wandb_init.py:init():1014] starting run threads in backend
|
| 18 |
+
2025-11-18 01:38:29,206 INFO MainThread:2405533 [wandb_run.py:_console_start():2454] atexit reg
|
| 19 |
+
2025-11-18 01:38:29,207 INFO MainThread:2405533 [wandb_run.py:_redirect():2306] redirect: wrap_raw
|
| 20 |
+
2025-11-18 01:38:29,207 INFO MainThread:2405533 [wandb_run.py:_redirect():2371] Wrapping output streams.
|
| 21 |
+
2025-11-18 01:38:29,207 INFO MainThread:2405533 [wandb_run.py:_redirect():2394] Redirects installed.
|
| 22 |
+
2025-11-18 01:38:29,209 INFO MainThread:2405533 [wandb_init.py:init():1056] run started, returning control to user process
|
| 23 |
+
2025-11-18 04:13:54,474 INFO MsgRouterThr:2405533 [mailbox.py:close():129] [no run ID] Closing mailbox, abandoning 1 handles.
|
diffusion_anubis_put_into_pot/wandb/run-20251118_013827-yx7en6s6/files/config.yaml
ADDED
|
@@ -0,0 +1,184 @@
|
|
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|
|
|
|
|
|
|
|
|
|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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| 82 |
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| 83 |
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| 87 |
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|
| 112 |
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| 116 |
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|
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|
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| 166 |
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|
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project: lerobot
|
| 184 |
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run_id: null
|
diffusion_anubis_put_into_pot/wandb/run-20251118_013827-yx7en6s6/files/output.log
ADDED
|
@@ -0,0 +1,518 @@
|
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| 1 |
+
Logs will be synced with wandb.
|
| 2 |
+
INFO 2025-11-18 01:38:29 ndb_utils.py:96 Track this run --> https://wandb.ai/jinprelude/lerobot/runs/yx7en6s6
|
| 3 |
+
INFO 2025-11-18 01:38:29 ts/train.py:127 Creating dataset
|
| 4 |
+
INFO 2025-11-18 01:38:30 ts/train.py:138 Creating policy
|
| 5 |
+
INFO 2025-11-18 01:38:32 ts/train.py:144 Creating optimizer and scheduler
|
| 6 |
+
INFO 2025-11-18 01:38:32 ts/train.py:156 Output dir: outputs/train/2025-11-18/01-38-26_diffusion
|
| 7 |
+
INFO 2025-11-18 01:38:32 ts/train.py:159 cfg.steps=100000 (100K)
|
| 8 |
+
INFO 2025-11-18 01:38:32 ts/train.py:160 dataset.num_frames=12330 (12K)
|
| 9 |
+
INFO 2025-11-18 01:38:32 ts/train.py:161 dataset.num_episodes=54
|
| 10 |
+
INFO 2025-11-18 01:38:32 ts/train.py:162 num_learnable_params=271145780 (271M)
|
| 11 |
+
INFO 2025-11-18 01:38:32 ts/train.py:163 num_total_params=271145918 (271M)
|
| 12 |
+
INFO 2025-11-18 01:38:32 ts/train.py:202 Start offline training on a fixed dataset
|
| 13 |
+
INFO 2025-11-18 01:38:51 ts/train.py:232 step:200 smpl:2K ep:7 epch:0.13 loss:0.996 grdn:2.595 lr:2.0e-05 updt_s:0.070 data_s:0.025
|
| 14 |
+
INFO 2025-11-18 01:39:09 ts/train.py:232 step:400 smpl:3K ep:14 epch:0.26 loss:0.401 grdn:2.996 lr:6.0e-05 updt_s:0.064 data_s:0.026
|
| 15 |
+
INFO 2025-11-18 01:39:27 ts/train.py:232 step:600 smpl:5K ep:21 epch:0.39 loss:0.191 grdn:1.773 lr:9.5e-05 updt_s:0.064 data_s:0.028
|
| 16 |
+
INFO 2025-11-18 01:39:46 ts/train.py:232 step:800 smpl:6K ep:28 epch:0.52 loss:0.131 grdn:1.256 lr:1.0e-04 updt_s:0.064 data_s:0.030
|
| 17 |
+
INFO 2025-11-18 01:40:05 ts/train.py:232 step:1K smpl:8K ep:35 epch:0.65 loss:0.101 grdn:1.031 lr:1.0e-04 updt_s:0.064 data_s:0.030
|
| 18 |
+
INFO 2025-11-18 01:40:22 ts/train.py:232 step:1K smpl:10K ep:42 epch:0.78 loss:0.094 grdn:0.962 lr:1.0e-04 updt_s:0.065 data_s:0.019
|
| 19 |
+
INFO 2025-11-18 01:40:39 ts/train.py:232 step:1K smpl:11K ep:49 epch:0.91 loss:0.083 grdn:0.847 lr:1.0e-04 updt_s:0.064 data_s:0.020
|
| 20 |
+
INFO 2025-11-18 01:40:58 ts/train.py:232 step:2K smpl:13K ep:56 epch:1.04 loss:0.070 grdn:0.731 lr:1.0e-04 updt_s:0.065 data_s:0.031
|
| 21 |
+
INFO 2025-11-18 01:41:17 ts/train.py:232 step:2K smpl:14K ep:63 epch:1.17 loss:0.068 grdn:0.699 lr:1.0e-04 updt_s:0.065 data_s:0.028
|
| 22 |
+
INFO 2025-11-18 01:41:35 ts/train.py:232 step:2K smpl:16K ep:70 epch:1.30 loss:0.063 grdn:0.659 lr:1.0e-04 updt_s:0.065 data_s:0.026
|
| 23 |
+
INFO 2025-11-18 01:41:53 ts/train.py:232 step:2K smpl:18K ep:77 epch:1.43 loss:0.064 grdn:0.647 lr:1.0e-04 updt_s:0.065 data_s:0.026
|
| 24 |
+
INFO 2025-11-18 01:42:12 ts/train.py:232 step:2K smpl:19K ep:84 epch:1.56 loss:0.065 grdn:0.618 lr:1.0e-04 updt_s:0.065 data_s:0.029
|
| 25 |
+
INFO 2025-11-18 01:42:31 ts/train.py:232 step:3K smpl:21K ep:91 epch:1.69 loss:0.061 grdn:0.603 lr:1.0e-04 updt_s:0.065 data_s:0.029
|
| 26 |
+
INFO 2025-11-18 01:42:50 ts/train.py:232 step:3K smpl:22K ep:98 epch:1.82 loss:0.055 grdn:0.544 lr:1.0e-04 updt_s:0.065 data_s:0.027
|
| 27 |
+
INFO 2025-11-18 01:43:08 ts/train.py:232 step:3K smpl:24K ep:105 epch:1.95 loss:0.054 grdn:0.535 lr:1.0e-04 updt_s:0.065 data_s:0.024
|
| 28 |
+
INFO 2025-11-18 01:43:26 ts/train.py:232 step:3K smpl:26K ep:112 epch:2.08 loss:0.054 grdn:0.530 lr:1.0e-04 updt_s:0.064 data_s:0.028
|
| 29 |
+
INFO 2025-11-18 01:43:45 ts/train.py:232 step:3K smpl:27K ep:119 epch:2.21 loss:0.052 grdn:0.512 lr:1.0e-04 updt_s:0.064 data_s:0.030
|
| 30 |
+
INFO 2025-11-18 01:44:04 ts/train.py:232 step:4K smpl:29K ep:126 epch:2.34 loss:0.050 grdn:0.490 lr:1.0e-04 updt_s:0.065 data_s:0.027
|
| 31 |
+
INFO 2025-11-18 01:44:22 ts/train.py:232 step:4K smpl:30K ep:133 epch:2.47 loss:0.049 grdn:0.479 lr:1.0e-04 updt_s:0.064 data_s:0.027
|
| 32 |
+
INFO 2025-11-18 01:44:41 ts/train.py:232 step:4K smpl:32K ep:140 epch:2.60 loss:0.049 grdn:0.470 lr:1.0e-04 updt_s:0.064 data_s:0.027
|
| 33 |
+
INFO 2025-11-18 01:44:59 ts/train.py:232 step:4K smpl:34K ep:147 epch:2.73 loss:0.046 grdn:0.448 lr:1.0e-04 updt_s:0.065 data_s:0.027
|
| 34 |
+
INFO 2025-11-18 01:45:17 ts/train.py:232 step:4K smpl:35K ep:154 epch:2.85 loss:0.045 grdn:0.441 lr:1.0e-04 updt_s:0.065 data_s:0.024
|
| 35 |
+
INFO 2025-11-18 01:45:36 ts/train.py:232 step:5K smpl:37K ep:161 epch:2.98 loss:0.045 grdn:0.429 lr:1.0e-04 updt_s:0.065 data_s:0.032
|
| 36 |
+
INFO 2025-11-18 01:45:55 ts/train.py:232 step:5K smpl:38K ep:168 epch:3.11 loss:0.047 grdn:0.444 lr:1.0e-04 updt_s:0.065 data_s:0.026
|
| 37 |
+
INFO 2025-11-18 01:46:13 ts/train.py:232 step:5K smpl:40K ep:175 epch:3.24 loss:0.044 grdn:0.406 lr:1.0e-04 updt_s:0.065 data_s:0.027
|
| 38 |
+
INFO 2025-11-18 01:46:35 ts/train.py:232 step:5K smpl:42K ep:182 epch:3.37 loss:0.044 grdn:0.410 lr:9.9e-05 updt_s:0.064 data_s:0.044
|
| 39 |
+
INFO 2025-11-18 01:46:53 ts/train.py:232 step:5K smpl:43K ep:189 epch:3.50 loss:0.043 grdn:0.395 lr:9.9e-05 updt_s:0.065 data_s:0.026
|
| 40 |
+
INFO 2025-11-18 01:47:11 ts/train.py:232 step:6K smpl:45K ep:196 epch:3.63 loss:0.041 grdn:0.388 lr:9.9e-05 updt_s:0.064 data_s:0.026
|
| 41 |
+
INFO 2025-11-18 01:47:29 ts/train.py:232 step:6K smpl:46K ep:203 epch:3.76 loss:0.045 grdn:0.392 lr:9.9e-05 updt_s:0.065 data_s:0.025
|
| 42 |
+
INFO 2025-11-18 01:47:48 ts/train.py:232 step:6K smpl:48K ep:210 epch:3.89 loss:0.041 grdn:0.376 lr:9.9e-05 updt_s:0.067 data_s:0.027
|
| 43 |
+
INFO 2025-11-18 01:48:07 ts/train.py:232 step:6K smpl:50K ep:217 epch:4.02 loss:0.036 grdn:0.349 lr:9.9e-05 updt_s:0.064 data_s:0.027
|
| 44 |
+
INFO 2025-11-18 01:48:25 ts/train.py:232 step:6K smpl:51K ep:224 epch:4.15 loss:0.042 grdn:0.373 lr:9.9e-05 updt_s:0.065 data_s:0.028
|
| 45 |
+
INFO 2025-11-18 01:48:44 ts/train.py:232 step:7K smpl:53K ep:231 epch:4.28 loss:0.039 grdn:0.356 lr:9.9e-05 updt_s:0.065 data_s:0.027
|
| 46 |
+
INFO 2025-11-18 01:49:02 ts/train.py:232 step:7K smpl:54K ep:238 epch:4.41 loss:0.041 grdn:0.363 lr:9.9e-05 updt_s:0.064 data_s:0.027
|
| 47 |
+
INFO 2025-11-18 01:49:21 ts/train.py:232 step:7K smpl:56K ep:245 epch:4.54 loss:0.038 grdn:0.335 lr:9.9e-05 updt_s:0.065 data_s:0.028
|
| 48 |
+
INFO 2025-11-18 01:49:39 ts/train.py:232 step:7K smpl:58K ep:252 epch:4.67 loss:0.040 grdn:0.355 lr:9.9e-05 updt_s:0.065 data_s:0.026
|
| 49 |
+
INFO 2025-11-18 01:49:57 ts/train.py:232 step:7K smpl:59K ep:259 epch:4.80 loss:0.039 grdn:0.343 lr:9.9e-05 updt_s:0.064 data_s:0.026
|
| 50 |
+
INFO 2025-11-18 01:50:16 ts/train.py:232 step:8K smpl:61K ep:266 epch:4.93 loss:0.037 grdn:0.333 lr:9.9e-05 updt_s:0.065 data_s:0.030
|
| 51 |
+
INFO 2025-11-18 01:50:36 ts/train.py:232 step:8K smpl:62K ep:273 epch:5.06 loss:0.033 grdn:0.303 lr:9.9e-05 updt_s:0.067 data_s:0.030
|
| 52 |
+
INFO 2025-11-18 01:50:54 ts/train.py:232 step:8K smpl:64K ep:280 epch:5.19 loss:0.038 grdn:0.335 lr:9.9e-05 updt_s:0.065 data_s:0.027
|
| 53 |
+
INFO 2025-11-18 01:51:13 ts/train.py:232 step:8K smpl:66K ep:287 epch:5.32 loss:0.036 grdn:0.316 lr:9.9e-05 updt_s:0.065 data_s:0.028
|
| 54 |
+
INFO 2025-11-18 01:51:31 ts/train.py:232 step:8K smpl:67K ep:294 epch:5.45 loss:0.038 grdn:0.327 lr:9.8e-05 updt_s:0.065 data_s:0.028
|
| 55 |
+
INFO 2025-11-18 01:51:50 ts/train.py:232 step:9K smpl:69K ep:301 epch:5.58 loss:0.038 grdn:0.324 lr:9.8e-05 updt_s:0.065 data_s:0.027
|
| 56 |
+
INFO 2025-11-18 01:52:08 ts/train.py:232 step:9K smpl:70K ep:308 epch:5.71 loss:0.038 grdn:0.318 lr:9.8e-05 updt_s:0.065 data_s:0.029
|
| 57 |
+
INFO 2025-11-18 01:52:28 ts/train.py:232 step:9K smpl:72K ep:315 epch:5.84 loss:0.035 grdn:0.302 lr:9.8e-05 updt_s:0.064 data_s:0.031
|
| 58 |
+
INFO 2025-11-18 01:52:46 ts/train.py:232 step:9K smpl:74K ep:322 epch:5.97 loss:0.035 grdn:0.296 lr:9.8e-05 updt_s:0.064 data_s:0.029
|
| 59 |
+
INFO 2025-11-18 01:53:05 ts/train.py:232 step:9K smpl:75K ep:329 epch:6.10 loss:0.035 grdn:0.294 lr:9.8e-05 updt_s:0.064 data_s:0.029
|
| 60 |
+
INFO 2025-11-18 01:53:24 ts/train.py:232 step:10K smpl:77K ep:336 epch:6.23 loss:0.034 grdn:0.293 lr:9.8e-05 updt_s:0.064 data_s:0.029
|
| 61 |
+
INFO 2025-11-18 01:53:43 ts/train.py:232 step:10K smpl:78K ep:343 epch:6.36 loss:0.035 grdn:0.299 lr:9.8e-05 updt_s:0.065 data_s:0.030
|
| 62 |
+
INFO 2025-11-18 01:54:02 ts/train.py:232 step:10K smpl:80K ep:350 epch:6.49 loss:0.035 grdn:0.291 lr:9.8e-05 updt_s:0.065 data_s:0.029
|
| 63 |
+
INFO 2025-11-18 01:54:21 ts/train.py:232 step:10K smpl:82K ep:357 epch:6.62 loss:0.034 grdn:0.290 lr:9.8e-05 updt_s:0.065 data_s:0.028
|
| 64 |
+
INFO 2025-11-18 01:54:39 ts/train.py:232 step:10K smpl:83K ep:364 epch:6.75 loss:0.033 grdn:0.277 lr:9.8e-05 updt_s:0.065 data_s:0.025
|
| 65 |
+
INFO 2025-11-18 01:54:59 ts/train.py:232 step:11K smpl:85K ep:371 epch:6.88 loss:0.031 grdn:0.262 lr:9.8e-05 updt_s:0.065 data_s:0.034
|
| 66 |
+
INFO 2025-11-18 01:55:17 ts/train.py:232 step:11K smpl:86K ep:378 epch:7.01 loss:0.030 grdn:0.269 lr:9.7e-05 updt_s:0.065 data_s:0.028
|
| 67 |
+
INFO 2025-11-18 01:55:36 ts/train.py:232 step:11K smpl:88K ep:385 epch:7.14 loss:0.036 grdn:0.298 lr:9.7e-05 updt_s:0.065 data_s:0.029
|
| 68 |
+
INFO 2025-11-18 01:55:54 ts/train.py:232 step:11K smpl:90K ep:392 epch:7.27 loss:0.036 grdn:0.290 lr:9.7e-05 updt_s:0.065 data_s:0.027
|
| 69 |
+
INFO 2025-11-18 01:56:13 ts/train.py:232 step:11K smpl:91K ep:399 epch:7.40 loss:0.036 grdn:0.288 lr:9.7e-05 updt_s:0.065 data_s:0.027
|
| 70 |
+
INFO 2025-11-18 01:56:35 ts/train.py:232 step:12K smpl:93K ep:406 epch:7.53 loss:0.033 grdn:0.277 lr:9.7e-05 updt_s:0.065 data_s:0.046
|
| 71 |
+
INFO 2025-11-18 01:56:54 ts/train.py:232 step:12K smpl:94K ep:413 epch:7.66 loss:0.031 grdn:0.265 lr:9.7e-05 updt_s:0.066 data_s:0.027
|
| 72 |
+
INFO 2025-11-18 01:57:12 ts/train.py:232 step:12K smpl:96K ep:420 epch:7.79 loss:0.032 grdn:0.269 lr:9.7e-05 updt_s:0.065 data_s:0.026
|
| 73 |
+
INFO 2025-11-18 01:57:30 ts/train.py:232 step:12K smpl:98K ep:427 epch:7.92 loss:0.032 grdn:0.258 lr:9.7e-05 updt_s:0.065 data_s:0.023
|
| 74 |
+
INFO 2025-11-18 01:57:48 ts/train.py:232 step:12K smpl:99K ep:434 epch:8.05 loss:0.032 grdn:0.266 lr:9.7e-05 updt_s:0.065 data_s:0.025
|
| 75 |
+
INFO 2025-11-18 01:58:06 ts/train.py:232 step:13K smpl:101K ep:441 epch:8.18 loss:0.033 grdn:0.272 lr:9.6e-05 updt_s:0.064 data_s:0.023
|
| 76 |
+
INFO 2025-11-18 01:58:24 ts/train.py:232 step:13K smpl:102K ep:448 epch:8.30 loss:0.029 grdn:0.251 lr:9.6e-05 updt_s:0.065 data_s:0.024
|
| 77 |
+
INFO 2025-11-18 01:58:41 ts/train.py:232 step:13K smpl:104K ep:455 epch:8.43 loss:0.031 grdn:0.261 lr:9.6e-05 updt_s:0.064 data_s:0.023
|
| 78 |
+
INFO 2025-11-18 01:58:58 ts/train.py:232 step:13K smpl:106K ep:462 epch:8.56 loss:0.033 grdn:0.269 lr:9.6e-05 updt_s:0.065 data_s:0.020
|
| 79 |
+
INFO 2025-11-18 01:59:15 ts/train.py:232 step:13K smpl:107K ep:469 epch:8.69 loss:0.033 grdn:0.262 lr:9.6e-05 updt_s:0.065 data_s:0.019
|
| 80 |
+
INFO 2025-11-18 01:59:34 ts/train.py:232 step:14K smpl:109K ep:476 epch:8.82 loss:0.029 grdn:0.244 lr:9.6e-05 updt_s:0.065 data_s:0.029
|
| 81 |
+
INFO 2025-11-18 01:59:53 ts/train.py:232 step:14K smpl:110K ep:484 epch:8.95 loss:0.029 grdn:0.244 lr:9.6e-05 updt_s:0.065 data_s:0.026
|
| 82 |
+
INFO 2025-11-18 02:00:11 ts/train.py:232 step:14K smpl:112K ep:491 epch:9.08 loss:0.030 grdn:0.261 lr:9.6e-05 updt_s:0.064 data_s:0.028
|
| 83 |
+
INFO 2025-11-18 02:00:30 ts/train.py:232 step:14K smpl:114K ep:498 epch:9.21 loss:0.032 grdn:0.253 lr:9.5e-05 updt_s:0.065 data_s:0.028
|
| 84 |
+
INFO 2025-11-18 02:00:49 ts/train.py:232 step:14K smpl:115K ep:505 epch:9.34 loss:0.030 grdn:0.252 lr:9.5e-05 updt_s:0.066 data_s:0.029
|
| 85 |
+
INFO 2025-11-18 02:01:07 ts/train.py:232 step:15K smpl:117K ep:512 epch:9.47 loss:0.026 grdn:0.226 lr:9.5e-05 updt_s:0.064 data_s:0.026
|
| 86 |
+
INFO 2025-11-18 02:01:26 ts/train.py:232 step:15K smpl:118K ep:519 epch:9.60 loss:0.028 grdn:0.237 lr:9.5e-05 updt_s:0.065 data_s:0.027
|
| 87 |
+
INFO 2025-11-18 02:01:43 ts/train.py:232 step:15K smpl:120K ep:526 epch:9.73 loss:0.029 grdn:0.237 lr:9.5e-05 updt_s:0.065 data_s:0.023
|
| 88 |
+
INFO 2025-11-18 02:02:02 ts/train.py:232 step:15K smpl:122K ep:533 epch:9.86 loss:0.029 grdn:0.242 lr:9.5e-05 updt_s:0.065 data_s:0.029
|
| 89 |
+
INFO 2025-11-18 02:02:21 ts/train.py:232 step:15K smpl:123K ep:540 epch:9.99 loss:0.030 grdn:0.243 lr:9.5e-05 updt_s:0.065 data_s:0.028
|
| 90 |
+
INFO 2025-11-18 02:02:40 ts/train.py:232 step:16K smpl:125K ep:547 epch:10.12 loss:0.032 grdn:0.256 lr:9.4e-05 updt_s:0.064 data_s:0.029
|
| 91 |
+
INFO 2025-11-18 02:02:58 ts/train.py:232 step:16K smpl:126K ep:554 epch:10.25 loss:0.027 grdn:0.240 lr:9.4e-05 updt_s:0.064 data_s:0.028
|
| 92 |
+
INFO 2025-11-18 02:03:17 ts/train.py:232 step:16K smpl:128K ep:561 epch:10.38 loss:0.032 grdn:0.253 lr:9.4e-05 updt_s:0.065 data_s:0.028
|
| 93 |
+
INFO 2025-11-18 02:03:35 ts/train.py:232 step:16K smpl:130K ep:568 epch:10.51 loss:0.030 grdn:0.242 lr:9.4e-05 updt_s:0.065 data_s:0.027
|
| 94 |
+
INFO 2025-11-18 02:03:54 ts/train.py:232 step:16K smpl:131K ep:575 epch:10.64 loss:0.028 grdn:0.235 lr:9.4e-05 updt_s:0.067 data_s:0.026
|
| 95 |
+
INFO 2025-11-18 02:04:14 ts/train.py:232 step:17K smpl:133K ep:582 epch:10.77 loss:0.028 grdn:0.232 lr:9.4e-05 updt_s:0.066 data_s:0.032
|
| 96 |
+
INFO 2025-11-18 02:04:33 ts/train.py:232 step:17K smpl:134K ep:589 epch:10.90 loss:0.032 grdn:0.250 lr:9.4e-05 updt_s:0.065 data_s:0.028
|
| 97 |
+
INFO 2025-11-18 02:04:52 ts/train.py:232 step:17K smpl:136K ep:596 epch:11.03 loss:0.026 grdn:0.226 lr:9.3e-05 updt_s:0.065 data_s:0.030
|
| 98 |
+
INFO 2025-11-18 02:05:11 ts/train.py:232 step:17K smpl:138K ep:603 epch:11.16 loss:0.028 grdn:0.228 lr:9.3e-05 updt_s:0.065 data_s:0.030
|
| 99 |
+
INFO 2025-11-18 02:05:29 ts/train.py:232 step:17K smpl:139K ep:610 epch:11.29 loss:0.027 grdn:0.227 lr:9.3e-05 updt_s:0.065 data_s:0.027
|
| 100 |
+
INFO 2025-11-18 02:05:48 ts/train.py:232 step:18K smpl:141K ep:617 epch:11.42 loss:0.027 grdn:0.228 lr:9.3e-05 updt_s:0.064 data_s:0.027
