| /home/ubuntu/Isaac-GR00T/.venv/lib/python3.10/site-packages/albumentations/__init__.py:13: UserWarning: A new version of Albumentations is available: 2.0.8 (you have 1.4.18). Upgrade using: pip install -U albumentations. To disable automatic update checks, set the environment variable NO_ALBUMENTATIONS_UPDATE to 1. |
| check_for_updates() |
| /home/ubuntu/Isaac-GR00T/gr00t/experiment/experiment.py:98: UserWarning: image_crop_size and image_target_size will be deprecated in the future. Please use shortest_image_edge and crop_fraction instead. |
| warnings.warn( |
| 05/26/2026 21:34:00 - INFO - Saved config to /home/ubuntu/groot-files/checkpoints/g1_finetune-20260526-213350-gpu0/experiment_cfg |
| wandb: Currently logged in as: lucafrat (lucafrat-microsoft) to https://api.wandb.ai. Use `wandb login |
| wandb: setting up run zw5ihkoo |
| wandb: Tracking run with wandb version 0.23.0 |
| wandb: Run data is saved locally in /home/ubuntu/Isaac-GR00T/wandb/run-20260526_213400-zw5ihkoo |
| wandb: Run `wandb offline` to turn off syncing. |
| wandb: Syncing run g1_finetune-20260526-213350-gpu0 |
| wandb: ⭐️ View project at https://wandb.ai/lucafrat-microsoft/groot-finetune |
| wandb: 🚀 View run at https://wandb.ai/lucafrat-microsoft/groot-finetune/runs/zw5ihkoo |
| Flash Attention 2 only supports torch.float16 and torch.bfloat16 dtypes, but the current dype in Qwen3VLForConditionalGeneration is torch.float32. You should run training or inference using Automatic Mixed-Precision via the `with torch.autocast(device_type='torch_device'):` decorator, or load the model with the `dtype` argument. Example: `model = AutoModel.from_pretrained("openai/whisper-tiny", attn_implementation="flash_attention_2", dtype=torch.float16)` |
| Flash Attention 2 only supports torch.float16 and torch.bfloat16 dtypes, but the current dype in Qwen3VLModel is torch.float32. You should run training or inference using Automatic Mixed-Precision via the `with torch.autocast(device_type='torch_device'):` decorator, or load the model with the `dtype` argument. Example: `model = AutoModel.from_pretrained("openai/whisper-tiny", attn_implementation="flash_attention_2", dtype=torch.float16)` |
| Flash Attention 2 only supports torch.float16 and torch.bfloat16 dtypes, but the current dype in Qwen3VLVisionModel is torch.float32. You should run training or inference using Automatic Mixed-Precision via the `with torch.autocast(device_type='torch_device'):` decorator, or load the model with the `dtype` argument. Example: `model = AutoModel.from_pretrained("openai/whisper-tiny", attn_implementation="flash_attention_2", dtype=torch.float16)` |
| Flash Attention 2 only supports torch.float16 and torch.bfloat16 dtypes, but the current dype in Qwen3VLTextModel is torch.float32. You should run training or inference using Automatic Mixed-Precision via the `with torch.autocast(device_type='torch_device'):` decorator, or load the model with the `dtype` argument. Example: `model = AutoModel.from_pretrained("openai/whisper-tiny", attn_implementation="flash_attention_2", dtype=torch.float16)` |
| /home/ubuntu/Isaac-GR00T/gr00t/model/modules/dit.py:255: FutureWarning: Accessing config attribute `compute_dtype` directly via 'AlternateVLDiT' object attribute is deprecated. Please access 'compute_dtype' over 'AlternateVLDiT's config object instead, e.g. 'unet.config.compute_dtype'. |
| embedding_dim=self.inner_dim, compute_dtype=self.compute_dtype |
| /home/ubuntu/Isaac-GR00T/gr00t/model/modules/dit.py:286: FutureWarning: Accessing config attribute `output_dim` directly via 'AlternateVLDiT' object attribute is deprecated. Please access 'output_dim' over 'AlternateVLDiT's config object instead, e.g. 'unet.config.output_dim'. |
| self.proj_out_2 = nn.Linear(self.inner_dim, self.output_dim) |
| Total number of DiT parameters: 1091722240 |
| 05/26/2026 21:34:02 - INFO - Using AlternateVLDiT for diffusion model |
| Total number of SelfAttentionTransformer parameters: 201433088 |
|
Loading checkpoint shards: 0%| | 0/2 [00:00<?, ?it/s]
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Loading checkpoint shards: 100%|██████████| 2/2 [00:00<00:00, 2.55it/s] |
| 05/26/2026 21:34:07 - INFO - Total parameters: 3,144,016,000 |
| 05/26/2026 21:34:07 - INFO - Trainable parameters: 1,620,515,968 (51.54%) |
|
Initializing datasets: 0%| | 0/1 [00:00<?, ?it/s]Generating stats for /home/ubuntu/groot-files/dataset |
| Generated 64 shards for dataset /home/ubuntu/groot-files/dataset |
| Total steps: 64712, average shard length: 1011.125, shard length std: 17.115873480485885 |
|
Initializing datasets: 100%|██████████| 1/1 [00:00<00:00, 97.75it/s] |
| 05/26/2026 21:34:10 - INFO - Overriding statistics for embodiment 'unitree_g1_sonic' |
| 05/26/2026 21:34:10 - INFO - Saved dataset statistics for inference |
| 05/26/2026 21:34:14 - INFO - 🚀 Starting training... |
| 05/26/2026 21:34:14 - WARNING - No valid checkpoint found in output directory (/home/ubuntu/groot-files/checkpoints/g1_finetune-20260526-213350-gpu0) |
| Current global step: 0 |
| Creating custom train dataloader |
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| Rank 0, Worker 4: Caching shard... |
| Casting fp32 inputs back to torch.bfloat16 for flash-attn compatibility. |
| Could not estimate the number of tokens of the input, floating-point operations will not be computed |
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| Rank 0, Worker 1: Caching shard... |
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6%|▌ | 176/3000 [01:06<11:59, 3.93it/s]Rank 0, Worker 2: Wait for shard 0 in dataset 0 in 0.00 seconds |
| Rank 0, Worker 2: Caching shard... |
|
6%|▌ | 177/3000 [01:07<12:02, 3.91it/s]Rank 0, Worker 3: Wait for shard 2 in dataset 0 in 0.00 seconds |
| Rank 0, Worker 3: Caching shard... |
|
6%|▌ | 178/3000 [01:07<12:17, 3.83it/s]
6%|▌ | 179/3000 [01:07<12:23, 3.80it/s]Rank 0, Worker 5: Wait for shard 9 in dataset 0 in 0.00 seconds |
| Rank 0, Worker 5: Caching shard... |
|
6%|▌ | 180/3000 [01:07<12:19, 3.81it/s]
{'loss': 0.8221, 'grad_norm': 0.5763223767280579, 'learning_rate': 9.997445481536973e-05} |
|
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6%|▌ | 184/3000 [01:08<12:35, 3.73it/s]Rank 0, Worker 4: Wait for shard 18 in dataset 0 in 0.00 seconds |
| Rank 0, Worker 4: Caching shard... |
