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checkpoints/dagger/1iter/wandb/debug.log

@@ -17,3 +17,18 @@ config: {'dataset': {'repo_id': 'local/dagger_episodes', 'root': '/home/shadefor
 2026-05-20 17:38:54,712 INFO    MainThread:1855373 [wandb_run.py:_redirect():2428] Wrapping output streams.
 2026-05-20 17:38:54,712 INFO    MainThread:1855373 [wandb_run.py:_redirect():2451] Redirects installed.
 2026-05-20 17:38:54,714 INFO    MainThread:1855373 [wandb_init.py:init():1095] run started, returning control to user process
+2026-05-20 18:18:46,787 INFO    wandb-AsyncioManager-main:1855373 [service_client.py:_forward_responses():122] Reached EOF.
+2026-05-20 18:18:46,787 INFO    wandb-AsyncioManager-main:1855373 [mailbox.py:close():154] Closing mailbox, abandoning 1 handles.
+2026-05-20 18:18:47,226 ERROR   wandb-AsyncioManager-main:1855373 [asyncio_manager.py:fn_wrap_exceptions():184] Uncaught exception in run_soon callback.
+Traceback (most recent call last):
+  File "/home/shadeform/Desktop/robot_learning/lerobot/.venv/lib/python3.12/site-packages/wandb/sdk/lib/asyncio_manager.py", line 182, in fn_wrap_exceptions
+    await fn()
+  File "/home/shadeform/Desktop/robot_learning/lerobot/.venv/lib/python3.12/site-packages/wandb/sdk/lib/run_messages.py", line 105, in loop
+    await self._poll_and_print(timeout=None)
+  File "/home/shadeform/Desktop/robot_learning/lerobot/.venv/lib/python3.12/site-packages/wandb/sdk/lib/run_messages.py", line 133, in _poll_and_print
+    handle = await self._interface.deliver_async(request)
+             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/home/shadeform/Desktop/robot_learning/lerobot/.venv/lib/python3.12/site-packages/wandb/sdk/interface/interface_sock.py", line 58, in deliver_async
+    handle = await self._client.deliver(request)
+             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/home

checkpoints/dagger/1iter/wandb/run-20260520_173853-ql0pvhal/files/output.log

@@ -871,4 +871,268 @@ Training:  68%|█████████████████████
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 Training:  68%|█████████████████████████▊            | 16979/25000 [29:42<13:33,  9.86step/s]INFO 2026-05-20 18:08:39 ot_train.py:488 step:17K smpl:1M ep:3K epch:4.06 loss:0.008 grdn:0.168 lr:1.2e-05 updt_s:0.093 data_s:0.007
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+Training:  71%|██████████████████████████▊           | 17680/25000 [30:51<11:02, 11.05step/s]INFO 2026-05-20 18:09:48 ot_train.py:488 step:18K smpl:1M ep:3K epch:4.22 loss:0.008 grdn:0.155 lr:9.9e-06 updt_s:0.088 data_s:0.011
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+Training:  72%|███████████████████████████▎          | 17999/25000 [31:23<11:08, 10.47step/s]INFO 2026-05-20 18:10:20 ot_train.py:488 step:18K smpl:1M ep:3K epch:4.30 loss:0.008 grdn:0.163 lr:9.2e-06 updt_s:0.089 data_s:0.006
+INFO 2026-05-20 18:10:20 ot_train.py:502 Checkpoint policy after step 18000
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+Training:  72%|███████████████████████████▌          | 18099/25000 [31:42<11:17, 10.18step/s]INFO 2026-05-20 18:10:39 ot_train.py:488 step:18K smpl:1M ep:3K epch:4.32 loss:0.008 grdn:0.179 lr:8.9e-06 updt_s:0.088 data_s:0.010
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+Training:  73%|███████████████████████████▋          | 18239/25000 [31:55<11:33,  9.75step/s]INFO 2026-05-20 18:10:52 ot_train.py:488 step:18K smpl:1M ep:3K epch:4.36 loss:0.008 grdn:0.182 lr:8.6e-06 updt_s:0.090 data_s:0.007
+Training:  73%|███████████████████████████▊          | 18259/25000 [31:57<12:29,  8.99step/s]INFO 2026-05-20 18:10:54 ot_train.py:488 step:18K smpl:1M ep:3K epch:4.36 loss:0.008 grdn:0.172 lr:8.5e-06 updt_s:0.093 data_s:0.008
+Training:  73%|███████████████████████████▊          | 18279/25000 [31:59<10:17, 10.88step/s]INFO 2026-05-20 18:10:56 ot_train.py:488 step:18K smpl:1M ep:3K epch:4.37 loss:0.009 grdn:0.186 lr:8.5e-06 updt_s:0.086 data_s:0.008