|
| 101 |
+
INFO 2025-11-18 02:06:06 ts/train.py:232 step:18K smpl:142K ep:624 epch:11.55 loss:0.026 grdn:0.226 lr:9.3e-05 updt_s:0.065 data_s:0.026
|
| 102 |
+
INFO 2025-11-18 02:06:24 ts/train.py:232 step:18K smpl:144K ep:631 epch:11.68 loss:0.031 grdn:0.247 lr:9.3e-05 updt_s:0.065 data_s:0.025
|
| 103 |
+
INFO 2025-11-18 02:06:43 ts/train.py:232 step:18K smpl:146K ep:638 epch:11.81 loss:0.028 grdn:0.228 lr:9.2e-05 updt_s:0.065 data_s:0.027
|
| 104 |
+
INFO 2025-11-18 02:07:04 ts/train.py:232 step:18K smpl:147K ep:645 epch:11.94 loss:0.029 grdn:0.233 lr:9.2e-05 updt_s:0.065 data_s:0.043
|
| 105 |
+
INFO 2025-11-18 02:07:23 ts/train.py:232 step:19K smpl:149K ep:652 epch:12.07 loss:0.028 grdn:0.234 lr:9.2e-05 updt_s:0.065 data_s:0.027
|
| 106 |
+
INFO 2025-11-18 02:07:41 ts/train.py:232 step:19K smpl:150K ep:659 epch:12.20 loss:0.027 grdn:0.219 lr:9.2e-05 updt_s:0.065 data_s:0.027
|
| 107 |
+
INFO 2025-11-18 02:08:00 ts/train.py:232 step:19K smpl:152K ep:666 epch:12.33 loss:0.029 grdn:0.235 lr:9.2e-05 updt_s:0.065 data_s:0.028
|
| 108 |
+
INFO 2025-11-18 02:08:18 ts/train.py:232 step:19K smpl:154K ep:673 epch:12.46 loss:0.026 grdn:0.225 lr:9.2e-05 updt_s:0.065 data_s:0.025
|
| 109 |
+
INFO 2025-11-18 02:08:35 ts/train.py:232 step:19K smpl:155K ep:680 epch:12.59 loss:0.026 grdn:0.219 lr:9.1e-05 updt_s:0.065 data_s:0.019
|
| 110 |
+
INFO 2025-11-18 02:08:55 ts/train.py:232 step:20K smpl:157K ep:687 epch:12.72 loss:0.026 grdn:0.223 lr:9.1e-05 updt_s:0.065 data_s:0.032
|
| 111 |
+
INFO 2025-11-18 02:09:12 ts/train.py:232 step:20K smpl:158K ep:694 epch:12.85 loss:0.025 grdn:0.219 lr:9.1e-05 updt_s:0.065 data_s:0.021
|
| 112 |
+
INFO 2025-11-18 02:09:29 ts/train.py:232 step:20K smpl:160K ep:701 epch:12.98 loss:0.028 grdn:0.234 lr:9.1e-05 updt_s:0.065 data_s:0.021
|
| 113 |
+
INFO 2025-11-18 02:09:29 ts/train.py:241 Checkpoint policy after step 20000
|
| 114 |
+
INFO 2025-11-18 02:10:21 ts/train.py:232 step:20K smpl:162K ep:708 epch:13.11 loss:0.029 grdn:0.238 lr:9.1e-05 updt_s:0.066 data_s:0.019
|
| 115 |
+
INFO 2025-11-18 02:10:38 ts/train.py:232 step:20K smpl:163K ep:715 epch:13.24 loss:0.026 grdn:0.219 lr:9.1e-05 updt_s:0.064 data_s:0.020
|
| 116 |
+
INFO 2025-11-18 02:10:55 ts/train.py:232 step:21K smpl:165K ep:722 epch:13.37 loss:0.027 grdn:0.223 lr:9.0e-05 updt_s:0.065 data_s:0.020
|
| 117 |
+
INFO 2025-11-18 02:11:13 ts/train.py:232 step:21K smpl:166K ep:729 epch:13.50 loss:0.026 grdn:0.215 lr:9.0e-05 updt_s:0.066 data_s:0.021
|
| 118 |
+
INFO 2025-11-18 02:11:31 ts/train.py:232 step:21K smpl:168K ep:736 epch:13.63 loss:0.026 grdn:0.216 lr:9.0e-05 updt_s:0.065 data_s:0.025
|
| 119 |
+
INFO 2025-11-18 02:11:49 ts/train.py:232 step:21K smpl:170K ep:743 epch:13.76 loss:0.025 grdn:0.224 lr:9.0e-05 updt_s:0.065 data_s:0.023
|
| 120 |
+
INFO 2025-11-18 02:12:06 ts/train.py:232 step:21K smpl:171K ep:750 epch:13.88 loss:0.026 grdn:0.218 lr:9.0e-05 updt_s:0.064 data_s:0.022
|
| 121 |
+
INFO 2025-11-18 02:12:24 ts/train.py:232 step:22K smpl:173K ep:757 epch:14.01 loss:0.026 grdn:0.221 lr:8.9e-05 updt_s:0.065 data_s:0.023
|
| 122 |
+
INFO 2025-11-18 02:12:41 ts/train.py:232 step:22K smpl:174K ep:764 epch:14.14 loss:0.027 grdn:0.223 lr:8.9e-05 updt_s:0.064 data_s:0.023
|
| 123 |
+
INFO 2025-11-18 02:12:59 ts/train.py:232 step:22K smpl:176K ep:771 epch:14.27 loss:0.026 grdn:0.224 lr:8.9e-05 updt_s:0.065 data_s:0.024
|
| 124 |
+
INFO 2025-11-18 02:13:17 ts/train.py:232 step:22K smpl:178K ep:778 epch:14.40 loss:0.027 grdn:0.228 lr:8.9e-05 updt_s:0.065 data_s:0.024
|
| 125 |
+
INFO 2025-11-18 02:13:34 ts/train.py:232 step:22K smpl:179K ep:785 epch:14.53 loss:0.026 grdn:0.228 lr:8.9e-05 updt_s:0.064 data_s:0.021
|
| 126 |
+
INFO 2025-11-18 02:13:53 ts/train.py:232 step:23K smpl:181K ep:792 epch:14.66 loss:0.024 grdn:0.215 lr:8.8e-05 updt_s:0.065 data_s:0.031
|
| 127 |
+
INFO 2025-11-18 02:14:12 ts/train.py:232 step:23K smpl:182K ep:799 epch:14.79 loss:0.025 grdn:0.214 lr:8.8e-05 updt_s:0.064 data_s:0.027
|
| 128 |
+
INFO 2025-11-18 02:14:31 ts/train.py:232 step:23K smpl:184K ep:806 epch:14.92 loss:0.024 grdn:0.209 lr:8.8e-05 updt_s:0.066 data_s:0.029
|
| 129 |
+
INFO 2025-11-18 02:14:49 ts/train.py:232 step:23K smpl:186K ep:813 epch:15.05 loss:0.022 grdn:0.196 lr:8.8e-05 updt_s:0.065 data_s:0.027
|
| 130 |
+
INFO 2025-11-18 02:15:08 ts/train.py:232 step:23K smpl:187K ep:820 epch:15.18 loss:0.024 grdn:0.211 lr:8.8e-05 updt_s:0.065 data_s:0.028
|
| 131 |
+
INFO 2025-11-18 02:15:26 ts/train.py:232 step:24K smpl:189K ep:827 epch:15.31 loss:0.023 grdn:0.207 lr:8.7e-05 updt_s:0.065 data_s:0.027
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| 132 |
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INFO 2025-11-18 02:15:45 ts/train.py:232 step:24K smpl:190K ep:834 epch:15.44 loss:0.024 grdn:0.209 lr:8.7e-05 updt_s:0.065 data_s:0.025
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| 133 |
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INFO 2025-11-18 02:16:03 ts/train.py:232 step:24K smpl:192K ep:841 epch:15.57 loss:0.026 grdn:0.225 lr:8.7e-05 updt_s:0.065 data_s:0.027
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| 134 |
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INFO 2025-11-18 02:16:22 ts/train.py:232 step:24K smpl:194K ep:848 epch:15.70 loss:0.024 grdn:0.210 lr:8.7e-05 updt_s:0.065 data_s:0.028
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| 135 |
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INFO 2025-11-18 02:16:40 ts/train.py:232 step:24K smpl:195K ep:855 epch:15.83 loss:0.023 grdn:0.210 lr:8.7e-05 updt_s:0.065 data_s:0.028
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| 136 |
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INFO 2025-11-18 02:16:59 ts/train.py:232 step:25K smpl:197K ep:862 epch:15.96 loss:0.023 grdn:0.205 lr:8.6e-05 updt_s:0.064 data_s:0.027
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| 137 |
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INFO 2025-11-18 02:17:20 ts/train.py:232 step:25K smpl:198K ep:869 epch:16.09 loss:0.023 grdn:0.208 lr:8.6e-05 updt_s:0.065 data_s:0.042
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| 138 |
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INFO 2025-11-18 02:17:39 ts/train.py:232 step:25K smpl:200K ep:876 epch:16.22 loss:0.024 grdn:0.218 lr:8.6e-05 updt_s:0.065 data_s:0.028
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| 139 |
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INFO 2025-11-18 02:17:57 ts/train.py:232 step:25K smpl:202K ep:883 epch:16.35 loss:0.024 grdn:0.208 lr:8.6e-05 updt_s:0.065 data_s:0.026
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| 140 |
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INFO 2025-11-18 02:18:15 ts/train.py:232 step:25K smpl:203K ep:890 epch:16.48 loss:0.025 grdn:0.223 lr:8.5e-05 updt_s:0.065 data_s:0.025
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| 141 |
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INFO 2025-11-18 02:18:33 ts/train.py:232 step:26K smpl:205K ep:897 epch:16.61 loss:0.026 grdn:0.227 lr:8.5e-05 updt_s:0.066 data_s:0.024
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| 142 |
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INFO 2025-11-18 02:18:51 ts/train.py:232 step:26K smpl:206K ep:904 epch:16.74 loss:0.023 grdn:0.202 lr:8.5e-05 updt_s:0.065 data_s:0.024
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| 143 |
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INFO 2025-11-18 02:19:09 ts/train.py:232 step:26K smpl:208K ep:911 epch:16.87 loss:0.023 grdn:0.206 lr:8.5e-05 updt_s:0.065 data_s:0.024
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| 144 |
+
INFO 2025-11-18 02:19:27 ts/train.py:232 step:26K smpl:210K ep:918 epch:17.00 loss:0.022 grdn:0.204 lr:8.5e-05 updt_s:0.065 data_s:0.023
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INFO 2025-11-18 02:19:45 ts/train.py:232 step:26K smpl:211K ep:925 epch:17.13 loss:0.023 grdn:0.205 lr:8.4e-05 updt_s:0.065 data_s:0.025
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INFO 2025-11-18 02:20:03 ts/train.py:232 step:27K smpl:213K ep:932 epch:17.26 loss:0.023 grdn:0.218 lr:8.4e-05 updt_s:0.065 data_s:0.023
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| 147 |
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INFO 2025-11-18 02:20:20 ts/train.py:232 step:27K smpl:214K ep:939 epch:17.39 loss:0.026 grdn:0.233 lr:8.4e-05 updt_s:0.064 data_s:0.023
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| 148 |
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INFO 2025-11-18 02:20:39 ts/train.py:232 step:27K smpl:216K ep:946 epch:17.52 loss:0.022 grdn:0.209 lr:8.4e-05 updt_s:0.065 data_s:0.026
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| 149 |
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INFO 2025-11-18 02:20:57 ts/train.py:232 step:27K smpl:218K ep:953 epch:17.65 loss:0.026 grdn:0.230 lr:8.3e-05 updt_s:0.065 data_s:0.027
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| 150 |
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INFO 2025-11-18 02:21:15 ts/train.py:232 step:27K smpl:219K ep:960 epch:17.78 loss:0.022 grdn:0.212 lr:8.3e-05 updt_s:0.065 data_s:0.023
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| 151 |
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INFO 2025-11-18 02:21:33 ts/train.py:232 step:28K smpl:221K ep:967 epch:17.91 loss:0.025 grdn:0.226 lr:8.3e-05 updt_s:0.064 data_s:0.024
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INFO 2025-11-18 02:21:51 ts/train.py:232 step:28K smpl:222K ep:974 epch:18.04 loss:0.025 grdn:0.224 lr:8.3e-05 updt_s:0.065 data_s:0.024
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| 153 |
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INFO 2025-11-18 02:22:09 ts/train.py:232 step:28K smpl:224K ep:981 epch:18.17 loss:0.022 grdn:0.199 lr:8.2e-05 updt_s:0.065 data_s:0.025
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INFO 2025-11-18 02:22:27 ts/train.py:232 step:28K smpl:226K ep:988 epch:18.30 loss:0.023 grdn:0.215 lr:8.2e-05 updt_s:0.066 data_s:0.024
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INFO 2025-11-18 02:22:44 ts/train.py:232 step:28K smpl:227K ep:995 epch:18.43 loss:0.022 grdn:0.209 lr:8.2e-05 updt_s:0.065 data_s:0.023
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| 156 |
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INFO 2025-11-18 02:23:03 ts/train.py:232 step:29K smpl:229K ep:1K epch:18.56 loss:0.023 grdn:0.209 lr:8.2e-05 updt_s:0.065 data_s:0.027
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| 157 |
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INFO 2025-11-18 02:23:21 ts/train.py:232 step:29K smpl:230K ep:1K epch:18.69 loss:0.024 grdn:0.232 lr:8.1e-05 updt_s:0.065 data_s:0.027
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| 158 |
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INFO 2025-11-18 02:23:39 ts/train.py:232 step:29K smpl:232K ep:1K epch:18.82 loss:0.026 grdn:0.223 lr:8.1e-05 updt_s:0.064 data_s:0.025
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| 159 |
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INFO 2025-11-18 02:23:58 ts/train.py:232 step:29K smpl:234K ep:1K epch:18.95 loss:0.024 grdn:0.219 lr:8.1e-05 updt_s:0.065 data_s:0.026
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| 160 |
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INFO 2025-11-18 02:24:16 ts/train.py:232 step:29K smpl:235K ep:1K epch:19.08 loss:0.022 grdn:0.211 lr:8.1e-05 updt_s:0.064 data_s:0.026
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| 161 |
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INFO 2025-11-18 02:24:35 ts/train.py:232 step:30K smpl:237K ep:1K epch:19.21 loss:0.024 grdn:0.225 lr:8.0e-05 updt_s:0.065 data_s:0.028
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| 162 |
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INFO 2025-11-18 02:24:53 ts/train.py:232 step:30K smpl:238K ep:1K epch:19.33 loss:0.021 grdn:0.210 lr:8.0e-05 updt_s:0.065 data_s:0.025
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| 163 |
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INFO 2025-11-18 02:25:11 ts/train.py:232 step:30K smpl:240K ep:1K epch:19.46 loss:0.022 grdn:0.213 lr:8.0e-05 updt_s:0.065 data_s:0.027
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| 164 |
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INFO 2025-11-18 02:25:30 ts/train.py:232 step:30K smpl:242K ep:1K epch:19.59 loss:0.022 grdn:0.210 lr:8.0e-05 updt_s:0.066 data_s:0.026
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| 165 |
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INFO 2025-11-18 02:25:47 ts/train.py:232 step:30K smpl:243K ep:1K epch:19.72 loss:0.022 grdn:0.208 lr:7.9e-05 updt_s:0.065 data_s:0.023
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| 166 |
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INFO 2025-11-18 02:26:06 ts/train.py:232 step:31K smpl:245K ep:1K epch:19.85 loss:0.020 grdn:0.207 lr:7.9e-05 updt_s:0.066 data_s:0.025
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| 167 |
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INFO 2025-11-18 02:26:24 ts/train.py:232 step:31K smpl:246K ep:1K epch:19.98 loss:0.021 grdn:0.202 lr:7.9e-05 updt_s:0.065 data_s:0.027
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| 168 |
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INFO 2025-11-18 02:26:43 ts/train.py:232 step:31K smpl:248K ep:1K epch:20.11 loss:0.021 grdn:0.202 lr:7.9e-05 updt_s:0.065 data_s:0.026
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| 169 |
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INFO 2025-11-18 02:27:00 ts/train.py:232 step:31K smpl:250K ep:1K epch:20.24 loss:0.023 grdn:0.217 lr:7.8e-05 updt_s:0.066 data_s:0.023
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| 170 |
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INFO 2025-11-18 02:27:21 ts/train.py:232 step:31K smpl:251K ep:1K epch:20.37 loss:0.024 grdn:0.222 lr:7.8e-05 updt_s:0.066 data_s:0.036
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| 171 |
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INFO 2025-11-18 02:27:42 ts/train.py:232 step:32K smpl:253K ep:1K epch:20.50 loss:0.020 grdn:0.198 lr:7.8e-05 updt_s:0.065 data_s:0.041
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| 172 |
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INFO 2025-11-18 02:28:00 ts/train.py:232 step:32K smpl:254K ep:1K epch:20.63 loss:0.024 grdn:0.223 lr:7.8e-05 updt_s:0.065 data_s:0.025
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| 173 |
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INFO 2025-11-18 02:28:18 ts/train.py:232 step:32K smpl:256K ep:1K epch:20.76 loss:0.023 grdn:0.214 lr:7.7e-05 updt_s:0.066 data_s:0.023
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| 174 |
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INFO 2025-11-18 02:28:36 ts/train.py:232 step:32K smpl:258K ep:1K epch:20.89 loss:0.022 grdn:0.212 lr:7.7e-05 updt_s:0.066 data_s:0.025
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| 175 |
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INFO 2025-11-18 02:28:55 ts/train.py:232 step:32K smpl:259K ep:1K epch:21.02 loss:0.023 grdn:0.216 lr:7.7e-05 updt_s:0.065 data_s:0.026
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| 176 |
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INFO 2025-11-18 02:29:13 ts/train.py:232 step:33K smpl:261K ep:1K epch:21.15 loss:0.023 grdn:0.216 lr:7.7e-05 updt_s:0.065 data_s:0.025
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| 177 |
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INFO 2025-11-18 02:29:30 ts/train.py:232 step:33K smpl:262K ep:1K epch:21.28 loss:0.020 grdn:0.205 lr:7.6e-05 updt_s:0.065 data_s:0.021
