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Browse files- .gitattributes +1 -0
- scale_40_finetune_fastvggt_default/2025-09-26/16-33-33_libero_40%_fastvggt_pre_embed_60k/checkpoints/060000/pretrained_model/config.json +123 -0
- scale_40_finetune_fastvggt_default/2025-09-26/16-33-33_libero_40%_fastvggt_pre_embed_60k/checkpoints/060000/pretrained_model/model.safetensors +3 -0
- scale_40_finetune_fastvggt_default/2025-09-26/16-33-33_libero_40%_fastvggt_pre_embed_60k/checkpoints/060000/pretrained_model/train_config.json +316 -0
- scale_40_finetune_fastvggt_default/2025-09-26/16-33-33_libero_40%_fastvggt_pre_embed_60k/checkpoints/060000/training_state/optimizer_param_groups.json +810 -0
- scale_40_finetune_fastvggt_default/2025-09-26/16-33-33_libero_40%_fastvggt_pre_embed_60k/checkpoints/060000/training_state/optimizer_state.safetensors +3 -0
- scale_40_finetune_fastvggt_default/2025-09-26/16-33-33_libero_40%_fastvggt_pre_embed_60k/checkpoints/060000/training_state/rng_state.safetensors +3 -0
- scale_40_finetune_fastvggt_default/2025-09-26/16-33-33_libero_40%_fastvggt_pre_embed_60k/checkpoints/060000/training_state/scheduler_state.json +15 -0
- scale_40_finetune_fastvggt_default/2025-09-26/16-33-33_libero_40%_fastvggt_pre_embed_60k/checkpoints/060000/training_state/training_step.json +3 -0
- scale_40_finetune_fastvggt_default/2025-09-26/16-33-33_libero_40%_fastvggt_pre_embed_60k/wandb/debug-internal.log +13 -0
- scale_40_finetune_fastvggt_default/2025-09-26/16-33-33_libero_40%_fastvggt_pre_embed_60k/wandb/debug.log +23 -0
- scale_40_finetune_fastvggt_default/2025-09-26/16-33-33_libero_40%_fastvggt_pre_embed_60k/wandb/run-20250926_163345-t5anomje/files/config.yaml +264 -0
- scale_40_finetune_fastvggt_default/2025-09-26/16-33-33_libero_40%_fastvggt_pre_embed_60k/wandb/run-20250926_163345-t5anomje/files/output.log +635 -0
- scale_40_finetune_fastvggt_default/2025-09-26/16-33-33_libero_40%_fastvggt_pre_embed_60k/wandb/run-20250926_163345-t5anomje/files/requirements.txt +229 -0
- scale_40_finetune_fastvggt_default/2025-09-26/16-33-33_libero_40%_fastvggt_pre_embed_60k/wandb/run-20250926_163345-t5anomje/files/wandb-metadata.json +39 -0
- scale_40_finetune_fastvggt_default/2025-09-26/16-33-33_libero_40%_fastvggt_pre_embed_60k/wandb/run-20250926_163345-t5anomje/files/wandb-summary.json +1 -0
- scale_40_finetune_fastvggt_default/2025-09-26/16-33-33_libero_40%_fastvggt_pre_embed_60k/wandb/run-20250926_163345-t5anomje/logs/debug-core.log +15 -0
- scale_40_finetune_fastvggt_default/2025-09-26/16-33-33_libero_40%_fastvggt_pre_embed_60k/wandb/run-20250926_163345-t5anomje/logs/debug-internal.log +13 -0
- scale_40_finetune_fastvggt_default/2025-09-26/16-33-33_libero_40%_fastvggt_pre_embed_60k/wandb/run-20250926_163345-t5anomje/logs/debug.log +23 -0
- scale_40_finetune_fastvggt_default/2025-09-26/16-33-33_libero_40%_fastvggt_pre_embed_60k/wandb/run-20250926_163345-t5anomje/run-t5anomje.wandb +3 -0
.gitattributes
CHANGED
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@@ -63,3 +63,4 @@ scale_40_finetune_vggt_default/2025-09-14/09-50-29_libero_40%_vggt_pre_embed_60k
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scale_40_finetune_vggt_default/2025-09-14/09-50-29_libero_40%_vggt_pre_embed_60k/wandb/run-20250914_095043-z16zg7mm/run-z16zg7mm.wandb filter=lfs diff=lfs merge=lfs -text
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scale_40_finetune_vggt_add_on_key_value/2025-09-20/13-16-41_libero_40%_vggt_pre_embed_add_on_key_value_60k/wandb/run-20250920_131653-tx4khomx/run-tx4khomx.wandb filter=lfs diff=lfs merge=lfs -text
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scale_40_finetune_vggt_add_on_key_value_with_project_on_key/2025-09-21/16-20-41_libero_40%_vggt_pre_embed_add_on_key_value_with_project_on_key_60k/wandb/run-20250921_162052-9z5o8xr3/run-9z5o8xr3.wandb filter=lfs diff=lfs merge=lfs -text
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scale_40_finetune_vggt_default/2025-09-14/09-50-29_libero_40%_vggt_pre_embed_60k/wandb/run-20250914_095043-z16zg7mm/run-z16zg7mm.wandb filter=lfs diff=lfs merge=lfs -text
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scale_40_finetune_vggt_add_on_key_value/2025-09-20/13-16-41_libero_40%_vggt_pre_embed_add_on_key_value_60k/wandb/run-20250920_131653-tx4khomx/run-tx4khomx.wandb filter=lfs diff=lfs merge=lfs -text
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scale_40_finetune_vggt_add_on_key_value_with_project_on_key/2025-09-21/16-20-41_libero_40%_vggt_pre_embed_add_on_key_value_with_project_on_key_60k/wandb/run-20250921_162052-9z5o8xr3/run-9z5o8xr3.wandb filter=lfs diff=lfs merge=lfs -text
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scale_40_finetune_fastvggt_default/2025-09-26/16-33-33_libero_40%_fastvggt_pre_embed_60k/wandb/run-20250926_163345-t5anomje/run-t5anomje.wandb filter=lfs diff=lfs merge=lfs -text
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scale_40_finetune_fastvggt_default/2025-09-26/16-33-33_libero_40%_fastvggt_pre_embed_60k/checkpoints/060000/pretrained_model/config.json
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scale_40_finetune_fastvggt_default/2025-09-26/16-33-33_libero_40%_fastvggt_pre_embed_60k/checkpoints/060000/pretrained_model/model.safetensors
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version https://git-lfs.github.com/spec/v1
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size 7536023464
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scale_40_finetune_fastvggt_default/2025-09-26/16-33-33_libero_40%_fastvggt_pre_embed_60k/checkpoints/060000/pretrained_model/train_config.json
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scale_40_finetune_fastvggt_default/2025-09-26/16-33-33_libero_40%_fastvggt_pre_embed_60k/checkpoints/060000/training_state/optimizer_param_groups.json
ADDED
|
@@ -0,0 +1,810 @@
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|
|
|
| 1 |
+
[
|
| 2 |
+
{
|
| 3 |
+
"lr": 2.5e-06,
|
| 4 |
+
"betas": [
|
| 5 |
+
0.9,
|
| 6 |
+
0.95
|
| 7 |
+
],
|
| 8 |
+
"eps": 1e-08,
|
| 9 |
+
"weight_decay": 1e-10,
|
| 10 |
+
"amsgrad": false,
|
| 11 |
+
"maximize": false,
|
| 12 |
+
"foreach": null,
|
| 13 |
+
"capturable": false,
|
| 14 |
+
"differentiable": false,
|
| 15 |
+
"fused": null,
|
| 16 |
+
"decoupled_weight_decay": true,
|
| 17 |
+
"initial_lr": 0.0001,
|
| 18 |
+
"params": [
|
| 19 |
+
0,
|
| 20 |
+
1,
|
| 21 |
+
2,
|
| 22 |
+
3,
|
| 23 |
+
4,
|
| 24 |
+
5,
|
| 25 |
+
6,
|
| 26 |
+
7,
|
| 27 |
+
8,
|
| 28 |
+
9,
|
| 29 |
+
10,
|
| 30 |
+
11,
|
| 31 |
+
12,
|
| 32 |
+
13,
|
| 33 |
+
14,
|
| 34 |
+
15,
|
| 35 |
+
16,
|
| 36 |
+
17,
|
| 37 |
+
18,
|
| 38 |
+
19,
|
| 39 |
+
20,
|
| 40 |
+
21,
|
| 41 |
+
22,
|
| 42 |
+
23,
|
| 43 |
+
24,
|
| 44 |
+
25,
|
| 45 |
+
26,
|
| 46 |
+
27,
|
| 47 |
+
28,
|
| 48 |
+
29,
|
| 49 |
+
30,
|
| 50 |
+
31,
|
| 51 |
+
32,
|
| 52 |
+
33,
|
| 53 |
+
34,
|
| 54 |
+
35,
|
| 55 |
+
36,
|
| 56 |
+
37,
|
| 57 |
+
38,
|
| 58 |
+
39,
|
| 59 |
+
40,
|
| 60 |
+
41,
|
| 61 |
+
42,
|
| 62 |
+
43,
|
| 63 |
+
44,
|
| 64 |
+
45,
|
| 65 |
+
46,
|
| 66 |
+
47,
|
| 67 |
+
48,
|
| 68 |
+
49,
|
| 69 |
+
50,
|
| 70 |
+
51,
|
| 71 |
+
52,
|
| 72 |
+
53,
|
| 73 |
+
54,
|
| 74 |
+
55,
|
| 75 |
+
56,
|
| 76 |
+
57,
|
| 77 |
+
58,
|
| 78 |
+
59,
|
| 79 |
+
60,
|
| 80 |
+
61,
|
| 81 |
+
62,
|
| 82 |
+
63,
|
| 83 |
+
64,
|
| 84 |
+
65,
|
| 85 |
+
66,
|
| 86 |
+
67,
|
| 87 |
+
68,
|
| 88 |
+
69,
|
| 89 |
+
70,
|
| 90 |
+
71,
|
| 91 |
+
72,
|
| 92 |
+
73,
|
| 93 |
+
74,
|
| 94 |
+
75,
|
| 95 |
+
76,
|
| 96 |
+
77,
|
| 97 |
+
78,
|
| 98 |
+
79,
|
| 99 |
+
80,
|
| 100 |
+
81,
|
| 101 |
+
82,
|
| 102 |
+
83,
|
| 103 |
+
84,
|
| 104 |
+
85,
|
| 105 |
+
86,
|
| 106 |
+
87,
|
| 107 |
+
88,
|
| 108 |
+
89,
|
| 109 |
+
90,
|
| 110 |
+
91,
|
| 111 |
+
92,
|
| 112 |
+
93,
|
| 113 |
+
94,
|
| 114 |
+
95,
|
| 115 |
+
96,
|
| 116 |
+
97,
|
| 117 |
+
98,
|
| 118 |
+
99,
|
| 119 |
+
100,
|
| 120 |
+
101,
|
| 121 |
+
102,
|
| 122 |
+
103,
|
| 123 |
+
104,
|
| 124 |
+
105,
|
| 125 |
+
106,
|
| 126 |
+
107,
|
| 127 |
+
108,
|
| 128 |
+
109,
|
| 129 |
+
110,
|
| 130 |
+
111,
|
| 131 |
+
112,
|
| 132 |
+
113,
|
| 133 |
+
114,
|
| 134 |
+
115,
|
| 135 |
+
116,
|
| 136 |
+
117,
|
| 137 |
+
118,
|
| 138 |
+
119,
|
| 139 |
+
120,
|
| 140 |
+
121,
|
| 141 |
+
122,
|
| 142 |
+
123,
|
| 143 |
+
124,
|
| 144 |
+
125,
|
| 145 |
+
126,
|
| 146 |
+
127,
|
| 147 |
+
128,
|
| 148 |
+
129,
|
| 149 |
+
130,
|
| 150 |
+
131,
|
| 151 |
+
132,
|
| 152 |
+
133,
|
| 153 |
+
134,
|
| 154 |
+
135,
|
| 155 |
+
136,
|
| 156 |
+
137,
|
| 157 |
+
138,
|
| 158 |
+
139,
|
| 159 |
+
140,
|
| 160 |
+
141,
|
| 161 |
+
142,
|
| 162 |
+
143,
|
| 163 |
+
144,
|
| 164 |
+
145,
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scale_40_finetune_fastvggt_default/2025-09-26/16-33-33_libero_40%_fastvggt_pre_embed_60k/checkpoints/060000/training_state/training_step.json
ADDED
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scale_40_finetune_fastvggt_default/2025-09-26/16-33-33_libero_40%_fastvggt_pre_embed_60k/wandb/debug-internal.log
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{"time":"2025-09-26T16:33:46.109906398Z","level":"INFO","msg":"stream: starting","core version":"0.22.0"}
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scale_40_finetune_fastvggt_default/2025-09-26/16-33-33_libero_40%_fastvggt_pre_embed_60k/wandb/debug.log
ADDED
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2025-09-26 16:33:45,889 INFO MainThread:20875 [wandb_setup.py:_flush():81] Current SDK version is 0.22.0
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2025-09-26 16:33:45,889 INFO MainThread:20875 [wandb_setup.py:_flush():81] Loading settings from /workspace/nhan/VLA-Humanoid/wandb/settings
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2025-09-26 16:33:45,889 INFO MainThread:20875 [wandb_init.py:setup_run_log_directory():687] Logging internal logs to /data/outputs/scale_40_finetune_fastvggt_default/2025-09-26/16-33-33_libero_40%_fastvggt_pre_embed_60k/wandb/run-20250926_163345-t5anomje/logs/debug-internal.log
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2025-09-26 16:33:45,890 INFO MainThread:20875 [wandb_init.py:init():818] wandb.init called with sweep_config: {}
|
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|
| 11 |
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2025-09-26 16:33:45,890 INFO MainThread:20875 [wandb_init.py:init():861] starting backend
|
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2025-09-26 16:33:46,102 INFO MainThread:20875 [wandb_init.py:init():864] sending inform_init request
|
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|
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2025-09-26 16:33:46,110 INFO MainThread:20875 [wandb_init.py:init():942] updated telemetry
|
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2025-09-26 16:33:46,115 INFO MainThread:20875 [wandb_init.py:init():966] communicating run to backend with 90.0 second timeout
|
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2025-09-26 16:33:46,688 INFO MainThread:20875 [wandb_init.py:init():1017] starting run threads in backend
|
| 17 |
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2025-09-26 16:33:46,848 INFO MainThread:20875 [wandb_run.py:_console_start():2506] atexit reg
|
| 18 |
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2025-09-26 16:33:46,848 INFO MainThread:20875 [wandb_run.py:_redirect():2354] redirect: wrap_raw
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2025-09-26 16:33:46,848 INFO MainThread:20875 [wandb_run.py:_redirect():2423] Wrapping output streams.
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2025-09-26 16:33:46,853 INFO MainThread:20875 [wandb_init.py:init():1057] run started, returning control to user process
|
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2025-09-27 11:29:12,219 INFO wandb-AsyncioManager-main:20875 [service_client.py:_forward_responses():84] Reached EOF.
|
| 23 |
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2025-09-27 11:29:12,220 INFO wandb-AsyncioManager-main:20875 [mailbox.py:close():137] Closing mailbox, abandoning 1 handles.
|
scale_40_finetune_fastvggt_default/2025-09-26/16-33-33_libero_40%_fastvggt_pre_embed_60k/wandb/run-20250926_163345-t5anomje/files/config.yaml
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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|
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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: 0.22.0
|
| 4 |
+
e:
|
| 5 |
+
vo2etbmrr0x34p4sex2rt7yxq0lrkbcv:
|
| 6 |
+
args:
|
| 7 |
+
- --policy.path=/data/temp/baseline
|
| 8 |
+
- --dataset.root=/data/merged_libero_mask_depth_noops_lerobot_40
|
| 9 |
+
- --output_dir=/data/outputs/scale_40_finetune_fastvggt_default/2025-09-26/16-33-33_libero_40%_fastvggt_pre_embed_60k
|
| 10 |
+
- --job_name=libero_40%_fastvggt_pre_embed_60k
|
| 11 |
+
- --config_path=configs/libero_config/vggt.json
|
| 12 |
+
- --batch_size=14
|
| 13 |
+
- --policy.gradient_accumulation_steps=2
|
| 14 |
+
- --log_freq=100
|
| 15 |
+
- --save_freq=5000
|
| 16 |
+
codePath: lerobot/scripts/train_accelerate.py
|
| 17 |
+
codePathLocal: lerobot/scripts/train_accelerate.py
|
| 18 |
+
cpu_count: 64
|
| 19 |
+
cpu_count_logical: 128
|
| 20 |
+
disk:
|
| 21 |
+
/:
|
| 22 |
+
total: "34359738368"
|
| 23 |
+
used: "5329375232"
|
| 24 |
+
email: nguyenducnhan.work@gmail.com
|
| 25 |
+
executable: /data/conda/envs/pitorch/bin/python3
|
| 26 |
+
git:
|
| 27 |
+
commit: 60c06109e0d1fb67ac453a9501d798b2705c77b0
|
| 28 |
+
remote: https://github.com/duyhominhnguyen/VLA-Humanoid
|
| 29 |
+
host: 2fa4306d5586
|
| 30 |
+
memory:
|
| 31 |
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total: "540598104064"
|
| 32 |
+
os: Linux-5.15.0-156-generic-x86_64-with-glibc2.39
|
| 33 |
+
program: /workspace/nhan/VLA-Humanoid/lerobot/scripts/train_accelerate.py
|
| 34 |
+
python: CPython 3.10.18
|
| 35 |
+
root: /data/outputs/scale_40_finetune_fastvggt_default/2025-09-26/16-33-33_libero_40%_fastvggt_pre_embed_60k
|
| 36 |
+
startedAt: "2025-09-26T16:33:45.888427Z"
|
| 37 |
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writerId: vo2etbmrr0x34p4sex2rt7yxq0lrkbcv
|
| 38 |
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m: []
|
| 39 |
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python_version: 3.10.18
|
| 40 |
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t:
|
| 41 |
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"1":
|
| 42 |
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|
| 43 |
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|
| 44 |
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|
| 45 |
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|
| 46 |
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|
| 47 |
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|
| 48 |
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|
| 49 |
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|
| 50 |
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|
| 51 |
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|
| 52 |
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|
| 53 |
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|
| 54 |
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|
| 55 |
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|
| 56 |
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"3":
|
| 57 |
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|
| 58 |
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|
| 59 |
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|
| 60 |
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|
| 61 |
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|
| 62 |
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|
| 63 |
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"12": 0.22.0
|
| 64 |
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"13": linux-x86_64
|
| 65 |
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batch_size:
|
| 66 |
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value: 14
|
| 67 |
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dataset:
|
| 68 |
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value:
|
| 69 |
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episodes: null
|
| 70 |
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image_transforms:
|
| 71 |
+
enable: true
|
| 72 |
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image_tfs:
|
| 73 |
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brightness:
|
| 74 |
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kwargs:
|
| 75 |
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brightness:
|
| 76 |
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|
| 77 |
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|
| 78 |
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type: ColorJitter
|
| 79 |
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weight: 1
|
| 80 |
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|
| 81 |
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kwargs:
|
| 82 |
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|
| 83 |
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|
| 84 |
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| 85 |
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|
| 86 |
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| 87 |
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|
| 88 |
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|
| 89 |
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ratio:
|
| 90 |
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|
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| 92 |
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| 93 |
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| 94 |
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| 95 |
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size:
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| 96 |
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| 97 |
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| 98 |
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type: RandomResizedCrop
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| 99 |
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| 101 |
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| 102 |
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| 103 |
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| 104 |
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type: ColorJitter
|
| 106 |
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| 107 |
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rotate:
|
| 108 |
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kwargs:
|
| 109 |
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degrees:
|
| 110 |
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|
| 111 |
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|
| 112 |
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type: RandomRotate
|
| 113 |
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|
| 114 |
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saturation:
|
| 115 |
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|
| 116 |
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saturation:
|
| 117 |
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|
| 118 |
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|
| 119 |
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type: ColorJitter
|
| 120 |
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weight: 1
|
| 121 |
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sharpness:
|
| 122 |
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kwargs:
|
| 123 |
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sharpness:
|
| 124 |
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|
| 125 |
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|
| 126 |
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type: SharpnessJitter
|
| 127 |
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weight: 1
|
| 128 |
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max_num_transforms: 3
|
| 129 |
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random_order: false
|
| 130 |
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wrist_tfs:
|
| 131 |
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brightness:
|
| 132 |
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kwargs:
|
| 133 |
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brightness:
|
| 134 |
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|
| 135 |
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|
| 136 |
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type: ColorJitter
|
| 137 |
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weight: 1
|
| 138 |
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contrast:
|
| 139 |
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kwargs:
|
| 140 |
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contrast:
|
| 141 |
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|
| 142 |
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- 1.2
|
| 143 |
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type: ColorJitter
|
| 144 |
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weight: 1
|
| 145 |
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hue:
|
| 146 |
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kwargs:
|
| 147 |
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hue:
|
| 148 |
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|
| 149 |
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|
| 150 |
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type: ColorJitter
|
| 151 |
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weight: 1
|
| 152 |
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saturation:
|
| 153 |
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kwargs:
|
| 154 |
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saturation:
|
| 155 |
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|
| 156 |
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|
| 157 |
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type: ColorJitter
|
| 158 |
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weight: 1
|
| 159 |
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sharpness:
|
| 160 |
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kwargs:
|
| 161 |
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sharpness:
|
| 162 |
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|
| 163 |
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|
| 164 |
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type: SharpnessJitter
|
| 165 |
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weight: 1
|
| 166 |
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repo_id: .
|
| 167 |
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revision: null
|
| 168 |
+
root: /data/merged_libero_mask_depth_noops_lerobot_40
|
| 169 |
+
use_imagenet_stats: true
|
| 170 |
+
video_backend: torchcodec
|
| 171 |
+
vqa_data_path: .