+Training:  73%|███████████████████████████▊          | 18300/25000 [32:02<11:08, 10.02step/s]INFO 2026-05-20 18:10:58 ot_train.py:488 step:18K smpl:1M ep:3K epch:4.37 loss:0.007 grdn:0.171 lr:8.4e-06 updt_s:0.093 data_s:0.008
+Training:  73%|███████████████████████████▊          | 18320/25000 [32:03<11:52,  9.37step/s]INFO 2026-05-20 18:11:00 ot_train.py:488 step:18K smpl:1M ep:3K epch:4.38 loss:0.007 grdn:0.167 lr:8.4e-06 updt_s:0.088 data_s:0.009
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+Training:  73%|███████████████████████████▉          | 18359/25000 [32:07<11:20,  9.76step/s]INFO 2026-05-20 18:11:04 ot_train.py:488 step:18K smpl:1M ep:3K epch:4.39 loss:0.008 grdn:0.161 lr:8.3e-06 updt_s:0.090 data_s:0.006
+Training:  74%|███████████████████████████▉          | 18379/25000 [32:09<10:42, 10.31step/s]INFO 2026-05-20 18:11:06 ot_train.py:488 step:18K smpl:1M ep:3K epch:4.39 loss:0.008 grdn:0.177 lr:8.2e-06 updt_s:0.088 data_s:0.009
+Training:  74%|███████████████████████████▉          | 18399/25000 [32:11<10:55, 10.07step/s]INFO 2026-05-20 18:11:08 ot_train.py:488 step:18K smpl:1M ep:3K epch:4.40 loss:0.008 grdn:0.166 lr:8.2e-06 updt_s:0.090 data_s:0.011
+Training:  74%|███████████████████████████▉          | 18419/25000 [32:13<10:53, 10.07step/s]INFO 2026-05-20 18:11:10 ot_train.py:488 step:18K smpl:1M ep:3K epch:4.40 loss:0.007 grdn:0.156 lr:8.2e-06 updt_s:0.089 data_s:0.006
+Training:  74%|████████████████████████████          | 18439/25000 [32:15<10:18, 10.60step/s]INFO 2026-05-20 18:11:12 ot_train.py:488 step:18K smpl:1M ep:3K epch:4.41 loss:0.008 grdn:0.183 lr:8.1e-06 updt_s:0.084 data_s:0.012
+Training:  74%|████████████████████████████          | 18459/25000 [32:17<10:31, 10.36step/s]INFO 2026-05-20 18:11:14 ot_train.py:488 step:18K smpl:1M ep:3K epch:4.41 loss:0.008 grdn:0.175 lr:8.1e-06 updt_s:0.087 data_s:0.012
+Training:  74%|████████████████████████████          | 18479/25000 [32:19<10:55,  9.95step/s]INFO 2026-05-20 18:11:16 ot_train.py:488 step:18K smpl:1M ep:3K epch:4.41 loss:0.008 grdn:0.188 lr:8.0e-06 updt_s:0.091 data_s:0.009
+Training:  74%|████████████████████████████          | 18499/25000 [32:21<09:55, 10.91step/s]INFO 2026-05-20 18:11:18 ot_train.py:488 step:18K smpl:1M ep:3K epch:4.42 loss:0.008 grdn:0.196 lr:8.0e-06 updt_s:0.087 data_s:0.006
+Training:  74%|████████████████████████████▏         | 18519/25000 [32:23<10:25, 10.36step/s]INFO 2026-05-20 18:11:20 ot_train.py:488 step:19K smpl:1M ep:3K epch:4.42 loss:0.007 grdn:0.181 lr:7.9e-06 updt_s:0.091 data_s:0.010
+Training:  74%|████████████████████████████▏         | 18539/25000 [32:25<11:33,  9.32step/s]INFO 2026-05-20 18:11:22 ot_train.py:488 step:19K smpl:1M ep:3K epch:4.43 loss:0.008 grdn:0.176 lr:7.9e-06 updt_s:0.092 data_s:0.006
+Training:  74%|████████████████████████████▏         | 18559/25000 [32:27<10:22, 10.34step/s]INFO 2026-05-20 18:11:24 ot_train.py:488 step:19K smpl:1M ep:3K epch:4.43 loss:0.008 grdn:0.173 lr:7.8e-06 updt_s:0.088 data_s:0.007
+Training:  74%|████████████████████████████▏         | 18580/25000 [32:29<11:09,  9.59step/s]INFO 2026-05-20 18:11:26 ot_train.py:488 step:19K smpl:1M ep:3K epch:4.44 loss:0.008 grdn:0.182 lr:7.8e-06 updt_s:0.091 data_s:0.008
+Training:  74%|████████████████████████████▎         | 18599/25000 [32:31<10:12, 10.44step/s]INFO 2026-05-20 18:11:28 ot_train.py:488 step:19K smpl:1M ep:3K epch:4.44 loss:0.008 grdn:0.187 lr:7.7e-06 updt_s:0.088 data_s:0.008
+Training:  74%|████████████████████████████▎         | 18619/25000 [32:33<11:38,  9.14step/s]INFO 2026-05-20 18:11:30 ot_train.py:488 step:19K smpl:1M ep:3K epch:4.45 loss:0.008 grdn:0.180 lr:7.7e-06 updt_s:0.093 data_s:0.006
+Training:  75%|████████████████████████████▎         | 18640/25000 [32:35<10:32, 10.06step/s]INFO 2026-05-20 18:11:32 ot_train.py:488 step:19K smpl:1M ep:3K epch:4.45 loss:0.007 grdn:0.166 lr:7.6e-06 updt_s:0.089 data_s:0.011