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| 178 |
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INFO 2025-11-18 02:29:49 ts/train.py:232 step:33K smpl:264K ep:1K epch:21.41 loss:0.021 grdn:0.216 lr:7.6e-05 updt_s:0.065 data_s:0.026
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| 179 |
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INFO 2025-11-18 02:30:07 ts/train.py:232 step:33K smpl:266K ep:1K epch:21.54 loss:0.023 grdn:0.228 lr:7.6e-05 updt_s:0.065 data_s:0.024
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| 180 |
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INFO 2025-11-18 02:30:25 ts/train.py:232 step:33K smpl:267K ep:1K epch:21.67 loss:0.019 grdn:0.198 lr:7.5e-05 updt_s:0.065 data_s:0.024
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| 181 |
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INFO 2025-11-18 02:30:43 ts/train.py:232 step:34K smpl:269K ep:1K epch:21.80 loss:0.023 grdn:0.231 lr:7.5e-05 updt_s:0.065 data_s:0.025
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| 182 |
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INFO 2025-11-18 02:31:01 ts/train.py:232 step:34K smpl:270K ep:1K epch:21.93 loss:0.023 grdn:0.218 lr:7.5e-05 updt_s:0.065 data_s:0.026
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| 183 |
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INFO 2025-11-18 02:31:19 ts/train.py:232 step:34K smpl:272K ep:1K epch:22.06 loss:0.022 grdn:0.218 lr:7.5e-05 updt_s:0.064 data_s:0.023
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| 184 |
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INFO 2025-11-18 02:31:37 ts/train.py:232 step:34K smpl:274K ep:1K epch:22.19 loss:0.021 grdn:0.218 lr:7.4e-05 updt_s:0.066 data_s:0.025
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INFO 2025-11-18 02:31:55 ts/train.py:232 step:34K smpl:275K ep:1K epch:22.32 loss:0.021 grdn:0.213 lr:7.4e-05 updt_s:0.065 data_s:0.023
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INFO 2025-11-18 02:32:12 ts/train.py:232 step:35K smpl:277K ep:1K epch:22.45 loss:0.020 grdn:0.208 lr:7.4e-05 updt_s:0.065 data_s:0.023
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INFO 2025-11-18 02:32:30 ts/train.py:232 step:35K smpl:278K ep:1K epch:22.58 loss:0.023 grdn:0.222 lr:7.4e-05 updt_s:0.065 data_s:0.024
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INFO 2025-11-18 02:32:48 ts/train.py:232 step:35K smpl:280K ep:1K epch:22.71 loss:0.020 grdn:0.198 lr:7.3e-05 updt_s:0.065 data_s:0.024
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INFO 2025-11-18 02:33:06 ts/train.py:232 step:35K smpl:282K ep:1K epch:22.84 loss:0.020 grdn:0.211 lr:7.3e-05 updt_s:0.065 data_s:0.024
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INFO 2025-11-18 02:33:24 ts/train.py:232 step:35K smpl:283K ep:1K epch:22.97 loss:0.021 grdn:0.211 lr:7.3e-05 updt_s:0.065 data_s:0.024
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INFO 2025-11-18 02:33:43 ts/train.py:232 step:36K smpl:285K ep:1K epch:23.10 loss:0.020 grdn:0.209 lr:7.2e-05 updt_s:0.066 data_s:0.026
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INFO 2025-11-18 02:34:00 ts/train.py:232 step:36K smpl:286K ep:1K epch:23.23 loss:0.020 grdn:0.209 lr:7.2e-05 updt_s:0.064 data_s:0.023
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INFO 2025-11-18 02:34:21 ts/train.py:232 step:36K smpl:288K ep:1K epch:23.36 loss:0.019 grdn:0.195 lr:7.2e-05 updt_s:0.065 data_s:0.040
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INFO 2025-11-18 02:34:40 ts/train.py:232 step:36K smpl:290K ep:1K epch:23.49 loss:0.020 grdn:0.204 lr:7.2e-05 updt_s:0.065 data_s:0.026
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INFO 2025-11-18 02:34:58 ts/train.py:232 step:36K smpl:291K ep:1K epch:23.62 loss:0.021 grdn:0.215 lr:7.1e-05 updt_s:0.064 data_s:0.026
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INFO 2025-11-18 02:35:16 ts/train.py:232 step:37K smpl:293K ep:1K epch:23.75 loss:0.021 grdn:0.220 lr:7.1e-05 updt_s:0.065 data_s:0.028
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INFO 2025-11-18 02:35:35 ts/train.py:232 step:37K smpl:294K ep:1K epch:23.88 loss:0.020 grdn:0.210 lr:7.1e-05 updt_s:0.065 data_s:0.027
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INFO 2025-11-18 02:35:54 ts/train.py:232 step:37K smpl:296K ep:1K epch:24.01 loss:0.022 grdn:0.223 lr:7.0e-05 updt_s:0.065 data_s:0.028
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INFO 2025-11-18 02:36:12 ts/train.py:232 step:37K smpl:298K ep:1K epch:24.14 loss:0.021 grdn:0.220 lr:7.0e-05 updt_s:0.065 data_s:0.027
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INFO 2025-11-18 02:36:32 ts/train.py:232 step:37K smpl:299K ep:1K epch:24.27 loss:0.019 grdn:0.207 lr:7.0e-05 updt_s:0.064 data_s:0.037
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INFO 2025-11-18 02:36:51 ts/train.py:232 step:38K smpl:301K ep:1K epch:24.40 loss:0.018 grdn:0.196 lr:7.0e-05 updt_s:0.065 data_s:0.030
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INFO 2025-11-18 02:37:10 ts/train.py:232 step:38K smpl:302K ep:1K epch:24.53 loss:0.019 grdn:0.209 lr:6.9e-05 updt_s:0.064 data_s:0.028
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INFO 2025-11-18 02:37:29 ts/train.py:232 step:38K smpl:304K ep:1K epch:24.66 loss:0.020 grdn:0.207 lr:6.9e-05 updt_s:0.065 data_s:0.028
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INFO 2025-11-18 02:37:47 ts/train.py:232 step:38K smpl:306K ep:1K epch:24.79 loss:0.019 grdn:0.210 lr:6.9e-05 updt_s:0.064 data_s:0.027
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INFO 2025-11-18 02:38:08 ts/train.py:232 step:38K smpl:307K ep:1K epch:24.91 loss:0.020 grdn:0.217 lr:6.8e-05 updt_s:0.064 data_s:0.040
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INFO 2025-11-18 02:38:26 ts/train.py:232 step:39K smpl:309K ep:1K epch:25.04 loss:0.021 grdn:0.219 lr:6.8e-05 updt_s:0.064 data_s:0.024
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INFO 2025-11-18 02:38:43 ts/train.py:232 step:39K smpl:310K ep:1K epch:25.17 loss:0.020 grdn:0.212 lr:6.8e-05 updt_s:0.064 data_s:0.022
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INFO 2025-11-18 02:39:06 ts/train.py:232 step:39K smpl:312K ep:1K epch:25.30 loss:0.021 grdn:0.219 lr:6.8e-05 updt_s:0.066 data_s:0.049
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INFO 2025-11-18 02:39:24 ts/train.py:232 step:39K smpl:314K ep:1K epch:25.43 loss:0.020 grdn:0.209 lr:6.7e-05 updt_s:0.064 data_s:0.025
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INFO 2025-11-18 02:39:42 ts/train.py:232 step:39K smpl:315K ep:1K epch:25.56 loss:0.022 grdn:0.237 lr:6.7e-05 updt_s:0.064 data_s:0.026
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INFO 2025-11-18 02:40:00 ts/train.py:232 step:40K smpl:317K ep:1K epch:25.69 loss:0.019 grdn:0.212 lr:6.7e-05 updt_s:0.064 data_s:0.025
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INFO 2025-11-18 02:40:18 ts/train.py:232 step:40K smpl:318K ep:1K epch:25.82 loss:0.019 grdn:0.210 lr:6.6e-05 updt_s:0.064 data_s:0.025
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INFO 2025-11-18 02:40:36 ts/train.py:232 step:40K smpl:320K ep:1K epch:25.95 loss:0.021 grdn:0.222 lr:6.6e-05 updt_s:0.065 data_s:0.025
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INFO 2025-11-18 02:40:36 ts/train.py:241 Checkpoint policy after step 40000
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INFO 2025-11-18 02:41:50 ts/train.py:232 step:40K smpl:322K ep:1K epch:26.08 loss:0.020 grdn:0.221 lr:6.6e-05 updt_s:0.065 data_s:0.022
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INFO 2025-11-18 02:42:10 ts/train.py:232 step:40K smpl:323K ep:1K epch:26.21 loss:0.020 grdn:0.224 lr:6.5e-05 updt_s:0.065 data_s:0.034
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INFO 2025-11-18 02:42:29 ts/train.py:232 step:41K smpl:325K ep:1K epch:26.34 loss:0.019 grdn:0.207 lr:6.5e-05 updt_s:0.065 data_s:0.025
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INFO 2025-11-18 02:42:46 ts/train.py:232 step:41K smpl:326K ep:1K epch:26.47 loss:0.020 grdn:0.225 lr:6.5e-05 updt_s:0.065 data_s:0.025
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INFO 2025-11-18 02:43:05 ts/train.py:232 step:41K smpl:328K ep:1K epch:26.60 loss:0.021 grdn:0.224 lr:6.5e-05 updt_s:0.065 data_s:0.025
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INFO 2025-11-18 02:43:23 ts/train.py:232 step:41K smpl:330K ep:1K epch:26.73 loss:0.019 grdn:0.208 lr:6.4e-05 updt_s:0.064 data_s:0.027
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INFO 2025-11-18 02:43:41 ts/train.py:232 step:41K smpl:331K ep:1K epch:26.86 loss:0.019 grdn:0.213 lr:6.4e-05 updt_s:0.065 data_s:0.023
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INFO 2025-11-18 02:43:59 ts/train.py:232 step:42K smpl:333K ep:1K epch:26.99 loss:0.020 grdn:0.216 lr:6.4e-05 updt_s:0.065 data_s:0.026
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INFO 2025-11-18 02:44:17 ts/train.py:232 step:42K smpl:334K ep:1K epch:27.12 loss:0.019 grdn:0.214 lr:6.3e-05 updt_s:0.065 data_s:0.024
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INFO 2025-11-18 02:44:38 ts/train.py:232 step:42K smpl:336K ep:1K epch:27.25 loss:0.019 grdn:0.205 lr:6.3e-05 updt_s:0.065 data_s:0.039
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INFO 2025-11-18 02:44:56 ts/train.py:232 step:42K smpl:338K ep:1K epch:27.38 loss:0.018 grdn:0.206 lr:6.3e-05 updt_s:0.065 data_s:0.028
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INFO 2025-11-18 02:45:15 ts/train.py:232 step:42K smpl:339K ep:1K epch:27.51 loss:0.019 grdn:0.212 lr:6.2e-05 updt_s:0.065 data_s:0.027
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INFO 2025-11-18 02:45:33 ts/train.py:232 step:43K smpl:341K ep:1K epch:27.64 loss:0.021 grdn:0.224 lr:6.2e-05 updt_s:0.065 data_s:0.027
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INFO 2025-11-18 02:45:52 ts/train.py:232 step:43K smpl:342K ep:1K epch:27.77 loss:0.020 grdn:0.217 lr:6.2e-05 updt_s:0.065 data_s:0.028
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INFO 2025-11-18 02:46:11 ts/train.py:232 step:43K smpl:344K ep:2K epch:27.90 loss:0.019 grdn:0.213 lr:6.1e-05 updt_s:0.065 data_s:0.028
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INFO 2025-11-18 02:46:29 ts/train.py:232 step:43K smpl:346K ep:2K epch:28.03 loss:0.019 grdn:0.213 lr:6.1e-05 updt_s:0.065 data_s:0.028
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INFO 2025-11-18 02:46:47 ts/train.py:232 step:43K smpl:347K ep:2K epch:28.16 loss:0.017 grdn:0.207 lr:6.1e-05 updt_s:0.064 data_s:0.025
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INFO 2025-11-18 02:47:06 ts/train.py:232 step:44K smpl:349K ep:2K epch:28.29 loss:0.017 grdn:0.202 lr:6.1e-05 updt_s:0.065 data_s:0.028
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INFO 2025-11-18 02:47:25 ts/train.py:232 step:44K smpl:350K ep:2K epch:28.42 loss:0.018 grdn:0.212 lr:6.0e-05 updt_s:0.065 data_s:0.028
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INFO 2025-11-18 02:47:43 ts/train.py:232 step:44K smpl:352K ep:2K epch:28.55 loss:0.019 grdn:0.214 lr:6.0e-05 updt_s:0.064 data_s:0.027
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INFO 2025-11-18 02:48:05 ts/train.py:232 step:44K smpl:354K ep:2K epch:28.68 loss:0.019 grdn:0.220 lr:6.0e-05 updt_s:0.065 data_s:0.042
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INFO 2025-11-18 02:48:23 ts/train.py:232 step:44K smpl:355K ep:2K epch:28.81 loss:0.020 grdn:0.222 lr:5.9e-05 updt_s:0.064 data_s:0.026
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INFO 2025-11-18 02:48:41 ts/train.py:232 step:45K smpl:357K ep:2K epch:28.94 loss:0.018 grdn:0.207 lr:5.9e-05 updt_s:0.065 data_s:0.026
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INFO 2025-11-18 02:48:58 ts/train.py:232 step:45K smpl:358K ep:2K epch:29.07 loss:0.019 grdn:0.220 lr:5.9e-05 updt_s:0.065 data_s:0.022
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INFO 2025-11-18 02:49:19 ts/train.py:232 step:45K smpl:360K ep:2K epch:29.20 loss:0.022 grdn:0.243 lr:5.8e-05 updt_s:0.065 data_s:0.039
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INFO 2025-11-18 02:49:37 ts/train.py:232 step:45K smpl:362K ep:2K epch:29.33 loss:0.020 grdn:0.220 lr:5.8e-05 updt_s:0.065 data_s:0.025
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INFO 2025-11-18 02:49:55 ts/train.py:232 step:45K smpl:363K ep:2K epch:29.46 loss:0.019 grdn:0.211 lr:5.8e-05 updt_s:0.065 data_s:0.024
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INFO 2025-11-18 02:50:13 ts/train.py:232 step:46K smpl:365K ep:2K epch:29.59 loss:0.018 grdn:0.218 lr:5.7e-05 updt_s:0.065 data_s:0.025
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INFO 2025-11-18 02:50:31 ts/train.py:232 step:46K smpl:366K ep:2K epch:29.72 loss:0.019 grdn:0.217 lr:5.7e-05 updt_s:0.065 data_s:0.025
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INFO 2025-11-18 02:50:49 ts/train.py:232 step:46K smpl:368K ep:2K epch:29.85 loss:0.019 grdn:0.214 lr:5.7e-05 updt_s:0.064 data_s:0.023
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INFO 2025-11-18 02:51:06 ts/train.py:232 step:46K smpl:370K ep:2K epch:29.98 loss:0.019 grdn:0.218 lr:5.7e-05 updt_s:0.064 data_s:0.023
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INFO 2025-11-18 02:51:26 ts/train.py:232 step:46K smpl:371K ep:2K epch:30.11 loss:0.018 grdn:0.199 lr:5.6e-05 updt_s:0.065 data_s:0.032
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INFO 2025-11-18 02:51:44 ts/train.py:232 step:47K smpl:373K ep:2K epch:30.24 loss:0.018 grdn:0.207 lr:5.6e-05 updt_s:0.064 data_s:0.023
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INFO 2025-11-18 02:52:02 ts/train.py:232 step:47K smpl:374K ep:2K epch:30.36 loss:0.018 grdn:0.215 lr:5.6e-05 updt_s:0.065 data_s:0.025
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INFO 2025-11-18 02:52:20 ts/train.py:232 step:47K smpl:376K ep:2K epch:30.49 loss:0.018 grdn:0.221 lr:5.5e-05 updt_s:0.064 data_s:0.029
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INFO 2025-11-18 02:52:39 ts/train.py:232 step:47K smpl:378K ep:2K epch:30.62 loss:0.018 grdn:0.209 lr:5.5e-05 updt_s:0.065 data_s:0.028
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INFO 2025-11-18 02:52:57 ts/train.py:232 step:47K smpl:379K ep:2K epch:30.75 loss:0.018 grdn:0.218 lr:5.5e-05 updt_s:0.065 data_s:0.024
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INFO 2025-11-18 02:53:16 ts/train.py:232 step:48K smpl:381K ep:2K epch:30.88 loss:0.018 grdn:0.216 lr:5.4e-05 updt_s:0.065 data_s:0.027
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INFO 2025-11-18 02:53:33 ts/train.py:232 step:48K smpl:382K ep:2K epch:31.01 loss:0.019 grdn:0.221 lr:5.4e-05 updt_s:0.066 data_s:0.023
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INFO 2025-11-18 02:53:53 ts/train.py:232 step:48K smpl:384K ep:2K epch:31.14 loss:0.018 grdn:0.207 lr:5.4e-05 updt_s:0.064 data_s:0.031
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INFO 2025-11-18 02:54:10 ts/train.py:232 step:48K smpl:386K ep:2K epch:31.27 loss:0.017 grdn:0.207 lr:5.3e-05 updt_s:0.065 data_s:0.022
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INFO 2025-11-18 02:54:28 ts/train.py:232 step:48K smpl:387K ep:2K epch:31.40 loss:0.019 grdn:0.221 lr:5.3e-05 updt_s:0.065 data_s:0.024
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INFO 2025-11-18 02:54:46 ts/train.py:232 step:49K smpl:389K ep:2K epch:31.53 loss:0.019 grdn:0.218 lr:5.3e-05 updt_s:0.065 data_s:0.024