|
| 172 |
+
env:
|
| 173 |
+
value: null
|
| 174 |
+
eval:
|
| 175 |
+
value:
|
| 176 |
+
batch_size: 50
|
| 177 |
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n_episodes: 50
|
| 178 |
+
use_async_envs: false
|
| 179 |
+
eval_freq:
|
| 180 |
+
value: 20000
|
| 181 |
+
job_name:
|
| 182 |
+
value: libero_40%_fastvggt_pre_embed_60k
|
| 183 |
+
log_freq:
|
| 184 |
+
value: 100
|
| 185 |
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num_workers:
|
| 186 |
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value: 16
|
| 187 |
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optimizer:
|
| 188 |
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value:
|
| 189 |
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betas:
|
| 190 |
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- 0.9
|
| 191 |
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- 0.95
|
| 192 |
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eps: 1e-08
|
| 193 |
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grad_clip_norm: 10
|
| 194 |
+
lr: 0.0001
|
| 195 |
+
type: adamw
|
| 196 |
+
weight_decay: 1e-10
|
| 197 |
+
output_dir:
|
| 198 |
+
value: /data/outputs/scale_40_finetune_fastvggt_default/2025-09-26/16-33-33_libero_40%_fastvggt_pre_embed_60k
|
| 199 |
+
policy:
|
| 200 |
+
value:
|
| 201 |
+
adapt_to_pi_aloha: false
|
| 202 |
+
attention_implementation: eager
|
| 203 |
+
chunk_size: 50
|
| 204 |
+
device: cuda
|
| 205 |
+
empty_cameras: 0
|
| 206 |
+
freeze_vision_encoder: true
|
| 207 |
+
gradient_accumulation_steps: 2
|
| 208 |
+
max_action_dim: 32
|
| 209 |
+
max_state_dim: 32
|
| 210 |
+
n_action_steps: 50
|
| 211 |
+
n_obs_steps: 1
|
| 212 |
+
normalization_mapping:
|
| 213 |
+
ACTION: MEAN_STD
|
| 214 |
+
STATE: MEAN_STD
|
| 215 |
+
VISUAL: IDENTITY
|
| 216 |
+
num_steps: 10
|
| 217 |
+
optimizer_betas:
|
| 218 |
+
- 0.9
|
| 219 |
+
- 0.95
|
| 220 |
+
optimizer_eps: 1e-08
|
| 221 |
+
optimizer_lr: 0.0001
|
| 222 |
+
optimizer_weight_decay: 1e-10
|
| 223 |
+
proj_width: 1024
|
| 224 |
+
resize_imgs_with_padding:
|
| 225 |
+
- 224
|
| 226 |
+
- 224
|
| 227 |
+
scheduler_decay_lr: 2.5e-06
|
| 228 |
+
scheduler_decay_steps: 240000
|
| 229 |
+
scheduler_warmup_steps: 1000
|
| 230 |
+
tokenizer_max_length: 48
|
| 231 |
+
train_expert_only: false
|
| 232 |
+
train_state_proj: true
|
| 233 |
+
type: pi0
|
| 234 |
+
use_amp: false
|
| 235 |
+
use_cache: true
|
| 236 |
+
use_delta_joint_actions_aloha: false
|
| 237 |
+
resume:
|
| 238 |
+
value: false
|
| 239 |
+
save_checkpoint:
|
| 240 |
+
value: true
|
| 241 |
+
save_freq:
|
| 242 |
+
value: 5000
|
| 243 |
+
scheduler:
|
| 244 |
+
value:
|
| 245 |
+
decay_lr: 2.5e-06
|
| 246 |
+
num_decay_steps: 240000
|
| 247 |
+
num_warmup_steps: 1000
|
| 248 |
+
peak_lr: 0.0001
|
| 249 |
+
type: cosine_decay_with_warmup
|
| 250 |
+
seed:
|
| 251 |
+
value: 42
|
| 252 |
+
steps:
|
| 253 |
+
value: 60000
|
| 254 |
+
use_policy_training_preset:
|
| 255 |
+
value: true
|
| 256 |
+
wandb:
|
| 257 |
+
value:
|
| 258 |
+
disable_artifact: true
|
| 259 |
+
enable: true
|
| 260 |
+
entity: Robotics_VLA
|
| 261 |
+
mode: online
|
| 262 |
+
notes: null
|
| 263 |
+
project: pi0_lerobot
|
| 264 |
+
run_id: null
|
scale_40_finetune_fastvggt_default/2025-09-26/16-33-33_libero_40%_fastvggt_pre_embed_60k/wandb/run-20250926_163345-t5anomje/files/output.log
ADDED
|
@@ -0,0 +1,635 @@
|
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|
|
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|
| 1 |
+
[Rank 0] Set device to cuda:0
|
| 2 |
+
INFO 2025-09-26 16:33:47 celerate.py:162 Creating dataset
|
| 3 |
+
Resolving data files: 100%|███████████████████████████████████████████████████████████████████| 800/800 [00:00<00:00, 25579.31it/s]
|
| 4 |
+
[DEBUG] Embeddings loaded for 800 episodes.
|
| 5 |
+
[DEBUG] Total cached frames: 133851
|
| 6 |
+
[DEBUG] Estimated memory usage: 136465.28 MB
|
| 7 |
+
INFO 2025-09-26 16:33:50 celerate.py:173 Creating policy
|
| 8 |
+
load pretrained policy
|
| 9 |
+
Loading weights from local directory
|
| 10 |
+
/data/conda/envs/pitorch/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py:4807: UserWarning: No device id is provided via `init_process_group` or `barrier `. Using the current device set by the user.
|
| 11 |
+
warnings.warn( # warn only once
|
| 12 |
+
INFO 2025-09-26 16:34:43 celerate.py:184 Creating optimizer and scheduler
|
| 13 |
+
INFO 2025-09-26 16:35:41 celerate.py:224 [1m[33mOutput dir:[0m /data/outputs/scale_40_finetune_fastvggt_default/2025-09-26/16-33-33_libero_40%_fastvggt_pre_embed_60k
|
| 14 |
+
INFO 2025-09-26 16:35:41 celerate.py:227 cfg.steps=60000 (60K)
|
| 15 |
+
INFO 2025-09-26 16:35:41 celerate.py:228 dataset.num_frames=133851 (134K)
|
| 16 |
+
INFO 2025-09-26 16:35:41 celerate.py:229 dataset.num_episodes=800
|
| 17 |
+
INFO 2025-09-26 16:35:41 celerate.py:230 num_learnable_params=3088929824 (3B)
|
| 18 |
+
INFO 2025-09-26 16:35:41 celerate.py:231 num_total_params=3501372250 (4B)
|
| 19 |
+
INFO 2025-09-26 16:35:41 celerate.py:232 Number of processes: 4
|
| 20 |
+
INFO 2025-09-26 16:35:41 celerate.py:233 Device: cuda:0
|
| 21 |
+
INFO 2025-09-26 16:35:41 celerate.py:234 Mixed precision: no
|
| 22 |
+
INFO 2025-09-26 16:35:41 celerate.py:256 Start offline training on a fixed dataset
|
| 23 |
+
INFO 2025-09-26 16:37:45 celerate.py:309 step:100 smpl:6K ep:33 epch:0.04 loss:0.511 grdn:3.249 lr:2.0e-05 updt_s:1.161 data_s:0.077
|
| 24 |
+
INFO 2025-09-26 16:39:40 celerate.py:309 step:200 smpl:11K ep:67 epch:0.08 loss:0.376 grdn:1.279 lr:6.0e-05 updt_s:1.125 data_s:0.010
|
| 25 |
+
INFO 2025-09-26 16:41:33 celerate.py:309 step:300 smpl:17K ep:100 epch:0.13 loss:0.356 grdn:1.028 lr:9.5e-05 updt_s:1.111 data_s:0.010
|
| 26 |
+
INFO 2025-09-26 16:43:26 celerate.py:309 step:400 smpl:22K ep:134 epch:0.17 loss:0.336 grdn:0.869 lr:1.0e-04 updt_s:1.109 data_s:0.010
|
| 27 |
+
INFO 2025-09-26 16:45:18 celerate.py:309 step:500 smpl:28K ep:167 epch:0.21 loss:0.321 grdn:0.769 lr:1.0e-04 updt_s:1.106 data_s:0.011
|
| 28 |
+
INFO 2025-09-26 16:47:10 celerate.py:309 step:600 smpl:34K ep:201 epch:0.25 loss:0.305 grdn:0.790 lr:1.0e-04 updt_s:1.101 data_s:0.010
|
| 29 |
+
INFO 2025-09-26 16:49:02 celerate.py:309 step:700 smpl:39K ep:234 epch:0.29 loss:0.305 grdn:0.830 lr:1.0e-04 updt_s:1.102 data_s:0.010
|
| 30 |
+
INFO 2025-09-26 16:50:55 celerate.py:309 step:800 smpl:45K ep:268 epch:0.33 loss:0.299 grdn:0.746 lr:1.0e-04 updt_s:1.110 data_s:0.010
|
| 31 |
+
INFO 2025-09-26 16:52:48 celerate.py:309 step:900 smpl:50K ep:301 epch:0.38 loss:0.300 grdn:0.728 lr:1.0e-04 updt_s:1.105 data_s:0.010
|
| 32 |
+
INFO 2025-09-26 16:54:40 celerate.py:309 step:1K smpl:56K ep:335 epch:0.42 loss:0.293 grdn:0.694 lr:1.0e-04 updt_s:1.101 data_s:0.010
|
| 33 |
+
INFO 2025-09-26 16:56:32 celerate.py:309 step:1K smpl:62K ep:368 epch:0.46 loss:0.289 grdn:0.732 lr:1.0e-04 updt_s:1.103 data_s:0.010
|
| 34 |
+
INFO 2025-09-26 16:58:24 celerate.py:309 step:1K smpl:67K ep:402 epch:0.50 loss:0.286 grdn:0.691 lr:1.0e-04 updt_s:1.107 data_s:0.010
|
| 35 |
+
INFO 2025-09-26 17:00:17 celerate.py:309 step:1K smpl:73K ep:435 epch:0.54 loss:0.283 grdn:0.649 lr:1.0e-04 updt_s:1.105 data_s:0.010
|
| 36 |
+
INFO 2025-09-26 17:02:09 celerate.py:309 step:1K smpl:78K ep:469 epch:0.59 loss:0.280 grdn:0.647 lr:1.0e-04 updt_s:1.102 data_s:0.010
|
| 37 |
+
INFO 2025-09-26 17:04:01 celerate.py:309 step:2K smpl:84K ep:502 epch:0.63 loss:0.277 grdn:0.672 lr:1.0e-04 updt_s:1.106 data_s:0.009
|
| 38 |
+
INFO 2025-09-26 17:05:54 celerate.py:309 step:2K smpl:90K ep:536 epch:0.67 loss:0.270 grdn:0.602 lr:1.0e-04 updt_s:1.105 data_s:0.010
|
| 39 |
+
INFO 2025-09-26 17:07:46 celerate.py:309 step:2K smpl:95K ep:569 epch:0.71 loss:0.272 grdn:0.633 lr:1.0e-04 updt_s:1.102 data_s:0.010
|
| 40 |
+
INFO 2025-09-26 17:09:38 celerate.py:309 step:2K smpl:101K ep:602 epch:0.75 loss:0.265 grdn:0.610 lr:1.0e-04 updt_s:1.103 data_s:0.010
|
| 41 |
+
INFO 2025-09-26 17:11:31 celerate.py:309 step:2K smpl:106K ep:636 epch:0.79 loss:0.268 grdn:0.614 lr:1.0e-04 updt_s:1.107 data_s:0.010
|
| 42 |
+
INFO 2025-09-26 17:13:23 celerate.py:309 step:2K smpl:112K ep:669 epch:0.84 loss:0.262 grdn:0.571 lr:1.0e-04 updt_s:1.107 data_s:0.010
|
| 43 |
+
INFO 2025-09-26 17:15:15 celerate.py:309 step:2K smpl:118K ep:703 epch:0.88 loss:0.263 grdn:0.625 lr:1.0e-04 updt_s:1.102 data_s:0.010
|
| 44 |
+
INFO 2025-09-26 17:17:08 celerate.py:309 step:2K smpl:123K ep:736 epch:0.92 loss:0.256 grdn:0.572 lr:1.0e-04 updt_s:1.104 data_s:0.010
|
| 45 |
+
INFO 2025-09-26 17:19:00 celerate.py:309 step:2K smpl:129K ep:770 epch:0.96 loss:0.257 grdn:0.592 lr:1.0e-04 updt_s:1.109 data_s:0.010
|
| 46 |
+
INFO 2025-09-26 17:21:00 celerate.py:309 step:2K smpl:134K ep:803 epch:1.00 loss:0.257 grdn:0.643 lr:1.0e-04 updt_s:1.104 data_s:0.082
|
| 47 |
+
INFO 2025-09-26 17:22:52 celerate.py:309 step:2K smpl:140K ep:837 epch:1.05 loss:0.252 grdn:0.599 lr:1.0e-04 updt_s:1.101 data_s:0.010
|
| 48 |
+
INFO 2025-09-26 17:24:44 celerate.py:309 step:3K smpl:146K ep:870 epch:1.09 loss:0.249 grdn:0.595 lr:1.0e-04 updt_s:1.106 data_s:0.010
|
| 49 |
+
INFO 2025-09-26 17:26:37 celerate.py:309 step:3K smpl:151K ep:904 epch:1.13 loss:0.253 grdn:0.638 lr:1.0e-04 updt_s:1.107 data_s:0.010
|
| 50 |
+
INFO 2025-09-26 17:28:29 celerate.py:309 step:3K smpl:157K ep:937 epch:1.17 loss:0.248 grdn:0.609 lr:9.9e-05 updt_s:1.103 data_s:0.010
|
| 51 |
+
INFO 2025-09-26 17:30:21 celerate.py:309 step:3K smpl:162K ep:971 epch:1.21 loss:0.249 grdn:0.585 lr:9.9e-05 updt_s:1.102 data_s:0.010
|
| 52 |
+
INFO 2025-09-26 17:32:14 celerate.py:309 step:3K smpl:168K ep:1K epch:1.26 loss:0.247 grdn:0.623 lr:9.9e-05 updt_s:1.109 data_s:0.010
|
| 53 |
+
INFO 2025-09-26 17:34:07 celerate.py:309 step:3K smpl:174K ep:1K epch:1.30 loss:0.247 grdn:0.650 lr:9.9e-05 updt_s:1.108 data_s:0.010
|
| 54 |
+
INFO 2025-09-26 17:35:59 celerate.py:309 step:3K smpl:179K ep:1K epch:1.34 loss:0.244 grdn:0.580 lr:9.9e-05 updt_s:1.108 data_s:0.009
|
| 55 |
+
INFO 2025-09-26 17:37:52 celerate.py:309 step:3K smpl:185K ep:1K epch:1.38 loss:0.243 grdn:0.640 lr:9.9e-05 updt_s:1.104 data_s:0.010
|
| 56 |
+
INFO 2025-09-26 17:39:45 celerate.py:309 step:3K smpl:190K ep:1K epch:1.42 loss:0.244 grdn:0.595 lr:9.9e-05 updt_s:1.110 data_s:0.009
|
| 57 |
+
INFO 2025-09-26 17:41:37 celerate.py:309 step:4K smpl:196K ep:1K epch:1.46 loss:0.240 grdn:0.577 lr:9.9e-05 updt_s:1.108 data_s:0.009
|
| 58 |
+
INFO 2025-09-26 17:43:29 celerate.py:309 step:4K smpl:202K ep:1K epch:1.51 loss:0.234 grdn:0.524 lr:9.9e-05 updt_s:1.104 data_s:0.010
|
| 59 |
+
INFO 2025-09-26 17:45:22 celerate.py:309 step:4K smpl:207K ep:1K epch:1.55 loss:0.234 grdn:0.649 lr:9.9e-05 updt_s:1.105 data_s:0.010
|
| 60 |
+
INFO 2025-09-26 17:47:15 celerate.py:309 step:4K smpl:213K ep:1K epch:1.59 loss:0.234 grdn:0.544 lr:9.9e-05 updt_s:1.111 data_s:0.010
|
| 61 |
+
INFO 2025-09-26 17:49:07 celerate.py:309 step:4K smpl:218K ep:1K epch:1.63 loss:0.235 grdn:0.587 lr:9.9e-05 updt_s:1.104 data_s:0.010
|
| 62 |
+
INFO 2025-09-26 17:50:59 celerate.py:309 step:4K smpl:224K ep:1K epch:1.67 loss:0.232 grdn:0.519 lr:9.9e-05 updt_s:1.103 data_s:0.009
|
| 63 |
+
INFO 2025-09-26 17:52:52 celerate.py:309 step:4K smpl:230K ep:1K epch:1.72 loss:0.226 grdn:0.486 lr:9.9e-05 updt_s:1.107 data_s:0.010
|
| 64 |
+
INFO 2025-09-26 17:54:45 celerate.py:309 step:4K smpl:235K ep:1K epch:1.76 loss:0.224 grdn:0.542 lr:9.9e-05 updt_s:1.109 data_s:0.010
|
| 65 |
+
INFO 2025-09-26 17:56:37 celerate.py:309 step:4K smpl:241K ep:1K epch:1.80 loss:0.223 grdn:0.523 lr:9.9e-05 updt_s:1.104 data_s:0.009
|
| 66 |
+
INFO 2025-09-26 17:58:29 celerate.py:309 step:4K smpl:246K ep:1K epch:1.84 loss:0.224 grdn:0.556 lr:9.9e-05 updt_s:1.106 data_s:0.010
|
| 67 |
+
INFO 2025-09-26 18:00:22 celerate.py:309 step:4K smpl:252K ep:2K epch:1.88 loss:0.222 grdn:0.578 lr:9.9e-05 updt_s:1.109 data_s:0.010
|
| 68 |
+
INFO 2025-09-26 18:02:15 celerate.py:309 step:5K smpl:258K ep:2K epch:1.92 loss:0.220 grdn:0.532 lr:9.9e-05 updt_s:1.108 data_s:0.010
|
| 69 |
+
INFO 2025-09-26 18:04:07 celerate.py:309 step:5K smpl:263K ep:2K epch:1.97 loss:0.219 grdn:0.552 lr:9.9e-05 updt_s:1.104 data_s:0.010
|
| 70 |
+
INFO 2025-09-26 18:06:09 celerate.py:309 step:5K smpl:269K ep:2K epch:2.01 loss:0.216 grdn:0.572 lr:9.8e-05 updt_s:1.115 data_s:0.092
|
| 71 |
+
INFO 2025-09-26 18:08:01 celerate.py:309 step:5K smpl:274K ep:2K epch:2.05 loss:0.211 grdn:0.513 lr:9.8e-05 updt_s:1.107 data_s:0.010
|
| 72 |
+
INFO 2025-09-26 18:09:54 celerate.py:309 step:5K smpl:280K ep:2K epch:2.09 loss:0.211 grdn:0.525 lr:9.8e-05 updt_s:1.105 data_s:0.010
|
| 73 |
+
INFO 2025-09-26 18:09:54 celerate.py:334 Checkpoint policy after step 5000
|
| 74 |
+
INFO 2025-09-26 18:12:08 celerate.py:309 step:5K smpl:286K ep:2K epch:2.13 loss:0.211 grdn:0.485 lr:9.8e-05 updt_s:1.099 data_s:0.010
|
| 75 |
+
INFO 2025-09-26 18:14:00 celerate.py:309 step:5K smpl:291K ep:2K epch:2.18 loss:0.204 grdn:0.492 lr:9.8e-05 updt_s:1.106 data_s:0.010
|
| 76 |
+
INFO 2025-09-26 18:15:53 celerate.py:309 step:5K smpl:297K ep:2K epch:2.22 loss:0.206 grdn:0.518 lr:9.8e-05 updt_s:1.109 data_s:0.010
|
| 77 |
+
INFO 2025-09-26 18:17:46 celerate.py:309 step:5K smpl:302K ep:2K epch:2.26 loss:0.205 grdn:0.520 lr:9.8e-05 updt_s:1.104 data_s:0.009
|
| 78 |
+
INFO 2025-09-26 18:19:38 celerate.py:309 step:6K smpl:308K ep:2K epch:2.30 loss:0.208 grdn:0.524 lr:9.8e-05 updt_s:1.103 data_s:0.009
|
| 79 |
+
INFO 2025-09-26 18:21:31 celerate.py:309 step:6K smpl:314K ep:2K epch:2.34 loss:0.201 grdn:0.494 lr:9.8e-05 updt_s:1.114 data_s:0.010
|
| 80 |
+
INFO 2025-09-26 18:23:24 celerate.py:309 step:6K smpl:319K ep:2K epch:2.38 loss:0.204 grdn:0.499 lr:9.8e-05 updt_s:1.109 data_s:0.010
|
| 81 |
+
INFO 2025-09-26 18:25:16 celerate.py:309 step:6K smpl:325K ep:2K epch:2.43 loss:0.200 grdn:0.485 lr:9.8e-05 updt_s:1.105 data_s:0.010
|
| 82 |
+
INFO 2025-09-26 18:27:08 celerate.py:309 step:6K smpl:330K ep:2K epch:2.47 loss:0.199 grdn:0.494 lr:9.8e-05 updt_s:1.105 data_s:0.010
|
| 83 |
+
INFO 2025-09-26 18:29:01 celerate.py:309 step:6K smpl:336K ep:2K epch:2.51 loss:0.198 grdn:0.509 lr:9.8e-05 updt_s:1.111 data_s:0.010
|
| 84 |
+
INFO 2025-09-26 18:30:54 celerate.py:309 step:6K smpl:342K ep:2K epch:2.55 loss:0.194 grdn:0.486 lr:9.8e-05 updt_s:1.109 data_s:0.010
|
| 85 |
+
INFO 2025-09-26 18:32:46 celerate.py:309 step:6K smpl:347K ep:2K epch:2.59 loss:0.193 grdn:0.417 lr:9.7e-05 updt_s:1.105 data_s:0.010
|
| 86 |
+
INFO 2025-09-26 18:34:39 celerate.py:309 step:6K smpl:353K ep:2K epch:2.64 loss:0.193 grdn:0.486 lr:9.7e-05 updt_s:1.106 data_s:0.010
|
| 87 |
+
INFO 2025-09-26 18:36:32 celerate.py:309 step:6K smpl:358K ep:2K epch:2.68 loss:0.193 grdn:0.492 lr:9.7e-05 updt_s:1.113 data_s:0.010
|
| 88 |
+
INFO 2025-09-26 18:38:25 celerate.py:309 step:6K smpl:364K ep:2K epch:2.72 loss:0.190 grdn:0.469 lr:9.7e-05 updt_s:1.107 data_s:0.010
|
| 89 |
+
INFO 2025-09-26 18:40:17 celerate.py:309 step:7K smpl:370K ep:2K epch:2.76 loss:0.191 grdn:0.498 lr:9.7e-05 updt_s:1.104 data_s:0.010
|
| 90 |
+
INFO 2025-09-26 18:42:09 celerate.py:309 step:7K smpl:375K ep:2K epch:2.80 loss:0.186 grdn:0.492 lr:9.7e-05 updt_s:1.107 data_s:0.010
|
| 91 |
+
INFO 2025-09-26 18:44:03 celerate.py:309 step:7K smpl:381K ep:2K epch:2.84 loss:0.192 grdn:0.481 lr:9.7e-05 updt_s:1.114 data_s:0.010
|
| 92 |
+
INFO 2025-09-26 18:45:55 celerate.py:309 step:7K smpl:386K ep:2K epch:2.89 loss:0.189 grdn:0.439 lr:9.7e-05 updt_s:1.105 data_s:0.010
|
| 93 |
+
INFO 2025-09-26 18:47:47 celerate.py:309 step:7K smpl:392K ep:2K epch:2.93 loss:0.188 grdn:0.531 lr:9.7e-05 updt_s:1.104 data_s:0.009
|
| 94 |
+
INFO 2025-09-26 18:49:40 celerate.py:309 step:7K smpl:398K ep:2K epch:2.97 loss:0.182 grdn:0.469 lr:9.7e-05 updt_s:1.110 data_s:0.010
|
| 95 |
+
INFO 2025-09-26 18:51:40 celerate.py:309 step:7K smpl:403K ep:2K epch:3.01 loss:0.178 grdn:0.447 lr:9.7e-05 updt_s:1.112 data_s:0.081
|
| 96 |
+
INFO 2025-09-26 18:53:33 celerate.py:309 step:7K smpl:409K ep:2K epch:3.05 loss:0.175 grdn:0.429 lr:9.7e-05 updt_s:1.104 data_s:0.010
|
| 97 |
+
INFO 2025-09-26 18:55:25 celerate.py:309 step:7K smpl:414K ep:2K epch:3.10 loss:0.178 grdn:0.432 lr:9.6e-05 updt_s:1.105 data_s:0.010
|
| 98 |
+
INFO 2025-09-26 18:57:18 celerate.py:309 step:8K smpl:420K ep:3K epch:3.14 loss:0.171 grdn:0.441 lr:9.6e-05 updt_s:1.110 data_s:0.010
|
| 99 |
+
INFO 2025-09-26 18:59:11 celerate.py:309 step:8K smpl:426K ep:3K epch:3.18 loss:0.173 grdn:0.477 lr:9.6e-05 updt_s:1.108 data_s:0.010
|
| 100 |
+
INFO 2025-09-26 19:01:03 celerate.py:309 step:8K smpl:431K ep:3K epch:3.22 loss:0.174 grdn:0.472 lr:9.6e-05 updt_s:1.105 data_s:0.010
|
| 101 |
+
INFO 2025-09-26 19:02:55 celerate.py:309 step:8K smpl:437K ep:3K epch:3.26 loss:0.173 grdn:0.411 lr:9.6e-05 updt_s:1.106 data_s:0.010
|
| 102 |
+
INFO 2025-09-26 19:04:49 celerate.py:309 step:8K smpl:442K ep:3K epch:3.31 loss:0.175 grdn:0.460 lr:9.6e-05 updt_s:1.113 data_s:0.010
|
| 103 |
+
INFO 2025-09-26 19:06:42 celerate.py:309 step:8K smpl:448K ep:3K epch:3.35 loss:0.168 grdn:0.462 lr:9.6e-05 updt_s:1.112 data_s:0.010
|
| 104 |
+