|
6%|▌ | 185/3000 [01:09<12:26, 3.77it/s]
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{'loss': 0.7922, 'grad_norm': 0.5941640734672546, 'learning_rate': 9.995380315038119e-05} |
|
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{'loss': 0.7702, 'grad_norm': 0.7477675080299377, 'learning_rate': 9.99270816881235e-05} |
|
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{'loss': 0.7553, 'grad_norm': 0.5304926633834839, 'learning_rate': 9.989429367547377e-05} |
|
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{'loss': 0.7369, 'grad_norm': 0.5700099468231201, 'learning_rate': 9.985544309644475e-05} |
|
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{'loss': 0.7222, 'grad_norm': 0.7928358316421509, 'learning_rate': 9.98105346717008e-05} |
|
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{'loss': 0.7114, 'grad_norm': 0.7667017579078674, 'learning_rate': 9.97595738579843e-05} |
|
8%|▊ | 240/3000 [01:24<12:26, 3.70it/s]
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{'loss': 0.6861, 'grad_norm': 0.5060045123100281, 'learning_rate': 9.970256684745258e-05} |
|
8%|▊ | 250/3000 [01:27<12:06, 3.79it/s]
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9%|▊ | 260/3000 [01:29<11:26, 3.99it/s]
{'loss': 0.675, 'grad_norm': 0.6732467412948608, 'learning_rate': 9.963952056692549e-05} |
|
9%|▊ | 260/3000 [01:29<11:26, 3.99it/s]
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9%|▉ | 270/3000 [01:32<11:37, 3.91it/s]
{'loss': 0.6767, 'grad_norm': 0.6021248698234558, 'learning_rate': 9.957044267704384e-05} |
|
9%|▉ | 270/3000 [01:32<11:37, 3.91it/s]
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{'loss': 0.6512, 'grad_norm': 0.6704761981964111, 'learning_rate': 9.949534157133844e-05} |
|
9%|▉ | 280/3000 [01:35<11:33, 3.92it/s]
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{'loss': 0.6512, 'grad_norm': 0.7285646200180054, 'learning_rate': 9.941422637521035e-05} |
|
10%|▉ | 290/3000 [01:37<12:03, 3.75it/s]
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10%|█ | 300/3000 [01:40<12:18, 3.66it/s]
{'loss': 0.6196, 'grad_norm': 0.7110922336578369, 'learning_rate': 9.932710694482191e-05} |
|
10%|█ | 300/3000 [01:40<12:18, 3.66it/s]
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10%|█ | 309/3000 [01:42<11:40, 3.84it/s]
10%|█ | 310/3000 [01:42<12:22, 3.62it/s]
{'loss': 0.6118, 'grad_norm': 0.6850391626358032, 'learning_rate': 9.923399386589933e-05} |
|
10%|█ | 310/3000 [01:43<12:22, 3.62it/s]
10%|█ | 311/3000 [01:43<12:25, 3.60it/s]
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11%|█ | 316/3000 [01:44<11:49, 3.78it/s]
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11%|█ | 319/3000 [01:45<12:42, 3.52it/s]
11%|█ | 320/3000 [01:45<12:32, 3.56it/s]
{'loss': 0.5941, 'grad_norm': 0.6997315883636475, 'learning_rate': 9.913489845244626e-05} |
|
11%|█ | 320/3000 [01:45<12:32, 3.56it/s]
11%|█ | 321/3000 [01:46<12:24, 3.60it/s]
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11%|█ | 329/3000 [01:48<12:00, 3.71it/s]
11%|█ | 330/3000 [01:48<11:53, 3.74it/s]
{'loss': 0.5891, 'grad_norm': 0.760143518447876, 'learning_rate': 9.902983274536912e-05} |
|
11%|█ | 330/3000 [01:48<11:53, 3.74it/s]
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11%|█▏ | 339/3000 [01:50<11:58, 3.70it/s]
11%|█▏ | 340/3000 [01:51<11:45, 3.77it/s]
{'loss': 0.5812, 'grad_norm': 0.759657084941864, 'learning_rate': 9.891880951101407e-05} |
|
11%|█▏ | 340/3000 [01:51<11:45, 3.77it/s]
11%|█▏ | 341/3000 [01:51<11:49, 3.75it/s]
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12%|█▏ | 348/3000 [01:53<11:44, 3.77it/s]
12%|█▏ | 349/3000 [01:53<11:32, 3.83it/s]
12%|█▏ | 350/3000 [01:53<11:25, 3.87it/s]
{'loss': 0.5674, 'grad_norm': 0.8276827931404114, 'learning_rate': 9.880184223961573e-05} |
|
12%|█▏ | 350/3000 [01:53<11:25, 3.87it/s]
12%|█▏ | 351/3000 [01:53<11:24, 3.87it/s]
12%|█▏ | 352/3000 [01:54<11:15, 3.92it/s]
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12%|█▏ | 358/3000 [01:55<11:24, 3.86it/s]
12%|█▏ | 359/3000 [01:56<11:15, 3.91it/s]
12%|█▏ | 360/3000 [01:56<11:24, 3.86it/s]
{'loss': 0.5544, 'grad_norm': 0.5555763244628906, 'learning_rate': 9.867894514365802e-05} |
|
12%|█▏ | 360/3000 [01:56<11:24, 3.86it/s]Rank 0, Worker 0: Wait for shard 10 in dataset 0 in 0.00 seconds |
| Rank 0, Worker 0: Caching shard... |
|
12%|█▏ | 361/3000 [01:56<11:26, 3.84it/s]
12%|█▏ | 362/3000 [01:56<11:28, 3.83it/s]
12%|█▏ | 363/3000 [01:57<11:30, 3.82it/s]Rank 0, Worker 3: Wait for shard 20 in dataset 0 in 0.00 seconds |
| Rank 0, Worker 3: Caching shard... |
|
12%|█▏ | 364/3000 [01:57<11:28, 3.83it/s]
12%|█▏ | 365/3000 [01:57<11:47, 3.72it/s]
12%|█▏ | 366/3000 [01:57<11:57, 3.67it/s]
12%|█▏ | 367/3000 [01:58<11:57, 3.67it/s]Rank 0, Worker 1: Wait for shard 32 in dataset 0 in 0.00 seconds |
| Rank 0, Worker 1: Caching shard... |
|
12%|█▏ | 368/3000 [01:58<11:45, 3.73it/s]Rank 0, Worker 2: Wait for shard 34 in dataset 0 in 0.00 seconds |
| Rank 0, Worker 2: Caching shard... |
|
12%|█▏ | 369/3000 [01:58<11:37, 3.77it/s]
12%|█▏ | 370/3000 [01:58<11:29, 3.81it/s]
{'loss': 0.5504, 'grad_norm': 0.6141887307167053, 'learning_rate': 9.855013315614725e-05} |
|
12%|█▏ | 370/3000 [01:59<11:29, 3.81it/s]
12%|█▏ | 371/3000 [01:59<11:31, 3.80it/s]Rank 0, Worker 5: Wait for shard 51 in dataset 0 in 0.00 seconds |
| Rank 0, Worker 5: Caching shard... |
|
12%|█▏ | 372/3000 [01:59<11:23, 3.84it/s]
12%|█▏ | 373/3000 [01:59<11:28, 3.82it/s]
12%|█▏ | 374/3000 [02:00<11:32, 3.79it/s]
12%|█▎ | 375/3000 [02:00<11:26, 3.83it/s]
13%|█▎ | 376/3000 [02:00<11:24, 3.83it/s]Rank 0, Worker 4: Wait for shard 56 in dataset 0 in 0.00 seconds |
| Rank 0, Worker 4: Caching shard... |
|
13%|█▎ | 377/3000 [02:00<11:27, 3.82it/s]
13%|█▎ | 378/3000 [02:01<11:33, 3.78it/s]
13%|█▎ | 379/3000 [02:01<12:05, 3.61it/s]
13%|█▎ | 380/3000 [02:01<11:42, 3.73it/s]
{'loss': 0.5447, 'grad_norm': 0.7782378792762756, 'learning_rate': 9.841542192879762e-05} |
|
13%|█▎ | 380/3000 [02:01<11:42, 3.73it/s]
13%|█▎ | 381/3000 [02:01<11:40, 3.74it/s]
13%|█▎ | 382/3000 [02:02<12:01, 3.63it/s]
13%|█▎ | 383/3000 [02:02<11:47, 3.70it/s]
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13%|█▎ | 385/3000 [02:02<11:26, 3.81it/s]
13%|█▎ | 386/3000 [02:03<11:35, 3.76it/s]
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13%|█▎ | 388/3000 [02:03<11:17, 3.85it/s]