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INFO 2025-11-18 02:55:04 ts/train.py:232 step:49K smpl:390K ep:2K epch:31.66 loss:0.018 grdn:0.212 lr:5.2e-05 updt_s:0.065 data_s:0.023
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INFO 2025-11-18 02:55:21 ts/train.py:232 step:49K smpl:392K ep:2K epch:31.79 loss:0.019 grdn:0.216 lr:5.2e-05 updt_s:0.064 data_s:0.022
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INFO 2025-11-18 02:55:39 ts/train.py:232 step:49K smpl:394K ep:2K epch:31.92 loss:0.016 grdn:0.199 lr:5.2e-05 updt_s:0.065 data_s:0.023
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INFO 2025-11-18 02:55:57 ts/train.py:232 step:49K smpl:395K ep:2K epch:32.05 loss:0.018 grdn:0.207 lr:5.1e-05 updt_s:0.065 data_s:0.026
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INFO 2025-11-18 02:56:15 ts/train.py:232 step:50K smpl:397K ep:2K epch:32.18 loss:0.017 grdn:0.202 lr:5.1e-05 updt_s:0.065 data_s:0.026
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INFO 2025-11-18 02:56:34 ts/train.py:232 step:50K smpl:398K ep:2K epch:32.31 loss:0.017 grdn:0.209 lr:5.1e-05 updt_s:0.064 data_s:0.027
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INFO 2025-11-18 02:56:52 ts/train.py:232 step:50K smpl:400K ep:2K epch:32.44 loss:0.017 grdn:0.214 lr:5.1e-05 updt_s:0.065 data_s:0.028
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INFO 2025-11-18 02:57:11 ts/train.py:232 step:50K smpl:402K ep:2K epch:32.57 loss:0.018 grdn:0.216 lr:5.0e-05 updt_s:0.064 data_s:0.027
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INFO 2025-11-18 02:57:30 ts/train.py:232 step:50K smpl:403K ep:2K epch:32.70 loss:0.016 grdn:0.201 lr:5.0e-05 updt_s:0.066 data_s:0.027
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INFO 2025-11-18 02:57:48 ts/train.py:232 step:51K smpl:405K ep:2K epch:32.83 loss:0.018 grdn:0.210 lr:5.0e-05 updt_s:0.065 data_s:0.026
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INFO 2025-11-18 02:58:05 ts/train.py:232 step:51K smpl:406K ep:2K epch:32.96 loss:0.016 grdn:0.198 lr:4.9e-05 updt_s:0.065 data_s:0.023
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INFO 2025-11-18 02:58:27 ts/train.py:232 step:51K smpl:408K ep:2K epch:33.09 loss:0.018 grdn:0.219 lr:4.9e-05 updt_s:0.065 data_s:0.043
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INFO 2025-11-18 02:58:46 ts/train.py:232 step:51K smpl:410K ep:2K epch:33.22 loss:0.016 grdn:0.203 lr:4.9e-05 updt_s:0.064 data_s:0.027
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INFO 2025-11-18 02:59:04 ts/train.py:232 step:51K smpl:411K ep:2K epch:33.35 loss:0.016 grdn:0.198 lr:4.8e-05 updt_s:0.065 data_s:0.025
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INFO 2025-11-18 02:59:22 ts/train.py:232 step:52K smpl:413K ep:2K epch:33.48 loss:0.017 grdn:0.220 lr:4.8e-05 updt_s:0.065 data_s:0.026
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INFO 2025-11-18 02:59:40 ts/train.py:232 step:52K smpl:414K ep:2K epch:33.61 loss:0.017 grdn:0.210 lr:4.8e-05 updt_s:0.064 data_s:0.025
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INFO 2025-11-18 02:59:58 ts/train.py:232 step:52K smpl:416K ep:2K epch:33.74 loss:0.017 grdn:0.207 lr:4.7e-05 updt_s:0.065 data_s:0.025
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INFO 2025-11-18 03:00:15 ts/train.py:232 step:52K smpl:418K ep:2K epch:33.87 loss:0.019 grdn:0.227 lr:4.7e-05 updt_s:0.064 data_s:0.022
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INFO 2025-11-18 03:00:35 ts/train.py:232 step:52K smpl:419K ep:2K epch:34.00 loss:0.017 grdn:0.209 lr:4.7e-05 updt_s:0.065 data_s:0.034
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INFO 2025-11-18 03:00:53 ts/train.py:232 step:53K smpl:421K ep:2K epch:34.13 loss:0.017 grdn:0.208 lr:4.6e-05 updt_s:0.065 data_s:0.024
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INFO 2025-11-18 03:01:11 ts/train.py:232 step:53K smpl:422K ep:2K epch:34.26 loss:0.017 grdn:0.211 lr:4.6e-05 updt_s:0.065 data_s:0.024
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INFO 2025-11-18 03:01:29 ts/train.py:232 step:53K smpl:424K ep:2K epch:34.39 loss:0.017 grdn:0.210 lr:4.6e-05 updt_s:0.065 data_s:0.025
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INFO 2025-11-18 03:01:47 ts/train.py:232 step:53K smpl:426K ep:2K epch:34.52 loss:0.016 grdn:0.201 lr:4.6e-05 updt_s:0.065 data_s:0.026
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INFO 2025-11-18 03:02:05 ts/train.py:232 step:53K smpl:427K ep:2K epch:34.65 loss:0.018 grdn:0.222 lr:4.5e-05 updt_s:0.065 data_s:0.024
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INFO 2025-11-18 03:02:23 ts/train.py:232 step:54K smpl:429K ep:2K epch:34.78 loss:0.017 grdn:0.208 lr:4.5e-05 updt_s:0.064 data_s:0.024
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INFO 2025-11-18 03:02:40 ts/train.py:232 step:54K smpl:430K ep:2K epch:34.91 loss:0.017 grdn:0.213 lr:4.5e-05 updt_s:0.065 data_s:0.023
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INFO 2025-11-18 03:02:59 ts/train.py:232 step:54K smpl:432K ep:2K epch:35.04 loss:0.018 grdn:0.213 lr:4.4e-05 updt_s:0.064 data_s:0.026
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INFO 2025-11-18 03:03:16 ts/train.py:232 step:54K smpl:434K ep:2K epch:35.17 loss:0.015 grdn:0.195 lr:4.4e-05 updt_s:0.064 data_s:0.025
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INFO 2025-11-18 03:03:35 ts/train.py:232 step:54K smpl:435K ep:2K epch:35.30 loss:0.015 grdn:0.195 lr:4.4e-05 updt_s:0.065 data_s:0.028
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INFO 2025-11-18 03:03:53 ts/train.py:232 step:55K smpl:437K ep:2K epch:35.43 loss:0.016 grdn:0.211 lr:4.3e-05 updt_s:0.065 data_s:0.025
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INFO 2025-11-18 03:04:11 ts/train.py:232 step:55K smpl:438K ep:2K epch:35.56 loss:0.017 grdn:0.214 lr:4.3e-05 updt_s:0.065 data_s:0.025
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INFO 2025-11-18 03:04:29 ts/train.py:232 step:55K smpl:440K ep:2K epch:35.69 loss:0.017 grdn:0.216 lr:4.3e-05 updt_s:0.065 data_s:0.026
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INFO 2025-11-18 03:04:47 ts/train.py:232 step:55K smpl:442K ep:2K epch:35.82 loss:0.017 grdn:0.211 lr:4.2e-05 updt_s:0.065 data_s:0.024
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INFO 2025-11-18 03:05:06 ts/train.py:232 step:55K smpl:443K ep:2K epch:35.94 loss:0.017 grdn:0.211 lr:4.2e-05 updt_s:0.065 data_s:0.026
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INFO 2025-11-18 03:05:24 ts/train.py:232 step:56K smpl:445K ep:2K epch:36.07 loss:0.017 grdn:0.210 lr:4.2e-05 updt_s:0.065 data_s:0.025
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INFO 2025-11-18 03:05:43 ts/train.py:232 step:56K smpl:446K ep:2K epch:36.20 loss:0.017 grdn:0.208 lr:4.1e-05 updt_s:0.065 data_s:0.030
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INFO 2025-11-18 03:06:01 ts/train.py:232 step:56K smpl:448K ep:2K epch:36.33 loss:0.017 grdn:0.214 lr:4.1e-05 updt_s:0.065 data_s:0.026
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INFO 2025-11-18 03:06:19 ts/train.py:232 step:56K smpl:450K ep:2K epch:36.46 loss:0.017 grdn:0.218 lr:4.1e-05 updt_s:0.065 data_s:0.026
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INFO 2025-11-18 03:06:38 ts/train.py:232 step:56K smpl:451K ep:2K epch:36.59 loss:0.016 grdn:0.215 lr:4.1e-05 updt_s:0.065 data_s:0.026
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INFO 2025-11-18 03:06:56 ts/train.py:232 step:57K smpl:453K ep:2K epch:36.72 loss:0.017 grdn:0.214 lr:4.0e-05 updt_s:0.064 data_s:0.027
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INFO 2025-11-18 03:07:14 ts/train.py:232 step:57K smpl:454K ep:2K epch:36.85 loss:0.017 grdn:0.213 lr:4.0e-05 updt_s:0.065 data_s:0.028
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INFO 2025-11-18 03:07:33 ts/train.py:232 step:57K smpl:456K ep:2K epch:36.98 loss:0.016 grdn:0.205 lr:4.0e-05 updt_s:0.065 data_s:0.025
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INFO 2025-11-18 03:07:51 ts/train.py:232 step:57K smpl:458K ep:2K epch:37.11 loss:0.015 grdn:0.196 lr:3.9e-05 updt_s:0.065 data_s:0.026
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INFO 2025-11-18 03:08:09 ts/train.py:232 step:57K smpl:459K ep:2K epch:37.24 loss:0.015 grdn:0.203 lr:3.9e-05 updt_s:0.065 data_s:0.025
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INFO 2025-11-18 03:08:30 ts/train.py:232 step:58K smpl:461K ep:2K epch:37.37 loss:0.017 grdn:0.220 lr:3.9e-05 updt_s:0.065 data_s:0.040
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INFO 2025-11-18 03:08:48 ts/train.py:232 step:58K smpl:462K ep:2K epch:37.50 loss:0.017 grdn:0.207 lr:3.8e-05 updt_s:0.064 data_s:0.022
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INFO 2025-11-18 03:09:06 ts/train.py:232 step:58K smpl:464K ep:2K epch:37.63 loss:0.016 grdn:0.212 lr:3.8e-05 updt_s:0.065 data_s:0.024
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INFO 2025-11-18 03:09:23 ts/train.py:232 step:58K smpl:466K ep:2K epch:37.76 loss:0.015 grdn:0.196 lr:3.8e-05 updt_s:0.064 data_s:0.024
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INFO 2025-11-18 03:09:42 ts/train.py:232 step:58K smpl:467K ep:2K epch:37.89 loss:0.015 grdn:0.203 lr:3.7e-05 updt_s:0.065 data_s:0.027
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INFO 2025-11-18 03:10:00 ts/train.py:232 step:59K smpl:469K ep:2K epch:38.02 loss:0.016 grdn:0.207 lr:3.7e-05 updt_s:0.065 data_s:0.026
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INFO 2025-11-18 03:10:18 ts/train.py:232 step:59K smpl:470K ep:2K epch:38.15 loss:0.016 grdn:0.205 lr:3.7e-05 updt_s:0.065 data_s:0.026
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INFO 2025-11-18 03:10:37 ts/train.py:232 step:59K smpl:472K ep:2K epch:38.28 loss:0.015 grdn:0.203 lr:3.7e-05 updt_s:0.065 data_s:0.026
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INFO 2025-11-18 03:10:56 ts/train.py:232 step:59K smpl:474K ep:2K epch:38.41 loss:0.015 grdn:0.199 lr:3.6e-05 updt_s:0.065 data_s:0.029
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INFO 2025-11-18 03:11:14 ts/train.py:232 step:59K smpl:475K ep:2K epch:38.54 loss:0.016 grdn:0.213 lr:3.6e-05 updt_s:0.065 data_s:0.026
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INFO 2025-11-18 03:11:32 ts/train.py:232 step:60K smpl:477K ep:2K epch:38.67 loss:0.016 grdn:0.212 lr:3.6e-05 updt_s:0.065 data_s:0.026
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INFO 2025-11-18 03:11:50 ts/train.py:232 step:60K smpl:478K ep:2K epch:38.80 loss:0.016 grdn:0.213 lr:3.5e-05 updt_s:0.064 data_s:0.025
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INFO 2025-11-18 03:12:09 ts/train.py:232 step:60K smpl:480K ep:2K epch:38.93 loss:0.015 grdn:0.200 lr:3.5e-05 updt_s:0.065 data_s:0.028
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INFO 2025-11-18 03:12:09 ts/train.py:241 Checkpoint policy after step 60000
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INFO 2025-11-18 03:12:53 ts/train.py:232 step:60K smpl:482K ep:2K epch:39.06 loss:0.017 grdn:0.228 lr:3.5e-05 updt_s:0.064 data_s:0.027
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INFO 2025-11-18 03:13:12 ts/train.py:232 step:60K smpl:483K ep:2K epch:39.19 loss:0.015 grdn:0.210 lr:3.4e-05 updt_s:0.065 data_s:0.029
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INFO 2025-11-18 03:13:31 ts/train.py:232 step:61K smpl:485K ep:2K epch:39.32 loss:0.015 grdn:0.210 lr:3.4e-05 updt_s:0.065 data_s:0.027
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INFO 2025-11-18 03:13:49 ts/train.py:232 step:61K smpl:486K ep:2K epch:39.45 loss:0.017 grdn:0.221 lr:3.4e-05 updt_s:0.065 data_s:0.028
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INFO 2025-11-18 03:14:08 ts/train.py:232 step:61K smpl:488K ep:2K epch:39.58 loss:0.015 grdn:0.207 lr:3.4e-05 updt_s:0.064 data_s:0.027
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INFO 2025-11-18 03:14:26 ts/train.py:232 step:61K smpl:490K ep:2K epch:39.71 loss:0.016 grdn:0.204 lr:3.3e-05 updt_s:0.065 data_s:0.026
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INFO 2025-11-18 03:14:45 ts/train.py:232 step:61K smpl:491K ep:2K epch:39.84 loss:0.015 grdn:0.207 lr:3.3e-05 updt_s:0.065 data_s:0.030
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INFO 2025-11-18 03:15:03 ts/train.py:232 step:62K smpl:493K ep:2K epch:39.97 loss:0.015 grdn:0.200 lr:3.3e-05 updt_s:0.065 data_s:0.026
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INFO 2025-11-18 03:15:22 ts/train.py:232 step:62K smpl:494K ep:2K epch:40.10 loss:0.015 grdn:0.206 lr:3.2e-05 updt_s:0.065 data_s:0.028
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INFO 2025-11-18 03:15:41 ts/train.py:232 step:62K smpl:496K ep:2K epch:40.23 loss:0.015 grdn:0.202 lr:3.2e-05 updt_s:0.065 data_s:0.028
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INFO 2025-11-18 03:15:59 ts/train.py:232 step:62K smpl:498K ep:2K epch:40.36 loss:0.014 grdn:0.196 lr:3.2e-05 updt_s:0.064 data_s:0.027
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INFO 2025-11-18 03:16:18 ts/train.py:232 step:62K smpl:499K ep:2K epch:40.49 loss:0.015 grdn:0.201 lr:3.1e-05 updt_s:0.065 data_s:0.026
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INFO 2025-11-18 03:16:36 ts/train.py:232 step:63K smpl:501K ep:2K epch:40.62 loss:0.014 grdn:0.201 lr:3.1e-05 updt_s:0.064 data_s:0.027
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INFO 2025-11-18 03:16:54 ts/train.py:232 step:63K smpl:502K ep:2K epch:40.75 loss:0.013 grdn:0.188 lr:3.1e-05 updt_s:0.065 data_s:0.026
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INFO 2025-11-18 03:17:12 ts/train.py:232 step:63K smpl:504K ep:2K epch:40.88 loss:0.015 grdn:0.208 lr:3.1e-05 updt_s:0.065 data_s:0.023
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INFO 2025-11-18 03:17:30 ts/train.py:232 step:63K smpl:506K ep:2K epch:41.01 loss:0.014 grdn:0.196 lr:3.0e-05 updt_s:0.065 data_s:0.024
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INFO 2025-11-18 03:17:47 ts/train.py:232 step:63K smpl:507K ep:2K epch:41.14 loss:0.015 grdn:0.204 lr:3.0e-05 updt_s:0.065 data_s:0.021
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INFO 2025-11-18 03:18:04 ts/train.py:232 step:64K smpl:509K ep:2K epch:41.27 loss:0.015 grdn:0.219 lr:3.0e-05 updt_s:0.064 data_s:0.021
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INFO 2025-11-18 03:18:22 ts/train.py:232 step:64K smpl:510K ep:2K epch:41.39 loss:0.016 grdn:0.210 lr:2.9e-05 updt_s:0.065 data_s:0.023
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INFO 2025-11-18 03:18:43 ts/train.py:232 step:64K smpl:512K ep:2K epch:41.52 loss:0.015 grdn:0.210 lr:2.9e-05 updt_s:0.064 data_s:0.039
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INFO 2025-11-18 03:19:01 ts/train.py:232 step:64K smpl:514K ep:2K epch:41.65 loss:0.014 grdn:0.197 lr:2.9e-05 updt_s:0.065 data_s:0.023
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INFO 2025-11-18 03:19:19 ts/train.py:232 step:64K smpl:515K ep:2K epch:41.78 loss:0.012 grdn:0.184 lr:2.9e-05 updt_s:0.065 data_s:0.028
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INFO 2025-11-18 03:19:38 ts/train.py:232 step:65K smpl:517K ep:2K epch:41.91 loss:0.014 grdn:0.202 lr:2.8e-05 updt_s:0.064 data_s:0.026
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INFO 2025-11-18 03:19:56 ts/train.py:232 step:65K smpl:518K ep:2K epch:42.04 loss:0.015 grdn:0.202 lr:2.8e-05 updt_s:0.065 data_s:0.026
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INFO 2025-11-18 03:20:14 ts/train.py:232 step:65K smpl:520K ep:2K epch:42.17 loss:0.015 grdn:0.203 lr:2.8e-05 updt_s:0.064 data_s:0.026
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INFO 2025-11-18 03:20:32 ts/train.py:232 step:65K smpl:522K ep:2K epch:42.30 loss:0.015 grdn:0.210 lr:2.7e-05 updt_s:0.064 data_s:0.026