INFO 2025-09-26 19:08:34 celerate.py:309 step:8K smpl:454K ep:3K epch:3.39 loss:0.176 grdn:0.464 lr:9.6e-05 updt_s:1.105 data_s:0.010
|
| 105 |
+
INFO 2025-09-26 19:10:27 celerate.py:309 step:8K smpl:459K ep:3K epch:3.43 loss:0.170 grdn:0.452 lr:9.6e-05 updt_s:1.109 data_s:0.010
|
| 106 |
+
INFO 2025-09-26 19:12:20 celerate.py:309 step:8K smpl:465K ep:3K epch:3.47 loss:0.168 grdn:0.447 lr:9.6e-05 updt_s:1.113 data_s:0.010
|
| 107 |
+
INFO 2025-09-26 19:14:13 celerate.py:309 step:8K smpl:470K ep:3K epch:3.51 loss:0.169 grdn:0.434 lr:9.5e-05 updt_s:1.108 data_s:0.010
|
| 108 |
+
INFO 2025-09-26 19:16:05 celerate.py:309 step:8K smpl:476K ep:3K epch:3.56 loss:0.165 grdn:0.439 lr:9.5e-05 updt_s:1.106 data_s:0.010
|
| 109 |
+
INFO 2025-09-26 19:17:58 celerate.py:309 step:9K smpl:482K ep:3K epch:3.60 loss:0.164 grdn:0.421 lr:9.5e-05 updt_s:1.110 data_s:0.010
|
| 110 |
+
INFO 2025-09-26 19:19:51 celerate.py:309 step:9K smpl:487K ep:3K epch:3.64 loss:0.164 grdn:0.420 lr:9.5e-05 updt_s:1.113 data_s:0.010
|
| 111 |
+
INFO 2025-09-26 19:21:44 celerate.py:309 step:9K smpl:493K ep:3K epch:3.68 loss:0.164 grdn:0.411 lr:9.5e-05 updt_s:1.108 data_s:0.010
|
| 112 |
+
INFO 2025-09-26 19:23:36 celerate.py:309 step:9K smpl:498K ep:3K epch:3.72 loss:0.160 grdn:0.429 lr:9.5e-05 updt_s:1.106 data_s:0.010
|
| 113 |
+
INFO 2025-09-26 19:25:29 celerate.py:309 step:9K smpl:504K ep:3K epch:3.77 loss:0.164 grdn:0.442 lr:9.5e-05 updt_s:1.109 data_s:0.010
|
| 114 |
+
INFO 2025-09-26 19:27:22 celerate.py:309 step:9K smpl:510K ep:3K epch:3.81 loss:0.159 grdn:0.395 lr:9.5e-05 updt_s:1.112 data_s:0.010
|
| 115 |
+
INFO 2025-09-26 19:29:15 celerate.py:309 step:9K smpl:515K ep:3K epch:3.85 loss:0.161 grdn:0.424 lr:9.5e-05 updt_s:1.109 data_s:0.010
|
| 116 |
+
INFO 2025-09-26 19:31:07 celerate.py:309 step:9K smpl:521K ep:3K epch:3.89 loss:0.156 grdn:0.424 lr:9.4e-05 updt_s:1.103 data_s:0.010
|
| 117 |
+
INFO 2025-09-26 19:33:00 celerate.py:309 step:9K smpl:526K ep:3K epch:3.93 loss:0.158 grdn:0.427 lr:9.4e-05 updt_s:1.111 data_s:0.010
|
| 118 |
+
INFO 2025-09-26 19:34:53 celerate.py:309 step:10K smpl:532K ep:3K epch:3.97 loss:0.154 grdn:0.401 lr:9.4e-05 updt_s:1.111 data_s:0.010
|
| 119 |
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INFO 2025-09-26 19:36:52 celerate.py:309 step:10K smpl:538K ep:3K epch:4.02 loss:0.152 grdn:0.429 lr:9.4e-05 updt_s:1.121 data_s:0.062
|
| 120 |
+
INFO 2025-09-26 19:38:45 celerate.py:309 step:10K smpl:543K ep:3K epch:4.06 loss:0.150 grdn:0.404 lr:9.4e-05 updt_s:1.105 data_s:0.009
|
| 121 |
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INFO 2025-09-26 19:40:38 celerate.py:309 step:10K smpl:549K ep:3K epch:4.10 loss:0.149 grdn:0.410 lr:9.4e-05 updt_s:1.111 data_s:0.009
|
| 122 |
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INFO 2025-09-26 19:42:30 celerate.py:309 step:10K smpl:554K ep:3K epch:4.14 loss:0.153 grdn:0.460 lr:9.4e-05 updt_s:1.110 data_s:0.010
|
| 123 |
+
INFO 2025-09-26 19:44:23 celerate.py:309 step:10K smpl:560K ep:3K epch:4.18 loss:0.152 grdn:0.388 lr:9.4e-05 updt_s:1.105 data_s:0.010
|
| 124 |
+
INFO 2025-09-26 19:44:23 celerate.py:334 Checkpoint policy after step 10000
|
| 125 |
+
INFO 2025-09-26 19:46:38 celerate.py:309 step:10K smpl:566K ep:3K epch:4.23 loss:0.148 grdn:0.405 lr:9.3e-05 updt_s:1.103 data_s:0.009
|
| 126 |
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INFO 2025-09-26 19:48:32 celerate.py:309 step:10K smpl:571K ep:3K epch:4.27 loss:0.148 grdn:0.416 lr:9.3e-05 updt_s:1.112 data_s:0.010
|
| 127 |
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INFO 2025-09-26 19:50:24 celerate.py:309 step:10K smpl:577K ep:3K epch:4.31 loss:0.147 grdn:0.391 lr:9.3e-05 updt_s:1.109 data_s:0.010
|
| 128 |
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INFO 2025-09-26 19:52:17 celerate.py:309 step:10K smpl:582K ep:3K epch:4.35 loss:0.147 grdn:0.411 lr:9.3e-05 updt_s:1.109 data_s:0.010
|
| 129 |
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INFO 2025-09-26 19:54:10 celerate.py:309 step:10K smpl:588K ep:4K epch:4.39 loss:0.145 grdn:0.398 lr:9.3e-05 updt_s:1.110 data_s:0.010
|
| 130 |
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INFO 2025-09-26 19:56:03 celerate.py:309 step:11K smpl:594K ep:4K epch:4.43 loss:0.140 grdn:0.402 lr:9.3e-05 updt_s:1.117 data_s:0.010
|
| 131 |
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INFO 2025-09-26 19:57:56 celerate.py:309 step:11K smpl:599K ep:4K epch:4.48 loss:0.140 grdn:0.392 lr:9.3e-05 updt_s:1.108 data_s:0.010
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| 132 |
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INFO 2025-09-26 19:59:48 celerate.py:309 step:11K smpl:605K ep:4K epch:4.52 loss:0.142 grdn:0.407 lr:9.2e-05 updt_s:1.104 data_s:0.010
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| 133 |
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INFO 2025-09-26 20:01:41 celerate.py:309 step:11K smpl:610K ep:4K epch:4.56 loss:0.138 grdn:0.414 lr:9.2e-05 updt_s:1.107 data_s:0.010
|
| 134 |
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INFO 2025-09-26 20:03:34 celerate.py:309 step:11K smpl:616K ep:4K epch:4.60 loss:0.140 grdn:0.386 lr:9.2e-05 updt_s:1.108 data_s:0.010
|
| 135 |
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INFO 2025-09-26 20:05:26 celerate.py:309 step:11K smpl:622K ep:4K epch:4.64 loss:0.139 grdn:0.380 lr:9.2e-05 updt_s:1.109 data_s:0.010
|
| 136 |
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INFO 2025-09-26 20:07:19 celerate.py:309 step:11K smpl:627K ep:4K epch:4.69 loss:0.137 grdn:0.407 lr:9.2e-05 updt_s:1.106 data_s:0.010
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| 137 |
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INFO 2025-09-26 20:09:11 celerate.py:309 step:11K smpl:633K ep:4K epch:4.73 loss:0.137 grdn:0.407 lr:9.2e-05 updt_s:1.104 data_s:0.009
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| 138 |
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INFO 2025-09-26 20:11:03 celerate.py:309 step:11K smpl:638K ep:4K epch:4.77 loss:0.134 grdn:0.382 lr:9.2e-05 updt_s:1.105 data_s:0.010
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| 139 |
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INFO 2025-09-26 20:12:56 celerate.py:309 step:12K smpl:644K ep:4K epch:4.81 loss:0.139 grdn:0.385 lr:9.1e-05 updt_s:1.109 data_s:0.010
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| 140 |
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INFO 2025-09-26 20:14:49 celerate.py:309 step:12K smpl:650K ep:4K epch:4.85 loss:0.135 grdn:0.391 lr:9.1e-05 updt_s:1.106 data_s:0.010
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| 141 |
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INFO 2025-09-26 20:16:41 celerate.py:309 step:12K smpl:655K ep:4K epch:4.89 loss:0.136 grdn:0.411 lr:9.1e-05 updt_s:1.104 data_s:0.010
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| 142 |
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INFO 2025-09-26 20:18:33 celerate.py:309 step:12K smpl:661K ep:4K epch:4.94 loss:0.132 grdn:0.363 lr:9.1e-05 updt_s:1.104 data_s:0.010
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| 143 |
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INFO 2025-09-26 20:20:26 celerate.py:309 step:12K smpl:666K ep:4K epch:4.98 loss:0.131 grdn:0.388 lr:9.1e-05 updt_s:1.106 data_s:0.010
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| 144 |
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INFO 2025-09-26 20:22:25 celerate.py:309 step:12K smpl:672K ep:4K epch:5.02 loss:0.130 grdn:0.361 lr:9.1e-05 updt_s:1.104 data_s:0.078
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INFO 2025-09-26 20:24:17 celerate.py:309 step:12K smpl:678K ep:4K epch:5.06 loss:0.130 grdn:0.379 lr:9.1e-05 updt_s:1.100 data_s:0.010
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| 146 |
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INFO 2025-09-26 20:26:09 celerate.py:309 step:12K smpl:683K ep:4K epch:5.10 loss:0.125 grdn:0.362 lr:9.0e-05 updt_s:1.102 data_s:0.010
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| 147 |
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INFO 2025-09-26 20:28:01 celerate.py:309 step:12K smpl:689K ep:4K epch:5.15 loss:0.127 grdn:0.360 lr:9.0e-05 updt_s:1.101 data_s:0.010
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INFO 2025-09-26 20:29:53 celerate.py:309 step:12K smpl:694K ep:4K epch:5.19 loss:0.126 grdn:0.362 lr:9.0e-05 updt_s:1.099 data_s:0.010
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INFO 2025-09-26 20:31:45 celerate.py:309 step:12K smpl:700K ep:4K epch:5.23 loss:0.124 grdn:0.352 lr:9.0e-05 updt_s:1.100 data_s:0.010
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INFO 2025-09-26 20:33:37 celerate.py:309 step:13K smpl:706K ep:4K epch:5.27 loss:0.126 grdn:0.367 lr:9.0e-05 updt_s:1.102 data_s:0.010
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INFO 2025-09-26 20:35:29 celerate.py:309 step:13K smpl:711K ep:4K epch:5.31 loss:0.123 grdn:0.350 lr:9.0e-05 updt_s:1.101 data_s:0.010
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| 152 |
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INFO 2025-09-26 20:37:21 celerate.py:309 step:13K smpl:717K ep:4K epch:5.36 loss:0.126 grdn:0.373 lr:9.0e-05 updt_s:1.107 data_s:0.010
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| 153 |
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INFO 2025-09-26 20:39:14 celerate.py:309 step:13K smpl:722K ep:4K epch:5.40 loss:0.124 grdn:0.367 lr:8.9e-05 updt_s:1.105 data_s:0.011
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| 154 |
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INFO 2025-09-26 20:41:06 celerate.py:309 step:13K smpl:728K ep:4K epch:5.44 loss:0.124 grdn:0.369 lr:8.9e-05 updt_s:1.105 data_s:0.011
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| 155 |
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INFO 2025-09-26 20:42:58 celerate.py:309 step:13K smpl:734K ep:4K epch:5.48 loss:0.126 grdn:0.374 lr:8.9e-05 updt_s:1.102 data_s:0.010
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| 156 |
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INFO 2025-09-26 20:44:50 celerate.py:309 step:13K smpl:739K ep:4K epch:5.52 loss:0.122 grdn:0.357 lr:8.9e-05 updt_s:1.105 data_s:0.010
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INFO 2025-09-26 20:46:43 celerate.py:309 step:13K smpl:745K ep:4K epch:5.56 loss:0.124 grdn:0.391 lr:8.9e-05 updt_s:1.108 data_s:0.010
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| 158 |
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INFO 2025-09-26 20:48:35 celerate.py:309 step:13K smpl:750K ep:4K epch:5.61 loss:0.121 grdn:0.357 lr:8.9e-05 updt_s:1.103 data_s:0.011
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INFO 2025-09-26 20:50:27 celerate.py:309 step:14K smpl:756K ep:5K epch:5.65 loss:0.120 grdn:0.358 lr:8.8e-05 updt_s:1.104 data_s:0.010
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INFO 2025-09-26 20:52:20 celerate.py:309 step:14K smpl:762K ep:5K epch:5.69 loss:0.120 grdn:0.366 lr:8.8e-05 updt_s:1.107 data_s:0.010
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INFO 2025-09-26 20:54:12 celerate.py:309 step:14K smpl:767K ep:5K epch:5.73 loss:0.121 grdn:0.368 lr:8.8e-05 updt_s:1.106 data_s:0.010
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INFO 2025-09-26 20:56:05 celerate.py:309 step:14K smpl:773K ep:5K epch:5.77 loss:0.117 grdn:0.341 lr:8.8e-05 updt_s:1.103 data_s:0.010
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INFO 2025-09-26 20:57:57 celerate.py:309 step:14K smpl:778K ep:5K epch:5.82 loss:0.119 grdn:0.361 lr:8.8e-05 updt_s:1.105 data_s:0.010
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INFO 2025-09-26 20:59:50 celerate.py:309 step:14K smpl:784K ep:5K epch:5.86 loss:0.117 grdn:0.343 lr:8.8e-05 updt_s:1.108 data_s:0.010
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INFO 2025-09-26 21:01:42 celerate.py:309 step:14K smpl:790K ep:5K epch:5.90 loss:0.122 grdn:0.371 lr:8.7e-05 updt_s:1.107 data_s:0.010
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INFO 2025-09-26 21:03:34 celerate.py:309 step:14K smpl:795K ep:5K epch:5.94 loss:0.118 grdn:0.359 lr:8.7e-05 updt_s:1.103 data_s:0.010
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INFO 2025-09-26 21:05:27 celerate.py:309 step:14K smpl:801K ep:5K epch:5.98 loss:0.115 grdn:0.353 lr:8.7e-05 updt_s:1.105 data_s:0.010
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INFO 2025-09-26 21:07:25 celerate.py:309 step:14K smpl:806K ep:5K epch:6.02 loss:0.109 grdn:0.344 lr:8.7e-05 updt_s:1.118 data_s:0.060
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INFO 2025-09-26 21:09:18 celerate.py:309 step:14K smpl:812K ep:5K epch:6.07 loss:0.116 grdn:0.377 lr:8.7e-05 updt_s:1.104 data_s:0.010
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INFO 2025-09-26 21:11:10 celerate.py:309 step:15K smpl:818K ep:5K epch:6.11 loss:0.111 grdn:0.339 lr:8.7e-05 updt_s:1.102 data_s:0.010
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INFO 2025-09-26 21:13:02 celerate.py:309 step:15K smpl:823K ep:5K epch:6.15 loss:0.108 grdn:0.350 lr:8.6e-05 updt_s:1.105 data_s:0.010
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INFO 2025-09-26 21:14:55 celerate.py:309 step:15K smpl:829K ep:5K epch:6.19 loss:0.109 grdn:0.315 lr:8.6e-05 updt_s:1.106 data_s:0.010
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INFO 2025-09-26 21:16:47 celerate.py:309 step:15K smpl:834K ep:5K epch:6.23 loss:0.111 grdn:0.342 lr:8.6e-05 updt_s:1.105 data_s:0.010
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INFO 2025-09-26 21:18:39 celerate.py:309 step:15K smpl:840K ep:5K epch:6.28 loss:0.112 grdn:0.355 lr:8.6e-05 updt_s:1.105 data_s:0.010
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INFO 2025-09-26 21:18:39 celerate.py:334 Checkpoint policy after step 15000
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INFO 2025-09-26 21:20:55 celerate.py:309 step:15K smpl:846K ep:5K epch:6.32 loss:0.109 grdn:0.348 lr:8.6e-05 updt_s:1.103 data_s:0.010
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INFO 2025-09-26 21:22:47 celerate.py:309 step:15K smpl:851K ep:5K epch:6.36 loss:0.108 grdn:0.342 lr:8.5e-05 updt_s:1.110 data_s:0.010
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INFO 2025-09-26 21:24:40 celerate.py:309 step:15K smpl:857K ep:5K epch:6.40 loss:0.109 grdn:0.345 lr:8.5e-05 updt_s:1.108 data_s:0.010
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INFO 2025-09-26 21:26:33 celerate.py:309 step:15K smpl:862K ep:5K epch:6.44 loss:0.109 grdn:0.353 lr:8.5e-05 updt_s:1.107 data_s:0.010
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INFO 2025-09-26 21:28:25 celerate.py:309 step:16K smpl:868K ep:5K epch:6.48 loss:0.109 grdn:0.335 lr:8.5e-05 updt_s:1.109 data_s:0.010
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INFO 2025-09-26 21:30:18 celerate.py:309 step:16K smpl:874K ep:5K epch:6.53 loss:0.105 grdn:0.343 lr:8.5e-05 updt_s:1.107 data_s:0.010
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INFO 2025-09-26 21:32:11 celerate.py:309 step:16K smpl:879K ep:5K epch:6.57 loss:0.110 grdn:0.347 lr:8.5e-05 updt_s:1.107 data_s:0.010
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INFO 2025-09-26 21:34:03 celerate.py:309 step:16K smpl:885K ep:5K epch:6.61 loss:0.108 grdn:0.341 lr:8.4e-05 updt_s:1.107 data_s:0.010
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INFO 2025-09-26 21:35:56 celerate.py:309 step:16K smpl:890K ep:5K epch:6.65 loss:0.104 grdn:0.316 lr:8.4e-05 updt_s:1.109 data_s:0.010
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INFO 2025-09-26 21:37:48 celerate.py:309 step:16K smpl:896K ep:5K epch:6.69 loss:0.106 grdn:0.322 lr:8.4e-05 updt_s:1.106 data_s:0.010
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INFO 2025-09-26 21:39:41 celerate.py:309 step:16K smpl:902K ep:5K epch:6.74 loss:0.103 grdn:0.347 lr:8.4e-05 updt_s:1.106 data_s:0.010
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INFO 2025-09-26 21:41:33 celerate.py:309 step:16K smpl:907K ep:5K epch:6.78 loss:0.101 grdn:0.319 lr:8.4e-05 updt_s:1.107 data_s:0.010
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INFO 2025-09-26 21:43:26 celerate.py:309 step:16K smpl:913K ep:5K epch:6.82 loss:0.102 grdn:0.339 lr:8.3e-05 updt_s:1.109 data_s:0.010
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INFO 2025-09-26 21:45:19 celerate.py:309 step:16K smpl:918K ep:5K epch:6.86 loss:0.103 grdn:0.336 lr:8.3e-05 updt_s:1.108 data_s:0.010
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INFO 2025-09-26 21:47:11 celerate.py:309 step:16K smpl:924K ep:6K epch:6.90 loss:0.102 grdn:0.324 lr:8.3e-05 updt_s:1.108 data_s:0.010
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INFO 2025-09-26 21:49:04 celerate.py:309 step:17K smpl:930K ep:6K epch:6.95 loss:0.100 grdn:0.320 lr:8.3e-05 updt_s:1.107 data_s:0.010
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INFO 2025-09-26 21:50:57 celerate.py:309 step:17K smpl:935K ep:6K epch:6.99 loss:0.101 grdn:0.339 lr:8.3e-05 updt_s:1.107 data_s:0.009
