[tab] /fast/project/HFMI_SynergyUnit/mihir/logs/nemo/qwen3_600m_finetune_34704.log (log)
#!/usr/bin/env bash

#SBATCH --nodes=1
#SBATCH --ntasks-per-node=1
#SBATCH --time=24:00:00
#SBATCH --cpus-per-task=5
#SBATCH --gres=gpu:1
#SBATCH --output=/fast/project/HFMI_SynergyUnit/mihir/logs/nemo/%x_%j.log
#SBATCH --error=/fast/project/HFMI_SynergyUnit/mihir/logs/nemo/%x_%j.log
#SBATCH --job-name=qwen3_600m_finetune
#SBATCH --mem=400GB
#SBATCH --qos=low

# Log the sbatch script
cat $0

source .uv_venv/bin/activate

python "$1"/fast/home/mihir.mahajan/Projects/crowd-pilot/.uv_venv/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
  import pynvml  # type: ignore[import]
─ Entering Experiment qwen3_600m_lora_4k_tokens_no_act_ckpt with id: qwen3_60… ─
[16:10:54] INFO     Log directory is:                     local_scheduler.py:777
                    /home/mihir.mahajan/.nemo_run/experim                       
                    ents/qwen3_600m_lora_4k_tokens_no_act                       
                    _ckpt/qwen3_600m_lora_4k_tokens_no_ac                       
                    t_ckpt_1764083454/qwen3_600m_lora_4k_                       
                    tokens_no_act_ckpt                                          
[16:10:54] Launching job qwen3_600m_lora_4k_tokens_no_act_ckpt experiment.py:744
           for experiment                                                       
           qwen3_600m_lora_4k_tokens_no_act_ckpt                                
           INFO     Log directory is:                     local_scheduler.py:777
                    /home/mihir.mahajan/.nemo_run/experim                       
                    ents/qwen3_600m_lora_4k_tokens_no_act                       
                    _ckpt/qwen3_600m_lora_4k_tokens_no_ac                       
                    t_ckpt_1764083454/qwen3_600m_lora_4k_                       
                    tokens_no_act_ckpt                                          
           INFO     Launched app:                                launcher.py:111
                    local_persistent://nemo_run/qwen3_600m_lora_                
                    4k_tokens_no_act_ckpt-cvpbg4k7zz33g                         
─ Waiting for Experiment qwen3_600m_lora_4k_tokens_no_act_ckpt_1764083454 to … ─

Experiment Status for qwen3_600m_lora_4k_tokens_no_act_ckpt_1764083454

Task 0: qwen3_600m_lora_4k_tokens_no_act_ckpt
- Status: RUNNING
- Executor: LocalExecutor
- Job id: qwen3_600m_lora_4k_tokens_no_act_ckpt-cvpbg4k7zz33g
- Local Directory: /home/mihir.mahajan/.nemo_run/experiments/qwen3_600m_lora_4k_tokens_no_act_ckpt/qwen3_600m_lora_4k_tokens_no_act_ckpt_1764083454/qwen3_600m_lora_4k_tokens_no_act_ckpt