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INFO 2025-11-18 03:20:50 ts/train.py:232 step:65K smpl:523K ep:2K epch:42.43 loss:0.014 grdn:0.198 lr:2.7e-05 updt_s:0.064 data_s:0.026
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INFO 2025-11-18 03:21:09 ts/train.py:232 step:66K smpl:525K ep:2K epch:42.56 loss:0.015 grdn:0.213 lr:2.7e-05 updt_s:0.065 data_s:0.026
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INFO 2025-11-18 03:21:27 ts/train.py:232 step:66K smpl:526K ep:2K epch:42.69 loss:0.014 grdn:0.207 lr:2.7e-05 updt_s:0.065 data_s:0.025
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INFO 2025-11-18 03:21:45 ts/train.py:232 step:66K smpl:528K ep:2K epch:42.82 loss:0.014 grdn:0.205 lr:2.6e-05 updt_s:0.065 data_s:0.027
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INFO 2025-11-18 03:22:04 ts/train.py:232 step:66K smpl:530K ep:2K epch:42.95 loss:0.014 grdn:0.202 lr:2.6e-05 updt_s:0.065 data_s:0.029
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INFO 2025-11-18 03:22:23 ts/train.py:232 step:66K smpl:531K ep:2K epch:43.08 loss:0.015 grdn:0.202 lr:2.6e-05 updt_s:0.065 data_s:0.028
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INFO 2025-11-18 03:22:41 ts/train.py:232 step:67K smpl:533K ep:2K epch:43.21 loss:0.014 grdn:0.201 lr:2.5e-05 updt_s:0.065 data_s:0.028
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INFO 2025-11-18 03:23:00 ts/train.py:232 step:67K smpl:534K ep:2K epch:43.34 loss:0.015 grdn:0.215 lr:2.5e-05 updt_s:0.065 data_s:0.026
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INFO 2025-11-18 03:23:18 ts/train.py:232 step:67K smpl:536K ep:2K epch:43.47 loss:0.013 grdn:0.191 lr:2.5e-05 updt_s:0.065 data_s:0.027
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INFO 2025-11-18 03:23:36 ts/train.py:232 step:67K smpl:538K ep:2K epch:43.60 loss:0.013 grdn:0.193 lr:2.5e-05 updt_s:0.065 data_s:0.023
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INFO 2025-11-18 03:23:55 ts/train.py:232 step:67K smpl:539K ep:2K epch:43.73 loss:0.016 grdn:0.208 lr:2.4e-05 updt_s:0.065 data_s:0.029
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INFO 2025-11-18 03:24:13 ts/train.py:232 step:68K smpl:541K ep:2K epch:43.86 loss:0.013 grdn:0.198 lr:2.4e-05 updt_s:0.065 data_s:0.027
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INFO 2025-11-18 03:24:32 ts/train.py:232 step:68K smpl:542K ep:2K epch:43.99 loss:0.014 grdn:0.212 lr:2.4e-05 updt_s:0.065 data_s:0.028
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INFO 2025-11-18 03:24:51 ts/train.py:232 step:68K smpl:544K ep:2K epch:44.12 loss:0.014 grdn:0.208 lr:2.4e-05 updt_s:0.066 data_s:0.027
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INFO 2025-11-18 03:25:09 ts/train.py:232 step:68K smpl:546K ep:2K epch:44.25 loss:0.014 grdn:0.208 lr:2.3e-05 updt_s:0.065 data_s:0.026
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INFO 2025-11-18 03:25:27 ts/train.py:232 step:68K smpl:547K ep:2K epch:44.38 loss:0.013 grdn:0.198 lr:2.3e-05 updt_s:0.065 data_s:0.026
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INFO 2025-11-18 03:25:45 ts/train.py:232 step:69K smpl:549K ep:2K epch:44.51 loss:0.014 grdn:0.210 lr:2.3e-05 updt_s:0.065 data_s:0.026
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INFO 2025-11-18 03:26:04 ts/train.py:232 step:69K smpl:550K ep:2K epch:44.64 loss:0.014 grdn:0.205 lr:2.2e-05 updt_s:0.065 data_s:0.026
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INFO 2025-11-18 03:26:22 ts/train.py:232 step:69K smpl:552K ep:2K epch:44.77 loss:0.015 grdn:0.219 lr:2.2e-05 updt_s:0.065 data_s:0.026
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INFO 2025-11-18 03:26:40 ts/train.py:232 step:69K smpl:554K ep:2K epch:44.90 loss:0.014 grdn:0.210 lr:2.2e-05 updt_s:0.065 data_s:0.026
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INFO 2025-11-18 03:26:58 ts/train.py:232 step:69K smpl:555K ep:2K epch:45.03 loss:0.013 grdn:0.192 lr:2.2e-05 updt_s:0.065 data_s:0.027
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INFO 2025-11-18 03:27:17 ts/train.py:232 step:70K smpl:557K ep:2K epch:45.16 loss:0.013 grdn:0.195 lr:2.1e-05 updt_s:0.065 data_s:0.026
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INFO 2025-11-18 03:27:35 ts/train.py:232 step:70K smpl:558K ep:2K epch:45.29 loss:0.013 grdn:0.203 lr:2.1e-05 updt_s:0.065 data_s:0.025
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INFO 2025-11-18 03:27:53 ts/train.py:232 step:70K smpl:560K ep:2K epch:45.42 loss:0.014 grdn:0.207 lr:2.1e-05 updt_s:0.065 data_s:0.026
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INFO 2025-11-18 03:28:10 ts/train.py:232 step:70K smpl:562K ep:2K epch:45.55 loss:0.014 grdn:0.211 lr:2.1e-05 updt_s:0.065 data_s:0.020
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INFO 2025-11-18 03:28:29 ts/train.py:232 step:70K smpl:563K ep:2K epch:45.68 loss:0.014 grdn:0.214 lr:2.0e-05 updt_s:0.065 data_s:0.029
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INFO 2025-11-18 03:28:48 ts/train.py:232 step:71K smpl:565K ep:2K epch:45.81 loss:0.013 grdn:0.202 lr:2.0e-05 updt_s:0.064 data_s:0.027
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INFO 2025-11-18 03:29:09 ts/train.py:232 step:71K smpl:566K ep:2K epch:45.94 loss:0.013 grdn:0.193 lr:2.0e-05 updt_s:0.064 data_s:0.040
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INFO 2025-11-18 03:29:27 ts/train.py:232 step:71K smpl:568K ep:2K epch:46.07 loss:0.012 grdn:0.193 lr:2.0e-05 updt_s:0.065 data_s:0.027
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INFO 2025-11-18 03:29:45 ts/train.py:232 step:71K smpl:570K ep:2K epch:46.20 loss:0.014 grdn:0.200 lr:1.9e-05 updt_s:0.064 data_s:0.026
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INFO 2025-11-18 03:30:03 ts/train.py:232 step:71K smpl:571K ep:3K epch:46.33 loss:0.014 grdn:0.203 lr:1.9e-05 updt_s:0.065 data_s:0.027
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INFO 2025-11-18 03:30:21 ts/train.py:232 step:72K smpl:573K ep:3K epch:46.46 loss:0.013 grdn:0.193 lr:1.9e-05 updt_s:0.064 data_s:0.024
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INFO 2025-11-18 03:30:40 ts/train.py:232 step:72K smpl:574K ep:3K epch:46.59 loss:0.015 grdn:0.212 lr:1.9e-05 updt_s:0.065 data_s:0.026
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INFO 2025-11-18 03:30:58 ts/train.py:232 step:72K smpl:576K ep:3K epch:46.72 loss:0.013 grdn:0.193 lr:1.8e-05 updt_s:0.065 data_s:0.026
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INFO 2025-11-18 03:31:16 ts/train.py:232 step:72K smpl:578K ep:3K epch:46.85 loss:0.013 grdn:0.195 lr:1.8e-05 updt_s:0.065 data_s:0.025
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INFO 2025-11-18 03:31:34 ts/train.py:232 step:72K smpl:579K ep:3K epch:46.97 loss:0.014 grdn:0.203 lr:1.8e-05 updt_s:0.065 data_s:0.025
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| 378 |
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INFO 2025-11-18 03:31:52 ts/train.py:232 step:73K smpl:581K ep:3K epch:47.10 loss:0.014 grdn:0.206 lr:1.8e-05 updt_s:0.064 data_s:0.025
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| 379 |
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INFO 2025-11-18 03:32:10 ts/train.py:232 step:73K smpl:582K ep:3K epch:47.23 loss:0.014 grdn:0.201 lr:1.7e-05 updt_s:0.064 data_s:0.025
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| 380 |
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INFO 2025-11-18 03:32:28 ts/train.py:232 step:73K smpl:584K ep:3K epch:47.36 loss:0.013 grdn:0.200 lr:1.7e-05 updt_s:0.065 data_s:0.024
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| 381 |
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INFO 2025-11-18 03:32:45 ts/train.py:232 step:73K smpl:586K ep:3K epch:47.49 loss:0.012 grdn:0.193 lr:1.7e-05 updt_s:0.064 data_s:0.021
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| 382 |
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INFO 2025-11-18 03:33:04 ts/train.py:232 step:73K smpl:587K ep:3K epch:47.62 loss:0.012 grdn:0.188 lr:1.7e-05 updt_s:0.065 data_s:0.029
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| 383 |
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INFO 2025-11-18 03:33:22 ts/train.py:232 step:74K smpl:589K ep:3K epch:47.75 loss:0.013 grdn:0.198 lr:1.7e-05 updt_s:0.064 data_s:0.028
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| 384 |
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INFO 2025-11-18 03:33:41 ts/train.py:232 step:74K smpl:590K ep:3K epch:47.88 loss:0.012 grdn:0.198 lr:1.6e-05 updt_s:0.065 data_s:0.028
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| 385 |
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INFO 2025-11-18 03:33:59 ts/train.py:232 step:74K smpl:592K ep:3K epch:48.01 loss:0.012 grdn:0.191 lr:1.6e-05 updt_s:0.064 data_s:0.027
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| 386 |
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INFO 2025-11-18 03:34:18 ts/train.py:232 step:74K smpl:594K ep:3K epch:48.14 loss:0.012 grdn:0.196 lr:1.6e-05 updt_s:0.065 data_s:0.028
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| 387 |
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INFO 2025-11-18 03:34:37 ts/train.py:232 step:74K smpl:595K ep:3K epch:48.27 loss:0.012 grdn:0.192 lr:1.6e-05 updt_s:0.065 data_s:0.027
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| 388 |
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INFO 2025-11-18 03:34:54 ts/train.py:232 step:75K smpl:597K ep:3K epch:48.40 loss:0.013 grdn:0.195 lr:1.5e-05 updt_s:0.064 data_s:0.023
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| 389 |
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INFO 2025-11-18 03:35:13 ts/train.py:232 step:75K smpl:598K ep:3K epch:48.53 loss:0.013 grdn:0.199 lr:1.5e-05 updt_s:0.065 data_s:0.029
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| 390 |
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INFO 2025-11-18 03:35:31 ts/train.py:232 step:75K smpl:600K ep:3K epch:48.66 loss:0.013 grdn:0.200 lr:1.5e-05 updt_s:0.065 data_s:0.026
|
| 391 |
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INFO 2025-11-18 03:35:49 ts/train.py:232 step:75K smpl:602K ep:3K epch:48.79 loss:0.012 grdn:0.191 lr:1.5e-05 updt_s:0.065 data_s:0.024
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| 392 |
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INFO 2025-11-18 03:36:07 ts/train.py:232 step:75K smpl:603K ep:3K epch:48.92 loss:0.014 grdn:0.220 lr:1.4e-05 updt_s:0.065 data_s:0.026
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| 393 |
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INFO 2025-11-18 03:36:26 ts/train.py:232 step:76K smpl:605K ep:3K epch:49.05 loss:0.013 grdn:0.195 lr:1.4e-05 updt_s:0.065 data_s:0.027
|
| 394 |
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INFO 2025-11-18 03:36:44 ts/train.py:232 step:76K smpl:606K ep:3K epch:49.18 loss:0.012 grdn:0.197 lr:1.4e-05 updt_s:0.065 data_s:0.025
|
| 395 |
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INFO 2025-11-18 03:37:02 ts/train.py:232 step:76K smpl:608K ep:3K epch:49.31 loss:0.013 grdn:0.207 lr:1.4e-05 updt_s:0.066 data_s:0.024
|
| 396 |
+
INFO 2025-11-18 03:37:20 ts/train.py:232 step:76K smpl:610K ep:3K epch:49.44 loss:0.013 grdn:0.204 lr:1.4e-05 updt_s:0.065 data_s:0.023
|
| 397 |
+
INFO 2025-11-18 03:37:39 ts/train.py:232 step:76K smpl:611K ep:3K epch:49.57 loss:0.013 grdn:0.206 lr:1.3e-05 updt_s:0.065 data_s:0.029
|
| 398 |
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INFO 2025-11-18 03:37:57 ts/train.py:232 step:77K smpl:613K ep:3K epch:49.70 loss:0.013 grdn:0.204 lr:1.3e-05 updt_s:0.065 data_s:0.026
|
| 399 |
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INFO 2025-11-18 03:38:15 ts/train.py:232 step:77K smpl:614K ep:3K epch:49.83 loss:0.013 grdn:0.197 lr:1.3e-05 updt_s:0.065 data_s:0.024
|
| 400 |
+
INFO 2025-11-18 03:38:33 ts/train.py:232 step:77K smpl:616K ep:3K epch:49.96 loss:0.011 grdn:0.181 lr:1.3e-05 updt_s:0.066 data_s:0.026
|
| 401 |
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INFO 2025-11-18 03:38:51 ts/train.py:232 step:77K smpl:618K ep:3K epch:50.09 loss:0.012 grdn:0.194 lr:1.3e-05 updt_s:0.065 data_s:0.025
|
| 402 |
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INFO 2025-11-18 03:39:12 ts/train.py:232 step:77K smpl:619K ep:3K epch:50.22 loss:0.013 grdn:0.199 lr:1.2e-05 updt_s:0.065 data_s:0.038
|
| 403 |
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INFO 2025-11-18 03:39:30 ts/train.py:232 step:78K smpl:621K ep:3K epch:50.35 loss:0.013 grdn:0.207 lr:1.2e-05 updt_s:0.065 data_s:0.022
|
| 404 |
+
INFO 2025-11-18 03:39:48 ts/train.py:232 step:78K smpl:622K ep:3K epch:50.48 loss:0.013 grdn:0.197 lr:1.2e-05 updt_s:0.065 data_s:0.026
|
| 405 |
+
INFO 2025-11-18 03:40:07 ts/train.py:232 step:78K smpl:624K ep:3K epch:50.61 loss:0.012 grdn:0.196 lr:1.2e-05 updt_s:0.065 data_s:0.028
|
| 406 |
+
INFO 2025-11-18 03:40:25 ts/train.py:232 step:78K smpl:626K ep:3K epch:50.74 loss:0.013 grdn:0.203 lr:1.1e-05 updt_s:0.064 data_s:0.027
|
| 407 |
+
INFO 2025-11-18 03:40:43 ts/train.py:232 step:78K smpl:627K ep:3K epch:50.87 loss:0.011 grdn:0.186 lr:1.1e-05 updt_s:0.064 data_s:0.026
|
| 408 |
+
INFO 2025-11-18 03:41:01 ts/train.py:232 step:79K smpl:629K ep:3K epch:51.00 loss:0.012 grdn:0.194 lr:1.1e-05 updt_s:0.065 data_s:0.026
|
| 409 |
+
INFO 2025-11-18 03:41:20 ts/train.py:232 step:79K smpl:630K ep:3K epch:51.13 loss:0.011 grdn:0.186 lr:1.1e-05 updt_s:0.065 data_s:0.026
|
| 410 |
+
INFO 2025-11-18 03:41:38 ts/train.py:232 step:79K smpl:632K ep:3K epch:51.26 loss:0.012 grdn:0.202 lr:1.1e-05 updt_s:0.065 data_s:0.024
|
| 411 |
+
INFO 2025-11-18 03:41:55 ts/train.py:232 step:79K smpl:634K ep:3K epch:51.39 loss:0.012 grdn:0.203 lr:1.0e-05 updt_s:0.065 data_s:0.022
|
| 412 |
+
INFO 2025-11-18 03:42:13 ts/train.py:232 step:79K smpl:635K ep:3K epch:51.52 loss:0.013 grdn:0.202 lr:1.0e-05 updt_s:0.065 data_s:0.026
|
| 413 |
+
INFO 2025-11-18 03:42:32 ts/train.py:232 step:80K smpl:637K ep:3K epch:51.65 loss:0.011 grdn:0.192 lr:1.0e-05 updt_s:0.065 data_s:0.027
|
| 414 |
+
INFO 2025-11-18 03:42:51 ts/train.py:232 step:80K smpl:638K ep:3K epch:51.78 loss:0.013 grdn:0.205 lr:9.9e-06 updt_s:0.065 data_s:0.027
|
| 415 |
+
INFO 2025-11-18 03:43:09 ts/train.py:232 step:80K smpl:640K ep:3K epch:51.91 loss:0.013 grdn:0.211 lr:9.7e-06 updt_s:0.065 data_s:0.028
|
| 416 |
+
INFO 2025-11-18 03:43:09 ts/train.py:241 Checkpoint policy after step 80000
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| 417 |
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INFO 2025-11-18 03:43:42 ts/train.py:232 step:80K smpl:642K ep:3K epch:52.04 loss:0.012 grdn:0.198 lr:9.5e-06 updt_s:0.065 data_s:0.028
|
| 418 |
+
INFO 2025-11-18 03:44:00 ts/train.py:232 step:80K smpl:643K ep:3K epch:52.17 loss:0.012 grdn:0.197 lr:9.4e-06 updt_s:0.065 data_s:0.026
|
| 419 |
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INFO 2025-11-18 03:44:19 ts/train.py:232 step:81K smpl:645K ep:3K epch:52.30 loss:0.011 grdn:0.188 lr:9.2e-06 updt_s:0.065 data_s:0.027
|
| 420 |
+
INFO 2025-11-18 03:44:38 ts/train.py:232 step:81K smpl:646K ep:3K epch:52.42 loss:0.012 grdn:0.194 lr:9.0e-06 updt_s:0.065 data_s:0.030
|
| 421 |
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INFO 2025-11-18 03:44:56 ts/train.py:232 step:81K smpl:648K ep:3K epch:52.55 loss:0.012 grdn:0.201 lr:8.8e-06 updt_s:0.065 data_s:0.026
|
| 422 |
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INFO 2025-11-18 03:45:15 ts/train.py:232 step:81K smpl:650K ep:3K epch:52.68 loss:0.012 grdn:0.199 lr:8.6e-06 updt_s:0.065 data_s:0.028