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INFO 2025-09-26 21:52:56 celerate.py:309 step:17K smpl:941K ep:6K epch:7.03 loss:0.098 grdn:0.318 lr:8.2e-05 updt_s:1.102 data_s:0.083
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INFO 2025-09-26 21:54:48 celerate.py:309 step:17K smpl:946K ep:6K epch:7.07 loss:0.099 grdn:0.319 lr:8.2e-05 updt_s:1.106 data_s:0.010
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INFO 2025-09-26 21:56:41 celerate.py:309 step:17K smpl:952K ep:6K epch:7.11 loss:0.097 grdn:0.323 lr:8.2e-05 updt_s:1.108 data_s:0.010
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INFO 2025-09-26 21:58:34 celerate.py:309 step:17K smpl:958K ep:6K epch:7.15 loss:0.097 grdn:0.321 lr:8.2e-05 updt_s:1.105 data_s:0.010
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INFO 2025-09-26 22:00:26 celerate.py:309 step:17K smpl:963K ep:6K epch:7.20 loss:0.095 grdn:0.316 lr:8.2e-05 updt_s:1.103 data_s:0.009
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INFO 2025-09-26 22:02:18 celerate.py:309 step:17K smpl:969K ep:6K epch:7.24 loss:0.097 grdn:0.337 lr:8.1e-05 updt_s:1.102 data_s:0.009
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INFO 2025-09-26 22:04:10 celerate.py:309 step:17K smpl:974K ep:6K epch:7.28 loss:0.098 grdn:0.330 lr:8.1e-05 updt_s:1.105 data_s:0.010
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INFO 2025-09-26 22:06:02 celerate.py:309 step:18K smpl:980K ep:6K epch:7.32 loss:0.097 grdn:0.333 lr:8.1e-05 updt_s:1.102 data_s:0.010
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INFO 2025-09-26 22:07:55 celerate.py:309 step:18K smpl:986K ep:6K epch:7.36 loss:0.097 grdn:0.311 lr:8.1e-05 updt_s:1.107 data_s:0.010
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INFO 2025-09-26 22:09:47 celerate.py:309 step:18K smpl:991K ep:6K epch:7.41 loss:0.097 grdn:0.332 lr:8.1e-05 updt_s:1.103 data_s:0.010
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INFO 2025-09-26 22:11:39 celerate.py:309 step:18K smpl:997K ep:6K epch:7.45 loss:0.093 grdn:0.319 lr:8.0e-05 updt_s:1.105 data_s:0.011
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INFO 2025-09-26 22:13:32 celerate.py:309 step:18K smpl:1M ep:6K epch:7.49 loss:0.094 grdn:0.322 lr:8.0e-05 updt_s:1.108 data_s:0.010
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INFO 2025-09-26 22:15:25 celerate.py:309 step:18K smpl:1M ep:6K epch:7.53 loss:0.096 grdn:0.326 lr:8.0e-05 updt_s:1.106 data_s:0.010
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INFO 2025-09-26 22:17:17 celerate.py:309 step:18K smpl:1M ep:6K epch:7.57 loss:0.093 grdn:0.326 lr:8.0e-05 updt_s:1.105 data_s:0.009
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INFO 2025-09-26 22:19:10 celerate.py:309 step:18K smpl:1M ep:6K epch:7.61 loss:0.095 grdn:0.323 lr:8.0e-05 updt_s:1.107 data_s:0.009
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INFO 2025-09-26 22:21:02 celerate.py:309 step:18K smpl:1M ep:6K epch:7.66 loss:0.092 grdn:0.328 lr:7.9e-05 updt_s:1.108 data_s:0.008
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INFO 2025-09-26 22:22:55 celerate.py:309 step:18K smpl:1M ep:6K epch:7.70 loss:0.092 grdn:0.307 lr:7.9e-05 updt_s:1.105 data_s:0.010
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INFO 2025-09-26 22:24:47 celerate.py:309 step:18K smpl:1M ep:6K epch:7.74 loss:0.091 grdn:0.347 lr:7.9e-05 updt_s:1.105 data_s:0.010
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INFO 2025-09-26 22:26:40 celerate.py:309 step:19K smpl:1M ep:6K epch:7.78 loss:0.090 grdn:0.291 lr:7.9e-05 updt_s:1.107 data_s:0.010
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INFO 2025-09-26 22:28:33 celerate.py:309 step:19K smpl:1M ep:6K epch:7.82 loss:0.089 grdn:0.305 lr:7.9e-05 updt_s:1.107 data_s:0.010
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INFO 2025-09-26 22:30:25 celerate.py:309 step:19K smpl:1M ep:6K epch:7.87 loss:0.094 grdn:0.318 lr:7.8e-05 updt_s:1.107 data_s:0.011
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INFO 2025-09-26 22:32:17 celerate.py:309 step:19K smpl:1M ep:6K epch:7.91 loss:0.086 grdn:0.300 lr:7.8e-05 updt_s:1.105 data_s:0.010
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INFO 2025-09-26 22:34:10 celerate.py:309 step:19K smpl:1M ep:6K epch:7.95 loss:0.089 grdn:0.295 lr:7.8e-05 updt_s:1.107 data_s:0.010
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INFO 2025-09-26 22:36:03 celerate.py:309 step:19K smpl:1M ep:6K epch:7.99 loss:0.089 grdn:0.301 lr:7.8e-05 updt_s:1.106 data_s:0.010
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INFO 2025-09-26 22:38:01 celerate.py:309 step:19K smpl:1M ep:6K epch:8.03 loss:0.087 grdn:0.302 lr:7.7e-05 updt_s:1.125 data_s:0.053
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INFO 2025-09-26 22:39:54 celerate.py:309 step:19K smpl:1M ep:6K epch:8.07 loss:0.088 grdn:0.304 lr:7.7e-05 updt_s:1.105 data_s:0.010
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INFO 2025-09-26 22:41:46 celerate.py:309 step:19K smpl:1M ep:6K epch:8.12 loss:0.088 grdn:0.308 lr:7.7e-05 updt_s:1.108 data_s:0.010
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INFO 2025-09-26 22:43:39 celerate.py:309 step:20K smpl:1M ep:7K epch:8.16 loss:0.088 grdn:0.312 lr:7.7e-05 updt_s:1.105 data_s:0.010
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INFO 2025-09-26 22:45:31 celerate.py:309 step:20K smpl:1M ep:7K epch:8.20 loss:0.085 grdn:0.301 lr:7.7e-05 updt_s:1.105 data_s:0.010
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INFO 2025-09-26 22:47:24 celerate.py:309 step:20K smpl:1M ep:7K epch:8.24 loss:0.083 grdn:0.307 lr:7.6e-05 updt_s:1.107 data_s:0.009
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INFO 2025-09-26 22:49:16 celerate.py:309 step:20K smpl:1M ep:7K epch:8.28 loss:0.083 grdn:0.297 lr:7.6e-05 updt_s:1.109 data_s:0.010
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INFO 2025-09-26 22:51:09 celerate.py:309 step:20K smpl:1M ep:7K epch:8.33 loss:0.083 grdn:0.297 lr:7.6e-05 updt_s:1.107 data_s:0.010
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INFO 2025-09-26 22:53:02 celerate.py:309 step:20K smpl:1M ep:7K epch:8.37 loss:0.083 grdn:0.277 lr:7.6e-05 updt_s:1.111 data_s:0.010
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INFO 2025-09-26 22:53:02 celerate.py:334 Checkpoint policy after step 20000
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INFO 2025-09-26 22:55:18 celerate.py:309 step:20K smpl:1M ep:7K epch:8.41 loss:0.086 grdn:0.292 lr:7.6e-05 updt_s:1.104 data_s:0.009
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INFO 2025-09-26 22:57:10 celerate.py:309 step:20K smpl:1M ep:7K epch:8.45 loss:0.085 grdn:0.294 lr:7.5e-05 updt_s:1.107 data_s:0.008
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INFO 2025-09-26 22:59:03 celerate.py:309 step:20K smpl:1M ep:7K epch:8.49 loss:0.082 grdn:0.288 lr:7.5e-05 updt_s:1.107 data_s:0.010
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INFO 2025-09-26 23:00:56 celerate.py:309 step:20K smpl:1M ep:7K epch:8.53 loss:0.081 grdn:0.287 lr:7.5e-05 updt_s:1.109 data_s:0.010
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INFO 2025-09-26 23:02:48 celerate.py:309 step:20K smpl:1M ep:7K epch:8.58 loss:0.085 grdn:0.302 lr:7.5e-05 updt_s:1.109 data_s:0.009
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INFO 2025-09-26 23:04:41 celerate.py:309 step:21K smpl:1M ep:7K epch:8.62 loss:0.081 grdn:0.287 lr:7.4e-05 updt_s:1.108 data_s:0.009
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INFO 2025-09-26 23:06:34 celerate.py:309 step:21K smpl:1M ep:7K epch:8.66 loss:0.079 grdn:0.281 lr:7.4e-05 updt_s:1.108 data_s:0.009
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INFO 2025-09-26 23:08:26 celerate.py:309 step:21K smpl:1M ep:7K epch:8.70 loss:0.080 grdn:0.302 lr:7.4e-05 updt_s:1.109 data_s:0.010
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INFO 2025-09-26 23:10:19 celerate.py:309 step:21K smpl:1M ep:7K epch:8.74 loss:0.083 grdn:0.307 lr:7.4e-05 updt_s:1.108 data_s:0.010
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INFO 2025-09-26 23:12:12 celerate.py:309 step:21K smpl:1M ep:7K epch:8.79 loss:0.081 grdn:0.289 lr:7.3e-05 updt_s:1.109 data_s:0.008
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INFO 2025-09-26 23:14:05 celerate.py:309 step:21K smpl:1M ep:7K epch:8.83 loss:0.077 grdn:0.286 lr:7.3e-05 updt_s:1.113 data_s:0.010
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INFO 2025-09-26 23:15:58 celerate.py:309 step:21K smpl:1M ep:7K epch:8.87 loss:0.081 grdn:0.295 lr:7.3e-05 updt_s:1.111 data_s:0.009
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INFO 2025-09-26 23:17:51 celerate.py:309 step:21K smpl:1M ep:7K epch:8.91 loss:0.078 grdn:0.278 lr:7.3e-05 updt_s:1.110 data_s:0.010
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INFO 2025-09-26 23:19:44 celerate.py:309 step:21K smpl:1M ep:7K epch:8.95 loss:0.079 grdn:0.288 lr:7.3e-05 updt_s:1.111 data_s:0.010
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INFO 2025-09-26 23:21:37 celerate.py:309 step:22K smpl:1M ep:7K epch:9.00 loss:0.078 grdn:0.287 lr:7.2e-05 updt_s:1.109 data_s:0.010
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INFO 2025-09-26 23:23:37 celerate.py:309 step:22K smpl:1M ep:7K epch:9.04 loss:0.077 grdn:0.277 lr:7.2e-05 updt_s:1.105 data_s:0.091
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INFO 2025-09-26 23:25:30 celerate.py:309 step:22K smpl:1M ep:7K epch:9.08 loss:0.075 grdn:0.276 lr:7.2e-05 updt_s:1.107 data_s:0.010
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INFO 2025-09-26 23:27:22 celerate.py:309 step:22K smpl:1M ep:7K epch:9.12 loss:0.079 grdn:0.282 lr:7.2e-05 updt_s:1.110 data_s:0.011
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INFO 2025-09-26 23:29:15 celerate.py:309 step:22K smpl:1M ep:7K epch:9.16 loss:0.074 grdn:0.264 lr:7.1e-05 updt_s:1.109 data_s:0.011
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INFO 2025-09-26 23:31:08 celerate.py:309 step:22K smpl:1M ep:7K epch:9.20 loss:0.076 grdn:0.280 lr:7.1e-05 updt_s:1.109 data_s:0.010
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INFO 2025-09-26 23:33:01 celerate.py:309 step:22K smpl:1M ep:7K epch:9.25 loss:0.075 grdn:0.260 lr:7.1e-05 updt_s:1.111 data_s:0.010
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INFO 2025-09-26 23:34:54 celerate.py:309 step:22K smpl:1M ep:7K epch:9.29 loss:0.075 grdn:0.280 lr:7.1e-05 updt_s:1.111 data_s:0.010
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INFO 2025-09-26 23:36:47 celerate.py:309 step:22K smpl:1M ep:7K epch:9.33 loss:0.073 grdn:0.281 lr:7.0e-05 updt_s:1.110 data_s:0.010
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INFO 2025-09-26 23:38:39 celerate.py:309 step:22K smpl:1M ep:7K epch:9.37 loss:0.072 grdn:0.263 lr:7.0e-05 updt_s:1.109 data_s:0.010
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INFO 2025-09-26 23:40:33 celerate.py:309 step:22K smpl:1M ep:8K epch:9.41 loss:0.073 grdn:0.270 lr:7.0e-05 updt_s:1.114 data_s:0.010
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INFO 2025-09-26 23:42:26 celerate.py:309 step:23K smpl:1M ep:8K epch:9.46 loss:0.071 grdn:0.272 lr:7.0e-05 updt_s:1.111 data_s:0.010
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INFO 2025-09-26 23:44:18 celerate.py:309 step:23K smpl:1M ep:8K epch:9.50 loss:0.070 grdn:0.260 lr:7.0e-05 updt_s:1.109 data_s:0.010
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INFO 2025-09-26 23:46:11 celerate.py:309 step:23K smpl:1M ep:8K epch:9.54 loss:0.070 grdn:0.269 lr:6.9e-05 updt_s:1.107 data_s:0.010
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INFO 2025-09-26 23:48:04 celerate.py:309 step:23K smpl:1M ep:8K epch:9.58 loss:0.071 grdn:0.281 lr:6.9e-05 updt_s:1.112 data_s:0.010
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INFO 2025-09-26 23:49:57 celerate.py:309 step:23K smpl:1M ep:8K epch:9.62 loss:0.071 grdn:0.280 lr:6.9e-05 updt_s:1.109 data_s:0.010
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INFO 2025-09-26 23:51:49 celerate.py:309 step:23K smpl:1M ep:8K epch:9.66 loss:0.070 grdn:0.263 lr:6.9e-05 updt_s:1.105 data_s:0.010
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INFO 2025-09-26 23:53:42 celerate.py:309 step:23K smpl:1M ep:8K epch:9.71 loss:0.069 grdn:0.266 lr:6.8e-05 updt_s:1.108 data_s:0.010
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INFO 2025-09-26 23:55:35 celerate.py:309 step:23K smpl:1M ep:8K epch:9.75 loss:0.067 grdn:0.274 lr:6.8e-05 updt_s:1.113 data_s:0.010
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INFO 2025-09-26 23:57:28 celerate.py:309 step:23K smpl:1M ep:8K epch:9.79 loss:0.070 grdn:0.254 lr:6.8e-05 updt_s:1.110 data_s:0.010
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INFO 2025-09-26 23:59:20 celerate.py:309 step:24K smpl:1M ep:8K epch:9.83 loss:0.068 grdn:0.261 lr:6.8e-05 updt_s:1.106 data_s:0.010
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INFO 2025-09-27 00:01:13 celerate.py:309 step:24K smpl:1M ep:8K epch:9.87 loss:0.068 grdn:0.255 lr:6.7e-05 updt_s:1.109 data_s:0.010
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INFO 2025-09-27 00:03:06 celerate.py:309 step:24K smpl:1M ep:8K epch:9.92 loss:0.067 grdn:0.264 lr:6.7e-05 updt_s:1.112 data_s:0.010
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INFO 2025-09-27 00:04:58 celerate.py:309 step:24K smpl:1M ep:8K epch:9.96 loss:0.069 grdn:0.268 lr:6.7e-05 updt_s:1.107 data_s:0.010
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INFO 2025-09-27 00:06:51 celerate.py:309 step:24K smpl:1M ep:8K epch:10.00 loss:0.069 grdn:0.261 lr:6.7e-05 updt_s:1.104 data_s:0.013
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INFO 2025-09-27 00:08:51 celerate.py:309 step:24K smpl:1M ep:8K epch:10.04 loss:0.066 grdn:0.265 lr:6.6e-05 updt_s:1.119 data_s:0.070
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INFO 2025-09-27 00:10:44 celerate.py:309 step:24K smpl:1M ep:8K epch:10.08 loss:0.067 grdn:0.269 lr:6.6e-05 updt_s:1.108 data_s:0.010
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INFO 2025-09-27 00:12:36 celerate.py:309 step:24K smpl:1M ep:8K epch:10.12 loss:0.067 grdn:0.255 lr:6.6e-05 updt_s:1.106 data_s:0.010
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INFO 2025-09-27 00:14:28 celerate.py:309 step:24K smpl:1M ep:8K epch:10.17 loss:0.066 grdn:0.271 lr:6.6e-05 updt_s:1.106 data_s:0.010
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INFO 2025-09-27 00:16:21 celerate.py:309 step:24K smpl:1M ep:8K epch:10.21 loss:0.063 grdn:0.256 lr:6.5e-05 updt_s:1.108 data_s:0.010
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INFO 2025-09-27 00:18:14 celerate.py:309 step:24K smpl:1M ep:8K epch:10.25 loss:0.066 grdn:0.253 lr:6.5e-05 updt_s:1.107 data_s:0.010
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INFO 2025-09-27 00:20:06 celerate.py:309 step:25K smpl:1M ep:8K epch:10.29 loss:0.066 grdn:0.257 lr:6.5e-05 updt_s:1.108 data_s:0.010
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INFO 2025-09-27 00:21:59 celerate.py:309 step:25K smpl:1M ep:8K epch:10.33 loss:0.066 grdn:0.250 lr:6.5e-05 updt_s:1.108 data_s:0.010
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INFO 2025-09-27 00:23:51 celerate.py:309 step:25K smpl:1M ep:8K epch:10.38 loss:0.064 grdn:0.256 lr:6.4e-05 updt_s:1.108 data_s:0.010
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INFO 2025-09-27 00:25:44 celerate.py:309 step:25K smpl:1M ep:8K epch:10.42 loss:0.061 grdn:0.252 lr:6.4e-05 updt_s:1.110 data_s:0.010
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INFO 2025-09-27 00:27:37 celerate.py:309 step:25K smpl:1M ep:8K epch:10.46 loss:0.063 grdn:0.249 lr:6.4e-05 updt_s:1.106 data_s:0.009
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INFO 2025-09-27 00:27:37 celerate.py:334 Checkpoint policy after step 25000
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INFO 2025-09-27 00:29:52 celerate.py:309 step:25K smpl:1M ep:8K epch:10.50 loss:0.061 grdn:0.234 lr:6.4e-05 updt_s:1.103 data_s:0.009
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INFO 2025-09-27 00:31:45 celerate.py:309 step:25K smpl:1M ep:8K epch:10.54 loss:0.063 grdn:0.248 lr:6.3e-05 updt_s:1.108 data_s:0.010
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INFO 2025-09-27 00:33:37 celerate.py:309 step:25K smpl:1M ep:8K epch:10.58 loss:0.062 grdn:0.244 lr:6.3e-05 updt_s:1.106 data_s:0.007
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INFO 2025-09-27 00:35:30 celerate.py:309 step:25K smpl:1M ep:9K epch:10.63 loss:0.061 grdn:0.246 lr:6.3e-05 updt_s:1.109 data_s:0.009
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INFO 2025-09-27 00:37:23 celerate.py:309 step:26K smpl:1M ep:9K epch:10.67 loss:0.064 grdn:0.244 lr:6.3e-05 updt_s:1.109 data_s:0.010
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INFO 2025-09-27 00:39:15 celerate.py:309 step:26K smpl:1M ep:9K epch:10.71 loss:0.062 grdn:0.244 lr:6.3e-05 updt_s:1.107 data_s:0.010
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INFO 2025-09-27 00:41:08 celerate.py:309 step:26K smpl:1M ep:9K epch:10.75 loss:0.061 grdn:0.255 lr:6.2e-05 updt_s:1.108 data_s:0.010