+Training:  75%|████████████████████████████▎         | 18660/25000 [32:37<10:39,  9.92step/s]INFO 2026-05-20 18:11:34 ot_train.py:488 step:19K smpl:1M ep:3K epch:4.46 loss:0.008 grdn:0.167 lr:7.6e-06 updt_s:0.092 data_s:0.006
+Training:  75%|████████████████████████████▍         | 18680/25000 [32:39<10:42,  9.84step/s]INFO 2026-05-20 18:11:36 ot_train.py:488 step:19K smpl:1M ep:3K epch:4.46 loss:0.008 grdn:0.180 lr:7.6e-06 updt_s:0.089 data_s:0.011
+Training:  75%|████████████████████████████▍         | 18699/25000 [32:41<10:15, 10.24step/s]INFO 2026-05-20 18:11:38 ot_train.py:488 step:19K smpl:1M ep:3K epch:4.47 loss:0.008 grdn:0.175 lr:7.5e-06 updt_s:0.088 data_s:0.009
+Training:  75%|████████████████████████████▍         | 18720/25000 [32:43<11:23,  9.19step/s]INFO 2026-05-20 18:11:40 ot_train.py:488 step:19K smpl:1M ep:3K epch:4.47 loss:0.008 grdn:0.163 lr:7.5e-06 updt_s:0.092 data_s:0.008
+Training:  75%|████████████████████████████▍         | 18739/25000 [32:45<10:40,  9.77step/s]INFO 2026-05-20 18:11:42 ot_train.py:488 step:19K smpl:1M ep:3K epch:4.48 loss:0.007 grdn:0.188 lr:7.4e-06 updt_s:0.089 data_s:0.007
+Training:  75%|████████████████████████████▌         | 18759/25000 [32:47<09:57, 10.44step/s]INFO 2026-05-20 18:11:44 ot_train.py:488 step:19K smpl:1M ep:3K epch:4.48 loss:0.008 grdn:0.181 lr:7.4e-06 updt_s:0.088 data_s:0.009
+Training:  75%|████████████████████████████▌         | 18779/25000 [32:49<10:12, 10.15step/s]INFO 2026-05-20 18:11:46 ot_train.py:488 step:19K smpl:1M ep:3K epch:4.49 loss:0.007 grdn:0.160 lr:7.3e-06 updt_s:0.088 data_s:0.009
+Training:  75%|████████████████████████████▌         | 18799/25000 [32:51<09:46, 10.58step/s]INFO 2026-05-20 18:11:48 ot_train.py:488 step:19K smpl:1M ep:3K epch:4.49 loss:0.007 grdn:0.176 lr:7.3e-06 updt_s:0.094 data_s:0.006
+Training:  75%|████████████████████████████▌         | 18819/25000 [32:53<10:59,  9.37step/s]INFO 2026-05-20 18:11:50 ot_train.py:488 step:19K smpl:1M ep:3K epch:4.50 loss:0.008 grdn:0.180 lr:7.2e-06 updt_s:0.091 data_s:0.008
+Training:  75%|████████████████████████████▋         | 18839/25000 [32:55<10:02, 10.23step/s]INFO 2026-05-20 18:11:52 ot_train.py:488 step:19K smpl:1M ep:3K epch:4.50 loss:0.007 grdn:0.158 lr:7.2e-06 updt_s:0.085 data_s:0.011
+Training:  75%|████████████████████████████▋         | 18859/25000 [32:57<11:20,  9.03step/s]INFO 2026-05-20 18:11:54 ot_train.py:488 step:19K smpl:1M ep:3K epch:4.51 loss:0.008 grdn:0.181 lr:7.2e-06 updt_s:0.096 data_s:0.006
+Training:  76%|████████████████████████████▋         | 18880/25000 [32:59<09:48, 10.40step/s]INFO 2026-05-20 18:11:56 ot_train.py:488 step:19K smpl:1M ep:3K epch:4.51 loss:0.008 grdn:0.171 lr:7.1e-06 updt_s:0.085 data_s:0.008
+Training:  76%|████████████████████████████▋         | 18899/25000 [33:01<09:52, 10.30step/s]INFO 2026-05-20 18:11:58 ot_train.py:488 step:19K smpl:1M ep:3K epch:4.52 loss:0.008 grdn:0.169 lr:7.1e-06 updt_s:0.094 data_s:0.006
+Training:  76%|████████████████████████████▊         | 18919/25000 [33:03<11:37,  8.72step/s]INFO 2026-05-20 18:12:00 ot_train.py:488 step:19K smpl:1M ep:3K epch:4.52 loss:0.007 grdn:0.167 lr:7.0e-06 updt_s:0.094 data_s:0.007
+Training:  76%|████████████████████████████▊         | 18939/25000 [33:05<09:43, 10.38step/s]INFO 2026-05-20 18:12:02 ot_train.py:488 step:19K smpl:1M ep:3K epch:4.52 loss:0.008 grdn:0.173 lr:7.0e-06 updt_s:0.084 data_s:0.011
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+Training:  77%|█████████████████████████████▎        | 19260/25000 [33:37<09:30, 10.05step/s]INFO 2026-05-20 18:12:34 ot_train.py:488 step:19K smpl:1M ep:3K epch:4.60 loss:0.007 grdn:0.166 lr:6.3e-06 updt_s:0.094 data_s:0.006