|
| 423 |
+
INFO 2025-11-18 03:45:33 ts/train.py:232 step:81K smpl:651K ep:3K epch:52.81 loss:0.011 grdn:0.192 lr:8.5e-06 updt_s:0.065 data_s:0.028
|
| 424 |
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INFO 2025-11-18 03:45:52 ts/train.py:232 step:82K smpl:653K ep:3K epch:52.94 loss:0.013 grdn:0.210 lr:8.3e-06 updt_s:0.065 data_s:0.028
|
| 425 |
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INFO 2025-11-18 03:46:10 ts/train.py:232 step:82K smpl:654K ep:3K epch:53.07 loss:0.012 grdn:0.199 lr:8.1e-06 updt_s:0.065 data_s:0.026
|
| 426 |
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INFO 2025-11-18 03:46:28 ts/train.py:232 step:82K smpl:656K ep:3K epch:53.20 loss:0.011 grdn:0.176 lr:7.9e-06 updt_s:0.065 data_s:0.026
|
| 427 |
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INFO 2025-11-18 03:46:46 ts/train.py:232 step:82K smpl:658K ep:3K epch:53.33 loss:0.011 grdn:0.189 lr:7.8e-06 updt_s:0.065 data_s:0.023
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| 428 |
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INFO 2025-11-18 03:47:04 ts/train.py:232 step:82K smpl:659K ep:3K epch:53.46 loss:0.012 grdn:0.198 lr:7.6e-06 updt_s:0.065 data_s:0.028
|
| 429 |
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INFO 2025-11-18 03:47:23 ts/train.py:232 step:83K smpl:661K ep:3K epch:53.59 loss:0.012 grdn:0.197 lr:7.4e-06 updt_s:0.065 data_s:0.029
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| 430 |
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INFO 2025-11-18 03:47:42 ts/train.py:232 step:83K smpl:662K ep:3K epch:53.72 loss:0.012 grdn:0.198 lr:7.3e-06 updt_s:0.065 data_s:0.028
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| 431 |
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INFO 2025-11-18 03:48:00 ts/train.py:232 step:83K smpl:664K ep:3K epch:53.85 loss:0.012 grdn:0.191 lr:7.1e-06 updt_s:0.065 data_s:0.027
|
| 432 |
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INFO 2025-11-18 03:48:18 ts/train.py:232 step:83K smpl:666K ep:3K epch:53.98 loss:0.012 grdn:0.203 lr:7.0e-06 updt_s:0.065 data_s:0.026
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| 433 |
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INFO 2025-11-18 03:48:37 ts/train.py:232 step:83K smpl:667K ep:3K epch:54.11 loss:0.012 grdn:0.192 lr:6.8e-06 updt_s:0.065 data_s:0.027
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| 434 |
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INFO 2025-11-18 03:48:55 ts/train.py:232 step:84K smpl:669K ep:3K epch:54.24 loss:0.012 grdn:0.199 lr:6.6e-06 updt_s:0.065 data_s:0.025
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| 435 |
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INFO 2025-11-18 03:49:13 ts/train.py:232 step:84K smpl:670K ep:3K epch:54.37 loss:0.012 grdn:0.196 lr:6.5e-06 updt_s:0.065 data_s:0.026
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| 436 |
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INFO 2025-11-18 03:49:34 ts/train.py:232 step:84K smpl:672K ep:3K epch:54.50 loss:0.012 grdn:0.206 lr:6.3e-06 updt_s:0.065 data_s:0.041
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| 437 |
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INFO 2025-11-18 03:49:52 ts/train.py:232 step:84K smpl:674K ep:3K epch:54.63 loss:0.012 grdn:0.191 lr:6.2e-06 updt_s:0.065 data_s:0.024
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| 438 |
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INFO 2025-11-18 03:50:10 ts/train.py:232 step:84K smpl:675K ep:3K epch:54.76 loss:0.011 grdn:0.197 lr:6.0e-06 updt_s:0.065 data_s:0.023
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| 439 |
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INFO 2025-11-18 03:50:29 ts/train.py:232 step:85K smpl:677K ep:3K epch:54.89 loss:0.011 grdn:0.193 lr:5.9e-06 updt_s:0.065 data_s:0.027
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| 440 |
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INFO 2025-11-18 03:50:47 ts/train.py:232 step:85K smpl:678K ep:3K epch:55.02 loss:0.011 grdn:0.184 lr:5.7e-06 updt_s:0.066 data_s:0.025
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| 441 |
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INFO 2025-11-18 03:51:05 ts/train.py:232 step:85K smpl:680K ep:3K epch:55.15 loss:0.012 grdn:0.193 lr:5.6e-06 updt_s:0.065 data_s:0.024
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| 442 |
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INFO 2025-11-18 03:51:22 ts/train.py:232 step:85K smpl:682K ep:3K epch:55.28 loss:0.012 grdn:0.197 lr:5.4e-06 updt_s:0.064 data_s:0.021
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| 443 |
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INFO 2025-11-18 03:51:40 ts/train.py:232 step:85K smpl:683K ep:3K epch:55.41 loss:0.012 grdn:0.200 lr:5.3e-06 updt_s:0.064 data_s:0.025
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| 444 |
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INFO 2025-11-18 03:51:58 ts/train.py:232 step:86K smpl:685K ep:3K epch:55.54 loss:0.011 grdn:0.185 lr:5.1e-06 updt_s:0.064 data_s:0.025
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| 445 |
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INFO 2025-11-18 03:52:16 ts/train.py:232 step:86K smpl:686K ep:3K epch:55.67 loss:0.013 grdn:0.206 lr:5.0e-06 updt_s:0.064 data_s:0.025
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| 446 |
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INFO 2025-11-18 03:52:34 ts/train.py:232 step:86K smpl:688K ep:3K epch:55.80 loss:0.012 grdn:0.195 lr:4.9e-06 updt_s:0.065 data_s:0.025
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| 447 |
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INFO 2025-11-18 03:52:52 ts/train.py:232 step:86K smpl:690K ep:3K epch:55.93 loss:0.012 grdn:0.201 lr:4.7e-06 updt_s:0.065 data_s:0.025
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| 448 |
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INFO 2025-11-18 03:53:10 ts/train.py:232 step:86K smpl:691K ep:3K epch:56.06 loss:0.012 grdn:0.199 lr:4.6e-06 updt_s:0.065 data_s:0.024
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| 449 |
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INFO 2025-11-18 03:53:28 ts/train.py:232 step:87K smpl:693K ep:3K epch:56.19 loss:0.011 grdn:0.188 lr:4.5e-06 updt_s:0.065 data_s:0.023
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| 450 |
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INFO 2025-11-18 03:53:46 ts/train.py:232 step:87K smpl:694K ep:3K epch:56.32 loss:0.011 grdn:0.191 lr:4.3e-06 updt_s:0.065 data_s:0.025
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| 451 |
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INFO 2025-11-18 03:54:03 ts/train.py:232 step:87K smpl:696K ep:3K epch:56.45 loss:0.013 grdn:0.206 lr:4.2e-06 updt_s:0.065 data_s:0.020
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| 452 |
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INFO 2025-11-18 03:54:20 ts/train.py:232 step:87K smpl:698K ep:3K epch:56.58 loss:0.011 grdn:0.185 lr:4.1e-06 updt_s:0.065 data_s:0.022
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| 453 |
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INFO 2025-11-18 03:54:38 ts/train.py:232 step:87K smpl:699K ep:3K epch:56.71 loss:0.012 grdn:0.195 lr:4.0e-06 updt_s:0.065 data_s:0.022
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| 454 |
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INFO 2025-11-18 03:54:55 ts/train.py:232 step:88K smpl:701K ep:3K epch:56.84 loss:0.011 grdn:0.193 lr:3.8e-06 updt_s:0.064 data_s:0.020
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| 455 |
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INFO 2025-11-18 03:55:12 ts/train.py:232 step:88K smpl:702K ep:3K epch:56.97 loss:0.012 grdn:0.206 lr:3.7e-06 updt_s:0.065 data_s:0.019
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| 456 |
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INFO 2025-11-18 03:55:29 ts/train.py:232 step:88K smpl:704K ep:3K epch:57.10 loss:0.010 grdn:0.182 lr:3.6e-06 updt_s:0.065 data_s:0.021
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| 457 |
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INFO 2025-11-18 03:55:47 ts/train.py:232 step:88K smpl:706K ep:3K epch:57.23 loss:0.012 grdn:0.200 lr:3.5e-06 updt_s:0.065 data_s:0.024
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| 458 |
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INFO 2025-11-18 03:56:06 ts/train.py:232 step:88K smpl:707K ep:3K epch:57.36 loss:0.011 grdn:0.195 lr:3.4e-06 updt_s:0.065 data_s:0.030
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| 459 |
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INFO 2025-11-18 03:56:24 ts/train.py:232 step:89K smpl:709K ep:3K epch:57.49 loss:0.012 grdn:0.199 lr:3.3e-06 updt_s:0.064 data_s:0.026
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| 460 |
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INFO 2025-11-18 03:56:43 ts/train.py:232 step:89K smpl:710K ep:3K epch:57.62 loss:0.010 grdn:0.189 lr:3.1e-06 updt_s:0.065 data_s:0.030
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| 461 |
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INFO 2025-11-18 03:57:02 ts/train.py:232 step:89K smpl:712K ep:3K epch:57.75 loss:0.012 grdn:0.198 lr:3.0e-06 updt_s:0.065 data_s:0.027
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| 462 |
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INFO 2025-11-18 03:57:21 ts/train.py:232 step:89K smpl:714K ep:3K epch:57.88 loss:0.011 grdn:0.188 lr:2.9e-06 updt_s:0.065 data_s:0.029
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| 463 |
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INFO 2025-11-18 03:57:39 ts/train.py:232 step:89K smpl:715K ep:3K epch:58.00 loss:0.011 grdn:0.187 lr:2.8e-06 updt_s:0.064 data_s:0.026
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| 464 |
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INFO 2025-11-18 03:57:56 ts/train.py:232 step:90K smpl:717K ep:3K epch:58.13 loss:0.012 grdn:0.204 lr:2.7e-06 updt_s:0.065 data_s:0.022
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| 465 |
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INFO 2025-11-18 03:58:15 ts/train.py:232 step:90K smpl:718K ep:3K epch:58.26 loss:0.011 grdn:0.190 lr:2.6e-06 updt_s:0.064 data_s:0.028
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| 466 |
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INFO 2025-11-18 03:58:34 ts/train.py:232 step:90K smpl:720K ep:3K epch:58.39 loss:0.012 grdn:0.206 lr:2.5e-06 updt_s:0.065 data_s:0.029
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| 467 |
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INFO 2025-11-18 03:58:52 ts/train.py:232 step:90K smpl:722K ep:3K epch:58.52 loss:0.012 grdn:0.199 lr:2.4e-06 updt_s:0.065 data_s:0.026
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| 468 |
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INFO 2025-11-18 03:59:11 ts/train.py:232 step:90K smpl:723K ep:3K epch:58.65 loss:0.011 grdn:0.198 lr:2.3e-06 updt_s:0.066 data_s:0.027
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| 469 |
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INFO 2025-11-18 03:59:29 ts/train.py:232 step:91K smpl:725K ep:3K epch:58.78 loss:0.012 grdn:0.201 lr:2.2e-06 updt_s:0.064 data_s:0.025
|
| 470 |
+
INFO 2025-11-18 03:59:47 ts/train.py:232 step:91K smpl:726K ep:3K epch:58.91 loss:0.011 grdn:0.190 lr:2.1e-06 updt_s:0.065 data_s:0.027
|
| 471 |
+
INFO 2025-11-18 04:00:05 ts/train.py:232 step:91K smpl:728K ep:3K epch:59.04 loss:0.012 grdn:0.195 lr:2.0e-06 updt_s:0.065 data_s:0.025
|
| 472 |
+
INFO 2025-11-18 04:00:26 ts/train.py:232 step:91K smpl:730K ep:3K epch:59.17 loss:0.011 grdn:0.185 lr:2.0e-06 updt_s:0.065 data_s:0.039
|
| 473 |
+
INFO 2025-11-18 04:00:45 ts/train.py:232 step:91K smpl:731K ep:3K epch:59.30 loss:0.012 grdn:0.198 lr:1.9e-06 updt_s:0.065 data_s:0.027
|
| 474 |
+
INFO 2025-11-18 04:01:03 ts/train.py:232 step:92K smpl:733K ep:3K epch:59.43 loss:0.012 grdn:0.197 lr:1.8e-06 updt_s:0.064 data_s:0.027
|
| 475 |
+
INFO 2025-11-18 04:01:21 ts/train.py:232 step:92K smpl:734K ep:3K epch:59.56 loss:0.012 grdn:0.211 lr:1.7e-06 updt_s:0.064 data_s:0.024
|
| 476 |
+
INFO 2025-11-18 04:01:39 ts/train.py:232 step:92K smpl:736K ep:3K epch:59.69 loss:0.012 grdn:0.192 lr:1.6e-06 updt_s:0.065 data_s:0.025
|
| 477 |
+
INFO 2025-11-18 04:01:57 ts/train.py:232 step:92K smpl:738K ep:3K epch:59.82 loss:0.012 grdn:0.196 lr:1.5e-06 updt_s:0.065 data_s:0.027
|
| 478 |
+
INFO 2025-11-18 04:02:15 ts/train.py:232 step:92K smpl:739K ep:3K epch:59.95 loss:0.011 grdn:0.191 lr:1.5e-06 updt_s:0.065 data_s:0.025
|
| 479 |
+
INFO 2025-11-18 04:02:33 ts/train.py:232 step:93K smpl:741K ep:3K epch:60.08 loss:0.012 grdn:0.203 lr:1.4e-06 updt_s:0.065 data_s:0.022
|
| 480 |
+
INFO 2025-11-18 04:02:50 ts/train.py:232 step:93K smpl:742K ep:3K epch:60.21 loss:0.011 grdn:0.183 lr:1.3e-06 updt_s:0.064 data_s:0.022
|
| 481 |
+
INFO 2025-11-18 04:03:07 ts/train.py:232 step:93K smpl:744K ep:3K epch:60.34 loss:0.012 grdn:0.197 lr:1.3e-06 updt_s:0.065 data_s:0.020
|
| 482 |
+
INFO 2025-11-18 04:03:25 ts/train.py:232 step:93K smpl:746K ep:3K epch:60.47 loss:0.011 grdn:0.186 lr:1.2e-06 updt_s:0.065 data_s:0.021
|
| 483 |
+
INFO 2025-11-18 04:03:42 ts/train.py:232 step:93K smpl:747K ep:3K epch:60.60 loss:0.010 grdn:0.177 lr:1.1e-06 updt_s:0.064 data_s:0.020
|
| 484 |
+
INFO 2025-11-18 04:03:58 ts/train.py:232 step:94K smpl:749K ep:3K epch:60.73 loss:0.011 grdn:0.189 lr:1.0e-06 updt_s:0.065 data_s:0.019
|
| 485 |
+
INFO 2025-11-18 04:04:15 ts/train.py:232 step:94K smpl:750K ep:3K epch:60.86 loss:0.011 grdn:0.189 lr:9.9e-07 updt_s:0.065 data_s:0.019
|
| 486 |
+
INFO 2025-11-18 04:04:32 ts/train.py:232 step:94K smpl:752K ep:3K epch:60.99 loss:0.011 grdn:0.192 lr:9.2e-07 updt_s:0.065 data_s:0.019
|
| 487 |
+
INFO 2025-11-18 04:04:50 ts/train.py:232 step:94K smpl:754K ep:3K epch:61.12 loss:0.011 grdn:0.194 lr:8.6e-07 updt_s:0.065 data_s:0.025
|
| 488 |
+
INFO 2025-11-18 04:05:08 ts/train.py:232 step:94K smpl:755K ep:3K epch:61.25 loss:0.011 grdn:0.195 lr:8.1e-07 updt_s:0.065 data_s:0.026
|
| 489 |
+
INFO 2025-11-18 04:05:27 ts/train.py:232 step:95K smpl:757K ep:3K epch:61.38 loss:0.011 grdn:0.187 lr:7.5e-07 updt_s:0.065 data_s:0.026
|
| 490 |
+
INFO 2025-11-18 04:05:45 ts/train.py:232 step:95K smpl:758K ep:3K epch:61.51 loss:0.011 grdn:0.195 lr:7.0e-07 updt_s:0.065 data_s:0.026
|
| 491 |
+
INFO 2025-11-18 04:06:03 ts/train.py:232 step:95K smpl:760K ep:3K epch:61.64 loss:0.011 grdn:0.191 lr:6.5e-07 updt_s:0.065 data_s:0.026
|
| 492 |
+
INFO 2025-11-18 04:06:21 ts/train.py:232 step:95K smpl:762K ep:3K epch:61.77 loss:0.011 grdn:0.188 lr:6.0e-07 updt_s:0.065 data_s:0.026
|
| 493 |
+
INFO 2025-11-18 04:06:39 ts/train.py:232 step:95K smpl:763K ep:3K epch:61.90 loss:0.011 grdn:0.184 lr:5.5e-07 updt_s:0.064 data_s:0.025
|
| 494 |
+
INFO 2025-11-18 04:06:57 ts/train.py:232 step:96K smpl:765K ep:3K epch:62.03 loss:0.011 grdn:0.195 lr:5.0e-07 updt_s:0.064 data_s:0.022
|
| 495 |
+
INFO 2025-11-18 04:07:15 ts/train.py:232 step:96K smpl:766K ep:3K epch:62.16 loss:0.012 grdn:0.202 lr:4.6e-07 updt_s:0.066 data_s:0.025
|
| 496 |
+
INFO 2025-11-18 04:07:32 ts/train.py:232 step:96K smpl:768K ep:3K epch:62.29 loss:0.011 grdn:0.183 lr:4.2e-07 updt_s:0.065 data_s:0.021
|
| 497 |
+
INFO 2025-11-18 04:07:50 ts/train.py:232 step:96K smpl:770K ep:3K epch:62.42 loss:0.012 grdn:0.193 lr:3.8e-07 updt_s:0.065 data_s:0.021
|
| 498 |
+
INFO 2025-11-18 04:08:07 ts/train.py:232 step:96K smpl:771K ep:3K epch:62.55 loss:0.011 grdn:0.192 lr:3.4e-07 updt_s:0.064 data_s:0.020
|
| 499 |