13%|█▎ | 389/3000 [02:04<11:26, 3.80it/s]
13%|█▎ | 390/3000 [02:04<11:30, 3.78it/s]
{'loss': 0.5435, 'grad_norm': 0.8065223693847656, 'learning_rate': 9.82748278301294e-05} |
|
13%|█▎ | 390/3000 [02:04<11:30, 3.78it/s]
13%|█▎ | 391/3000 [02:04<11:43, 3.71it/s]
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13%|█▎ | 398/3000 [02:06<11:32, 3.75it/s]
13%|█▎ | 399/3000 [02:06<12:12, 3.55it/s]
13%|█▎ | 400/3000 [02:07<12:47, 3.39it/s]
{'loss': 0.5344, 'grad_norm': 0.7179561257362366, 'learning_rate': 9.812836794348004e-05} |
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{'loss': 0.4481, 'grad_norm': 0.7813271284103394, 'learning_rate': 9.634541575171929e-05} |
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17%|█▋ | 500/3000 [02:33<12:36, 3.31it/s]Copying experiment config directory /home/ubuntu/groot-files/checkpoints/g1_finetune-20260526-213350-gpu0/experiment_cfg to /home/ubuntu/groot-files/checkpoints/g1_finetune-20260526-213350-gpu0/checkpoint-500/experiment_cfg |
| Copying processor directory /home/ubuntu/groot-files/checkpoints/g1_finetune-20260526-213350-gpu0/processor to /home/ubuntu/groot-files/checkpoints/g1_finetune-20260526-213350-gpu0/checkpoint-500 |
| Copying wandb_config.json from /home/ubuntu/groot-files/checkpoints/g1_finetune-20260526-213350-gpu0/wandb_config.json to /home/ubuntu/groot-files/checkpoints/g1_finetune-20260526-213350-gpu0/checkpoint-500/wandb_config.json |
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{'loss': 0.3647, 'grad_norm': 0.7548572421073914, 'learning_rate': 9.476105444595534e-05} |
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{'loss': 0.3526, 'grad_norm': 0.8562734723091125, 'learning_rate': 9.451273234763371e-05} |
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{'loss': 0.3541, 'grad_norm': 1.0484408140182495, 'learning_rate': 9.425900158682385e-05} |
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{'loss': 0.3495, 'grad_norm': 1.114036202430725, 'learning_rate': 9.399989299389661e-05} |
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{'loss': 0.3446, 'grad_norm': 1.0067291259765625, 'learning_rate': 9.373543805267368e-05} |
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{'loss': 0.3169, 'grad_norm': 1.0836315155029297, 'learning_rate': 9.346566889660193e-05} |
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{'loss': 0.3029, 'grad_norm': 1.1337170600891113, 'learning_rate': 9.319061830484898e-05} |
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{'loss': 0.3035, 'grad_norm': 1.0124084949493408, 'learning_rate': 9.291031969832026e-05} |
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{'loss': 0.3065, 'grad_norm': 1.1703892946243286, 'learning_rate': 9.262480713559808e-05} |
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{'loss': 0.2916, 'grad_norm': 0.8515862226486206, 'learning_rate': 9.233411530880326e-05} |
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{'loss': 0.2933, 'grad_norm': 1.3676186800003052, 'learning_rate': 9.20382795393797e-05} |
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{'loss': 0.2724, 'grad_norm': 0.8166829943656921, 'learning_rate': 9.173733577380258e-05} |
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{'loss': 0.26, 'grad_norm': 1.028581142425537, 'learning_rate': 9.143132057921058e-05} |
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{'loss': 0.2551, 'grad_norm': 1.035443663597107, 'learning_rate': 9.112027113896262e-05} |
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{'loss': 0.2613, 'grad_norm': 1.22231924533844, 'learning_rate': 9.080422524811982e-05} |
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{'loss': 0.2384, 'grad_norm': 1.0958259105682373, 'learning_rate': 9.048322130885305e-05} |
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{'loss': 0.2329, 'grad_norm': 0.8523461222648621, 'learning_rate': 9.015729832577681e-05} |
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25%|██▍ | 739/3000 [04:15<10:16, 3.66it/s]Rank 0, Worker 1: Wait for shard 28 in dataset 0 in 0.00 seconds |
| Rank 0, Worker 1: Caching shard... |
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{'loss': 0.2094, 'grad_norm': 0.964102029800415, 'learning_rate': 8.982649590120982e-05} |
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25%|██▍ | 741/3000 [04:15<10:22, 3.63it/s]Rank 0, Worker 3: Wait for shard 63 in dataset 0 in 0.00 seconds |
| Rank 0, Worker 3: Caching shard... |
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| Rank 0, Worker 0: Caching shard... |
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{'loss': 0.2132, 'grad_norm': 0.98223876953125, 'learning_rate': 8.949085423036296e-05} |
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25%|██▌ | 752/3000 [04:19<10:43, 3.49it/s]Rank 0, Worker 2: Wait for shard 47 in dataset 0 in 0.00 seconds |
| Rank 0, Worker 2: Caching shard... |
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25%|██▌ | 754/3000 [04:19<10:38, 3.52it/s]Rank 0, Worker 4: Wait for shard 12 in dataset 0 in 0.00 seconds |
| Rank 0, Worker 4: Caching shard... |
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| Rank 0, Worker 5: Caching shard... |
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{'loss': 0.1981, 'grad_norm': 1.0459887981414795, 'learning_rate': 8.91504140964553e-05} |
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{'loss': 0.1954, 'grad_norm': 1.3035297393798828, 'learning_rate': 8.880521686575857e-05} |
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{'loss': 0.1891, 'grad_norm': 0.9774158596992493, 'learning_rate': 8.845530448257085e-05} |
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{'loss': 0.1783, 'grad_norm': 1.1295584440231323, 'learning_rate': 8.810071946411989e-05} |
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{'loss': 0.1765, 'grad_norm': 0.8923147916793823, 'learning_rate': 8.774150489539707e-05} |
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{'loss': 0.1742, 'grad_norm': 1.3010443449020386, 'learning_rate': 8.737770442392212e-05} |
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{'loss': 0.1587, 'grad_norm': 0.9801855683326721, 'learning_rate': 8.700936225443959e-05} |
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{'loss': 0.1646, 'grad_norm': 1.0634956359863281, 'learning_rate': 8.663652314354765e-05} |