+Training:  77%|█████████████████████████████▎        | 19280/25000 [33:39<09:51,  9.67step/s]INFO 2026-05-20 18:12:36 ot_train.py:488 step:19K smpl:1M ep:3K epch:4.61 loss:0.008 grdn:0.187 lr:6.3e-06 updt_s:0.091 data_s:0.008
+Training:  77%|█████████████████████████████▎        | 19299/25000 [33:41<08:47, 10.81step/s]INFO 2026-05-20 18:12:38 ot_train.py:488 step:19K smpl:1M ep:3K epch:4.61 loss:0.008 grdn:0.174 lr:6.2e-06 updt_s:0.084 data_s:0.010
+Training:  77%|█████████████████████████████▎        | 19319/25000 [33:43<09:17, 10.20step/s]INFO 2026-05-20 18:12:40 ot_train.py:488 step:19K smpl:1M ep:3K epch:4.62 loss:0.008 grdn:0.171 lr:6.2e-06 updt_s:0.089 data_s:0.010
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+Training:  77%|█████████████████████████████▍        | 19359/25000 [33:47<09:00, 10.43step/s]INFO 2026-05-20 18:12:44 ot_train.py:488 step:19K smpl:1M ep:3K epch:4.63 loss:0.008 grdn:0.183 lr:6.1e-06 updt_s:0.090 data_s:0.006
+Training:  78%|█████████████████████████████▍        | 19380/25000 [33:49<09:01, 10.38step/s]INFO 2026-05-20 18:12:46 ot_train.py:488 step:19K smpl:1M ep:3K epch:4.63 loss:0.008 grdn:0.174 lr:6.0e-06 updt_s:0.092 data_s:0.008
+Training:  78%|█████████████████████████████▍        | 19400/25000 [33:51<09:45,  9.56step/s]INFO 2026-05-20 18:12:48 ot_train.py:488 step:19K smpl:1M ep:3K epch:4.63 loss:0.007 grdn:0.156 lr:6.0e-06 updt_s:0.090 data_s:0.010
+Training:  78%|█████████████████████████████▌        | 19420/25000 [33:53<08:59, 10.35step/s]INFO 2026-05-20 18:12:50 ot_train.py:488 step:19K smpl:1M ep:3K epch:4.64 loss:0.008 grdn:0.178 lr:6.0e-06 updt_s:0.089 data_s:0.006
+Training:  78%|█████████████████████████████▌        | 19440/25000 [33:55<09:28,  9.78step/s]INFO 2026-05-20 18:12:52 ot_train.py:488 step:19K smpl:1M ep:3K epch:4.64 loss:0.007 grdn:0.162 lr:5.9e-06 updt_s:0.089 data_s:0.011
+Training:  78%|█████████████████████████████▌        | 19460/25000 [33:57<09:16,  9.96step/s]INFO 2026-05-20 18:12:53 ot_train.py:488 step:19K smpl:1M ep:3K epch:4.65 loss:0.008 grdn:0.188 lr:5.9e-06 updt_s:0.090 data_s:0.006
+Training:  78%|█████████████████████████████▌        | 19480/25000 [33:59<08:45, 10.50step/s]INFO 2026-05-20 18:12:55 ot_train.py:488 step:19K smpl:1M ep:3K epch:4.65 loss:0.007 grdn:0.162 lr:5.8e-06 updt_s:0.089 data_s:0.006
+Training:  78%|█████████████████████████████▋        | 19499/25000 [34:00<09:09, 10.01step/s]INFO 2026-05-20 18:12:57 ot_train.py:488 step:20K smpl:1M ep:3K epch:4.66 loss:0.007 grdn:0.160 lr:5.8e-06 updt_s:0.092 data_s:0.006
+Training:  78%|█████████████████████████████▋        | 19519/25000 [34:02<09:00, 10.14step/s]INFO 2026-05-20 18:12:59 ot_train.py:488 step:20K smpl:1M ep:3K epch:4.66 loss:0.008 grdn:0.168 lr:5.8e-06 updt_s:0.085 data_s:0.012
+Training:  78%|█████████████████████████████▋        | 19540/25000 [34:04<08:38, 10.53step/s]INFO 2026-05-20 18:13:01 ot_train.py:488 step:20K smpl:1M ep:3K epch:4.67 loss:0.007 grdn:0.173 lr:5.7e-06 updt_s:0.090 data_s:0.006
+Training:  78%|█████████████████████████████▋        | 19560/25000 [34:06<09:10,  9.89step/s]INFO 2026-05-20 18:13:03 ot_train.py:488 step:20K smpl:1M ep:3K epch:4.67 loss:0.008 grdn:0.186 lr:5.7e-06 updt_s:0.088 data_s:0.009
+Training:  78%|█████████████████████████████▊        | 19580/25000 [34:08<09:07,  9.90step/s]INFO 2026-05-20 18:13:05 ot_train.py:488 step:20K smpl:1M ep:3K epch:4.68 loss:0.008 grdn:0.180 lr:5.6e-06 updt_s:0.086 data_s:0.009
+Training:  78%|█████████████████████████████▊        | 19600/25000 [34:10<08:39, 10.40step/s]INFO 2026-05-20 18:13:07 ot_train.py:488 step:20K smpl:1M ep:3K epch:4.68 loss:0.007 grdn:0.163 lr:5.6e-06 updt_s:0.090 data_s:0.008
+Training:  78%|█████████████████████████████▊        | 19620/25000 [34:12<08:59,  9.97step/s]INFO 2026-05-20 18:13:09 ot_train.py:488 step:20K smpl:1M ep:3K epch:4.69 loss:0.008 grdn:0.173 lr:5.6e-06 updt_s:0.087 data_s:0.009