+
INFO 2025-11-18 04:08:24 ts/train.py:232 step:97K smpl:773K ep:3K epch:62.68 loss:0.011 grdn:0.188 lr:3.0e-07 updt_s:0.064 data_s:0.020
|
| 500 |
+
INFO 2025-11-18 04:08:41 ts/train.py:232 step:97K smpl:774K ep:3K epch:62.81 loss:0.011 grdn:0.197 lr:2.7e-07 updt_s:0.065 data_s:0.020
|
| 501 |
+
INFO 2025-11-18 04:08:58 ts/train.py:232 step:97K smpl:776K ep:3K epch:62.94 loss:0.011 grdn:0.197 lr:2.4e-07 updt_s:0.065 data_s:0.024
|
| 502 |
+
INFO 2025-11-18 04:09:17 ts/train.py:232 step:97K smpl:778K ep:3K epch:63.07 loss:0.011 grdn:0.180 lr:2.1e-07 updt_s:0.065 data_s:0.025
|
| 503 |
+
INFO 2025-11-18 04:09:35 ts/train.py:232 step:97K smpl:779K ep:3K epch:63.20 loss:0.012 grdn:0.200 lr:1.8e-07 updt_s:0.065 data_s:0.025
|
| 504 |
+
INFO 2025-11-18 04:09:53 ts/train.py:232 step:98K smpl:781K ep:3K epch:63.33 loss:0.011 grdn:0.204 lr:1.6e-07 updt_s:0.065 data_s:0.028
|
| 505 |
+
INFO 2025-11-18 04:10:12 ts/train.py:232 step:98K smpl:782K ep:3K epch:63.45 loss:0.011 grdn:0.188 lr:1.3e-07 updt_s:0.065 data_s:0.027
|
| 506 |
+
INFO 2025-11-18 04:10:30 ts/train.py:232 step:98K smpl:784K ep:3K epch:63.58 loss:0.011 grdn:0.190 lr:1.1e-07 updt_s:0.066 data_s:0.026
|
| 507 |
+
INFO 2025-11-18 04:10:48 ts/train.py:232 step:98K smpl:786K ep:3K epch:63.71 loss:0.011 grdn:0.190 lr:9.0e-08 updt_s:0.065 data_s:0.025
|
| 508 |
+
INFO 2025-11-18 04:11:07 ts/train.py:232 step:98K smpl:787K ep:3K epch:63.84 loss:0.012 grdn:0.198 lr:7.2e-08 updt_s:0.066 data_s:0.027
|
| 509 |
+
INFO 2025-11-18 04:11:28 ts/train.py:232 step:99K smpl:789K ep:3K epch:63.97 loss:0.012 grdn:0.194 lr:5.6e-08 updt_s:0.064 data_s:0.038
|
| 510 |
+
INFO 2025-11-18 04:11:46 ts/train.py:232 step:99K smpl:790K ep:3K epch:64.10 loss:0.012 grdn:0.195 lr:4.2e-08 updt_s:0.065 data_s:0.028
|
| 511 |
+
INFO 2025-11-18 04:12:05 ts/train.py:232 step:99K smpl:792K ep:3K epch:64.23 loss:0.011 grdn:0.190 lr:3.0e-08 updt_s:0.065 data_s:0.026
|
| 512 |
+
INFO 2025-11-18 04:12:23 ts/train.py:232 step:99K smpl:794K ep:3K epch:64.36 loss:0.011 grdn:0.189 lr:2.0e-08 updt_s:0.065 data_s:0.029
|
| 513 |
+
INFO 2025-11-18 04:12:42 ts/train.py:232 step:99K smpl:795K ep:3K epch:64.49 loss:0.012 grdn:0.193 lr:1.2e-08 updt_s:0.065 data_s:0.027
|
| 514 |
+
INFO 2025-11-18 04:13:00 ts/train.py:232 step:100K smpl:797K ep:3K epch:64.62 loss:0.011 grdn:0.190 lr:6.3e-09 updt_s:0.065 data_s:0.026
|
| 515 |
+
INFO 2025-11-18 04:13:18 ts/train.py:232 step:100K smpl:798K ep:3K epch:64.75 loss:0.012 grdn:0.200 lr:2.3e-09 updt_s:0.064 data_s:0.025
|
| 516 |
+
INFO 2025-11-18 04:13:36 ts/train.py:232 step:100K smpl:800K ep:4K epch:64.88 loss:0.012 grdn:0.195 lr:3.3e-10 updt_s:0.065 data_s:0.024
|
| 517 |
+
INFO 2025-11-18 04:13:36 ts/train.py:241 Checkpoint policy after step 100000
|
| 518 |
+
INFO 2025-11-18 04:13:53 ts/train.py:283 End of training
|
diffusion_anubis_put_into_pot/wandb/run-20251118_013827-yx7en6s6/files/requirements.txt
ADDED
|
@@ -0,0 +1,264 @@
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|
| 1 |
+
setuptools==79.0.0
|
| 2 |
+
wheel==0.45.1
|
| 3 |
+
pip==25.0.1
|
| 4 |
+
wcwidth==0.2.13
|
| 5 |
+
triton==3.2.0
|
| 6 |
+
pytz==2025.2
|
| 7 |
+
nvidia-cusparselt-cu12==0.6.2
|
| 8 |
+
mpmath==1.3.0
|
| 9 |
+
Farama-Notifications==0.0.4
|
| 10 |
+
asciitree==0.3.3
|
| 11 |
+
antlr4-python3-runtime==4.9.3
|
| 12 |
+
zipp==3.21.0
|
| 13 |
+
xxhash==3.5.0
|
| 14 |
+
urllib3==2.4.0
|
| 15 |
+
tzdata==2025.2
|
| 16 |
+
typing_extensions==4.13.2
|
| 17 |
+
tqdm==4.67.1
|
| 18 |
+
uv==0.7.3
|
| 19 |
+
toml==0.10.2
|
| 20 |
+
termcolor==3.0.1
|
| 21 |
+
sympy==1.13.1
|
| 22 |
+
soupsieve==2.7
|
| 23 |
+
smmap==5.0.2
|
| 24 |
+
six==1.17.0
|
| 25 |
+
setproctitle==1.3.5
|
| 26 |
+
safetensors==0.5.3
|
| 27 |
+
regex==2024.11.6
|
| 28 |
+
pyzmq==26.4.0
|
| 29 |
+
PyYAML==6.0.2
|
| 30 |
+
PySocks==1.7.1
|
| 31 |
+
pycparser==2.22
|
| 32 |
+
pyarrow==19.0.1
|
| 33 |
+
pyarrow==19.0.1
|
| 34 |
+
psutil==7.0.0
|
| 35 |
+
protobuf==4.21.12
|
| 36 |
+
propcache==0.3.1
|
| 37 |
+
prompt_toolkit==3.0.51
|
| 38 |
+
platformdirs==4.3.7
|
| 39 |
+
pillow==11.2.1
|
| 40 |
+
pillow==11.1.0
|
| 41 |
+
pfzy==0.3.4
|
| 42 |
+
packaging==25.0
|
| 43 |
+
orderly-set==5.4.0
|
| 44 |
+
nvidia-nvtx-cu12==12.4.127
|
| 45 |
+
nvidia-nvjitlink-cu12==12.4.127
|
| 46 |
+
nvidia-nccl-cu12==2.21.5
|
| 47 |
+
nvidia-curand-cu12==10.3.5.147
|
| 48 |
+
nvidia-cufft-cu12==11.2.1.3
|
| 49 |
+
nvidia-cuda-runtime-cu12==12.4.127
|
| 50 |
+
nvidia-cuda-nvrtc-cu12==12.4.127
|
| 51 |
+
nvidia-cuda-cupti-cu12==12.4.127
|
| 52 |
+
nvidia-cublas-cu12==12.4.5.8
|
| 53 |
+
networkx==3.4.2
|
| 54 |
+
mypy-extensions==1.0.0
|
| 55 |
+
mergedeep==1.3.4
|
| 56 |
+
MarkupSafe==3.0.2
|
| 57 |
+
llvmlite==0.44.0
|
| 58 |
+
itsdangerous==2.2.0
|
| 59 |
+
imageio-ffmpeg==0.6.0
|
| 60 |
+
idna==3.10
|
| 61 |
+
hf_transfer==0.1.9
|
| 62 |
+
fsspec==2024.12.0
|
| 63 |
+
frozenlist==1.6.0
|
| 64 |
+
filelock==3.18.0
|
| 65 |
+
fasteners==0.19
|
| 66 |
+
evdev==1.9.1
|
| 67 |
+
einops==0.8.1
|
| 68 |
+
dill==0.3.8
|
| 69 |
+
cmake==4.0.0
|
| 70 |
+
cloudpickle==3.1.1
|
| 71 |
+
click==8.1.8
|
| 72 |
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| 73 |
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| 74 |
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|
| 75 |
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av==14.3.0
|
| 76 |
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| 77 |
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| 78 |
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| 87 |
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| 88 |
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| 89 |
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| 93 |
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torch==2.6.0
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torchvision==0.21.0
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dm-tree==0.1.9
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dm-env==1.6
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ptyprocess==0.7.0
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pure_eval==0.2.3
|
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|
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boto==2.49.0
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httplib2==0.20.4
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dm_control==1.0.21
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tensorflow-io-gcs-filesystem==0.37.1
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numpy==2.1.3
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tensorflow-metadata==1.17.1
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tensorboard==2.19.0
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markdown-it-py==3.0.0
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rich==14.0.0
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keras==3.9.2
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array_record==0.7.1
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tensorflow==2.19.0
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tensorflow-datasets==4.9.8
|
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tifffile==2025.3.30
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shapely==2.1.0
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pygame==2.6.1
|
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opencv-python==4.11.0.86
|
| 217 |
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lazy_loader==0.4
|
| 218 |
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scikit-image==0.25.2
|
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gym-pusht==0.1.5
|
| 220 |
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gdown==5.2.0
|
| 221 |
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pluggy==1.5.0
|
| 222 |
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iniconfig==2.1.0
|
| 223 |
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pytest==8.3.5
|
| 224 |
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iso8601==2.1.0
|
| 225 |
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future==1.0.0
|
| 226 |
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pyserial==3.5
|
| 227 |
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draccus==0.10.0
|
| 228 |
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transformers==4.51.3
|
| 229 |
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lerobot==0.1.0
|
| 230 |
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bottle==0.12.25
|
| 231 |
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waitress==3.0.2
|
| 232 |
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accelerate==1.6.0
|
| 233 |
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TorchCodec==0.2.1
|
| 234 |
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kiwisolver==1.4.9
|
| 235 |
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fonttools==4.59.2
|
| 236 |
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cycler==0.12.1
|
| 237 |
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contourpy==1.3.2
|
| 238 |
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matplotlib==3.10.6
|
| 239 |
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typer-slim==0.20.0
|
| 240 |
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sniffio==1.3.1
|
| 241 |
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shellingham==1.5.4
|
| 242 |
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hf-xet==1.2.0
|
| 243 |
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h11==0.16.0
|
| 244 |
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httpcore==1.0.9
|
| 245 |
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anyio==4.11.0
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| 246 |
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httpx==0.28.1
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| 247 |
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huggingface-hub==0.36.0
|
| 248 |
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tabletop_sim==0.0.0
|
| 249 |
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autocommand==2.2.2
|
| 250 |
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backports.tarfile==1.2.0
|
| 251 |
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importlib_metadata==8.0.0
|
| 252 |
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inflect==7.3.1
|
| 253 |
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jaraco.collections==5.1.0
|
| 254 |
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jaraco.context==5.3.0
|
| 255 |
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jaraco.functools==4.0.1
|
| 256 |
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jaraco.text==3.12.1
|
| 257 |
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more-itertools==10.3.0
|
| 258 |
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packaging==24.2
|
| 259 |
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platformdirs==4.2.2
|
| 260 |
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tomli==2.0.1
|
| 261 |
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typeguard==4.3.0
|
| 262 |
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typing_extensions==4.12.2
|
| 263 |
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wheel==0.45.1
|
| 264 |
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zipp==3.19.2
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diffusion_anubis_put_into_pot/wandb/run-20251118_013827-yx7en6s6/files/wandb-metadata.json
ADDED
|
@@ -0,0 +1,98 @@
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|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
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|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
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{
|
| 2 |
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"os": "Linux-4.18.0-477.10.1.el8_8.x86_64-x86_64-with-glibc2.28",
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| 3 |
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| 4 |
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"startedAt": "2025-11-17T16:38:27.861044Z",
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| 5 |
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|
| 6 |
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"--policy.type=diffusion",
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| 7 |
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"--num_workers=2",
|
| 8 |
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"--dataset.repo_id=anubis_put_into_pot__lerobot",
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| 9 |
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"--dataset.root=/data1/euijinrnd/hf_home_euijin/lerobot/lerobot/anubis_put_into_pot__lerobot",
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| 10 |
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| 11 |
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"--batch_size=8",
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| 12 |
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"--resume",
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| 13 |
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"false",
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| 14 |
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"--wandb.disable_artifact",
|
| 15 |
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"true"
|
| 16 |
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],
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| 17 |
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"program": "/home/euijinrnd/workspace/lerobot/lerobot/scripts/train.py",
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| 18 |
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"codePath": "lerobot/scripts/train.py",
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| 19 |
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"git": {
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| 20 |
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"remote": "https://github.com/huggingface/lerobot.git",
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| 21 |
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"commit": "8cfab3882480bdde38e42d93a9752de5ed42cae2"
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| 22 |
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},
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| 23 |
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"root": "outputs/train/2025-11-18/01-38-26_diffusion",
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| 24 |
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"host": "node01",
|
| 25 |
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"executable": "/home/euijinrnd/anaconda3/envs/lerobot/bin/python",
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| 26 |
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| 27 |
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| 28 |
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| 29 |
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"gpu": "NVIDIA L40S",
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| 30 |
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| 31 |
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"/": {
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| 33 |
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| 40 |
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| 41 |
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| 42 |
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| 44 |