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INFO 2025-09-27 00:43:01 celerate.py:309 step:26K smpl:1M ep:9K epch:10.79 loss:0.062 grdn:0.248 lr:6.2e-05 updt_s:1.112 data_s:0.010
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INFO 2025-09-27 00:44:54 celerate.py:309 step:26K smpl:1M ep:9K epch:10.84 loss:0.059 grdn:0.245 lr:6.2e-05 updt_s:1.108 data_s:0.009
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INFO 2025-09-27 00:46:46 celerate.py:309 step:26K smpl:1M ep:9K epch:10.88 loss:0.061 grdn:0.243 lr:6.2e-05 updt_s:1.108 data_s:0.010
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INFO 2025-09-27 00:48:39 celerate.py:309 step:26K smpl:1M ep:9K epch:10.92 loss:0.060 grdn:0.247 lr:6.1e-05 updt_s:1.112 data_s:0.010
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INFO 2025-09-27 00:50:32 celerate.py:309 step:26K smpl:1M ep:9K epch:10.96 loss:0.059 grdn:0.244 lr:6.1e-05 updt_s:1.109 data_s:0.010
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INFO 2025-09-27 00:52:32 celerate.py:309 step:26K smpl:1M ep:9K epch:11.00 loss:0.058 grdn:0.231 lr:6.1e-05 updt_s:1.106 data_s:0.084
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INFO 2025-09-27 00:54:25 celerate.py:309 step:26K smpl:1M ep:9K epch:11.05 loss:0.057 grdn:0.237 lr:6.1e-05 updt_s:1.108 data_s:0.010
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INFO 2025-09-27 00:56:17 celerate.py:309 step:26K smpl:1M ep:9K epch:11.09 loss:0.057 grdn:0.236 lr:6.0e-05 updt_s:1.110 data_s:0.010
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INFO 2025-09-27 00:58:10 celerate.py:309 step:27K smpl:1M ep:9K epch:11.13 loss:0.056 grdn:0.240 lr:6.0e-05 updt_s:1.110 data_s:0.010
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INFO 2025-09-27 01:00:03 celerate.py:309 step:27K smpl:1M ep:9K epch:11.17 loss:0.056 grdn:0.231 lr:6.0e-05 updt_s:1.108 data_s:0.010
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INFO 2025-09-27 01:01:56 celerate.py:309 step:27K smpl:2M ep:9K epch:11.21 loss:0.056 grdn:0.244 lr:6.0e-05 updt_s:1.109 data_s:0.010
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INFO 2025-09-27 01:03:49 celerate.py:309 step:27K smpl:2M ep:9K epch:11.25 loss:0.057 grdn:0.231 lr:5.9e-05 updt_s:1.111 data_s:0.011
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INFO 2025-09-27 01:05:41 celerate.py:309 step:27K smpl:2M ep:9K epch:11.30 loss:0.056 grdn:0.242 lr:5.9e-05 updt_s:1.108 data_s:0.010
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INFO 2025-09-27 01:07:34 celerate.py:309 step:27K smpl:2M ep:9K epch:11.34 loss:0.055 grdn:0.237 lr:5.9e-05 updt_s:1.107 data_s:0.010
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INFO 2025-09-27 01:09:27 celerate.py:309 step:27K smpl:2M ep:9K epch:11.38 loss:0.053 grdn:0.239 lr:5.8e-05 updt_s:1.112 data_s:0.010
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INFO 2025-09-27 01:11:20 celerate.py:309 step:27K smpl:2M ep:9K epch:11.42 loss:0.054 grdn:0.232 lr:5.8e-05 updt_s:1.112 data_s:0.010
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INFO 2025-09-27 01:13:13 celerate.py:309 step:27K smpl:2M ep:9K epch:11.46 loss:0.054 grdn:0.227 lr:5.8e-05 updt_s:1.109 data_s:0.010
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INFO 2025-09-27 01:15:05 celerate.py:309 step:28K smpl:2M ep:9K epch:11.51 loss:0.054 grdn:0.225 lr:5.8e-05 updt_s:1.110 data_s:0.010
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INFO 2025-09-27 01:16:59 celerate.py:309 step:28K smpl:2M ep:9K epch:11.55 loss:0.056 grdn:0.247 lr:5.7e-05 updt_s:1.112 data_s:0.011
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INFO 2025-09-27 01:18:51 celerate.py:309 step:28K smpl:2M ep:9K epch:11.59 loss:0.055 grdn:0.238 lr:5.7e-05 updt_s:1.110 data_s:0.010
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INFO 2025-09-27 01:20:44 celerate.py:309 step:28K smpl:2M ep:9K epch:11.63 loss:0.054 grdn:0.222 lr:5.7e-05 updt_s:1.107 data_s:0.010
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INFO 2025-09-27 01:22:37 celerate.py:309 step:28K smpl:2M ep:9K epch:11.67 loss:0.054 grdn:0.228 lr:5.7e-05 updt_s:1.110 data_s:0.010
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INFO 2025-09-27 01:24:30 celerate.py:309 step:28K smpl:2M ep:9K epch:11.71 loss:0.052 grdn:0.227 lr:5.6e-05 updt_s:1.111 data_s:0.010
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INFO 2025-09-27 01:26:22 celerate.py:309 step:28K smpl:2M ep:9K epch:11.76 loss:0.054 grdn:0.221 lr:5.6e-05 updt_s:1.109 data_s:0.009
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INFO 2025-09-27 01:28:15 celerate.py:309 step:28K smpl:2M ep:9K epch:11.80 loss:0.052 grdn:0.228 lr:5.6e-05 updt_s:1.108 data_s:0.010
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INFO 2025-09-27 01:30:08 celerate.py:309 step:28K smpl:2M ep:9K epch:11.84 loss:0.051 grdn:0.218 lr:5.6e-05 updt_s:1.112 data_s:0.010
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INFO 2025-09-27 01:32:01 celerate.py:309 step:28K smpl:2M ep:10K epch:11.88 loss:0.053 grdn:0.223 lr:5.5e-05 updt_s:1.110 data_s:0.010
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INFO 2025-09-27 01:33:54 celerate.py:309 step:28K smpl:2M ep:10K epch:11.92 loss:0.054 grdn:0.227 lr:5.5e-05 updt_s:1.110 data_s:0.010
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INFO 2025-09-27 01:35:47 celerate.py:309 step:29K smpl:2M ep:10K epch:11.97 loss:0.052 grdn:0.227 lr:5.5e-05 updt_s:1.109 data_s:0.010
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INFO 2025-09-27 01:37:47 celerate.py:309 step:29K smpl:2M ep:10K epch:12.01 loss:0.050 grdn:0.223 lr:5.5e-05 updt_s:1.125 data_s:0.067
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INFO 2025-09-27 01:39:39 celerate.py:309 step:29K smpl:2M ep:10K epch:12.05 loss:0.049 grdn:0.231 lr:5.4e-05 updt_s:1.107 data_s:0.010
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INFO 2025-09-27 01:41:31 celerate.py:309 step:29K smpl:2M ep:10K epch:12.09 loss:0.052 grdn:0.219 lr:5.4e-05 updt_s:1.105 data_s:0.010
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INFO 2025-09-27 01:43:24 celerate.py:309 step:29K smpl:2M ep:10K epch:12.13 loss:0.051 grdn:0.223 lr:5.4e-05 updt_s:1.108 data_s:0.009
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INFO 2025-09-27 01:45:17 celerate.py:309 step:29K smpl:2M ep:10K epch:12.17 loss:0.048 grdn:0.208 lr:5.4e-05 updt_s:1.110 data_s:0.010
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INFO 2025-09-27 01:47:09 celerate.py:309 step:29K smpl:2M ep:10K epch:12.22 loss:0.049 grdn:0.221 lr:5.3e-05 updt_s:1.108 data_s:0.010
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INFO 2025-09-27 01:49:02 celerate.py:309 step:29K smpl:2M ep:10K epch:12.26 loss:0.049 grdn:0.230 lr:5.3e-05 updt_s:1.106 data_s:0.010
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INFO 2025-09-27 01:50:55 celerate.py:309 step:29K smpl:2M ep:10K epch:12.30 loss:0.048 grdn:0.215 lr:5.3e-05 updt_s:1.109 data_s:0.010
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INFO 2025-09-27 01:52:47 celerate.py:309 step:30K smpl:2M ep:10K epch:12.34 loss:0.046 grdn:0.210 lr:5.3e-05 updt_s:1.109 data_s:0.010
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INFO 2025-09-27 01:54:40 celerate.py:309 step:30K smpl:2M ep:10K epch:12.38 loss:0.046 grdn:0.214 lr:5.2e-05 updt_s:1.106 data_s:0.010
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INFO 2025-09-27 01:56:32 celerate.py:309 step:30K smpl:2M ep:10K epch:12.43 loss:0.045 grdn:0.217 lr:5.2e-05 updt_s:1.109 data_s:0.010
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INFO 2025-09-27 01:58:25 celerate.py:309 step:30K smpl:2M ep:10K epch:12.47 loss:0.049 grdn:0.220 lr:5.2e-05 updt_s:1.111 data_s:0.010
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INFO 2025-09-27 02:00:18 celerate.py:309 step:30K smpl:2M ep:10K epch:12.51 loss:0.047 grdn:0.207 lr:5.2e-05 updt_s:1.111 data_s:0.010
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INFO 2025-09-27 02:02:11 celerate.py:309 step:30K smpl:2M ep:10K epch:12.55 loss:0.048 grdn:0.213 lr:5.1e-05 updt_s:1.106 data_s:0.010
|
| 328 |
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INFO 2025-09-27 02:02:11 celerate.py:334 Checkpoint policy after step 30000
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INFO 2025-09-27 02:04:27 celerate.py:309 step:30K smpl:2M ep:10K epch:12.59 loss:0.048 grdn:0.209 lr:5.1e-05 updt_s:1.105 data_s:0.010
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INFO 2025-09-27 02:06:20 celerate.py:309 step:30K smpl:2M ep:10K epch:12.63 loss:0.046 grdn:0.218 lr:5.1e-05 updt_s:1.108 data_s:0.010
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INFO 2025-09-27 02:08:13 celerate.py:309 step:30K smpl:2M ep:10K epch:12.68 loss:0.046 grdn:0.213 lr:5.1e-05 updt_s:1.108 data_s:0.010
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INFO 2025-09-27 02:10:05 celerate.py:309 step:30K smpl:2M ep:10K epch:12.72 loss:0.044 grdn:0.222 lr:5.0e-05 updt_s:1.105 data_s:0.010
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INFO 2025-09-27 02:11:58 celerate.py:309 step:30K smpl:2M ep:10K epch:12.76 loss:0.045 grdn:0.204 lr:5.0e-05 updt_s:1.109 data_s:0.010
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INFO 2025-09-27 02:13:50 celerate.py:309 step:31K smpl:2M ep:10K epch:12.80 loss:0.045 grdn:0.224 lr:5.0e-05 updt_s:1.109 data_s:0.010
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INFO 2025-09-27 02:15:43 celerate.py:309 step:31K smpl:2M ep:10K epch:12.84 loss:0.045 grdn:0.212 lr:5.0e-05 updt_s:1.107 data_s:0.010
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INFO 2025-09-27 02:17:36 celerate.py:309 step:31K smpl:2M ep:10K epch:12.89 loss:0.046 grdn:0.215 lr:4.9e-05 updt_s:1.107 data_s:0.010
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INFO 2025-09-27 02:19:28 celerate.py:309 step:31K smpl:2M ep:10K epch:12.93 loss:0.046 grdn:0.205 lr:4.9e-05 updt_s:1.111 data_s:0.010
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INFO 2025-09-27 02:21:21 celerate.py:309 step:31K smpl:2M ep:10K epch:12.97 loss:0.047 grdn:0.213 lr:4.9e-05 updt_s:1.107 data_s:0.010
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INFO 2025-09-27 02:23:20 celerate.py:309 step:31K smpl:2M ep:10K epch:13.01 loss:0.045 grdn:0.207 lr:4.9e-05 updt_s:1.119 data_s:0.062
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INFO 2025-09-27 02:25:12 celerate.py:309 step:31K smpl:2M ep:10K epch:13.05 loss:0.044 grdn:0.212 lr:4.8e-05 updt_s:1.107 data_s:0.010
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INFO 2025-09-27 02:27:05 celerate.py:309 step:31K smpl:2M ep:10K epch:13.10 loss:0.042 grdn:0.204 lr:4.8e-05 updt_s:1.108 data_s:0.010
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INFO 2025-09-27 02:28:58 celerate.py:309 step:31K smpl:2M ep:11K epch:13.14 loss:0.044 grdn:0.209 lr:4.8e-05 updt_s:1.108 data_s:0.010
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INFO 2025-09-27 02:30:50 celerate.py:309 step:32K smpl:2M ep:11K epch:13.18 loss:0.044 grdn:0.207 lr:4.8e-05 updt_s:1.109 data_s:0.010
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INFO 2025-09-27 02:32:43 celerate.py:309 step:32K smpl:2M ep:11K epch:13.22 loss:0.044 grdn:0.220 lr:4.7e-05 updt_s:1.110 data_s:0.011
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INFO 2025-09-27 02:34:36 celerate.py:309 step:32K smpl:2M ep:11K epch:13.26 loss:0.042 grdn:0.195 lr:4.7e-05 updt_s:1.107 data_s:0.010
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INFO 2025-09-27 02:36:28 celerate.py:309 step:32K smpl:2M ep:11K epch:13.30 loss:0.042 grdn:0.197 lr:4.7e-05 updt_s:1.107 data_s:0.008
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INFO 2025-09-27 02:38:21 celerate.py:309 step:32K smpl:2M ep:11K epch:13.35 loss:0.044 grdn:0.201 lr:4.7e-05 updt_s:1.110 data_s:0.010
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INFO 2025-09-27 02:40:14 celerate.py:309 step:32K smpl:2M ep:11K epch:13.39 loss:0.043 grdn:0.205 lr:4.6e-05 updt_s:1.107 data_s:0.010
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INFO 2025-09-27 02:42:07 celerate.py:309 step:32K smpl:2M ep:11K epch:13.43 loss:0.041 grdn:0.203 lr:4.6e-05 updt_s:1.113 data_s:0.010
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INFO 2025-09-27 02:43:59 celerate.py:309 step:32K smpl:2M ep:11K epch:13.47 loss:0.042 grdn:0.206 lr:4.6e-05 updt_s:1.109 data_s:0.011
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INFO 2025-09-27 02:45:53 celerate.py:309 step:32K smpl:2M ep:11K epch:13.51 loss:0.044 grdn:0.204 lr:4.6e-05 updt_s:1.112 data_s:0.011
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INFO 2025-09-27 02:47:45 celerate.py:309 step:32K smpl:2M ep:11K epch:13.56 loss:0.042 grdn:0.206 lr:4.5e-05 updt_s:1.108 data_s:0.010
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INFO 2025-09-27 02:49:38 celerate.py:309 step:32K smpl:2M ep:11K epch:13.60 loss:0.041 grdn:0.217 lr:4.5e-05 updt_s:1.108 data_s:0.010
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INFO 2025-09-27 02:51:31 celerate.py:309 step:33K smpl:2M ep:11K epch:13.64 loss:0.041 grdn:0.195 lr:4.5e-05 updt_s:1.111 data_s:0.010
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| 355 |
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INFO 2025-09-27 02:53:24 celerate.py:309 step:33K smpl:2M ep:11K epch:13.68 loss:0.044 grdn:0.208 lr:4.5e-05 updt_s:1.111 data_s:0.010
|
| 356 |
+
INFO 2025-09-27 02:55:16 celerate.py:309 step:33K smpl:2M ep:11K epch:13.72 loss:0.040 grdn:0.200 lr:4.4e-05 updt_s:1.107 data_s:0.010
|
| 357 |
+
INFO 2025-09-27 02:57:09 celerate.py:309 step:33K smpl:2M ep:11K epch:13.76 loss:0.041 grdn:0.208 lr:4.4e-05 updt_s:1.109 data_s:0.010
|
| 358 |
+
INFO 2025-09-27 02:59:02 celerate.py:309 step:33K smpl:2M ep:11K epch:13.81 loss:0.040 grdn:0.192 lr:4.4e-05 updt_s:1.111 data_s:0.010
|
| 359 |
+
INFO 2025-09-27 03:00:54 celerate.py:309 step:33K smpl:2M ep:11K epch:13.85 loss:0.041 grdn:0.200 lr:4.3e-05 updt_s:1.109 data_s:0.011
|
| 360 |
+
INFO 2025-09-27 03:02:47 celerate.py:309 step:33K smpl:2M ep:11K epch:13.89 loss:0.041 grdn:0.204 lr:4.3e-05 updt_s:1.108 data_s:0.010
|
| 361 |
+
INFO 2025-09-27 03:04:40 celerate.py:309 step:33K smpl:2M ep:11K epch:13.93 loss:0.040 grdn:0.205 lr:4.3e-05 updt_s:1.113 data_s:0.010
|
| 362 |
+
INFO 2025-09-27 03:06:33 celerate.py:309 step:33K smpl:2M ep:11K epch:13.97 loss:0.041 grdn:0.202 lr:4.3e-05 updt_s:1.111 data_s:0.010
|
| 363 |
+
INFO 2025-09-27 03:08:32 celerate.py:309 step:34K smpl:2M ep:11K epch:14.02 loss:0.039 grdn:0.191 lr:4.2e-05 updt_s:1.119 data_s:0.064
|
| 364 |
+
INFO 2025-09-27 03:10:25 celerate.py:309 step:34K smpl:2M ep:11K epch:14.06 loss:0.039 grdn:0.193 lr:4.2e-05 updt_s:1.108 data_s:0.011
|
| 365 |
+
INFO 2025-09-27 03:12:18 celerate.py:309 step:34K smpl:2M ep:11K epch:14.10 loss:0.039 grdn:0.199 lr:4.2e-05 updt_s:1.110 data_s:0.010
|
| 366 |
+
INFO 2025-09-27 03:14:10 celerate.py:309 step:34K smpl:2M ep:11K epch:14.14 loss:0.039 grdn:0.192 lr:4.2e-05 updt_s:1.109 data_s:0.010
|
| 367 |
+
INFO 2025-09-27 03:16:03 celerate.py:309 step:34K smpl:2M ep:11K epch:14.18 loss:0.038 grdn:0.196 lr:4.1e-05 updt_s:1.107 data_s:0.010
|
| 368 |
+
INFO 2025-09-27 03:17:56 celerate.py:309 step:34K smpl:2M ep:11K epch:14.22 loss:0.037 grdn:0.188 lr:4.1e-05 updt_s:1.108 data_s:0.010
|
| 369 |
+
INFO 2025-09-27 03:19:48 celerate.py:309 step:34K smpl:2M ep:11K epch:14.27 loss:0.038 grdn:0.196 lr:4.1e-05 updt_s:1.111 data_s:0.011
|
| 370 |
+
INFO 2025-09-27 03:21:41 celerate.py:309 step:34K smpl:2M ep:11K epch:14.31 loss:0.037 grdn:0.192 lr:4.1e-05 updt_s:1.107 data_s:0.011
|
| 371 |
+
INFO 2025-09-27 03:23:33 celerate.py:309 step:34K smpl:2M ep:11K epch:14.35 loss:0.039 grdn:0.193 lr:4.0e-05 updt_s:1.105 data_s:0.010
|
| 372 |
+
INFO 2025-09-27 03:25:26 celerate.py:309 step:34K smpl:2M ep:12K epch:14.39 loss:0.040 grdn:0.191 lr:4.0e-05 updt_s:1.112 data_s:0.010
|
| 373 |
+
INFO 2025-09-27 03:27:20 celerate.py:309 step:34K smpl:2M ep:12K epch:14.43 loss:0.037 grdn:0.190 lr:4.0e-05 updt_s:1.116 data_s:0.010
|
| 374 |
+
INFO 2025-09-27 03:29:12 celerate.py:309 step:35K smpl:2M ep:12K epch:14.48 loss:0.036 grdn:0.199 lr:4.0e-05 updt_s:1.109 data_s:0.010
|
| 375 |
+
INFO 2025-09-27 03:31:05 celerate.py:309 step:35K smpl:2M ep:12K epch:14.52 loss:0.036 grdn:0.189 lr:3.9e-05 updt_s:1.108 data_s:0.010
|
| 376 |
+
INFO 2025-09-27 03:32:58 celerate.py:309 step:35K smpl:2M ep:12K epch:14.56 loss:0.038 grdn:0.188 lr:3.9e-05 updt_s:1.110 data_s:0.010
|
| 377 |
+
INFO 2025-09-27 03:34:51 celerate.py:309 step:35K smpl:2M ep:12K epch:14.60 loss:0.036 grdn:0.188 lr:3.9e-05 updt_s:1.109 data_s:0.010
|
| 378 |
+
INFO 2025-09-27 03:36:43 celerate.py:309 step:35K smpl:2M ep:12K epch:14.64 loss:0.038 grdn:0.185 lr:3.9e-05 updt_s:1.108 data_s:0.010
|
| 379 |
+
INFO 2025-09-27 03:36:43 celerate.py:334 Checkpoint policy after step 35000
|
| 380 |
+
INFO 2025-09-27 03:39:00 celerate.py:309 step:35K smpl:2M ep:12K epch:14.68 loss:0.036 grdn:0.189 lr:3.9e-05 updt_s:1.105 data_s:0.010
|
| 381 |
+