+Training:  79%|█████████████████████████████▊        | 19640/25000 [34:14<08:21, 10.70step/s]INFO 2026-05-20 18:13:11 ot_train.py:488 step:20K smpl:1M ep:3K epch:4.69 loss:0.008 grdn:0.179 lr:5.5e-06 updt_s:0.088 data_s:0.008
+Training:  79%|█████████████████████████████▉        | 19659/25000 [34:16<09:52,  9.02step/s]INFO 2026-05-20 18:13:13 ot_train.py:488 step:20K smpl:1M ep:3K epch:4.70 loss:0.007 grdn:0.162 lr:5.5e-06 updt_s:0.091 data_s:0.011
+Training:  79%|█████████████████████████████▉        | 19680/25000 [34:18<08:29, 10.43step/s]INFO 2026-05-20 18:13:15 ot_train.py:488 step:20K smpl:1M ep:3K epch:4.70 loss:0.007 grdn:0.155 lr:5.4e-06 updt_s:0.087 data_s:0.011
+Training:  79%|█████████████████████████████▉        | 19700/25000 [34:20<08:43, 10.13step/s]INFO 2026-05-20 18:13:17 ot_train.py:488 step:20K smpl:1M ep:3K epch:4.71 loss:0.007 grdn:0.170 lr:5.4e-06 updt_s:0.090 data_s:0.006
+Training:  79%|█████████████████████████████▉        | 19720/25000 [34:22<08:56,  9.85step/s]INFO 2026-05-20 18:13:19 ot_train.py:488 step:20K smpl:1M ep:3K epch:4.71 loss:0.008 grdn:0.170 lr:5.4e-06 updt_s:0.092 data_s:0.006
+Training:  79%|██████████████████████████████        | 19740/25000 [34:24<08:46,  9.99step/s]INFO 2026-05-20 18:13:21 ot_train.py:488 step:20K smpl:1M ep:3K epch:4.72 loss:0.009 grdn:0.182 lr:5.3e-06 updt_s:0.087 data_s:0.011
+Training:  79%|██████████████████████████████        | 19759/25000 [34:26<08:38, 10.11step/s]INFO 2026-05-20 18:13:23 ot_train.py:488 step:20K smpl:1M ep:3K epch:4.72 loss:0.008 grdn:0.181 lr:5.3e-06 updt_s:0.089 data_s:0.012
+Training:  79%|██████████████████████████████        | 19779/25000 [34:28<07:58, 10.91step/s]INFO 2026-05-20 18:13:25 ot_train.py:488 step:20K smpl:1M ep:3K epch:4.73 loss:0.009 grdn:0.200 lr:5.2e-06 updt_s:0.089 data_s:0.007
+Training:  79%|██████████████████████████████        | 19799/25000 [34:30<08:01, 10.79step/s]INFO 2026-05-20 18:13:27 ot_train.py:488 step:20K smpl:1M ep:3K epch:4.73 loss:0.008 grdn:0.171 lr:5.2e-06 updt_s:0.092 data_s:0.008
+Training:  79%|██████████████████████████████        | 19819/25000 [34:32<08:40,  9.95step/s]INFO 2026-05-20 18:13:29 ot_train.py:488 step:20K smpl:1M ep:3K epch:4.73 loss:0.008 grdn:0.174 lr:5.2e-06 updt_s:0.091 data_s:0.008
+Training:  79%|██████████████████████████████▏       | 19839/25000 [34:34<08:23, 10.25step/s]INFO 2026-05-20 18:13:31 ot_train.py:488 step:20K smpl:1M ep:3K epch:4.74 loss:0.008 grdn:0.186 lr:5.1e-06 updt_s:0.086 data_s:0.011
+Training:  79%|██████████████████████████████▏       | 19860/25000 [34:36<08:46,  9.77step/s]INFO 2026-05-20 18:13:33 ot_train.py:488 step:20K smpl:1M ep:3K epch:4.74 loss:0.008 grdn:0.174 lr:5.1e-06 updt_s:0.087 data_s:0.008
+Training:  80%|██████████████████████████████▏       | 19879/25000 [34:38<08:25, 10.12step/s]INFO 2026-05-20 18:13:35 ot_train.py:488 step:20K smpl:1M ep:3K epch:4.75 loss:0.006 grdn:0.158 lr:5.1e-06 updt_s:0.092 data_s:0.008
+Training:  80%|██████████████████████████████▏       | 19899/25000 [34:40<08:18, 10.23step/s]INFO 2026-05-20 18:13:37 ot_train.py:488 step:20K smpl:1M ep:3K epch:4.75 loss:0.008 grdn:0.180 lr:5.0e-06 updt_s:0.087 data_s:0.009
+Training:  80%|██████████████████████████████▎       | 19920/25000 [34:42<08:55,  9.49step/s]INFO 2026-05-20 18:13:39 ot_train.py:488 step:20K smpl:1M ep:3K epch:4.76 loss:0.006 grdn:0.156 lr:5.0e-06 updt_s:0.088 data_s:0.008
+Training:  80%|██████████████████████████████▎       | 19939/25000 [34:44<08:25, 10.01step/s]INFO 2026-05-20 18:13:41 ot_train.py:488 step:20K smpl:1M ep:3K epch:4.76 loss:0.008 grdn:0.187 lr:4.9e-06 updt_s:0.089 data_s:0.011
+Training:  80%|██████████████████████████████▎       | 19959/25000 [34:46<08:16, 10.16step/s]INFO 2026-05-20 18:13:43 ot_train.py:488 step:20K smpl:1M ep:3K epch:4.77 loss:0.007 grdn:0.186 lr:4.9e-06 updt_s:0.089 data_s:0.009