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| 45 |
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{
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| 46 |
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| 47 |
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| 48 |
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|
| 49 |
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"architecture": "Ada"
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| 50 |
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}
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| 51 |
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],
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| 52 |
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| 53 |
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"cluster_name": "cluster",
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| 54 |
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"conf": "/etc/slurm/slurm.conf",
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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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"job_id": "16534",
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| 62 |
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"job_name": "python",
|
| 63 |
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"job_nodelist": "node01",
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| 64 |
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"job_num_nodes": "1",
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| 65 |
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"job_partition": "debug",
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| 66 |
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"job_uid": "1013",
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| 67 |
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"job_user": "euijinrnd",
|
| 68 |
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"jobid": "16534",
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| 69 |
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"launch_node_ipaddr": "172.20.1.100",
|
| 70 |
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"localid": "0",
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| 71 |
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| 72 |
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"nodeid": "0",
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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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"srun_comm_host": "172.20.1.100",
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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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"step_num_tasks": "1",
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| 86 |
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"step_tasks_per_node": "1",
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| 87 |
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"stepid": "0",
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| 88 |
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"submit_dir": "/home/euijinrnd/workspace/lerobot",
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| 89 |
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"submit_host": "node100",
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| 90 |
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"task_pid": "2405533",
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| 91 |
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| 92 |
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"topology_addr": "node01",
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| 93 |
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"topology_addr_pattern": "node",
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| 94 |
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| 95 |
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| 96 |
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},
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| 97 |
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"cudaVersion": "12.2"
|
| 98 |
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}
|
diffusion_anubis_put_into_pot/wandb/run-20251118_013827-yx7en6s6/files/wandb-summary.json
ADDED
|
@@ -0,0 +1 @@
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|
|
|
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|
| 1 |
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{"_wandb":{"runtime":9326},"train/loss":0.011827715162071399,"train/lr":3.298127591122574e-10,"train/steps":100000,"train/dataloading_s":0.023962713899090885,"_step":100000,"_timestamp":1.7634068164367812e+09,"train/grad_norm":0.19460559783503414,"train/update_s":0.0645534756151028,"_runtime":9326.614516114,"train/samples":800000,"train/episodes":3503.6496350364964,"train/epochs":64.882400648824}
|
diffusion_anubis_put_into_pot/wandb/run-20251118_013827-yx7en6s6/logs/debug-core.log
ADDED
|
@@ -0,0 +1,13 @@
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|
|
|
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|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{"time":"2025-11-18T01:38:27.655785759+09:00","level":"INFO","msg":"main: starting server","port-filename":"/tmp/tmpp6_9fd31/port-2405533.txt","pid":2405533,"log-level":0,"disable-analytics":false,"shutdown-on-parent-exit":false}
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| 2 |
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{"time":"2025-11-18T01:38:27.65630062+09:00","level":"INFO","msg":"Will exit if parent process dies.","ppid":2405533}
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| 3 |
+
{"time":"2025-11-18T01:38:27.656302623+09:00","level":"INFO","msg":"server is running","addr":{"IP":"127.0.0.1","Port":43333,"Zone":""}}
|
| 4 |
+
{"time":"2025-11-18T01:38:27.847301425+09:00","level":"INFO","msg":"connection: ManageConnectionData: new connection created","id":"127.0.0.1:56242"}
|
| 5 |
+
{"time":"2025-11-18T01:38:27.861781377+09:00","level":"INFO","msg":"handleInformInit: received","streamId":"yx7en6s6","id":"127.0.0.1:56242"}
|
| 6 |
+
{"time":"2025-11-18T01:38:28.164986544+09:00","level":"INFO","msg":"handleInformInit: stream started","streamId":"yx7en6s6","id":"127.0.0.1:56242"}
|
| 7 |
+
{"time":"2025-11-18T04:13:54.475242297+09:00","level":"INFO","msg":"handleInformTeardown: server teardown initiated","id":"127.0.0.1:56242"}
|
| 8 |
+
{"time":"2025-11-18T04:13:54.475485171+09:00","level":"INFO","msg":"connection: closing","id":"127.0.0.1:56242"}
|
| 9 |
+
{"time":"2025-11-18T04:13:54.475553374+09:00","level":"INFO","msg":"connection: closed successfully","id":"127.0.0.1:56242"}
|
| 10 |
+
{"time":"2025-11-18T04:13:54.475558972+09:00","level":"INFO","msg":"server is shutting down"}
|
| 11 |
+
{"time":"2025-11-18T04:13:55.650977967+09:00","level":"INFO","msg":"handleInformTeardown: server shutdown complete","id":"127.0.0.1:56242"}
|
| 12 |
+
{"time":"2025-11-18T04:13:55.65099338+09:00","level":"INFO","msg":"connection: ManageConnectionData: connection closed","id":"127.0.0.1:56242"}
|
| 13 |
+
{"time":"2025-11-18T04:13:55.651003054+09:00","level":"INFO","msg":"server is closed"}
|
diffusion_anubis_put_into_pot/wandb/run-20251118_013827-yx7en6s6/logs/debug-internal.log
ADDED
|
@@ -0,0 +1,15 @@
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|
|
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|
|
|
|
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|
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|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{"time":"2025-11-18T01:38:27.86226386+09:00","level":"INFO","msg":"stream: starting","core version":"0.19.9","symlink path":"outputs/train/2025-11-18/01-38-26_diffusion/wandb/run-20251118_013827-yx7en6s6/logs/debug-core.log"}
|
| 2 |
+
{"time":"2025-11-18T01:38:28.164948557+09:00","level":"INFO","msg":"created new stream","id":"yx7en6s6"}
|
| 3 |
+
{"time":"2025-11-18T01:38:28.164982138+09:00","level":"INFO","msg":"stream: started","id":"yx7en6s6"}
|
| 4 |
+
{"time":"2025-11-18T01:38:28.164994967+09:00","level":"INFO","msg":"handler: started","stream_id":"yx7en6s6"}
|
| 5 |
+
{"time":"2025-11-18T01:38:28.165018842+09:00","level":"INFO","msg":"sender: started","stream_id":"yx7en6s6"}
|
| 6 |
+
{"time":"2025-11-18T01:38:28.165033154+09:00","level":"INFO","msg":"writer: Do: started","stream_id":"yx7en6s6"}
|
| 7 |
+
{"time":"2025-11-18T01:38:28.632818175+09:00","level":"INFO","msg":"Starting system monitor"}
|
| 8 |
+
{"time":"2025-11-18T04:13:54.475529708+09:00","level":"INFO","msg":"stream: closing","id":"yx7en6s6"}
|
| 9 |
+
{"time":"2025-11-18T04:13:54.47557102+09:00","level":"INFO","msg":"Stopping system monitor"}
|
| 10 |
+
{"time":"2025-11-18T04:13:54.475653333+09:00","level":"INFO","msg":"Stopped system monitor"}
|
| 11 |
+
{"time":"2025-11-18T04:13:55.330036373+09:00","level":"INFO","msg":"fileTransfer: Close: file transfer manager closed"}
|
| 12 |
+
{"time":"2025-11-18T04:13:55.650223156+09:00","level":"INFO","msg":"handler: closed","stream_id":"yx7en6s6"}
|
| 13 |
+
{"time":"2025-11-18T04:13:55.650251138+09:00","level":"INFO","msg":"writer: Close: closed","stream_id":"yx7en6s6"}
|
| 14 |
+
{"time":"2025-11-18T04:13:55.65025934+09:00","level":"INFO","msg":"sender: closed","stream_id":"yx7en6s6"}
|
| 15 |
+
{"time":"2025-11-18T04:13:55.650702114+09:00","level":"INFO","msg":"stream: closed","id":"yx7en6s6"}
|
diffusion_anubis_put_into_pot/wandb/run-20251118_013827-yx7en6s6/logs/debug.log
ADDED
|
@@ -0,0 +1,23 @@
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|
| 1 |
+
2025-11-18 01:38:27,856 INFO MainThread:2405533 [wandb_setup.py:_flush():67] Current SDK version is 0.19.9
|
| 2 |
+
2025-11-18 01:38:27,857 INFO MainThread:2405533 [wandb_setup.py:_flush():67] Configure stats pid to 2405533
|
| 3 |
+
2025-11-18 01:38:27,857 INFO MainThread:2405533 [wandb_setup.py:_flush():67] Loading settings from /home/euijinrnd/.config/wandb/settings
|
| 4 |
+
2025-11-18 01:38:27,857 INFO MainThread:2405533 [wandb_setup.py:_flush():67] Loading settings from /home/euijinrnd/workspace/lerobot/wandb/settings
|
| 5 |
+
2025-11-18 01:38:27,857 INFO MainThread:2405533 [wandb_setup.py:_flush():67] Loading settings from environment variables
|
| 6 |
+
2025-11-18 01:38:27,857 INFO MainThread:2405533 [wandb_init.py:setup_run_log_directory():662] Logging user logs to outputs/train/2025-11-18/01-38-26_diffusion/wandb/run-20251118_013827-yx7en6s6/logs/debug.log
|
| 7 |
+
2025-11-18 01:38:27,857 INFO MainThread:2405533 [wandb_init.py:setup_run_log_directory():663] Logging internal logs to outputs/train/2025-11-18/01-38-26_diffusion/wandb/run-20251118_013827-yx7en6s6/logs/debug-internal.log
|
| 8 |
+
2025-11-18 01:38:27,857 INFO MainThread:2405533 [wandb_init.py:init():781] calling init triggers
|
| 9 |
+
2025-11-18 01:38:27,857 INFO MainThread:2405533 [wandb_init.py:init():786] wandb.init called with sweep_config: {}
|
| 10 |
+
config: {'dataset': {'repo_id': 'anubis_put_into_pot__lerobot', 'root': '/data1/euijinrnd/hf_home_euijin/lerobot/lerobot/anubis_put_into_pot__lerobot', 'episodes': None, 'image_transforms': {'enable': False, 'max_num_transforms': 3, 'random_order': False, 'tfs': {'brightness': {'weight': 1.0, 'type': 'ColorJitter', 'kwargs': {'brightness': [0.8, 1.2]}}, 'contrast': {'weight': 1.0, 'type': 'ColorJitter', 'kwargs': {'contrast': [0.8, 1.2]}}, 'saturation': {'weight': 1.0, 'type': 'ColorJitter', 'kwargs': {'saturation': [0.5, 1.5]}}, 'hue': {'weight': 1.0, 'type': 'ColorJitter', 'kwargs': {'hue': [-0.05, 0.05]}}, 'sharpness': {'weight': 1.0, 'type': 'SharpnessJitter', 'kwargs': {'sharpness': [0.5, 1.5]}}}}, 'revision': None, 'use_imagenet_stats': True, 'video_backend': 'torchcodec'}, 'env': None, 'policy': {'type': 'diffusion', 'n_obs_steps': 2, 'normalization_mapping': {'VISUAL': <NormalizationMode.MEAN_STD: 'MEAN_STD'>, 'STATE': <NormalizationMode.MIN_MAX: 'MIN_MAX'>, 'ACTION': <NormalizationMode.MIN_MAX: 'MIN_MAX'>}, 'input_features': {}, 'output_features': {}, 'device': 'cuda', 'use_amp': False, 'horizon': 16, 'n_action_steps': 8, 'drop_n_last_frames': 7, 'vision_backbone': 'resnet18', 'crop_shape': [84, 84], 'crop_is_random': True, 'pretrained_backbone_weights': None, 'use_group_norm': True, 'spatial_softmax_num_keypoints': 32, 'use_separate_rgb_encoder_per_camera': False, 'down_dims': [512, 1024, 2048], 'kernel_size': 5, 'n_groups': 8, 'diffusion_step_embed_dim': 128, 'use_film_scale_modulation': True, 'noise_scheduler_type': 'DDPM', 'num_train_timesteps': 100, 'beta_schedule': 'squaredcos_cap_v2', 'beta_start': 0.0001, 'beta_end': 0.02, 'prediction_type': 'epsilon', 'clip_sample': True, 'clip_sample_range': 1.0, 'num_inference_steps': None, 'do_mask_loss_for_padding': False, 'optimizer_lr': 0.0001, 'optimizer_betas': [0.95, 0.999], 'optimizer_eps': 1e-08, 'optimizer_weight_decay': 1e-06, 'scheduler_name': 'cosine', 'scheduler_warmup_steps': 500}, 'output_dir': 'outputs/train/2025-11-18/01-38-26_diffusion', 'job_name': 'diffusion', 'resume': False, 'seed': 1000, 'num_workers': 2, 'batch_size': 8, 'steps': 100000, 'eval_freq': 20000, 'log_freq': 200, 'save_checkpoint': True, 'save_freq': 20000, 'use_policy_training_preset': True, 'optimizer': {'type': 'adam', 'lr': 0.0001, 'weight_decay': 1e-06, 'grad_clip_norm': 10.0, 'betas': [0.95, 0.999], 'eps': 1e-08}, 'scheduler': {'type': 'diffuser', 'num_warmup_steps': 500, 'name': 'cosine'}, 'eval': {'n_episodes': 50, 'batch_size': 50, 'use_async_envs': False}, 'wandb': {'enable': True, 'disable_artifact': True, 'project': 'lerobot', 'entity': None, 'notes': None, 'run_id': None, 'mode': None}, '_wandb': {}}
|
| 11 |
+
2025-11-18 01:38:27,857 INFO MainThread:2405533 [wandb_init.py:init():809] starting backend
|
| 12 |
+
2025-11-18 01:38:27,857 INFO MainThread:2405533 [wandb_init.py:init():813] sending inform_init request
|
| 13 |
+
2025-11-18 01:38:27,860 INFO MainThread:2405533 [backend.py:_multiprocessing_setup():101] multiprocessing start_methods=fork,spawn,forkserver, using: spawn
|
| 14 |
+
2025-11-18 01:38:27,860 INFO MainThread:2405533 [wandb_init.py:init():823] backend started and connected
|
| 15 |
+
2025-11-18 01:38:27,863 INFO MainThread:2405533 [wandb_init.py:init():915] updated telemetry
|
| 16 |
+
2025-11-18 01:38:27,924 INFO MainThread:2405533 [wandb_init.py:init():939] communicating run to backend with 90.0 second timeout
|
| 17 |
+
2025-11-18 01:38:28,621 INFO MainThread:2405533 [wandb_init.py:init():1014] starting run threads in backend
|
| 18 |
+
2025-11-18 01:38:29,206 INFO MainThread:2405533 [wandb_run.py:_console_start():2454] atexit reg
|
| 19 |
+
2025-11-18 01:38:29,207 INFO MainThread:2405533 [wandb_run.py:_redirect():2306] redirect: wrap_raw
|
| 20 |
+
2025-11-18 01:38:29,207 INFO MainThread:2405533 [wandb_run.py:_redirect():2371] Wrapping output streams.
|
| 21 |
+
2025-11-18 01:38:29,207 INFO MainThread:2405533 [wandb_run.py:_redirect():2394] Redirects installed.
|
| 22 |
+
2025-11-18 01:38:29,209 INFO MainThread:2405533 [wandb_init.py:init():1056] run started, returning control to user process
|
| 23 |
+
2025-11-18 04:13:54,474 INFO MsgRouterThr:2405533 [mailbox.py:close():129] [no run ID] Closing mailbox, abandoning 1 handles.
|
diffusion_anubis_put_into_pot/wandb/run-20251118_013827-yx7en6s6/run-yx7en6s6.wandb
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
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| 2 |
+
oid sha256:a7105b432beef282cea53d3501b9e49e67a60f88d2de160554bcee5d265c484a
|
| 3 |
+
size 1054711
|