INFO 2025-09-27 03:40:53 celerate.py:309 step:35K smpl:2M ep:12K epch:14.73 loss:0.037 grdn:0.198 lr:3.8e-05 updt_s:1.111 data_s:0.010
|
| 382 |
+
INFO 2025-09-27 03:42:45 celerate.py:309 step:35K smpl:2M ep:12K epch:14.77 loss:0.037 grdn:0.188 lr:3.8e-05 updt_s:1.107 data_s:0.010
|
| 383 |
+
INFO 2025-09-27 03:44:38 celerate.py:309 step:35K smpl:2M ep:12K epch:14.81 loss:0.037 grdn:0.183 lr:3.8e-05 updt_s:1.108 data_s:0.010
|
| 384 |
+
INFO 2025-09-27 03:46:31 celerate.py:309 step:36K smpl:2M ep:12K epch:14.85 loss:0.037 grdn:0.191 lr:3.8e-05 updt_s:1.111 data_s:0.011
|
| 385 |
+
INFO 2025-09-27 03:48:24 celerate.py:309 step:36K smpl:2M ep:12K epch:14.89 loss:0.037 grdn:0.184 lr:3.7e-05 updt_s:1.111 data_s:0.010
|
| 386 |
+
INFO 2025-09-27 03:50:17 celerate.py:309 step:36K smpl:2M ep:12K epch:14.94 loss:0.036 grdn:0.188 lr:3.7e-05 updt_s:1.110 data_s:0.010
|
| 387 |
+
INFO 2025-09-27 03:52:09 celerate.py:309 step:36K smpl:2M ep:12K epch:14.98 loss:0.037 grdn:0.194 lr:3.7e-05 updt_s:1.109 data_s:0.011
|
| 388 |
+
INFO 2025-09-27 03:54:08 celerate.py:309 step:36K smpl:2M ep:12K epch:15.02 loss:0.035 grdn:0.186 lr:3.7e-05 updt_s:1.130 data_s:0.053
|
| 389 |
+
INFO 2025-09-27 03:56:01 celerate.py:309 step:36K smpl:2M ep:12K epch:15.06 loss:0.033 grdn:0.176 lr:3.6e-05 updt_s:1.106 data_s:0.010
|
| 390 |
+
INFO 2025-09-27 03:57:53 celerate.py:309 step:36K smpl:2M ep:12K epch:15.10 loss:0.035 grdn:0.191 lr:3.6e-05 updt_s:1.107 data_s:0.010
|
| 391 |
+
INFO 2025-09-27 03:59:46 celerate.py:309 step:36K smpl:2M ep:12K epch:15.15 loss:0.035 grdn:0.180 lr:3.6e-05 updt_s:1.111 data_s:0.010
|
| 392 |
+
INFO 2025-09-27 04:01:39 celerate.py:309 step:36K smpl:2M ep:12K epch:15.19 loss:0.034 grdn:0.185 lr:3.6e-05 updt_s:1.109 data_s:0.009
|
| 393 |
+
INFO 2025-09-27 04:03:31 celerate.py:309 step:36K smpl:2M ep:12K epch:15.23 loss:0.035 grdn:0.191 lr:3.5e-05 updt_s:1.106 data_s:0.008
|
| 394 |
+
INFO 2025-09-27 04:05:24 celerate.py:309 step:36K smpl:2M ep:12K epch:15.27 loss:0.034 grdn:0.187 lr:3.5e-05 updt_s:1.108 data_s:0.009
|
| 395 |
+
INFO 2025-09-27 04:07:17 celerate.py:309 step:37K smpl:2M ep:12K epch:15.31 loss:0.034 grdn:0.183 lr:3.5e-05 updt_s:1.108 data_s:0.009
|
| 396 |
+
INFO 2025-09-27 04:09:09 celerate.py:309 step:37K smpl:2M ep:12K epch:15.35 loss:0.035 grdn:0.179 lr:3.5e-05 updt_s:1.107 data_s:0.009
|
| 397 |
+
INFO 2025-09-27 04:11:02 celerate.py:309 step:37K smpl:2M ep:12K epch:15.40 loss:0.034 grdn:0.183 lr:3.4e-05 updt_s:1.107 data_s:0.008
|
| 398 |
+
INFO 2025-09-27 04:12:55 celerate.py:309 step:37K smpl:2M ep:12K epch:15.44 loss:0.034 grdn:0.185 lr:3.4e-05 updt_s:1.112 data_s:0.009
|
| 399 |
+
INFO 2025-09-27 04:14:48 celerate.py:309 step:37K smpl:2M ep:12K epch:15.48 loss:0.033 grdn:0.176 lr:3.4e-05 updt_s:1.109 data_s:0.009
|
| 400 |
+
INFO 2025-09-27 04:16:40 celerate.py:309 step:37K smpl:2M ep:12K epch:15.52 loss:0.034 grdn:0.180 lr:3.4e-05 updt_s:1.107 data_s:0.008
|
| 401 |
+
INFO 2025-09-27 04:18:33 celerate.py:309 step:37K smpl:2M ep:12K epch:15.56 loss:0.033 grdn:0.187 lr:3.3e-05 updt_s:1.107 data_s:0.010
|
| 402 |
+
INFO 2025-09-27 04:20:25 celerate.py:309 step:37K smpl:2M ep:12K epch:15.61 loss:0.034 grdn:0.181 lr:3.3e-05 updt_s:1.108 data_s:0.010
|
| 403 |
+
INFO 2025-09-27 04:22:18 celerate.py:309 step:37K smpl:2M ep:13K epch:15.65 loss:0.032 grdn:0.176 lr:3.3e-05 updt_s:1.109 data_s:0.009
|
| 404 |
+
INFO 2025-09-27 04:24:11 celerate.py:309 step:38K smpl:2M ep:13K epch:15.69 loss:0.032 grdn:0.185 lr:3.3e-05 updt_s:1.109 data_s:0.010
|
| 405 |
+
INFO 2025-09-27 04:26:03 celerate.py:309 step:38K smpl:2M ep:13K epch:15.73 loss:0.032 grdn:0.177 lr:3.2e-05 updt_s:1.108 data_s:0.010
|
| 406 |
+
INFO 2025-09-27 04:27:56 celerate.py:309 step:38K smpl:2M ep:13K epch:15.77 loss:0.033 grdn:0.177 lr:3.2e-05 updt_s:1.107 data_s:0.010
|
| 407 |
+
INFO 2025-09-27 04:29:49 celerate.py:309 step:38K smpl:2M ep:13K epch:15.81 loss:0.033 grdn:0.181 lr:3.2e-05 updt_s:1.107 data_s:0.010
|
| 408 |
+
INFO 2025-09-27 04:31:41 celerate.py:309 step:38K smpl:2M ep:13K epch:15.86 loss:0.032 grdn:0.169 lr:3.2e-05 updt_s:1.109 data_s:0.010
|
| 409 |
+
INFO 2025-09-27 04:33:34 celerate.py:309 step:38K smpl:2M ep:13K epch:15.90 loss:0.033 grdn:0.181 lr:3.2e-05 updt_s:1.110 data_s:0.010
|
| 410 |
+
INFO 2025-09-27 04:35:27 celerate.py:309 step:38K smpl:2M ep:13K epch:15.94 loss:0.032 grdn:0.181 lr:3.1e-05 updt_s:1.111 data_s:0.010
|
| 411 |
+
INFO 2025-09-27 04:37:20 celerate.py:309 step:38K smpl:2M ep:13K epch:15.98 loss:0.034 grdn:0.187 lr:3.1e-05 updt_s:1.108 data_s:0.010
|
| 412 |
+
INFO 2025-09-27 04:39:19 celerate.py:309 step:38K smpl:2M ep:13K epch:16.02 loss:0.030 grdn:0.168 lr:3.1e-05 updt_s:1.120 data_s:0.068
|
| 413 |
+
INFO 2025-09-27 04:41:12 celerate.py:309 step:38K smpl:2M ep:13K epch:16.07 loss:0.032 grdn:0.172 lr:3.1e-05 updt_s:1.106 data_s:0.010
|
| 414 |
+
INFO 2025-09-27 04:43:04 celerate.py:309 step:38K smpl:2M ep:13K epch:16.11 loss:0.031 grdn:0.171 lr:3.0e-05 updt_s:1.106 data_s:0.010
|
| 415 |
+
INFO 2025-09-27 04:44:56 celerate.py:309 step:39K smpl:2M ep:13K epch:16.15 loss:0.032 grdn:0.179 lr:3.0e-05 updt_s:1.107 data_s:0.010
|
| 416 |
+
INFO 2025-09-27 04:46:49 celerate.py:309 step:39K smpl:2M ep:13K epch:16.19 loss:0.031 grdn:0.184 lr:3.0e-05 updt_s:1.108 data_s:0.010
|
| 417 |
+
INFO 2025-09-27 04:48:41 celerate.py:309 step:39K smpl:2M ep:13K epch:16.23 loss:0.030 grdn:0.175 lr:3.0e-05 updt_s:1.104 data_s:0.010
|
| 418 |
+
INFO 2025-09-27 04:50:34 celerate.py:309 step:39K smpl:2M ep:13K epch:16.27 loss:0.030 grdn:0.174 lr:2.9e-05 updt_s:1.104 data_s:0.010
|
| 419 |
+
INFO 2025-09-27 04:52:26 celerate.py:309 step:39K smpl:2M ep:13K epch:16.32 loss:0.032 grdn:0.174 lr:2.9e-05 updt_s:1.107 data_s:0.010
|
| 420 |
+
INFO 2025-09-27 04:54:19 celerate.py:309 step:39K smpl:2M ep:13K epch:16.36 loss:0.032 grdn:0.170 lr:2.9e-05 updt_s:1.108 data_s:0.011
|
| 421 |
+
INFO 2025-09-27 04:56:11 celerate.py:309 step:39K smpl:2M ep:13K epch:16.40 loss:0.029 grdn:0.170 lr:2.9e-05 updt_s:1.105 data_s:0.010
|
| 422 |
+
INFO 2025-09-27 04:58:04 celerate.py:309 step:39K smpl:2M ep:13K epch:16.44 loss:0.030 grdn:0.172 lr:2.9e-05 updt_s:1.108 data_s:0.010
|
| 423 |
+
INFO 2025-09-27 04:59:57 celerate.py:309 step:39K smpl:2M ep:13K epch:16.48 loss:0.030 grdn:0.174 lr:2.8e-05 updt_s:1.112 data_s:0.010
|
| 424 |
+
INFO 2025-09-27 05:01:50 celerate.py:309 step:40K smpl:2M ep:13K epch:16.53 loss:0.030 grdn:0.176 lr:2.8e-05 updt_s:1.110 data_s:0.011
|
| 425 |
+
INFO 2025-09-27 05:03:42 celerate.py:309 step:40K smpl:2M ep:13K epch:16.57 loss:0.028 grdn:0.166 lr:2.8e-05 updt_s:1.105 data_s:0.010
|
| 426 |
+
INFO 2025-09-27 05:05:34 celerate.py:309 step:40K smpl:2M ep:13K epch:16.61 loss:0.032 grdn:0.175 lr:2.8e-05 updt_s:1.107 data_s:0.010
|
| 427 |
+
INFO 2025-09-27 05:07:27 celerate.py:309 step:40K smpl:2M ep:13K epch:16.65 loss:0.031 grdn:0.173 lr:2.7e-05 updt_s:1.110 data_s:0.010
|
| 428 |
+
INFO 2025-09-27 05:09:20 celerate.py:309 step:40K smpl:2M ep:13K epch:16.69 loss:0.029 grdn:0.173 lr:2.7e-05 updt_s:1.107 data_s:0.010
|
| 429 |
+
INFO 2025-09-27 05:11:12 celerate.py:309 step:40K smpl:2M ep:13K epch:16.74 loss:0.031 grdn:0.179 lr:2.7e-05 updt_s:1.107 data_s:0.010
|
| 430 |
+
INFO 2025-09-27 05:11:12 celerate.py:334 Checkpoint policy after step 40000
|
| 431 |
+
INFO 2025-09-27 05:13:29 celerate.py:309 step:40K smpl:2M ep:13K epch:16.78 loss:0.029 grdn:0.166 lr:2.7e-05 updt_s:1.104 data_s:0.010
|
| 432 |
+
INFO 2025-09-27 05:15:22 celerate.py:309 step:40K smpl:2M ep:13K epch:16.82 loss:0.030 grdn:0.173 lr:2.7e-05 updt_s:1.105 data_s:0.010
|
| 433 |
+
INFO 2025-09-27 05:17:14 celerate.py:309 step:40K smpl:2M ep:13K epch:16.86 loss:0.030 grdn:0.169 lr:2.6e-05 updt_s:1.104 data_s:0.010
|
| 434 |
+
INFO 2025-09-27 05:19:06 celerate.py:309 step:40K smpl:2M ep:14K epch:16.90 loss:0.031 grdn:0.171 lr:2.6e-05 updt_s:1.106 data_s:0.010
|
| 435 |
+
INFO 2025-09-27 05:20:59 celerate.py:309 step:40K smpl:2M ep:14K epch:16.94 loss:0.029 grdn:0.171 lr:2.6e-05 updt_s:1.110 data_s:0.010
|
| 436 |
+
INFO 2025-09-27 05:22:51 celerate.py:309 step:41K smpl:2M ep:14K epch:16.99 loss:0.028 grdn:0.168 lr:2.6e-05 updt_s:1.107 data_s:0.010
|
| 437 |
+
INFO 2025-09-27 05:24:50 celerate.py:309 step:41K smpl:2M ep:14K epch:17.03 loss:0.029 grdn:0.166 lr:2.5e-05 updt_s:1.122 data_s:0.057
|
| 438 |
+
INFO 2025-09-27 05:26:42 celerate.py:309 step:41K smpl:2M ep:14K epch:17.07 loss:0.029 grdn:0.176 lr:2.5e-05 updt_s:1.106 data_s:0.010
|
| 439 |
+
INFO 2025-09-27 05:28:35 celerate.py:309 step:41K smpl:2M ep:14K epch:17.11 loss:0.028 grdn:0.164 lr:2.5e-05 updt_s:1.107 data_s:0.010
|
| 440 |
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INFO 2025-09-27 05:30:27 celerate.py:309 step:41K smpl:2M ep:14K epch:17.15 loss:0.028 grdn:0.171 lr:2.5e-05 updt_s:1.104 data_s:0.010
|
| 441 |
+
INFO 2025-09-27 05:32:19 celerate.py:309 step:41K smpl:2M ep:14K epch:17.20 loss:0.028 grdn:0.165 lr:2.5e-05 updt_s:1.105 data_s:0.010
|
| 442 |
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INFO 2025-09-27 05:34:12 celerate.py:309 step:41K smpl:2M ep:14K epch:17.24 loss:0.029 grdn:0.169 lr:2.4e-05 updt_s:1.106 data_s:0.010
|
| 443 |
+
INFO 2025-09-27 05:36:04 celerate.py:309 step:41K smpl:2M ep:14K epch:17.28 loss:0.029 grdn:0.171 lr:2.4e-05 updt_s:1.106 data_s:0.010
|
| 444 |
+
INFO 2025-09-27 05:37:56 celerate.py:309 step:41K smpl:2M ep:14K epch:17.32 loss:0.029 grdn:0.166 lr:2.4e-05 updt_s:1.104 data_s:0.010
|
| 445 |
+
INFO 2025-09-27 05:39:49 celerate.py:309 step:42K smpl:2M ep:14K epch:17.36 loss:0.029 grdn:0.168 lr:2.4e-05 updt_s:1.104 data_s:0.010
|
| 446 |
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INFO 2025-09-27 05:41:41 celerate.py:309 step:42K smpl:2M ep:14K epch:17.40 loss:0.028 grdn:0.170 lr:2.4e-05 updt_s:1.107 data_s:0.010
|
| 447 |
+
INFO 2025-09-27 05:43:33 celerate.py:309 step:42K smpl:2M ep:14K epch:17.45 loss:0.028 grdn:0.161 lr:2.3e-05 updt_s:1.106 data_s:0.010
|
| 448 |
+
INFO 2025-09-27 05:45:26 celerate.py:309 step:42K smpl:2M ep:14K epch:17.49 loss:0.027 grdn:0.162 lr:2.3e-05 updt_s:1.105 data_s:0.010
|
| 449 |
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INFO 2025-09-27 05:47:18 celerate.py:309 step:42K smpl:2M ep:14K epch:17.53 loss:0.028 grdn:0.167 lr:2.3e-05 updt_s:1.105 data_s:0.010
|
| 450 |
+
INFO 2025-09-27 05:49:11 celerate.py:309 step:42K smpl:2M ep:14K epch:17.57 loss:0.028 grdn:0.163 lr:2.3e-05 updt_s:1.108 data_s:0.010
|
| 451 |
+
INFO 2025-09-27 05:51:03 celerate.py:309 step:42K smpl:2M ep:14K epch:17.61 loss:0.029 grdn:0.171 lr:2.2e-05 updt_s:1.105 data_s:0.010
|
| 452 |
+
INFO 2025-09-27 05:52:55 celerate.py:309 step:42K smpl:2M ep:14K epch:17.66 loss:0.028 grdn:0.163 lr:2.2e-05 updt_s:1.105 data_s:0.010
|
| 453 |
+
INFO 2025-09-27 05:54:48 celerate.py:309 step:42K smpl:2M ep:14K epch:17.70 loss:0.028 grdn:0.162 lr:2.2e-05 updt_s:1.107 data_s:0.010
|
| 454 |
+
INFO 2025-09-27 05:56:40 celerate.py:309 step:42K smpl:2M ep:14K epch:17.74 loss:0.028 grdn:0.162 lr:2.2e-05 updt_s:1.106 data_s:0.010
|
| 455 |
+
INFO 2025-09-27 05:58:32 celerate.py:309 step:42K smpl:2M ep:14K epch:17.78 loss:0.029 grdn:0.163 lr:2.2e-05 updt_s:1.105 data_s:0.010
|
| 456 |
+
INFO 2025-09-27 06:00:25 celerate.py:309 step:43K smpl:2M ep:14K epch:17.82 loss:0.029 grdn:0.163 lr:2.1e-05 updt_s:1.106 data_s:0.010
|
| 457 |
+
INFO 2025-09-27 06:02:17 celerate.py:309 step:43K smpl:2M ep:14K epch:17.86 loss:0.028 grdn:0.166 lr:2.1e-05 updt_s:1.106 data_s:0.010
|
| 458 |
+
INFO 2025-09-27 06:04:10 celerate.py:309 step:43K smpl:2M ep:14K epch:17.91 loss:0.029 grdn:0.165 lr:2.1e-05 updt_s:1.106 data_s:0.010
|
| 459 |
+
INFO 2025-09-27 06:06:02 celerate.py:309 step:43K smpl:2M ep:14K epch:17.95 loss:0.028 grdn:0.170 lr:2.1e-05 updt_s:1.105 data_s:0.010
|
| 460 |
+
INFO 2025-09-27 06:07:54 celerate.py:309 step:43K smpl:2M ep:14K epch:17.99 loss:0.027 grdn:0.160 lr:2.1e-05 updt_s:1.108 data_s:0.010
|
| 461 |
+
INFO 2025-09-27 06:09:53 celerate.py:309 step:43K smpl:2M ep:14K epch:18.03 loss:0.027 grdn:0.160 lr:2.0e-05 updt_s:1.117 data_s:0.060
|
| 462 |
+
INFO 2025-09-27 06:11:46 celerate.py:309 step:43K smpl:2M ep:14K epch:18.07 loss:0.026 grdn:0.164 lr:2.0e-05 updt_s:1.107 data_s:0.010
|
| 463 |
+
INFO 2025-09-27 06:13:38 celerate.py:309 step:43K smpl:2M ep:14K epch:18.12 loss:0.027 grdn:0.165 lr:2.0e-05 updt_s:1.107 data_s:0.010
|
| 464 |
+
INFO 2025-09-27 06:15:31 celerate.py:309 step:43K smpl:2M ep:15K epch:18.16 loss:0.028 grdn:0.163 lr:2.0e-05 updt_s:1.107 data_s:0.010
|
| 465 |
+
INFO 2025-09-27 06:17:23 celerate.py:309 step:44K smpl:2M ep:15K epch:18.20 loss:0.025 grdn:0.164 lr:2.0e-05 updt_s:1.106 data_s:0.010
|
| 466 |
+
INFO 2025-09-27 06:19:15 celerate.py:309 step:44K smpl:2M ep:15K epch:18.24 loss:0.026 grdn:0.162 lr:1.9e-05 updt_s:1.106 data_s:0.010
|
| 467 |
+
INFO 2025-09-27 06:21:08 celerate.py:309 step:44K smpl:2M ep:15K epch:18.28 loss:0.027 grdn:0.163 lr:1.9e-05 updt_s:1.106 data_s:0.010
|
| 468 |
+
INFO 2025-09-27 06:23:00 celerate.py:309 step:44K smpl:2M ep:15K epch:18.32 loss:0.028 grdn:0.166 lr:1.9e-05 updt_s:1.106 data_s:0.010
|
| 469 |
+
INFO 2025-09-27 06:24:53 celerate.py:309 step:44K smpl:2M ep:15K epch:18.37 loss:0.027 grdn:0.163 lr:1.9e-05 updt_s:1.105 data_s:0.010
|
| 470 |
+
INFO 2025-09-27 06:26:45 celerate.py:309 step:44K smpl:2M ep:15K epch:18.41 loss:0.026 grdn:0.156 lr:1.9e-05 updt_s:1.106 data_s:0.011
|
| 471 |
+
INFO 2025-09-27 06:28:38 celerate.py:309 step:44K smpl:2M ep:15K epch:18.45 loss:0.027 grdn:0.162 lr:1.9e-05 updt_s:1.108 data_s:0.010
|
| 472 |
+
INFO 2025-09-27 06:30:31 celerate.py:309 step:44K smpl:2M ep:15K epch:18.49 loss:0.026 grdn:0.159 lr:1.8e-05 updt_s:1.108 data_s:0.011
|
| 473 |
+
INFO 2025-09-27 06:32:23 celerate.py:309 step:44K smpl:2M ep:15K epch:18.53 loss:0.026 grdn:0.163 lr:1.8e-05 updt_s:1.105 data_s:0.010
|
| 474 |
+
INFO 2025-09-27 06:34:16 celerate.py:309 step:44K smpl:2M ep:15K epch:18.58 loss:0.027 grdn:0.159 lr:1.8e-05 updt_s:1.108 data_s:0.010
|
| 475 |
+
INFO 2025-09-27 06:36:08 celerate.py:309 step:44K smpl:2M ep:15K epch:18.62 loss:0.026 grdn:0.161 lr:1.8e-05 updt_s:1.108 data_s:0.010
|
| 476 |
+
INFO 2025-09-27 06:38:01 celerate.py:309 step:45K smpl:2M ep:15K epch:18.66 loss:0.027 grdn:0.164 lr:1.8e-05 updt_s:1.107 data_s:0.010
|
| 477 |
+
INFO 2025-09-27 06:39:53 celerate.py:309 step:45K smpl:3M ep:15K epch:18.70 loss:0.025 grdn:0.154 lr:1.7e-05 updt_s:1.108 data_s:0.010
|
| 478 |
+
INFO 2025-09-27 06:41:46 celerate.py:309 step:45K smpl:3M ep:15K epch:18.74 loss:0.027 grdn:0.159 lr:1.7e-05 updt_s:1.108 data_s:0.010
|
| 479 |
+
INFO 2025-09-27 06:43:38 celerate.py:309 step:45K smpl:3M ep:15K epch:18.79 loss:0.025 grdn:0.156 lr:1.7e-05 updt_s:1.106 data_s:0.010
|
| 480 |
+
INFO 2025-09-27 06:45:31 celerate.py:309 step:45K smpl:3M ep:15K epch:18.83 loss:0.026 grdn:0.158 lr:1.7e-05 updt_s:1.105 data_s:0.010
|
| 481 |
+
INFO 2025-09-27 06:45:31 celerate.py:334 Checkpoint policy after step 45000
|
| 482 |
+
INFO 2025-09-27 06:47:48 celerate.py:309 step:45K smpl:3M ep:15K epch:18.87 loss:0.025 grdn:0.153 lr:1.7e-05 updt_s:1.103 data_s:0.010
|
| 483 |
+
INFO 2025-09-27 06:49:41 celerate.py:309 step:45K smpl:3M ep:15K epch:18.91 loss:0.028 grdn:0.157 lr:1.7e-05 updt_s:1.108 data_s:0.010
|
| 484 |
+
INFO 2025-09-27 06:51:34 celerate.py:309 step:45K smpl:3M ep:15K epch:18.95 loss:0.025 grdn:0.161 lr:1.6e-05 updt_s:1.107 data_s:0.010
|
| 485 |
+
INFO 2025-09-27 06:53:26 celerate.py:309 step:45K smpl:3M ep:15K epch:18.99 loss:0.025 grdn:0.155 lr:1.6e-05 updt_s:1.107 data_s:0.011
|
| 486 |
+
INFO 2025-09-27 06:55:26 celerate.py:309 step:46K smpl:3M ep:15K epch:19.04 loss:0.026 grdn:0.158 lr:1.6e-05 updt_s:1.126 data_s:0.062
|
| 487 |
+
INFO 2025-09-27 06:57:18 celerate.py:309 step:46K smpl:3M ep:15K epch:19.08 loss:0.027 grdn:0.161 lr:1.6e-05 updt_s:1.107 data_s:0.010
|
| 488 |
+
INFO 2025-09-27 06:59:11 celerate.py:309 step:46K smpl:3M ep:15K epch:19.12 loss:0.025 grdn:0.151 lr:1.6e-05 updt_s:1.105 data_s:0.010
|
| 489 |
+
INFO 2025-09-27 07:01:03 celerate.py:309 step:46K smpl:3M ep:15K epch:19.16 loss:0.026 grdn:0.159 lr:1.5e-05 updt_s:1.107 data_s:0.010
|
| 490 |
+
INFO 2025-09-27 07:02:56 celerate.py:309 step:46K smpl:3M ep:15K epch:19.20 loss:0.026 grdn:0.161 lr:1.5e-05 updt_s:1.109 data_s:0.010
|
| 491 |
+
INFO 2025-09-27 07:04:48 celerate.py:309 step:46K smpl:3M ep:15K epch:19.25 loss:0.025 grdn:0.157 lr:1.5e-05 updt_s:1.105 data_s:0.010
|
| 492 |
+
INFO 2025-09-27 07:06:40 celerate.py:309 step:46K smpl:3M ep:15K epch:19.29 loss:0.026 grdn:0.162 lr:1.5e-05 updt_s:1.105 data_s:0.010
|
| 493 |
+
INFO 2025-09-27 07:08:33 celerate.py:309 step:46K smpl:3M ep:15K epch:19.33 loss:0.024 grdn:0.153 lr:1.5e-05 updt_s:1.109 data_s:0.010
|
| 494 |
+
INFO 2025-09-27 07:10:26 celerate.py:309 step:46K smpl:3M ep:15K epch:19.37 loss:0.027 grdn:0.160 lr:1.5e-05 updt_s:1.110 data_s:0.010
|
| 495 |
+
INFO 2025-09-27 07:12:18 celerate.py:309 step:46K smpl:3M ep:16K epch:19.41 loss:0.024 grdn:0.153 lr:1.4e-05 updt_s:1.107 data_s:0.010
|
| 496 |
+
INFO 2025-09-27 07:14:11 celerate.py:309 step:46K smpl:3M ep:16K epch:19.45 loss:0.024 grdn:0.152 lr:1.4e-05 updt_s:1.108 data_s:0.010