+Training:  80%|██████████████████████████████▎       | 19980/25000 [34:48<08:38,  9.68step/s]INFO 2026-05-20 18:13:45 ot_train.py:488 step:20K smpl:1M ep:3K epch:4.77 loss:0.007 grdn:0.172 lr:4.9e-06 updt_s:0.089 data_s:0.010
+Training:  80%|██████████████████████████████▍       | 19999/25000 [34:50<08:47,  9.48step/s]INFO 2026-05-20 18:13:47 ot_train.py:488 step:20K smpl:1M ep:3K epch:4.78 loss:0.007 grdn:0.177 lr:4.8e-06 updt_s:0.091 data_s:0.008
+INFO 2026-05-20 18:13:47 ot_train.py:502 Checkpoint policy after step 20000
+Training:  80%|██████████████████████████████▍       | 20019/25000 [35:01<11:36,  7.16step/s]INFO 2026-05-20 18:13:58 ot_train.py:488 step:20K smpl:1M ep:3K epch:4.78 loss:0.007 grdn:0.158 lr:4.8e-06 updt_s:0.071 data_s:0.005
+Training:  80%|██████████████████████████████▍       | 20040/25000 [35:03<07:36, 10.86step/s]INFO 2026-05-20 18:14:00 ot_train.py:488 step:20K smpl:1M ep:3K epch:4.79 loss:0.008 grdn:0.183 lr:4.8e-06 updt_s:0.088 data_s:0.009
+Training:  80%|██████████████████████████████▍       | 20059/25000 [35:05<08:20,  9.87step/s]INFO 2026-05-20 18:14:02 ot_train.py:488 step:20K smpl:1M ep:3K epch:4.79 loss:0.008 grdn:0.183 lr:4.7e-06 updt_s:0.092 data_s:0.009
+Training:  80%|██████████████████████████████▌       | 20079/25000 [35:07<08:29,  9.65step/s]INFO 2026-05-20 18:14:04 ot_train.py:488 step:20K smpl:1M ep:3K epch:4.80 loss:0.007 grdn:0.172 lr:4.7e-06 updt_s:0.087 data_s:0.010
+Training:  80%|██████████████████████████████▌       | 20099/25000 [35:09<07:59, 10.23step/s]INFO 2026-05-20 18:14:06 ot_train.py:488 step:20K smpl:1M ep:3K epch:4.80 loss:0.008 grdn:0.167 lr:4.6e-06 updt_s:0.084 data_s:0.009
+Training:  80%|██████████████████████████████▌       | 20120/25000 [35:11<08:11,  9.94step/s]INFO 2026-05-20 18:14:08 ot_train.py:488 step:20K smpl:1M ep:3K epch:4.81 loss:0.009 grdn:0.192 lr:4.6e-06 updt_s:0.088 data_s:0.013
+Training:  81%|██████████████████████████████▌       | 20140/25000 [35:13<08:00, 10.12step/s]INFO 2026-05-20 18:14:10 ot_train.py:488 step:20K smpl:1M ep:3K epch:4.81 loss:0.008 grdn:0.196 lr:4.6e-06 updt_s:0.087 data_s:0.008
+Training:  81%|██████████████████████████████▋       | 20160/25000 [35:15<07:58, 10.12step/s]INFO 2026-05-20 18:14:12 ot_train.py:488 step:20K smpl:1M ep:3K epch:4.82 loss:0.007 grdn:0.165 lr:4.5e-06 updt_s:0.086 data_s:0.010
+Training:  81%|██████████████████████████████▋       | 20179/25000 [35:17<08:20,  9.63step/s]INFO 2026-05-20 18:14:14 ot_train.py:488 step:20K smpl:1M ep:3K epch:4.82 loss:0.008 grdn:0.182 lr:4.5e-06 updt_s:0.093 data_s:0.006
+Training:  81%|██████████████████████████████▋       | 20200/25000 [35:19<07:41, 10.39step/s]INFO 2026-05-20 18:14:16 ot_train.py:488 step:20K smpl:1M ep:3K epch:4.83 loss:0.008 grdn:0.171 lr:4.5e-06 updt_s:0.089 data_s:0.008
+Training:  81%|██████████████████████████████▋       | 20220/25000 [35:21<07:21, 10.83step/s]INFO 2026-05-20 18:14:18 ot_train.py:488 step:20K smpl:1M ep:3K epch:4.83 loss:0.008 grdn:0.185 lr:4.4e-06 updt_s:0.085 data_s:0.009
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+Training:  86%|████████████████████████████████▋     | 21520/25000 [37:33<05:58,  9.69step/s]INFO 2026-05-20 18:16:30 ot_train.py:488 step:22K smpl:1M ep:3K epch:5.14 loss:0.007 grdn:0.171 lr:2.4e-06 updt_s:0.092 data_s:0.008
+Training:  86%|████████████████████████████████▋     | 21540/25000 [37:35<05:55,  9.73step/s]INFO 2026-05-20 18:16:32 ot_train.py:488 step:22K smpl:1M ep:3K epch:5.15 loss:0.007 grdn:0.168 lr:2.4e-06 updt_s:0.087 data_s:0.010
+Training:  86%|███████��████████████████████████▊     | 21560/25000 [37:37<05:26, 10.53step/s]INFO 2026-05-20 18:16:34 ot_train.py:488 step:22K smpl:1M ep:3K epch:5.15 loss:0.010 grdn:0.187 lr:2.3e-06 updt_s:0.087 data_s:0.008
+Training:  86%|████████████████████████████████▊     | 21580/25000 [37:39<05:27, 10.45step/s]INFO 2026-05-20 18:16:36 ot_train.py:488 step:22K smpl:1M ep:3K epch:5.16 loss:0.007 grdn:0.171 lr:2.3e-06 updt_s:0.090 data_s:0.008