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{'loss': 0.1485, 'grad_norm': 0.8811051845550537, 'learning_rate': 8.625923239425978e-05} |
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{'loss': 0.1388, 'grad_norm': 1.4074150323867798, 'learning_rate': 8.510111142632698e-05} |
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{'loss': 0.1199, 'grad_norm': 0.9820786118507385, 'learning_rate': 8.267103019950529e-05} |
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{'loss': 0.1149, 'grad_norm': 1.0110657215118408, 'learning_rate': 7.965615490979163e-05} |
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33%|███▎ | 1000/3000 [05:24<08:40, 3.84it/s]Copying experiment config directory /home/ubuntu/groot-files/checkpoints/g1_finetune-20260526-213350-gpu0/experiment_cfg to /home/ubuntu/groot-files/checkpoints/g1_finetune-20260526-213350-gpu0/checkpoint-1000/experiment_cfg |
| Copying processor directory /home/ubuntu/groot-files/checkpoints/g1_finetune-20260526-213350-gpu0/processor to /home/ubuntu/groot-files/checkpoints/g1_finetune-20260526-213350-gpu0/checkpoint-1000 |
| Copying wandb_config.json from /home/ubuntu/groot-files/checkpoints/g1_finetune-20260526-213350-gpu0/wandb_config.json to /home/ubuntu/groot-files/checkpoints/g1_finetune-20260526-213350-gpu0/checkpoint-1000/wandb_config.json |
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{'loss': 0.1034, 'grad_norm': 1.0371506214141846, 'learning_rate': 7.739353226541009e-05} |
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{'loss': 0.1159, 'grad_norm': 0.8586914539337158, 'learning_rate': 7.693080007570084e-05} |
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{'loss': 0.1115, 'grad_norm': 0.7747752070426941, 'learning_rate': 7.646479557264513e-05} |
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{'loss': 0.1106, 'grad_norm': 0.8298690915107727, 'learning_rate': 7.599557537961663e-05} |
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{'loss': 0.0915, 'grad_norm': 0.8888349533081055, 'learning_rate': 7.552319651072164e-05} |
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{'loss': 0.1019, 'grad_norm': 0.8841614127159119, 'learning_rate': 7.504771636387163e-05} |
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{'loss': 0.1104, 'grad_norm': 1.0035121440887451, 'learning_rate': 7.456919271380875e-05} |
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37%|███▋ | 1119/3000 [06:34<08:28, 3.70it/s]Rank 0, Worker 3: Wait for shard 19 in dataset 0 in 0.00 seconds |
| Rank 0, Worker 3: Caching shard... |
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{'loss': 0.1106, 'grad_norm': 0.8126855492591858, 'learning_rate': 7.408768370508576e-05} |
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| Rank 0, Worker 1: Caching shard... |
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{'loss': 0.1164, 'grad_norm': 0.9205325245857239, 'learning_rate': 7.36032478450011e-05} |
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| Rank 0, Worker 2: Caching shard... |
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| Rank 0, Worker 5: Caching shard... |
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| Rank 0, Worker 0: Caching shard... |
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| Rank 0, Worker 4: Caching shard... |
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{'loss': 0.1162, 'grad_norm': 0.8639265298843384, 'learning_rate': 7.311594399648957e-05} |
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{'loss': 0.1087, 'grad_norm': 0.9142033457756042, 'learning_rate': 7.262583137097018e-05} |
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{'loss': 0.1083, 'grad_norm': 0.9747472405433655, 'learning_rate': 7.213296952115144e-05} |
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{'loss': 0.107, 'grad_norm': 0.9333903789520264, 'learning_rate': 7.16374183337951e-05} |
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{'loss': 0.1063, 'grad_norm': 0.9898130297660828, 'learning_rate': 7.113923802243957e-05} |
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{'loss': 0.1067, 'grad_norm': 0.9155701398849487, 'learning_rate': 7.06384891200834e-05} |
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{'loss': 0.109, 'grad_norm': 0.8125437498092651, 'learning_rate': 7.013523247183e-05} |
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{'loss': 0.1063, 'grad_norm': 1.1674683094024658, 'learning_rate': 6.962952922749457e-05} |
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{'loss': 0.1014, 'grad_norm': 0.7635449767112732, 'learning_rate': 6.912144083417376e-05} |
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{'loss': 0.1098, 'grad_norm': 0.9461978673934937, 'learning_rate': 6.861102902877946e-05} |
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{'loss': 0.0984, 'grad_norm': 0.9153079986572266, 'learning_rate': 6.809835583053715e-05} |
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{'loss': 0.1082, 'grad_norm': 0.9081976413726807, 'learning_rate': 6.758348353345014e-05} |
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{'loss': 0.0989, 'grad_norm': 0.8417534232139587, 'learning_rate': 6.706647469873031e-05} |
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{'loss': 0.1092, 'grad_norm': 0.7554053664207458, 'learning_rate': 6.654739214719641e-05} |
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{'loss': 0.1084, 'grad_norm': 0.8323029279708862, 'learning_rate': 6.602629895164081e-05} |
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{'loss': 0.1096, 'grad_norm': 0.8539698719978333, 'learning_rate': 6.550325842916559e-05} |
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{'loss': 0.0989, 'grad_norm': 0.8106352686882019, 'learning_rate': 6.497833413348909e-05} |
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44%|████▎ | 1305/3000 [07:25<07:18, 3.86it/s]Rank 0, Worker 3: Wait for shard 29 in dataset 0 in 0.00 seconds |
| Rank 0, Worker 3: Caching shard... |
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| Rank 0, Worker 1: Caching shard... |
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{'loss': 0.0983, 'grad_norm': 0.7995074987411499, 'learning_rate': 6.445158984722358e-05} |