|
| 497 |
+
INFO 2025-09-27 07:16:04 celerate.py:309 step:47K smpl:3M ep:16K epch:19.50 loss:0.025 grdn:0.153 lr:1.4e-05 updt_s:1.111 data_s:0.010
|
| 498 |
+
INFO 2025-09-27 07:17:57 celerate.py:309 step:47K smpl:3M ep:16K epch:19.54 loss:0.026 grdn:0.158 lr:1.4e-05 updt_s:1.108 data_s:0.010
|
| 499 |
+
INFO 2025-09-27 07:19:49 celerate.py:309 step:47K smpl:3M ep:16K epch:19.58 loss:0.026 grdn:0.159 lr:1.4e-05 updt_s:1.104 data_s:0.010
|
| 500 |
+
INFO 2025-09-27 07:21:41 celerate.py:309 step:47K smpl:3M ep:16K epch:19.62 loss:0.025 grdn:0.153 lr:1.4e-05 updt_s:1.105 data_s:0.010
|
| 501 |
+
INFO 2025-09-27 07:23:34 celerate.py:309 step:47K smpl:3M ep:16K epch:19.66 loss:0.025 grdn:0.151 lr:1.3e-05 updt_s:1.109 data_s:0.010
|
| 502 |
+
INFO 2025-09-27 07:25:26 celerate.py:309 step:47K smpl:3M ep:16K epch:19.71 loss:0.024 grdn:0.151 lr:1.3e-05 updt_s:1.107 data_s:0.010
|
| 503 |
+
INFO 2025-09-27 07:27:19 celerate.py:309 step:47K smpl:3M ep:16K epch:19.75 loss:0.026 grdn:0.157 lr:1.3e-05 updt_s:1.107 data_s:0.010
|
| 504 |
+
INFO 2025-09-27 07:29:11 celerate.py:309 step:47K smpl:3M ep:16K epch:19.79 loss:0.026 grdn:0.159 lr:1.3e-05 updt_s:1.107 data_s:0.010
|
| 505 |
+
INFO 2025-09-27 07:31:04 celerate.py:309 step:47K smpl:3M ep:16K epch:19.83 loss:0.024 grdn:0.157 lr:1.3e-05 updt_s:1.109 data_s:0.010
|
| 506 |
+
INFO 2025-09-27 07:32:56 celerate.py:309 step:48K smpl:3M ep:16K epch:19.87 loss:0.026 grdn:0.160 lr:1.3e-05 updt_s:1.106 data_s:0.010
|
| 507 |
+
INFO 2025-09-27 07:34:49 celerate.py:309 step:48K smpl:3M ep:16K epch:19.91 loss:0.025 grdn:0.155 lr:1.2e-05 updt_s:1.104 data_s:0.010
|
| 508 |
+
INFO 2025-09-27 07:36:41 celerate.py:309 step:48K smpl:3M ep:16K epch:19.96 loss:0.026 grdn:0.157 lr:1.2e-05 updt_s:1.108 data_s:0.010
|
| 509 |
+
INFO 2025-09-27 07:38:34 celerate.py:309 step:48K smpl:3M ep:16K epch:20.00 loss:0.025 grdn:0.154 lr:1.2e-05 updt_s:1.109 data_s:0.013
|
| 510 |
+
INFO 2025-09-27 07:40:33 celerate.py:309 step:48K smpl:3M ep:16K epch:20.04 loss:0.025 grdn:0.158 lr:1.2e-05 updt_s:1.119 data_s:0.061
|
| 511 |
+
INFO 2025-09-27 07:42:25 celerate.py:309 step:48K smpl:3M ep:16K epch:20.08 loss:0.025 grdn:0.147 lr:1.2e-05 updt_s:1.105 data_s:0.010
|
| 512 |
+
INFO 2025-09-27 07:44:18 celerate.py:309 step:48K smpl:3M ep:16K epch:20.12 loss:0.025 grdn:0.154 lr:1.2e-05 updt_s:1.109 data_s:0.010
|
| 513 |
+
INFO 2025-09-27 07:46:11 celerate.py:309 step:48K smpl:3M ep:16K epch:20.17 loss:0.023 grdn:0.151 lr:1.2e-05 updt_s:1.108 data_s:0.010
|
| 514 |
+
INFO 2025-09-27 07:48:03 celerate.py:309 step:48K smpl:3M ep:16K epch:20.21 loss:0.024 grdn:0.151 lr:1.1e-05 updt_s:1.106 data_s:0.010
|
| 515 |
+
INFO 2025-09-27 07:49:56 celerate.py:309 step:48K smpl:3M ep:16K epch:20.25 loss:0.024 grdn:0.151 lr:1.1e-05 updt_s:1.106 data_s:0.010
|
| 516 |
+
INFO 2025-09-27 07:51:48 celerate.py:309 step:48K smpl:3M ep:16K epch:20.29 loss:0.024 grdn:0.153 lr:1.1e-05 updt_s:1.106 data_s:0.010
|
| 517 |
+
INFO 2025-09-27 07:53:40 celerate.py:309 step:49K smpl:3M ep:16K epch:20.33 loss:0.026 grdn:0.160 lr:1.1e-05 updt_s:1.106 data_s:0.010
|
| 518 |
+
INFO 2025-09-27 07:55:33 celerate.py:309 step:49K smpl:3M ep:16K epch:20.37 loss:0.025 grdn:0.153 lr:1.1e-05 updt_s:1.105 data_s:0.010
|
| 519 |
+
INFO 2025-09-27 07:57:25 celerate.py:309 step:49K smpl:3M ep:16K epch:20.42 loss:0.025 grdn:0.152 lr:1.1e-05 updt_s:1.107 data_s:0.010
|
| 520 |
+
INFO 2025-09-27 07:59:18 celerate.py:309 step:49K smpl:3M ep:16K epch:20.46 loss:0.025 grdn:0.153 lr:1.1e-05 updt_s:1.108 data_s:0.010
|
| 521 |
+
INFO 2025-09-27 08:01:11 celerate.py:309 step:49K smpl:3M ep:16K epch:20.50 loss:0.025 grdn:0.154 lr:1.0e-05 updt_s:1.111 data_s:0.010
|
| 522 |
+
INFO 2025-09-27 08:03:03 celerate.py:309 step:49K smpl:3M ep:16K epch:20.54 loss:0.024 grdn:0.150 lr:1.0e-05 updt_s:1.107 data_s:0.010
|
| 523 |
+
INFO 2025-09-27 08:04:56 celerate.py:309 step:49K smpl:3M ep:16K epch:20.58 loss:0.026 grdn:0.154 lr:1.0e-05 updt_s:1.108 data_s:0.010
|
| 524 |
+
INFO 2025-09-27 08:06:48 celerate.py:309 step:49K smpl:3M ep:17K epch:20.63 loss:0.024 grdn:0.155 lr:1.0e-05 updt_s:1.107 data_s:0.011
|
| 525 |
+
INFO 2025-09-27 08:08:41 celerate.py:309 step:49K smpl:3M ep:17K epch:20.67 loss:0.024 grdn:0.152 lr:9.9e-06 updt_s:1.106 data_s:0.010
|
| 526 |
+
INFO 2025-09-27 08:10:33 celerate.py:309 step:50K smpl:3M ep:17K epch:20.71 loss:0.025 grdn:0.151 lr:9.7e-06 updt_s:1.108 data_s:0.010
|
| 527 |
+
INFO 2025-09-27 08:12:26 celerate.py:309 step:50K smpl:3M ep:17K epch:20.75 loss:0.025 grdn:0.152 lr:9.6e-06 updt_s:1.108 data_s:0.010
|
| 528 |
+
INFO 2025-09-27 08:14:18 celerate.py:309 step:50K smpl:3M ep:17K epch:20.79 loss:0.024 grdn:0.151 lr:9.5e-06 updt_s:1.106 data_s:0.010
|
| 529 |
+
INFO 2025-09-27 08:16:11 celerate.py:309 step:50K smpl:3M ep:17K epch:20.84 loss:0.025 grdn:0.150 lr:9.4e-06 updt_s:1.106 data_s:0.010
|
| 530 |
+
INFO 2025-09-27 08:18:04 celerate.py:309 step:50K smpl:3M ep:17K epch:20.88 loss:0.024 grdn:0.154 lr:9.2e-06 updt_s:1.109 data_s:0.010
|
| 531 |
+
INFO 2025-09-27 08:19:56 celerate.py:309 step:50K smpl:3M ep:17K epch:20.92 loss:0.025 grdn:0.156 lr:9.1e-06 updt_s:1.107 data_s:0.010
|
| 532 |
+
INFO 2025-09-27 08:19:56 celerate.py:334 Checkpoint policy after step 50000
|
| 533 |
+
INFO 2025-09-27 08:22:14 celerate.py:309 step:50K smpl:3M ep:17K epch:20.96 loss:0.024 grdn:0.148 lr:9.0e-06 updt_s:1.102 data_s:0.010
|
| 534 |
+
INFO 2025-09-27 08:24:14 celerate.py:309 step:50K smpl:3M ep:17K epch:21.00 loss:0.024 grdn:0.151 lr:8.8e-06 updt_s:1.119 data_s:0.071
|
| 535 |
+
INFO 2025-09-27 08:26:07 celerate.py:309 step:50K smpl:3M ep:17K epch:21.04 loss:0.024 grdn:0.150 lr:8.7e-06 updt_s:1.107 data_s:0.010
|
| 536 |
+
INFO 2025-09-27 08:27:59 celerate.py:309 step:50K smpl:3M ep:17K epch:21.09 loss:0.023 grdn:0.149 lr:8.6e-06 updt_s:1.107 data_s:0.011
|
| 537 |
+
INFO 2025-09-27 08:29:52 celerate.py:309 step:50K smpl:3M ep:17K epch:21.13 loss:0.024 grdn:0.151 lr:8.5e-06 updt_s:1.107 data_s:0.010
|
| 538 |
+
INFO 2025-09-27 08:31:44 celerate.py:309 step:51K smpl:3M ep:17K epch:21.17 loss:0.025 grdn:0.155 lr:8.3e-06 updt_s:1.109 data_s:0.010
|
| 539 |
+
INFO 2025-09-27 08:33:37 celerate.py:309 step:51K smpl:3M ep:17K epch:21.21 loss:0.023 grdn:0.147 lr:8.2e-06 updt_s:1.107 data_s:0.010
|
| 540 |
+
INFO 2025-09-27 08:35:29 celerate.py:309 step:51K smpl:3M ep:17K epch:21.25 loss:0.026 grdn:0.154 lr:8.1e-06 updt_s:1.105 data_s:0.010
|
| 541 |
+
INFO 2025-09-27 08:37:22 celerate.py:309 step:51K smpl:3M ep:17K epch:21.30 loss:0.025 grdn:0.157 lr:8.0e-06 updt_s:1.107 data_s:0.010
|
| 542 |
+
INFO 2025-09-27 08:39:15 celerate.py:309 step:51K smpl:3M ep:17K epch:21.34 loss:0.024 grdn:0.154 lr:7.9e-06 updt_s:1.111 data_s:0.009
|
| 543 |
+
INFO 2025-09-27 08:41:07 celerate.py:309 step:51K smpl:3M ep:17K epch:21.38 loss:0.025 grdn:0.152 lr:7.8e-06 updt_s:1.106 data_s:0.009
|
| 544 |
+
INFO 2025-09-27 08:42:59 celerate.py:309 step:51K smpl:3M ep:17K epch:21.42 loss:0.026 grdn:0.150 lr:7.6e-06 updt_s:1.104 data_s:0.010
|
| 545 |
+
INFO 2025-09-27 08:44:52 celerate.py:309 step:51K smpl:3M ep:17K epch:21.46 loss:0.025 grdn:0.150 lr:7.5e-06 updt_s:1.107 data_s:0.010
|
| 546 |
+
INFO 2025-09-27 08:46:45 celerate.py:309 step:51K smpl:3M ep:17K epch:21.50 loss:0.025 grdn:0.149 lr:7.4e-06 updt_s:1.109 data_s:0.010
|
| 547 |
+
INFO 2025-09-27 08:48:37 celerate.py:309 step:52K smpl:3M ep:17K epch:21.55 loss:0.024 grdn:0.152 lr:7.3e-06 updt_s:1.105 data_s:0.010
|
| 548 |
+
INFO 2025-09-27 08:50:29 celerate.py:309 step:52K smpl:3M ep:17K epch:21.59 loss:0.023 grdn:0.147 lr:7.2e-06 updt_s:1.104 data_s:0.010
|
| 549 |
+
INFO 2025-09-27 08:52:22 celerate.py:309 step:52K smpl:3M ep:17K epch:21.63 loss:0.025 grdn:0.152 lr:7.1e-06 updt_s:1.108 data_s:0.010
|
| 550 |
+
INFO 2025-09-27 08:54:14 celerate.py:309 step:52K smpl:3M ep:17K epch:21.67 loss:0.024 grdn:0.148 lr:7.0e-06 updt_s:1.106 data_s:0.010
|
| 551 |
+
INFO 2025-09-27 08:56:06 celerate.py:309 step:52K smpl:3M ep:17K epch:21.71 loss:0.024 grdn:0.151 lr:6.9e-06 updt_s:1.105 data_s:0.010
|
| 552 |
+
INFO 2025-09-27 08:57:59 celerate.py:309 step:52K smpl:3M ep:17K epch:21.76 loss:0.024 grdn:0.152 lr:6.8e-06 updt_s:1.105 data_s:0.010
|
| 553 |
+
INFO 2025-09-27 08:59:51 celerate.py:309 step:52K smpl:3M ep:17K epch:21.80 loss:0.023 grdn:0.148 lr:6.7e-06 updt_s:1.108 data_s:0.010
|
| 554 |
+
INFO 2025-09-27 09:01:44 celerate.py:309 step:52K smpl:3M ep:17K epch:21.84 loss:0.024 grdn:0.152 lr:6.6e-06 updt_s:1.106 data_s:0.010
|
| 555 |
+
INFO 2025-09-27 09:03:36 celerate.py:309 step:52K smpl:3M ep:18K epch:21.88 loss:0.026 grdn:0.154 lr:6.5e-06 updt_s:1.104 data_s:0.010
|
| 556 |
+
INFO 2025-09-27 09:05:28 celerate.py:309 step:52K smpl:3M ep:18K epch:21.92 loss:0.024 grdn:0.148 lr:6.4e-06 updt_s:1.105 data_s:0.010
|
| 557 |
+
INFO 2025-09-27 09:07:21 celerate.py:309 step:52K smpl:3M ep:18K epch:21.96 loss:0.024 grdn:0.149 lr:6.3e-06 updt_s:1.109 data_s:0.010
|
| 558 |
+
INFO 2025-09-27 09:09:20 celerate.py:309 step:53K smpl:3M ep:18K epch:22.01 loss:0.024 grdn:0.150 lr:6.2e-06 updt_s:1.114 data_s:0.069
|
| 559 |
+
INFO 2025-09-27 09:11:12 celerate.py:309 step:53K smpl:3M ep:18K epch:22.05 loss:0.026 grdn:0.154 lr:6.1e-06 updt_s:1.105 data_s:0.010
|
| 560 |
+
INFO 2025-09-27 09:13:05 celerate.py:309 step:53K smpl:3M ep:18K epch:22.09 loss:0.024 grdn:0.150 lr:6.0e-06 updt_s:1.108 data_s:0.010
|
| 561 |
+
INFO 2025-09-27 09:14:58 celerate.py:309 step:53K smpl:3M ep:18K epch:22.13 loss:0.023 grdn:0.152 lr:5.9e-06 updt_s:1.107 data_s:0.011
|
| 562 |
+
INFO 2025-09-27 09:16:50 celerate.py:309 step:53K smpl:3M ep:18K epch:22.17 loss:0.026 grdn:0.155 lr:5.8e-06 updt_s:1.104 data_s:0.010
|
| 563 |
+
INFO 2025-09-27 09:18:42 celerate.py:309 step:53K smpl:3M ep:18K epch:22.22 loss:0.023 grdn:0.147 lr:5.7e-06 updt_s:1.106 data_s:0.010
|
| 564 |
+
INFO 2025-09-27 09:20:35 celerate.py:309 step:53K smpl:3M ep:18K epch:22.26 loss:0.023 grdn:0.148 lr:5.6e-06 updt_s:1.107 data_s:0.010
|
| 565 |
+
INFO 2025-09-27 09:22:27 celerate.py:309 step:53K smpl:3M ep:18K epch:22.30 loss:0.024 grdn:0.146 lr:5.5e-06 updt_s:1.105 data_s:0.011
|
| 566 |
+
INFO 2025-09-27 09:24:20 celerate.py:309 step:53K smpl:3M ep:18K epch:22.34 loss:0.024 grdn:0.146 lr:5.4e-06 updt_s:1.105 data_s:0.011
|
| 567 |
+
INFO 2025-09-27 09:26:12 celerate.py:309 step:54K smpl:3M ep:18K epch:22.38 loss:0.024 grdn:0.152 lr:5.3e-06 updt_s:1.106 data_s:0.010
|
| 568 |
+
INFO 2025-09-27 09:28:05 celerate.py:309 step:54K smpl:3M ep:18K epch:22.42 loss:0.023 grdn:0.146 lr:5.3e-06 updt_s:1.106 data_s:0.010
|
| 569 |
+
INFO 2025-09-27 09:29:57 celerate.py:309 step:54K smpl:3M ep:18K epch:22.47 loss:0.023 grdn:0.148 lr:5.2e-06 updt_s:1.107 data_s:0.010
|
| 570 |
+
INFO 2025-09-27 09:31:50 celerate.py:309 step:54K smpl:3M ep:18K epch:22.51 loss:0.025 grdn:0.150 lr:5.1e-06 updt_s:1.106 data_s:0.010
|
| 571 |
+
INFO 2025-09-27 09:33:42 celerate.py:309 step:54K smpl:3M ep:18K epch:22.55 loss:0.024 grdn:0.145 lr:5.0e-06 updt_s:1.109 data_s:0.011
|
| 572 |
+
INFO 2025-09-27 09:35:35 celerate.py:309 step:54K smpl:3M ep:18K epch:22.59 loss:0.023 grdn:0.146 lr:4.9e-06 updt_s:1.106 data_s:0.010
|
| 573 |
+
INFO 2025-09-27 09:37:27 celerate.py:309 step:54K smpl:3M ep:18K epch:22.63 loss:0.024 grdn:0.150 lr:4.8e-06 updt_s:1.104 data_s:0.010
|
| 574 |
+
INFO 2025-09-27 09:39:19 celerate.py:309 step:54K smpl:3M ep:18K epch:22.68 loss:0.023 grdn:0.150 lr:4.8e-06 updt_s:1.106 data_s:0.010
|
| 575 |
+
INFO 2025-09-27 09:41:12 celerate.py:309 step:54K smpl:3M ep:18K epch:22.72 loss:0.024 grdn:0.147 lr:4.7e-06 updt_s:1.108 data_s:0.011
|
| 576 |
+
INFO 2025-09-27 09:43:04 celerate.py:309 step:54K smpl:3M ep:18K epch:22.76 loss:0.023 grdn:0.146 lr:4.6e-06 updt_s:1.105 data_s:0.011
|
| 577 |
+
INFO 2025-09-27 09:44:57 celerate.py:309 step:54K smpl:3M ep:18K epch:22.80 loss:0.024 grdn:0.145 lr:4.5e-06 updt_s:1.105 data_s:0.010
|
| 578 |
+
INFO 2025-09-27 09:46:49 celerate.py:309 step:55K smpl:3M ep:18K epch:22.84 loss:0.022 grdn:0.145 lr:4.5e-06 updt_s:1.106 data_s:0.010
|
| 579 |
+
INFO 2025-09-27 09:48:42 celerate.py:309 step:55K smpl:3M ep:18K epch:22.89 loss:0.024 grdn:0.149 lr:4.4e-06 updt_s:1.106 data_s:0.010
|
| 580 |
+
INFO 2025-09-27 09:50:34 celerate.py:309 step:55K smpl:3M ep:18K epch:22.93 loss:0.024 grdn:0.146 lr:4.3e-06 updt_s:1.103 data_s:0.010
|
| 581 |
+
INFO 2025-09-27 09:52:26 celerate.py:309 step:55K smpl:3M ep:18K epch:22.97 loss:0.025 grdn:0.150 lr:4.3e-06 updt_s:1.107 data_s:0.010
|
| 582 |
+
INFO 2025-09-27 09:54:26 celerate.py:309 step:55K smpl:3M ep:18K epch:23.01 loss:0.025 grdn:0.150 lr:4.2e-06 updt_s:1.125 data_s:0.064
|
| 583 |
+
INFO 2025-09-27 09:54:26 celerate.py:334 Checkpoint policy after step 55000
|
| 584 |
+
INFO 2025-09-27 09:56:45 celerate.py:309 step:55K smpl:3M ep:18K epch:23.05 loss:0.025 grdn:0.150 lr:4.1e-06 updt_s:1.103 data_s:0.010
|
| 585 |
+
INFO 2025-09-27 09:58:37 celerate.py:309 step:55K smpl:3M ep:18K epch:23.09 loss:0.024 grdn:0.150 lr:4.1e-06 updt_s:1.106 data_s:0.010
|
| 586 |
+
INFO 2025-09-27 10:00:30 celerate.py:309 step:55K smpl:3M ep:19K epch:23.14 loss:0.022 grdn:0.143 lr:4.0e-06 updt_s:1.106 data_s:0.011
|
| 587 |
+
INFO 2025-09-27 10:02:22 celerate.py:309 step:55K smpl:3M ep:19K epch:23.18 loss:0.025 grdn:0.151 lr:3.9e-06 updt_s:1.106 data_s:0.010
|
| 588 |
+
INFO 2025-09-27 10:04:14 celerate.py:309 step:56K smpl:3M ep:19K epch:23.22 loss:0.023 grdn:0.144 lr:3.9e-06 updt_s:1.107 data_s:0.010
|
| 589 |
+
INFO 2025-09-27 10:06:07 celerate.py:309 step:56K smpl:3M ep:19K epch:23.26 loss:0.023 grdn:0.147 lr:3.8e-06 updt_s:1.104 data_s:0.011
|
| 590 |
+
INFO 2025-09-27 10:07:59 celerate.py:309 step:56K smpl:3M ep:19K epch:23.30 loss:0.025 grdn:0.152 lr:3.8e-06 updt_s:1.106 data_s:0.006
|
| 591 |
+
INFO 2025-09-27 10:09:52 celerate.py:309 step:56K smpl:3M ep:19K epch:23.35 loss:0.024 grdn:0.145 lr:3.7e-06 updt_s:1.107 data_s:0.009
|
| 592 |
+
INFO 2025-09-27 10:11:44 celerate.py:309 step:56K smpl:3M ep:19K epch:23.39 loss:0.024 grdn:0.147 lr:3.6e-06 updt_s:1.105 data_s:0.010
|
| 593 |
+
INFO 2025-09-27 10:13:37 celerate.py:309 step:56K smpl:3M ep:19K epch:23.43 loss:0.024 grdn:0.147 lr:3.6e-06 updt_s:1.107 data_s:0.010
|
| 594 |
+
INFO 2025-09-27 10:15:29 celerate.py:309 step:56K smpl:3M ep:19K epch:23.47 loss:0.024 grdn:0.144 lr:3.5e-06 updt_s:1.106 data_s:0.010
|
| 595 |
+
INFO 2025-09-27 10:17:22 celerate.py:309 step:56K smpl:3M ep:19K epch:23.51 loss:0.024 grdn:0.146 lr:3.5e-06 updt_s:1.108 data_s:0.010
|
| 596 |
+
INFO 2025-09-27 10:19:14 celerate.py:309 step:56K smpl:3M ep:19K epch:23.55 loss:0.024 grdn:0.147 lr:3.4e-06 updt_s:1.106 data_s:0.010
|
| 597 |
+
INFO 2025-09-27 10:21:07 celerate.py:309 step:56K smpl:3M ep:19K epch:23.60 loss:0.024 grdn:0.152 lr:3.4e-06 updt_s:1.104 data_s:0.010
|
| 598 |
+
INFO 2025-09-27 10:22:59 celerate.py:309 step:56K smpl:3M ep:19K epch:23.64 loss:0.023 grdn:0.147 lr:3.3e-06 updt_s:1.106 data_s:0.010
|
| 599 |
+
INFO 2025-09-27 10:24:51 celerate.py:309 step:57K smpl:3M ep:19K epch:23.68 loss:0.024 grdn:0.145 lr:3.3e-06 updt_s:1.106 data_s:0.010
|
| 600 |
+
INFO 2025-09-27 10:26:44 celerate.py:309 step:57K smpl:3M ep:19K epch:23.72 loss:0.023 grdn:0.147 lr:3.2e-06 updt_s:1.104 data_s:0.010
|
| 601 |
+
INFO 2025-09-27 10:28:36 celerate.py:309 step:57K smpl:3M ep:19K epch:23.76 loss:0.025 grdn:0.151 lr:3.2e-06 updt_s:1.106 data_s:0.010
|
| 602 |
+
INFO 2025-09-27 10:30:29 celerate.py:309 step:57K smpl:3M ep:19K epch:23.81 loss:0.024 grdn:0.150 lr:3.2e-06 updt_s:1.107 data_s:0.010
|
| 603 |
+
INFO 2025-09-27 10:32:21 celerate.py:309 step:57K smpl:3M ep:19K epch:23.85 loss:0.024 grdn:0.145 lr:3.1e-06 updt_s:1.106 data_s:0.010
|
| 604 |
+
INFO 2025-09-27 10:34:14 celerate.py:309 step:57K smpl:3M ep:19K epch:23.89 loss:0.024 grdn:0.148 lr:3.1e-06 updt_s:1.107 data_s:0.010
|
| 605 |
+
INFO 2025-09-27 10:36:06 celerate.py:309 step:57K smpl:3M ep:19K epch:23.93 loss:0.025 grdn:0.150 lr:3.0e-06 updt_s:1.109 data_s:0.010
|
| 606 |
+
INFO 2025-09-27 10:37:59 celerate.py:309 step:57K smpl:3M ep:19K epch:23.97 loss:0.024 grdn:0.149 lr:3.0e-06 updt_s:1.108 data_s:0.009
|
| 607 |
+
INFO 2025-09-27 10:39:59 celerate.py:309 step:57K smpl:3M ep:19K epch:24.01 loss:0.023 grdn:0.147 lr:3.0e-06 updt_s:1.111 data_s:0.080
|
| 608 |
+
INFO 2025-09-27 10:41:51 celerate.py:309 step:58K smpl:3M ep:19K epch:24.06 loss:0.023 grdn:0.146 lr:2.9e-06 updt_s:1.106 data_s:0.010
|
| 609 |
+
INFO 2025-09-27 10:43:44 celerate.py:309 step:58K smpl:3M ep:19K epch:24.10 loss:0.022 grdn:0.151 lr:2.9e-06 updt_s:1.106 data_s:0.010
|
| 610 |
+
INFO 2025-09-27 10:45:36 celerate.py:309 step:58K smpl:3M ep:19K epch:24.14 loss:0.024 grdn:0.149 lr:2.9e-06 updt_s:1.105 data_s:0.010
|
| 611 |
+
INFO 2025-09-27 10:47:28 celerate.py:309 step:58K smpl:3M ep:19K epch:24.18 loss:0.023 grdn:0.145 lr:2.8e-06 updt_s:1.104 data_s:0.010
|
| 612 |
+
INFO 2025-09-27 10:49:21 celerate.py:309 step:58K smpl:3M ep:19K epch:24.22 loss:0.025 grdn:0.150 lr:2.8e-06 updt_s:1.106 data_s:0.010
|
| 613 |
+