+Training:  86%|████████████████████████████████▊     | 21600/25000 [37:41<05:33, 10.19step/s]INFO 2026-05-20 18:16:38 ot_train.py:488 step:22K smpl:1M ep:3K epch:5.16 loss:0.007 grdn:0.179 lr:2.3e-06 updt_s:0.087 data_s:0.008
+Training:  86%|████████████████████████████████▊     | 21619/25000 [37:43<06:08,  9.18step/s]INFO 2026-05-20 18:16:40 ot_train.py:488 step:22K smpl:1M ep:3K epch:5.16 loss:0.007 grdn:0.161 lr:2.3e-06 updt_s:0.095 data_s:0.006
+Training:  87%|████████████████████████████████▉     | 21639/25000 [37:45<05:08, 10.89step/s]INFO 2026-05-20 18:16:42 ot_train.py:488 step:22K smpl:1M ep:3K epch:5.17 loss:0.008 grdn:0.189 lr:2.2e-06 updt_s:0.085 data_s:0.009
+Training:  87%|████████████████████████████████▉     | 21659/25000 [37:47<05:28, 10.17step/s]INFO 2026-05-20 18:16:44 ot_train.py:488 step:22K smpl:1M ep:3K epch:5.17 loss:0.008 grdn:0.168 lr:2.2e-06 updt_s:0.095 data_s:0.007
+Training:  87%|████████████████████████████████▉     | 21679/25000 [37:49<05:34,  9.93step/s]INFO 2026-05-20 18:16:46 ot_train.py:488 step:22K smpl:1M ep:3K epch:5.18 loss:0.008 grdn:0.180 lr:2.2e-06 updt_s:0.090 data_s:0.009
+Training:  87%|████████████████████████████████▉     | 21699/25000 [37:51<05:21, 10.27step/s]INFO 2026-05-20 18:16:48 ot_train.py:488 step:22K smpl:1M ep:3K epch:5.18 loss:0.008 grdn:0.185 lr:2.1e-06 updt_s:0.085 data_s:0.013
+Training:  87%|█████████████████████████████████     | 21720/25000 [37:53<05:12, 10.49step/s]INFO 2026-05-20 18:16:50 ot_train.py:488 step:22K smpl:1M ep:3K epch:5.19 loss:0.008 grdn:0.154 lr:2.1e-06 updt_s:0.087 data_s:0.010
+Training:  87%|█████████████████████████████████     | 21739/25000 [37:55<05:40,  9.58step/s]INFO 2026-05-20 18:16:52 ot_train.py:488 step:22K smpl:1M ep:3K epch:5.19 loss:0.008 grdn:0.170 lr:2.1e-06 updt_s:0.091 data_s:0.009
+Training:  87%|█████████████████████████████████     | 21759/25000 [37:57<05:18, 10.18step/s]INFO 2026-05-20 18:16:54 ot_train.py:488 step:22K smpl:1M ep:3K epch:5.20 loss:0.007 grdn:0.167 lr:2.1e-06 updt_s:0.086 data_s:0.010
+Training:  87%|█████████████████████████████████     | 21779/25000 [37:59<05:22,  9.99step/s]INFO 2026-05-20 18:16:56 ot_train.py:488 step:22K smpl:1M ep:3K epch:5.20 loss:0.008 grdn:0.181 lr:2.0e-06 updt_s:0.091 data_s:0.009
+Training:  87%|█████████████████████████████████▏    | 21799/25000 [38:01<04:49, 11.06step/s]INFO 2026-05-20 18:16:58 ot_train.py:488 step:22K smpl:1M ep:3K epch:5.21 loss:0.008 grdn:0.181 lr:2.0e-06 updt_s:0.088 data_s:0.006
+Training:  87%|█████████████████████████████████▏    | 21819/25000 [38:03<05:20,  9.92step/s]INFO 2026-05-20 18:17:00 ot_train.py:488 step:22K smpl:1M ep:3K epch:5.21 loss:0.008 grdn:0.171 lr:2.0e-06 updt_s:0.088 data_s:0.009
+Training:  87%|█████████████████████████████████▏    | 21840/25000 [38:05<05:16,  9.97step/s]INFO 2026-05-20 18:17:02 ot_train.py:488 step:22K smpl:1M ep:3K epch:5.22 loss:0.008 grdn:0.196 lr:2.0e-06 updt_s:0.092 data_s:0.006
+Training:  87%|█████████████████████████████████▏    | 21859/25000 [38:07<05:29,  9.54step/s]INFO 2026-05-20 18:17:04 ot_train.py:488 step:22K smpl:1M ep:3K epch:5.22 loss:0.008 grdn:0.169 lr:1.9e-06 updt_s:0.095 data_s:0.008
+Training:  88%|█████████████████████████████████▎    | 21880/25000 [38:09<04:57, 10.49step/s]INFO 2026-05-20 18:17:06 ot_train.py:488 step:22K smpl:1M ep:3K epch:5.23 loss:0.007 grdn:0.162 lr:1.9e-06 updt_s:0.086 data_s:0.009
+Training:  88%|█████████████████████████████████▎    | 21900/25000 [38:11<05:25,  9.51step/s]INFO 2026-05-20 18:17:08 ot_train.py:488 step:22K smpl:1M ep:3K epch:5.23 loss:0.008 grdn:0.178 lr:1.9e-06 updt_s:0.093 data_s:0.007
+Training:  88%|█████████████████████████████████▎    | 21919/25000 [38:13<04:43, 10.88step/s]INFO 2026-05-20 18:17:10 ot_train.py:488 step:22K smpl:1M ep:3K epch:5.24 loss:0.007 grdn:0.169 lr:1.9e-06 updt_s:0.089 data_s:0.006