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{'loss': 0.1061, 'grad_norm': 0.7924811244010925, 'learning_rate': 6.39230895741251e-05} |
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44%|████▍ | 1322/3000 [07:29<07:24, 3.77it/s]Rank 0, Worker 2: Wait for shard 41 in dataset 0 in 0.00 seconds |
| Rank 0, Worker 2: Caching shard... |
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44%|████▍ | 1324/3000 [07:30<07:49, 3.57it/s]Rank 0, Worker 4: Wait for shard 5 in dataset 0 in 0.00 seconds |
| Rank 0, Worker 4: Caching shard... |
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| Rank 0, Worker 5: Caching shard... |
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| Rank 0, Worker 0: Caching shard... |
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{'loss': 0.0937, 'grad_norm': 0.8590250015258789, 'learning_rate': 6.339289753131649e-05} |
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{'loss': 0.1028, 'grad_norm': 0.8390591740608215, 'learning_rate': 6.286107814148454e-05} |
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{'loss': 0.0928, 'grad_norm': 0.9238244891166687, 'learning_rate': 6.232769602505203e-05} |
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{'loss': 0.1027, 'grad_norm': 0.9588078260421753, 'learning_rate': 6.179281599232591e-05} |
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{'loss': 0.0845, 'grad_norm': 0.9879070520401001, 'learning_rate': 6.125650303562221e-05} |
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{'loss': 0.0996, 'grad_norm': 0.8994210362434387, 'learning_rate': 6.071882232136901e-05} |
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{'loss': 0.091, 'grad_norm': 0.7739790081977844, 'learning_rate': 6.017983918218812e-05} |
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{'loss': 0.0993, 'grad_norm': 0.7537702322006226, 'learning_rate': 5.963961910895676e-05} |
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{'loss': 0.0863, 'grad_norm': 0.7310131788253784, 'learning_rate': 5.909822774284971e-05} |
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{'loss': 0.0992, 'grad_norm': 0.7676811814308167, 'learning_rate': 5.85557308673635e-05} |
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{'loss': 0.0932, 'grad_norm': 0.8523777723312378, 'learning_rate': 5.8012194400323116e-05} |
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{'loss': 0.0952, 'grad_norm': 0.7514760494232178, 'learning_rate': 5.746768438587245e-05} |
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{'loss': 0.1012, 'grad_norm': 0.818895697593689, 'learning_rate': 5.692226698644938e-05} |
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{'loss': 0.0953, 'grad_norm': 0.924919605255127, 'learning_rate': 5.637600847474656e-05} |
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50%|█████ | 1500/3000 [08:18<07:27, 3.35it/s]Copying experiment config directory /home/ubuntu/groot-files/checkpoints/g1_finetune-20260526-213350-gpu0/experiment_cfg to /home/ubuntu/groot-files/checkpoints/g1_finetune-20260526-213350-gpu0/checkpoint-1500/experiment_cfg |
| Copying processor directory /home/ubuntu/groot-files/checkpoints/g1_finetune-20260526-213350-gpu0/processor to /home/ubuntu/groot-files/checkpoints/g1_finetune-20260526-213350-gpu0/checkpoint-1500 |
| Copying wandb_config.json from /home/ubuntu/groot-files/checkpoints/g1_finetune-20260526-213350-gpu0/wandb_config.json to /home/ubuntu/groot-files/checkpoints/g1_finetune-20260526-213350-gpu0/checkpoint-1500/wandb_config.json |
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{'loss': 0.086, 'grad_norm': 0.7272283434867859, 'learning_rate': 4.482839373204891e-05} |
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56%|█████▌ | 1677/3000 [09:43<05:44, 3.84it/s]Rank 0, Worker 3: Wait for shard 39 in dataset 0 in 0.00 seconds |
| Rank 0, Worker 3: Caching shard... |
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{'loss': 0.094, 'grad_norm': 0.8412664532661438, 'learning_rate': 4.428051854493623e-05} |
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| Rank 0, Worker 1: Caching shard... |
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{'loss': 0.0889, 'grad_norm': 0.7905071973800659, 'learning_rate': 4.373333832178478e-05} |
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{'loss': 0.0873, 'grad_norm': 0.7173388004302979, 'learning_rate': 4.3186919549484784e-05} |
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| Rank 0, Worker 5: Caching shard... |
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| Rank 0, Worker 0: Caching shard... |
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| Rank 0, Worker 2: Caching shard... |
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| Rank 0, Worker 4: Caching shard... |
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{'loss': 0.0852, 'grad_norm': 0.7447967529296875, 'learning_rate': 4.264132862240387e-05} |
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{'loss': 0.093, 'grad_norm': 0.6910264492034912, 'learning_rate': 4.209663183431969e-05} |
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{'loss': 0.0898, 'grad_norm': 0.6057111620903015, 'learning_rate': 4.155289537036466e-05} |
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{'loss': 0.0844, 'grad_norm': 0.7384588718414307, 'learning_rate': 4.1010185298983984e-05} |
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{'loss': 0.087, 'grad_norm': 0.658176064491272, 'learning_rate': 4.046856756390767e-05} |
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{'loss': 0.0895, 'grad_norm': 0.6321943402290344, 'learning_rate': 3.9928107976137906e-05} |
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{'loss': 0.0845, 'grad_norm': 0.6504121422767639, 'learning_rate': 3.9388872205952526e-05} |
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{'loss': 0.0838, 'grad_norm': 0.564155101776123, 'learning_rate': 3.8850925774925425e-05} |
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{'loss': 0.0902, 'grad_norm': 0.5792074799537659, 'learning_rate': 3.831433404796521e-05} |
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{'loss': 0.0866, 'grad_norm': 0.7973079085350037, 'learning_rate': 3.777916222537285e-05} |
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{'loss': 0.087, 'grad_norm': 0.7829543948173523, 'learning_rate': 3.7245475334919246e-05} |