INFO 2025-09-27 10:51:13 celerate.py:309 step:58K smpl:3M ep:19K epch:24.27 loss:0.023 grdn:0.147 lr:2.8e-06 updt_s:1.106 data_s:0.011
|
| 614 |
+
INFO 2025-09-27 10:53:06 celerate.py:309 step:58K smpl:3M ep:19K epch:24.31 loss:0.023 grdn:0.145 lr:2.8e-06 updt_s:1.104 data_s:0.010
|
| 615 |
+
INFO 2025-09-27 10:54:58 celerate.py:309 step:58K smpl:3M ep:19K epch:24.35 loss:0.024 grdn:0.148 lr:2.7e-06 updt_s:1.103 data_s:0.010
|
| 616 |
+
INFO 2025-09-27 10:56:50 celerate.py:309 step:58K smpl:3M ep:20K epch:24.39 loss:0.024 grdn:0.146 lr:2.7e-06 updt_s:1.105 data_s:0.010
|
| 617 |
+
INFO 2025-09-27 10:58:42 celerate.py:309 step:58K smpl:3M ep:20K epch:24.43 loss:0.025 grdn:0.153 lr:2.7e-06 updt_s:1.107 data_s:0.010
|
| 618 |
+
INFO 2025-09-27 11:00:35 celerate.py:309 step:58K smpl:3M ep:20K epch:24.47 loss:0.025 grdn:0.145 lr:2.7e-06 updt_s:1.105 data_s:0.010
|
| 619 |
+
INFO 2025-09-27 11:02:27 celerate.py:309 step:59K smpl:3M ep:20K epch:24.52 loss:0.024 grdn:0.145 lr:2.6e-06 updt_s:1.105 data_s:0.010
|
| 620 |
+
INFO 2025-09-27 11:04:20 celerate.py:309 step:59K smpl:3M ep:20K epch:24.56 loss:0.023 grdn:0.152 lr:2.6e-06 updt_s:1.107 data_s:0.010
|
| 621 |
+
INFO 2025-09-27 11:06:12 celerate.py:309 step:59K smpl:3M ep:20K epch:24.60 loss:0.026 grdn:0.150 lr:2.6e-06 updt_s:1.105 data_s:0.010
|
| 622 |
+
INFO 2025-09-27 11:08:04 celerate.py:309 step:59K smpl:3M ep:20K epch:24.64 loss:0.023 grdn:0.148 lr:2.6e-06 updt_s:1.104 data_s:0.010
|
| 623 |
+
INFO 2025-09-27 11:09:57 celerate.py:309 step:59K smpl:3M ep:20K epch:24.68 loss:0.024 grdn:0.148 lr:2.6e-06 updt_s:1.105 data_s:0.010
|
| 624 |
+
INFO 2025-09-27 11:11:49 celerate.py:309 step:59K smpl:3M ep:20K epch:24.73 loss:0.024 grdn:0.147 lr:2.6e-06 updt_s:1.106 data_s:0.010
|
| 625 |
+
INFO 2025-09-27 11:13:41 celerate.py:309 step:59K smpl:3M ep:20K epch:24.77 loss:0.024 grdn:0.144 lr:2.5e-06 updt_s:1.103 data_s:0.010
|
| 626 |
+
INFO 2025-09-27 11:15:33 celerate.py:309 step:59K smpl:3M ep:20K epch:24.81 loss:0.023 grdn:0.149 lr:2.5e-06 updt_s:1.104 data_s:0.010
|
| 627 |
+
INFO 2025-09-27 11:17:26 celerate.py:309 step:59K smpl:3M ep:20K epch:24.85 loss:0.024 grdn:0.147 lr:2.5e-06 updt_s:1.106 data_s:0.010
|
| 628 |
+
INFO 2025-09-27 11:19:18 celerate.py:309 step:60K smpl:3M ep:20K epch:24.89 loss:0.024 grdn:0.146 lr:2.5e-06 updt_s:1.106 data_s:0.010
|
| 629 |
+
INFO 2025-09-27 11:21:11 celerate.py:309 step:60K smpl:3M ep:20K epch:24.94 loss:0.024 grdn:0.145 lr:2.5e-06 updt_s:1.103 data_s:0.010
|
| 630 |
+
INFO 2025-09-27 11:23:03 celerate.py:309 step:60K smpl:3M ep:20K epch:24.98 loss:0.024 grdn:0.149 lr:2.5e-06 updt_s:1.105 data_s:0.010
|
| 631 |
+
INFO 2025-09-27 11:25:02 celerate.py:309 step:60K smpl:3M ep:20K epch:25.02 loss:0.024 grdn:0.147 lr:2.5e-06 updt_s:1.124 data_s:0.055
|
| 632 |
+
INFO 2025-09-27 11:26:54 celerate.py:309 step:60K smpl:3M ep:20K epch:25.06 loss:0.025 grdn:0.147 lr:2.5e-06 updt_s:1.106 data_s:0.010
|
| 633 |
+
INFO 2025-09-27 11:28:46 celerate.py:309 step:60K smpl:3M ep:20K epch:25.10 loss:0.024 grdn:0.148 lr:2.5e-06 updt_s:1.105 data_s:0.010
|
| 634 |
+
INFO 2025-09-27 11:28:46 celerate.py:334 Checkpoint policy after step 60000
|
| 635 |
+
INFO 2025-09-27 11:29:11 celerate.py:391 End of training
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scale_40_finetune_fastvggt_default/2025-09-26/16-33-33_libero_40%_fastvggt_pre_embed_60k/wandb/run-20250926_163345-t5anomje/files/requirements.txt
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
setuptools==80.9.0
|
| 2 |
+
wheel==0.45.1
|
| 3 |
+
pip==25.2
|
| 4 |
+
pytz==2025.2
|
| 5 |
+
nvidia-cusparselt-cu12==0.7.1
|
| 6 |
+
mpmath==1.3.0
|
| 7 |
+
Farama-Notifications==0.0.4
|
| 8 |
+
asciitree==0.3.3
|
| 9 |
+
antlr4-python3-runtime==4.9.3
|
| 10 |
+
zipp==3.23.0
|
| 11 |
+
xxhash==3.5.0
|
| 12 |
+
wcwidth==0.2.14
|
| 13 |
+
urllib3==2.5.0
|
| 14 |
+
tzdata==2025.2
|
| 15 |
+
typing_extensions==4.15.0
|
| 16 |
+
triton==3.4.0
|
| 17 |
+
tqdm==4.67.1
|
| 18 |
+
torchcodec==0.7.0
|
| 19 |
+
toml==0.10.2
|
| 20 |
+
termcolor==3.1.0
|
| 21 |
+
sympy==1.14.0
|
| 22 |
+
uv==0.8.22
|
| 23 |
+
multidict==6.6.4
|
| 24 |
+
MarkupSafe==3.0.2
|
| 25 |
+
rerun-sdk==0.25.1
|
| 26 |
+
safetensors==0.6.2
|
| 27 |
+
tokenizers==0.21.4
|
| 28 |
+
hf_transfer==0.1.9
|
| 29 |
+
yarl==1.20.1
|
| 30 |
+
jsonlines==4.0.0
|
| 31 |
+
orderly-set==5.5.0
|
| 32 |
+
pydantic_core==2.33.2
|
| 33 |
+
certifi==2025.8.3
|
| 34 |
+
wandb==0.22.0
|
| 35 |
+
frozenlist==1.7.0
|
| 36 |
+
annotated-types==0.7.0
|
| 37 |
+
PySocks==1.7.1
|
| 38 |
+
blinker==1.9.0
|
| 39 |
+
lerobot==0.1.0
|
| 40 |
+
mergedeep==1.3.4
|
| 41 |
+
idna==3.10
|
| 42 |
+
regex==2025.9.18
|
| 43 |
+
six==1.17.0
|
| 44 |
+
packaging==25.0
|
| 45 |
+
numcodecs==0.13.1
|
| 46 |
+
evdev==1.9.2
|
| 47 |
+
async-timeout==5.0.1
|
| 48 |
+
omegaconf==2.3.0
|
| 49 |
+
aiosignal==1.4.0
|
| 50 |
+
propcache==0.3.2
|
| 51 |
+
cffi==2.0.0
|
| 52 |
+
PyYAML==6.0.3
|
| 53 |
+
cloudpickle==3.1.1
|
| 54 |
+
pyyaml-include==1.4.1
|
| 55 |
+
pynput==1.8.1
|
| 56 |
+
smmap==5.0.2
|
| 57 |
+
typing-inspection==0.4.1
|
| 58 |
+
platformdirs==4.4.0
|
| 59 |
+
gdown==5.2.0
|
| 60 |
+
hf-xet==1.1.10
|
| 61 |
+
aiohappyeyeballs==2.6.1
|
| 62 |
+
soupsieve==2.8
|
| 63 |
+
Jinja2==3.1.6
|
| 64 |
+
nvidia-nvtx-cu12==12.8.90
|
| 65 |
+
itsdangerous==2.2.0
|
| 66 |
+
click==8.3.0
|
| 67 |
+
fasteners==0.20
|
| 68 |
+
filelock==3.19.1
|
| 69 |
+
typing-inspect==0.9.0
|
| 70 |
+
beautifulsoup4==4.13.5
|
| 71 |
+
mypy_extensions==1.1.0
|
| 72 |
+
attrs==25.3.0
|
| 73 |
+
nvidia-cufile-cu12==1.13.1.3
|
| 74 |
+
importlib_metadata==8.7.0
|
| 75 |
+
deepdiff==8.6.1
|
| 76 |
+
Flask==3.1.2
|
| 77 |
+
pycparser==2.23
|
| 78 |
+
requests==2.32.5
|
| 79 |
+
multiprocess==0.70.16
|
| 80 |
+
pfzy==0.3.4
|
| 81 |
+
python-dateutil==2.9.0.post0
|
| 82 |
+
psutil==7.1.0
|
| 83 |
+
imageio==2.37.0
|
| 84 |
+
gitdb==4.0.12
|
| 85 |
+
inquirerpy==0.3.4
|
| 86 |
+
einops==0.8.1
|
| 87 |
+
charset-normalizer==3.4.3
|
| 88 |
+
GitPython==3.1.45
|
| 89 |
+
zarr==2.18.3
|
| 90 |
+
Werkzeug==3.1.3
|
| 91 |
+
protobuf==6.32.1
|
| 92 |
+
python-xlib==0.33
|
| 93 |
+
pymunk==6.11.1
|
| 94 |
+
imageio-ffmpeg==0.6.0
|
| 95 |
+
draccus==0.10.0
|
| 96 |
+
aiohttp==3.12.15
|
| 97 |
+
pydantic==2.11.9
|
| 98 |
+
nvidia-cuda-runtime-cu12==12.8.90
|
| 99 |
+
pyzmq==27.1.0
|
| 100 |
+
h5py==3.14.0
|
| 101 |
+
nvidia-cuda-cupti-cu12==12.8.90
|
| 102 |
+
nvidia-nvjitlink-cu12==12.8.93
|
| 103 |
+
prompt_toolkit==3.0.52
|
| 104 |
+
sentry-sdk==2.39.0
|
| 105 |
+
huggingface-hub==0.35.1
|
| 106 |
+
pillow==11.3.0
|
| 107 |
+
gymnasium==0.29.1
|
| 108 |
+
torchvision==0.23.0
|
| 109 |
+
nvidia-curand-cu12==10.3.9.90
|
| 110 |
+
llvmlite==0.45.0
|
| 111 |
+
opencv-python-headless==4.12.0.88
|
| 112 |
+
networkx==3.4.2
|
| 113 |
+
av==15.1.0
|
| 114 |
+
nvidia-cuda-nvrtc-cu12==12.8.93
|
| 115 |
+
numba==0.62.0
|
| 116 |
+
diffusers==0.35.1
|
| 117 |
+
nvidia-cufft-cu12==11.3.3.83
|
| 118 |
+
numpy==2.2.6
|
| 119 |
+
pyarrow==21.0.0
|
| 120 |
+
nvidia-nccl-cu12==2.27.3
|
| 121 |
+
nvidia-cusolver-cu12==11.7.3.90
|
| 122 |
+
nvidia-cusparse-cu12==12.5.8.93
|
| 123 |
+
pandas==2.3.2
|
| 124 |
+
importlib_resources==6.5.2
|
| 125 |
+
cmake==4.1.0
|
| 126 |
+
nvidia-cublas-cu12==12.8.4.1
|
| 127 |
+
nvidia-cudnn-cu12==9.10.2.21
|
| 128 |
+
torch==2.8.0
|
| 129 |
+
iniconfig==2.1.0
|
| 130 |
+
iso8601==2.1.0
|
| 131 |
+
tomli==2.2.1
|
| 132 |
+
exceptiongroup==1.3.0
|
| 133 |
+
python-dotenv==1.1.1
|
| 134 |
+
nvidia-ml-py==13.580.82
|
| 135 |
+
pluggy==1.6.0
|
| 136 |
+
serial==0.0.97
|
| 137 |
+
nvitop==1.5.3
|
| 138 |
+
pytest==8.4.2
|
| 139 |
+
future==1.0.0
|
| 140 |
+
Pygments==2.19.2
|
| 141 |
+
gym==0.26.2
|
| 142 |
+
fsspec==2024.6.1
|
| 143 |
+
dill==0.3.8
|
| 144 |
+
accelerate==1.10.1
|
| 145 |
+
datasets==3.0.0
|
| 146 |
+
transformers==4.48.1
|
| 147 |
+
easydict==1.13
|
| 148 |
+
rpds-py==0.27.1
|
| 149 |
+
scipy==1.15.3
|
| 150 |
+
gym-notices==0.1.0
|
| 151 |
+
cycler==0.12.1
|
| 152 |
+
shtab==1.7.2
|
| 153 |
+
fastjsonschema==2.21.2
|
| 154 |
+
mdurl==0.1.2
|
| 155 |
+
kiwisolver==1.4.9
|
| 156 |
+
referencing==0.36.2
|
| 157 |
+
pyparsing==3.2.5
|
| 158 |
+
typeguard==4.4.4
|
| 159 |
+
jupyter_core==5.8.1
|
| 160 |
+
docstring_parser==0.17.0
|
| 161 |
+
glfw==2.10.0
|
| 162 |
+
absl-py==2.3.1
|
| 163 |
+
traitlets==5.14.3
|
| 164 |
+
jsonschema-specifications==2025.9.1
|
| 165 |
+
contourpy==1.3.2
|
| 166 |
+
tyro==0.9.32
|
| 167 |
+
jsonschema==4.25.1
|
| 168 |
+
mdit-py-plugins==0.5.0
|
| 169 |
+
nbformat==5.10.4
|
| 170 |
+
jupytext==1.17.3
|
| 171 |
+
markdown-it-py==4.0.0
|
| 172 |
+
rich==14.1.0
|
| 173 |
+
etils==1.13.0
|
| 174 |
+
joblib==1.5.2
|
| 175 |
+
mujoco==3.3.6
|
| 176 |
+
nltk==3.9.1
|
| 177 |
+
fonttools==4.60.0
|
| 178 |
+
matplotlib==3.10.6
|
| 179 |
+
opencv-python==4.12.0.88
|
| 180 |
+
bddl==3.6.0
|
| 181 |
+
PyOpenGL==3.1.10
|
| 182 |
+
robosuite==1.4.0
|
| 183 |
+
retrying==1.4.2
|
| 184 |
+
matplotlib-inline==0.1.7
|
| 185 |
+
asttokens==3.0.0
|
| 186 |
+
plotly==6.3.0
|
| 187 |
+
ptyprocess==0.7.0
|
| 188 |
+
pure_eval==0.2.3
|
| 189 |
+
argcomplete==3.6.2
|
| 190 |
+
threadpoolctl==3.6.0
|
| 191 |
+
addict==2.4.0
|
| 192 |
+
tifffile==2025.5.10
|
| 193 |
+
stack-data==0.6.3
|
| 194 |
+
lazy_loader==0.4
|
| 195 |
+
parso==0.8.5
|
| 196 |
+
ConfigArgParse==1.7.1
|
| 197 |
+
natsort==8.4.0
|
| 198 |
+
decorator==5.2.1
|
| 199 |
+
executing==2.2.1
|
| 200 |
+
jupyterlab_widgets==3.0.15
|
| 201 |
+
evo==1.31.1
|
| 202 |
+
lz4==4.4.4
|
| 203 |
+
colorama==0.4.6
|
| 204 |
+
ruamel.yaml.clib==0.2.14
|
| 205 |
+
pexpect==4.9.0
|
| 206 |
+
open3d==0.19.0
|
| 207 |
+
pycolmap==3.10.0
|
| 208 |
+
ruamel.yaml==0.18.15
|
| 209 |
+
pyquaternion==0.9.9
|
| 210 |
+
comm==0.2.3
|
| 211 |
+
ipywidgets==8.1.7
|
| 212 |
+
numexpr==2.13.0
|
| 213 |
+
widgetsnbextension==4.0.14
|
| 214 |
+
pyceres==2.5
|
| 215 |
+
rosbags==0.10.11
|
| 216 |
+
seaborn==0.13.2
|
| 217 |
+
zstandard==0.25.0
|
| 218 |
+
trimesh==4.8.2
|
| 219 |
+
narwhals==2.5.0
|
| 220 |
+
nest-asyncio==1.6.0
|
| 221 |
+
ipython==8.37.0
|
| 222 |
+
dash==3.2.0
|
| 223 |
+
scikit-image==0.25.2
|
| 224 |
+
scikit-learn==1.7.2
|
| 225 |
+
jedi==0.19.2
|
| 226 |
+
jupyter_client==8.6.3
|
| 227 |
+
ipykernel==6.30.1
|
| 228 |
+
tornado==6.5.2
|
| 229 |
+
debugpy==1.8.17
|
scale_40_finetune_fastvggt_default/2025-09-26/16-33-33_libero_40%_fastvggt_pre_embed_60k/wandb/run-20250926_163345-t5anomje/files/wandb-metadata.json
ADDED
|
@@ -0,0 +1,39 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"os": "Linux-5.15.0-156-generic-x86_64-with-glibc2.39",
|
| 3 |
+
"python": "CPython 3.10.18",
|
| 4 |
+
"startedAt": "2025-09-26T16:33:45.888427Z",
|
| 5 |
+
"args": [
|
| 6 |
+
"--policy.path=/data/temp/baseline",
|
| 7 |
+
"--dataset.root=/data/merged_libero_mask_depth_noops_lerobot_40",
|
| 8 |
+
"--output_dir=/data/outputs/scale_40_finetune_fastvggt_default/2025-09-26/16-33-33_libero_40%_fastvggt_pre_embed_60k",
|
| 9 |
+
"--job_name=libero_40%_fastvggt_pre_embed_60k",
|
| 10 |
+
"--config_path=configs/libero_config/vggt.json",
|
| 11 |
+
"--batch_size=14",
|
| 12 |
+
"--policy.gradient_accumulation_steps=2",
|
| 13 |
+
"--log_freq=100",
|
| 14 |
+
"--save_freq=5000"
|
| 15 |
+
],
|
| 16 |
+
"program": "/workspace/nhan/VLA-Humanoid/lerobot/scripts/train_accelerate.py",
|
| 17 |
+
"codePath": "lerobot/scripts/train_accelerate.py",
|
| 18 |
+
"codePathLocal": "lerobot/scripts/train_accelerate.py",
|
| 19 |
+
"git": {
|
| 20 |
+
"remote": "https://github.com/duyhominhnguyen/VLA-Humanoid",
|
| 21 |
+
"commit": "60c06109e0d1fb67ac453a9501d798b2705c77b0"
|
| 22 |
+
},
|
| 23 |
+
"email": "nguyenducnhan.work@gmail.com",
|
| 24 |
+
"root": "/data/outputs/scale_40_finetune_fastvggt_default/2025-09-26/16-33-33_libero_40%_fastvggt_pre_embed_60k",
|
| 25 |
+
"host": "2fa4306d5586",
|
| 26 |
+
"executable": "/data/conda/envs/pitorch/bin/python3",
|
| 27 |
+
"cpu_count": 64,
|
| 28 |
+
"cpu_count_logical": 128,
|
| 29 |
+
"disk": {
|
| 30 |
+
"/": {
|
| 31 |
+
"total": "34359738368",
|
| 32 |
+
"used": "5329375232"
|
| 33 |
+
}
|
| 34 |
+
},
|
| 35 |
+
"memory": {
|
| 36 |
+
"total": "540598104064"
|
| 37 |
+
},
|
| 38 |
+
"writerId": "vo2etbmrr0x34p4sex2rt7yxq0lrkbcv"
|
| 39 |
+
}
|
scale_40_finetune_fastvggt_default/2025-09-26/16-33-33_libero_40%_fastvggt_pre_embed_60k/wandb/run-20250926_163345-t5anomje/files/wandb-summary.json
ADDED
|
@@ -0,0 +1 @@
|
|
|
|
|
|
|
| 1 |
+
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scale_40_finetune_fastvggt_default/2025-09-26/16-33-33_libero_40%_fastvggt_pre_embed_60k/wandb/run-20250926_163345-t5anomje/logs/debug-core.log
ADDED
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scale_40_finetune_fastvggt_default/2025-09-26/16-33-33_libero_40%_fastvggt_pre_embed_60k/wandb/run-20250926_163345-t5anomje/logs/debug-internal.log
ADDED
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scale_40_finetune_fastvggt_default/2025-09-26/16-33-33_libero_40%_fastvggt_pre_embed_60k/wandb/run-20250926_163345-t5anomje/logs/debug.log
ADDED
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2025-09-26 16:33:45,889 INFO MainThread:20875 [wandb_setup.py:_flush():81] Current SDK version is 0.22.0
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2025-09-26 16:33:45,890 INFO MainThread:20875 [wandb_init.py:init():813] calling init triggers
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2025-09-26 16:33:45,890 INFO MainThread:20875 [wandb_init.py:init():818] wandb.init called with sweep_config: {}
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config: {'dataset': {'repo_id': '.', 'root': '/data/merged_libero_mask_depth_noops_lerobot_40', 'episodes': None, 'image_transforms': {'enable': True, 'max_num_transforms': 3, 'random_order': False, 'image_tfs': {'hue': {'weight': 1.0, 'type': 'ColorJitter', 'kwargs': {'hue': [-0.05, 0.05]}}, 'contrast': {'weight': 1.0, 'type': 'ColorJitter', 'kwargs': {'contrast': [0.8, 1.2]}}, 'sharpness': {'weight': 1.0, 'type': 'SharpnessJitter', 'kwargs': {'sharpness': [0.5, 1.5]}}, 'brightness': {'weight': 1.0, 'type': 'ColorJitter', 'kwargs': {'brightness': [0.8, 1.2]}}, 'saturation': {'weight': 1.0, 'type': 'ColorJitter', 'kwargs': {'saturation': [0.5, 1.5]}}, 'crop_resize': {'weight': 1.0, 'type': 'RandomResizedCrop', 'kwargs': {'size': [256, 256], 'ratio': [1, 1], 'scale': [0.9, 0.95]}}, 'rotate': {'weight': 1.0, 'type': 'RandomRotate', 'kwargs': {'degrees': [-5, 5]}}}, 'wrist_tfs': {'hue': {'weight': 1.0, 'type': 'ColorJitter', 'kwargs': {'hue': [-0.05, 0.05]}}, 'contrast': {'weight': 1.0, 'type': 'ColorJitter', 'kwargs': {'contrast': [0.8, 1.2]}}, 'sharpness': {'weight': 1.0, 'type': 'SharpnessJitter', 'kwargs': {'sharpness': [0.5, 1.5]}}, 'brightness': {'weight': 1.0, 'type': 'ColorJitter', 'kwargs': {'brightness': [0.8, 1.2]}}, 'saturation': {'weight': 1.0, 'type': 'ColorJitter', 'kwargs': {'saturation': [0.5, 1.5]}}}}, 'revision': None, 'use_imagenet_stats': True, 'video_backend': 'torchcodec', 'vqa_data_path': '.'}, 'env': None, 'policy': {'type': 'pi0', 'n_obs_steps': 1, 'normalization_mapping': {'VISUAL': <NormalizationMode.IDENTITY: 'IDENTITY'>, 'STATE': <NormalizationMode.MEAN_STD: 'MEAN_STD'>, 'ACTION': <NormalizationMode.MEAN_STD: 'MEAN_STD'>}, 'input_features': {}, 'output_features': {}, 'device': 'cuda', 'use_amp': False, 'gradient_accumulation_steps': 2, 'chunk_size': 50, 'n_action_steps': 50, 'max_state_dim': 32, 'max_action_dim': 32, 'resize_imgs_with_padding': [224, 224], 'empty_cameras': 0, 'adapt_to_pi_aloha': False, 'use_delta_joint_actions_aloha': False, 'tokenizer_max_length': 48, 'proj_width': 1024, 'num_steps': 10, 'use_cache': True, 'attention_implementation': 'eager', 'freeze_vision_encoder': True, 'train_expert_only': False, 'train_state_proj': True, 'optimizer_lr': 0.0001, 'optimizer_betas': [0.9, 0.95], 'optimizer_eps': 1e-08, 'optimizer_weight_decay': 1e-10, 'scheduler_warmup_steps': 1000, 'scheduler_decay_steps': 240000, 'scheduler_decay_lr': 2.5e-06}, 'output_dir': '/data/outputs/scale_40_finetune_fastvggt_default/2025-09-26/16-33-33_libero_40%_fastvggt_pre_embed_60k', 'job_name': 'libero_40%_fastvggt_pre_embed_60k', 'resume': False, 'seed': 42, 'num_workers': 16, 'batch_size': 14, 'steps': 60000, 'eval_freq': 20000, 'log_freq': 100, 'save_checkpoint': True, 'save_freq': 5000, 'use_policy_training_preset': True, 'optimizer': {'type': 'adamw', 'lr': 0.0001, 'weight_decay': 1e-10, 'grad_clip_norm': 10.0, 'betas': [0.9, 0.95], 'eps': 1e-08}, 'scheduler': {'type': 'cosine_decay_with_warmup', 'num_warmup_steps': 1000, 'num_decay_steps': 240000, 'peak_lr': 0.0001, 'decay_lr': 2.5e-06}, 'eval': {'n_episodes': 50, 'batch_size': 50, 'use_async_envs': False}, 'wandb': {'enable': True, 'disable_artifact': True, 'project': 'pi0_lerobot', 'entity': 'Robotics_VLA', 'notes': None, 'run_id': None, 'mode': 'online'}, '_wandb': {}}
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scale_40_finetune_fastvggt_default/2025-09-26/16-33-33_libero_40%_fastvggt_pre_embed_60k/wandb/run-20250926_163345-t5anomje/run-t5anomje.wandb
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