+Training:  88%|█████████████████████████████████▎    | 21940/25000 [38:15<05:04, 10.06step/s]INFO 2026-05-20 18:17:12 ot_train.py:488 step:22K smpl:1M ep:3K epch:5.24 loss:0.007 grdn:0.150 lr:1.9e-06 updt_s:0.094 data_s:0.010
+Training:  88%|█████████████████████████████████▍    | 21959/25000 [38:17<05:18,  9.56step/s]INFO 2026-05-20 18:17:14 ot_train.py:488 step:22K smpl:1M ep:3K epch:5.25 loss:0.009 grdn:0.190 lr:1.8e-06 updt_s:0.089 data_s:0.009
+Training:  88%|█████████████████████████████████▍    | 21979/25000 [38:19<04:49, 10.44step/s]INFO 2026-05-20 18:17:16 ot_train.py:488 step:22K smpl:1M ep:3K epch:5.25 loss:0.008 grdn:0.182 lr:1.8e-06 updt_s:0.085 data_s:0.010
+Training:  88%|█████████████████████████████████▍    | 21999/25000 [38:21<04:59, 10.03step/s]INFO 2026-05-20 18:17:18 ot_train.py:488 step:22K smpl:1M ep:3K epch:5.26 loss:0.008 grdn:0.185 lr:1.8e-06 updt_s:0.092 data_s:0.009
+INFO 2026-05-20 18:17:18 ot_train.py:502 Checkpoint policy after step 22000
+Traceback (most recent call last):
+  File "/home/shadeform/Desktop/robot_learning/lerobot/.venv/bin/lerobot-train", line 10, in <module>
+    sys.exit(main())
+             ^^^^^^
+  File "/home/shadeform/Desktop/robot_learning/lerobot/src/lerobot/scripts/lerobot_train.py", line 595, in main
+    train()
+  File "/home/shadeform/Desktop/robot_learning/lerobot/src/lerobot/configs/parser.py", line 233, in wrapper_inner
+    response = fn(cfg, *args, **kwargs)
+               ^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/home/shadeform/Desktop/robot_learning/lerobot/src/lerobot/scripts/lerobot_train.py", line 504, in train
+    save_checkpoint(

checkpoints/dagger/1iter/wandb/run-20260520_173853-ql0pvhal/logs/debug-core.log

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checkpoints/dagger/1iter/wandb/run-20260520_173853-ql0pvhal/logs/debug-internal.log

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checkpoints/dagger/1iter/wandb/run-20260520_173853-ql0pvhal/logs/debug.log

@@ -17,3 +17,18 @@ config: {'dataset': {'repo_id': 'local/dagger_episodes', 'root': '/home/shadefor
 2026-05-20 17:38:54,712 INFO    MainThread:1855373 [wandb_run.py:_redirect():2428] Wrapping output streams.
 2026-05-20 17:38:54,712 INFO    MainThread:1855373 [wandb_run.py:_redirect():2451] Redirects installed.
 2026-05-20 17:38:54,714 INFO    MainThread:1855373 [wandb_init.py:init():1095] run started, returning control to user process
+2026-05-20 18:18:46,787 INFO    wandb-AsyncioManager-main:1855373 [service_client.py:_forward_responses():122] Reached EOF.
+2026-05-20 18:18:46,787 INFO    wandb-AsyncioManager-main:1855373 [mailbox.py:close():154] Closing mailbox, abandoning 1 handles.
+2026-05-20 18:18:47,226 ERROR   wandb-AsyncioManager-main:1855373 [asyncio_manager.py:fn_wrap_exceptions():184] Uncaught exception in run_soon callback.
+Traceback (most recent call last):
+  File "/home/shadeform/Desktop/robot_learning/lerobot/.venv/lib/python3.12/site-packages/wandb/sdk/lib/asyncio_manager.py", line 182, in fn_wrap_exceptions
+    await fn()
+  File "/home/shadeform/Desktop/robot_learning/lerobot/.venv/lib/python3.12/site-packages/wandb/sdk/lib/run_messages.py", line 105, in loop
+    await self._poll_and_print(timeout=None)
+  File "/home/shadeform/Desktop/robot_learning/lerobot/.venv/lib/python3.12/site-packages/wandb/sdk/lib/run_messages.py", line 133, in _poll_and_print
+    handle = await self._interface.deliver_async(request)
+             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/home/shadeform/Desktop/robot_learning/lerobot/.venv/lib/python3.12/site-packages/wandb/sdk/interface/interface_sock.py", line 58, in deliver_async
+    handle = await self._client.deliver(request)
+             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/home

checkpoints/dagger/1iter/wandb/run-20260520_173853-ql0pvhal/run-ql0pvhal.wandb

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