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{'loss': 0.0843, 'grad_norm': 0.7178475260734558, 'learning_rate': 3.6713338223943867e-05} |
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{'loss': 0.0845, 'grad_norm': 0.5880443453788757, 'learning_rate': 3.618281555147522e-05} |
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{'loss': 0.0745, 'grad_norm': 0.6559892296791077, 'learning_rate': 3.5653971780374295e-05} |
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{'loss': 0.08, 'grad_norm': 0.6737433671951294, 'learning_rate': 3.512687116950182e-05} |
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{'loss': 0.0909, 'grad_norm': 0.7049776911735535, 'learning_rate': 3.460157776591018e-05} |
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62%|██████▏ | 1863/3000 [10:35<05:11, 3.65it/s]Rank 0, Worker 3: Wait for shard 6 in dataset 0 in 0.00 seconds |
| Rank 0, Worker 3: Caching shard... |
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{'loss': 0.0912, 'grad_norm': 0.7571489214897156, 'learning_rate': 3.407815539706124e-05} |
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| Rank 0, Worker 1: Caching shard... |
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{'loss': 0.074, 'grad_norm': 0.6526145339012146, 'learning_rate': 3.3037177928980735e-05} |
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63%|██████▎ | 1890/3000 [10:43<04:49, 3.84it/s]Rank 0, Worker 0: Wait for shard 15 in dataset 0 in 0.00 seconds |
| Rank 0, Worker 0: Caching shard... |
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| Rank 0, Worker 2: Caching shard... |
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| Rank 0, Worker 4: Caching shard... |
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| Rank 0, Worker 5: Caching shard... |
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{'loss': 0.094, 'grad_norm': 0.6423455476760864, 'learning_rate': 3.251974931705933e-05} |
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{'loss': 0.0877, 'grad_norm': 0.5167522430419922, 'learning_rate': 3.2004444699131727e-05} |
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{'loss': 0.0812, 'grad_norm': 0.6353688836097717, 'learning_rate': 3.1491326688940345e-05} |
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{'loss': 0.0867, 'grad_norm': 0.7268972396850586, 'learning_rate': 3.098045763453678e-05} |
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{'loss': 0.0856, 'grad_norm': 0.521489679813385, 'learning_rate': 3.0471899610706038e-05} |
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{'loss': 0.0839, 'grad_norm': 0.61240154504776, 'learning_rate': 2.9965714411423972e-05} |
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{'loss': 0.0751, 'grad_norm': 0.6277241110801697, 'learning_rate': 2.9461963542348737e-05} |
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{'loss': 0.0881, 'grad_norm': 0.6723438501358032, 'learning_rate': 2.8960708213347366e-05} |
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{'loss': 0.0938, 'grad_norm': 0.6539252996444702, 'learning_rate': 2.846200933105829e-05} |
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{'loss': 0.0797, 'grad_norm': 0.6006316542625427, 'learning_rate': 2.7965927491490705e-05} |
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{'loss': 0.0779, 'grad_norm': 0.9345439672470093, 'learning_rate': 2.747252297266162e-05} |
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67%|██████▋ | 2000/3000 [11:13<04:32, 3.67it/s]Copying experiment config directory /home/ubuntu/groot-files/checkpoints/g1_finetune-20260526-213350-gpu0/experiment_cfg to /home/ubuntu/groot-files/checkpoints/g1_finetune-20260526-213350-gpu0/checkpoint-2000/experiment_cfg |
| Copying processor directory /home/ubuntu/groot-files/checkpoints/g1_finetune-20260526-213350-gpu0/processor to /home/ubuntu/groot-files/checkpoints/g1_finetune-20260526-213350-gpu0/checkpoint-2000 |
| Copying wandb_config.json from /home/ubuntu/groot-files/checkpoints/g1_finetune-20260526-213350-gpu0/wandb_config.json to /home/ubuntu/groot-files/checkpoints/g1_finetune-20260526-213350-gpu0/checkpoint-2000/wandb_config.json |
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{'loss': 0.0751, 'grad_norm': 0.7097274661064148, 'learning_rate': 2.698185572727151e-05} |
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{'loss': 0.0794, 'grad_norm': 0.6569517254829407, 'learning_rate': 2.6493985375419778e-05} |
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{'loss': 0.0846, 'grad_norm': 0.5854899883270264, 'learning_rate': 2.6008971197360176e-05} |
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{'loss': 0.087, 'grad_norm': 0.6118670105934143, 'learning_rate': 2.552687212629799e-05} |
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68%|██████▊ | 2049/3000 [12:02<03:50, 4.13it/s]Rank 0, Worker 3: Wait for shard 26 in dataset 0 in 0.00 seconds |
| Rank 0, Worker 3: Caching shard... |
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| Rank 0, Worker 1: Caching shard... |
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{'loss': 0.0747, 'grad_norm': 0.6216926574707031, 'learning_rate': 2.4571653259821694e-05} |
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{'loss': 0.073, 'grad_norm': 0.5638583898544312, 'learning_rate': 2.4098649531343497e-05} |
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| Rank 0, Worker 0: Caching shard... |
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| Rank 0, Worker 2: Caching shard... |
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{'loss': 0.0722, 'grad_norm': 0.6165386438369751, 'learning_rate': 2.362879302963135e-05} |
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{'loss': 0.074, 'grad_norm': 0.6541428565979004, 'learning_rate': 2.3162140846108366e-05} |
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| Rank 0, Worker 4: Caching shard... |
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| Rank 0, Worker 5: Caching shard... |
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{'loss': 0.0734, 'grad_norm': 0.4623146951198578, 'learning_rate': 2.2698749682846687e-05} |
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{'loss': 0.0754, 'grad_norm': 0.7112588882446289, 'learning_rate': 2.2238675845677663e-05} |
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{'loss': 0.0714, 'grad_norm': 0.5454754829406738, 'learning_rate': 2.1781975237350366e-05} |
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{'loss': 0.0763, 'grad_norm': 0.4984387159347534, 'learning_rate': 2.1328703350738765e-05} |
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{'loss': 0.0768, 'grad_norm': 0.5290881395339966, 'learning_rate': 2.0878915262099098e-05} |
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{'loss': 0.0812, 'grad_norm': 0.5415129065513611, 'learning_rate': 2.0432665624377434e-05} |
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{'loss': 0.0769, 'grad_norm': 0.5350505709648132, 'learning_rate': 1.999000866056908e-05} |
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{'loss': 0.0685, 'grad_norm': 0.5751089453697205, 'learning_rate': 1.9550998157129946e-05} |
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{'loss': 0.0821, 'grad_norm': 0.4716225266456604, 'learning_rate': 1.9115687457441022e-05} |
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{'loss': 0.0686, 'grad_norm': 0.5699394941329956, 'learning_rate': 1.868412945532681e-05} |
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{'loss': 0.0735, 'grad_norm': 0.5516906976699829, 'learning_rate': 1.8256376588628238e-05} |
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{'loss': 0.0729, 'grad_norm': 0.4884108304977417, 'learning_rate': 1.7832480832830987e-05} |
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{'loss': 0.0691, 'grad_norm': 0.817842960357666, 'learning_rate': 1.7412493694750176e-05} |
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{'loss': 0.0792, 'grad_norm': 0.5762520432472229, 'learning_rate': 1.699646620627168e-05} |
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{'loss': 0.0675, 'grad_norm': 0.4962397813796997, 'learning_rate': 1.658444891815152e-05} |
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75%|███████▍ | 2241/3000 [12:54<03:27, 3.66it/s]Rank 0, Worker 3: Wait for shard 47 in dataset 0 in 0.00 seconds |
| Rank 0, Worker 3: Caching shard... |
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| Rank 0, Worker 1: Caching shard... |
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{'loss': 0.0786, 'grad_norm': 0.5862926840782166, 'learning_rate': 1.617649189387337e-05} |
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{'loss': 0.0796, 'grad_norm': 0.5360605120658875, 'learning_rate': 1.5772644703565565e-05} |
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| Rank 0, Worker 0: Caching shard... |
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| Rank 0, Worker 2: Caching shard... |
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{'loss': 0.0694, 'grad_norm': 0.5301634669303894, 'learning_rate': 1.537295641797785e-05} |
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| Rank 0, Worker 4: Caching shard... |
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| Rank 0, Worker 5: Caching shard... |
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{'loss': 0.0799, 'grad_norm': 0.4486077129840851, 'learning_rate': 1.4977475602518876e-05} |
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{'loss': 0.0685, 'grad_norm': 0.4608897268772125, 'learning_rate': 1.343858033448982e-05} |
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{'loss': 0.0816, 'grad_norm': 0.5362879633903503, 'learning_rate': 1.3064847254288797e-05} |
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{'loss': 0.0717, 'grad_norm': 0.46307265758514404, 'learning_rate': 1.2695602098432502e-05} |
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{'loss': 0.0787, 'grad_norm': 0.4995485842227936, 'learning_rate': 1.233088973323937e-05} |
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{'loss': 0.0714, 'grad_norm': 0.6543102860450745, 'learning_rate': 1.1970754474256563e-05} |
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{'loss': 0.0703, 'grad_norm': 0.4924975633621216, 'learning_rate': 1.16152400808752e-05} |
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{'loss': 0.0683, 'grad_norm': 0.46566370129585266, 'learning_rate': 1.1264389751013326e-05} |
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{'loss': 0.0793, 'grad_norm': 0.4437257945537567, 'learning_rate': 1.0918246115866964e-05} |
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{'loss': 0.0782, 'grad_norm': 0.5867979526519775, 'learning_rate': 1.0576851234730095e-05} |
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{'loss': 0.0667, 'grad_norm': 0.5302107334136963, 'learning_rate': 1.0240246589884044e-05} |
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{'loss': 0.072, 'grad_norm': 0.5226858854293823, 'learning_rate': 9.908473081557151e-06} |
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{'loss': 0.0677, 'grad_norm': 0.4361122250556946, 'learning_rate': 9.581571022954988e-06} |
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81%|████████ | 2433/3000 [13:47<02:34, 3.68it/s]Rank 0, Worker 3: Wait for shard 19 in dataset 0 in 0.00 seconds |
| Rank 0, Worker 3: Caching shard... |
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| Rank 0, Worker 1: Caching shard... |
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{'loss': 0.077, 'grad_norm': 0.5139945149421692, 'learning_rate': 9.259580135361929e-06} |
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{'loss': 0.0721, 'grad_norm': 0.4558435380458832, 'learning_rate': 8.9425395433148e-06} |
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| Rank 0, Worker 2: Caching shard... |
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| Rank 0, Worker 0: Caching shard... |
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{'loss': 0.0799, 'grad_norm': 0.5343697667121887, 'learning_rate': 8.630487769848877e-06} |
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83%|████████▎ | 2500/3000 [14:05<02:16, 3.67it/s]Copying experiment config directory /home/ubuntu/groot-files/checkpoints/g1_finetune-20260526-213350-gpu0/experiment_cfg to /home/ubuntu/groot-files/checkpoints/g1_finetune-20260526-213350-gpu0/checkpoint-2500/experiment_cfg |
| Copying processor directory /home/ubuntu/groot-files/checkpoints/g1_finetune-20260526-213350-gpu0/processor to /home/ubuntu/groot-files/checkpoints/g1_finetune-20260526-213350-gpu0/checkpoint-2500 |
| Copying wandb_config.json from /home/ubuntu/groot-files/checkpoints/g1_finetune-20260526-213350-gpu0/wandb_config.json to /home/ubuntu/groot-files/checkpoints/g1_finetune-20260526-213350-gpu0/checkpoint-2500/wandb_config.json |
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{'loss': 0.0685, 'grad_norm': 0.4761175215244293, 'learning_rate': 6.588919767147639e-06} |
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{'loss': 0.075, 'grad_norm': 0.4890459477901459, 'learning_rate': 6.318091681012772e-06} |
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{'loss': 0.068, 'grad_norm': 0.39969003200531006, 'learning_rate': 4.805691497504505e-06} |
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{'loss': 0.0677, 'grad_norm': 0.4076022803783417, 'learning_rate': 4.57267206366902e-06} |
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| Rank 0, Worker 3: Caching shard... |
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{'loss': 0.0698, 'grad_norm': 0.4183996617794037, 'learning_rate': 4.3451724231958644e-06} |
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| Rank 0, Worker 1: Caching shard... |
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{'loss': 0.0639, 'grad_norm': 0.4020463228225708, 'learning_rate': 4.123220219159418e-06} |
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{'loss': 0.0734, 'grad_norm': 0.4486771821975708, 'learning_rate': 3.696065319121833e-06} |
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| Rank 0, Worker 4: Caching shard... |
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{'loss': 0.0799, 'grad_norm': 0.4313182532787323, 'learning_rate': 3.4909145259485744e-06} |
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| Rank 0, Worker 5: Caching shard... |
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{'loss': 0.0728, 'grad_norm': 0.4147796034812927, 'learning_rate': 3.2914149685611073e-06} |
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{'loss': 0.0697, 'grad_norm': 0.4549005627632141, 'learning_rate': 2.9094658348640945e-06} |
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{'loss': 0.0785, 'grad_norm': 0.3670569360256195, 'learning_rate': 2.7270626685105828e-06} |
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{'loss': 0.0715, 'grad_norm': 0.3622991442680359, 'learning_rate': 2.5504035522157854e-06} |
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{'loss': 0.0682, 'grad_norm': 0.42583581805229187, 'learning_rate': 2.379509951512937e-06} |
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{'loss': 0.0689, 'grad_norm': 0.3878172039985657, 'learning_rate': 2.214402631377782e-06} |
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{'loss': 0.0714, 'grad_norm': 0.43555888533592224, 'learning_rate': 2.0551016537054493e-06} |
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{'loss': 0.064, 'grad_norm': 0.41738301515579224, 'learning_rate': 1.9016263748728114e-06} |
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{'loss': 0.066, 'grad_norm': 0.39067214727401733, 'learning_rate': 1.7539954433864858e-06} |
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{'loss': 0.0643, 'grad_norm': 0.5217285752296448, 'learning_rate': 1.6122267976168781e-06} |
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{'loss': 0.0701, 'grad_norm': 0.3757125437259674, 'learning_rate': 1.4763376636185599e-06} |
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{'loss': 0.062, 'grad_norm': 0.4145689606666565, 'learning_rate': 1.3463445530371488e-06} |
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{'loss': 0.0713, 'grad_norm': 0.4163986146450043, 'learning_rate': 1.222263261102985e-06} |
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94%|█████████▎| 2805/3000 [16:05<00:50, 3.85it/s]Rank 0, Worker 3: Wait for shard 41 in dataset 0 in 0.00 seconds |
| Rank 0, Worker 3: Caching shard... |
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{'loss': 0.0699, 'grad_norm': 0.3938809037208557, 'learning_rate': 1.1041088647119114e-06} |
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| Rank 0, Worker 1: Caching shard... |
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{'loss': 0.0608, 'grad_norm': 0.39454385638237, 'learning_rate': 9.918957205933e-07} |
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| Rank 0, Worker 2: Caching shard... |
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{'loss': 0.0678, 'grad_norm': 0.4002632200717926, 'learning_rate': 8.856374635655695e-07} |
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| Rank 0, Worker 0: Caching shard... |
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{'loss': 0.0689, 'grad_norm': 0.37098678946495056, 'learning_rate': 7.853470048794664e-07} |
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| Rank 0, Worker 4: Caching shard... |
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| Rank 0, Worker 3: Caching shard... |
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100%|██████████| 3000/3000 [16:57<00:00, 3.84it/s]Copying experiment config directory /home/ubuntu/groot-files/checkpoints/g1_finetune-20260526-213350-gpu0/experiment_cfg to /home/ubuntu/groot-files/checkpoints/g1_finetune-20260526-213350-gpu0/checkpoint-3000/experiment_cfg |
| Copying processor directory /home/ubuntu/groot-files/checkpoints/g1_finetune-20260526-213350-gpu0/processor to /home/ubuntu/groot-files/checkpoints/g1_finetune-20260526-213350-gpu0/checkpoint-3000 |
| Copying wandb_config.json from /home/ubuntu/groot-files/checkpoints/g1_finetune-20260526-213350-gpu0/wandb_config.json to /home/ubuntu/groot-files/checkpoints/g1_finetune-20260526-213350-gpu0/checkpoint-3000/wandb_config.json |
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{'train_runtime': 1054.5211, 'train_samples_per_second': 91.037, 'train_steps_per_second': 2.845, 'train_loss': 0.2204543206691742} |
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| 05/26/2026 21:52:08 - INFO - Model saved to /home/ubuntu/groot-files/checkpoints/g1_finetune-20260526-213350-gpu0 |
| 05/26/2026 21:52:08 - INFO - Training completed! |
| [1;34mwandb[0m: |
| [1;34mwandb[0m: 🚀 View run [33mg1_finetune-20260526-213350-gpu0[0m at: [34m[0m |
| [1;34mwandb[0m: Find logs at: [1;35mwandb/run-20260526_213400-zw5ihkoo/logs[0m |
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