           INFO     Waiting for job                              launcher.py:130
                    qwen3_600m_lora_4k_tokens_no_act_ckpt-cvpbg4                
                    k7zz33g to finish [log=True]...                             
o_act_ckpt/0 /fast/home/mihir.mahajan/Projects/crowd-pilot/.uv_venv/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
o_act_ckpt/0   import pynvml  # type: ignore[import]
o_act_ckpt/0 I1125 16:10:57.234000 1352484 torch/distributed/run.py:657] Using nproc_per_node=1.
o_act_ckpt/0 I1125 16:10:57.237000 1352484 torch/distributed/launcher/api.py:199] Starting elastic_operator with launch configs:
o_act_ckpt/0 I1125 16:10:57.237000 1352484 torch/distributed/launcher/api.py:199]   entrypoint         : nemo_run.core.runners.fdl_runner
o_act_ckpt/0 I1125 16:10:57.237000 1352484 torch/distributed/launcher/api.py:199]   min_nodes          : 1
o_act_ckpt/0 I1125 16:10:57.237000 1352484 torch/distributed/launcher/api.py:199]   max_nodes          : 1
o_act_ckpt/0 I1125 16:10:57.237000 1352484 torch/distributed/launcher/api.py:199]   nproc_per_node     : 1
o_act_ckpt/0 I1125 16:10:57.237000 1352484 torch/distributed/launcher/api.py:199]   run_id             : 2692
o_act_ckpt/0 I1125 16:10:57.237000 1352484 torch/distributed/launcher/api.py:199]   rdzv_backend       : c10d
o_act_ckpt/0 I1125 16:10:57.237000 1352484 torch/distributed/launcher/api.py:199]   rdzv_endpoint      : localhost:0
o_act_ckpt/0 I1125 16:10:57.237000 1352484 torch/distributed/launcher/api.py:199]   rdzv_configs       : {'timeout': 900}
o_act_ckpt/0 I1125 16:10:57.237000 1352484 torch/distributed/launcher/api.py:199]   max_restarts       : 0
o_act_ckpt/0 I1125 16:10:57.237000 1352484 torch/distributed/launcher/api.py:199]   monitor_interval   : 0.1
o_act_ckpt/0 I1125 16:10:57.237000 1352484 torch/distributed/launcher/api.py:199]   log_dir            : /home/mihir.mahajan/.nemo_run/experiments/qwen3_600m_lora_4k_tokens_no_act_ckpt/qwen3_600m_lora_4k_tokens_no_act_ckpt_1764083454/qwen3_600m_lora_4k_tokens_no_act_ckpt/nemo_run/qwen3_600m_lora_4k_tokens_no_act_ckpt-cvpbg4k7zz33g/torchelastic/qwen3_600m_lora_4k_tokens_no_act_ckpt
o_act_ckpt/0 I1125 16:10:57.237000 1352484 torch/distributed/launcher/api.py:199]   metrics_cfg        : {}
o_act_ckpt/0 I1125 16:10:57.237000 1352484 torch/distributed/launcher/api.py:199]   event_log_handler  : null
o_act_ckpt/0 I1125 16:10:57.237000 1352484 torch/distributed/launcher/api.py:199] 
o_act_ckpt/0 I1125 16:10:57.243000 1352484 torch/distributed/elastic/agent/server/api.py:869] [default] starting workers for entrypoint: python3
o_act_ckpt/0 I1125 16:10:57.244000 1352484 torch/distributed/elastic/agent/server/api.py:677] [default] Rendezvous'ing worker group
o_act_ckpt/0 I1125 16:10:57.433000 1352484 torch/distributed/elastic/agent/server/api.py:523] [default] Rendezvous complete for workers. Result:
o_act_ckpt/0 I1125 16:10:57.433000 1352484 torch/distributed/elastic/agent/server/api.py:523]   restart_count=0
o_act_ckpt/0 I1125 16:10:57.433000 1352484 torch/distributed/elastic/agent/server/api.py:523]   master_addr=hai001.haicore.berlin
o_act_ckpt/0 I1125 16:10:57.433000 1352484 torch/distributed/elastic/agent/server/api.py:523]   master_port=44679
o_act_ckpt/0 I1125 16:10:57.433000 1352484 torch/distributed/elastic/agent/server/api.py:523]   group_rank=0
o_act_ckpt/0 I1125 16:10:57.433000 1352484 torch/distributed/elastic/agent/server/api.py:523]   group_world_size=1
o_act_ckpt/0 I1125 16:10:57.433000 1352484 torch/distributed/elastic/agent/server/api.py:523]   local_ranks=[0]
o_act_ckpt/0 I1125 16:10:57.433000 1352484 torch/distributed/elastic/agent/server/api.py:523]   role_ranks=[0]
o_act_ckpt/0 I1125 16:10:57.433000 1352484 torch/distributed/elastic/agent/server/api.py:523]   global_ranks=[0]
o_act_ckpt/0 I1125 16:10:57.433000 1352484 torch/distributed/elastic/agent/server/api.py:523]   role_world_sizes=[1]
o_act_ckpt/0 I1125 16:10:57.433000 1352484 torch/distributed/elastic/agent/server/api.py:523]   global_world_sizes=[1]
o_act_ckpt/0 I1125 16:10:57.433000 1352484 torch/distributed/elastic/agent/server/api.py:523]   event_log_handler=null
o_act_ckpt/0 I1125 16:10:57.433000 1352484 torch/distributed/elastic/agent/server/api.py:523] 
o_act_ckpt/0 I1125 16:10:57.434000 1352484 torch/distributed/elastic/agent/server/api.py:685] [default] Starting worker group
o_act_ckpt/0 I1125 16:10:57.434000 1352484 torch/distributed/elastic/agent/server/local_elastic_agent.py:296] use_agent_store: True
o_act_ckpt/0 I1125 16:10:57.435000 1352484 torch/distributed/elastic/agent/server/local_elastic_agent.py:192] Environment variable 'TORCHELASTIC_ENABLE_FILE_TIMER' not found. Do not start FileTimerServer.
o_act_ckpt/0 I1125 16:10:57.435000 1352484 torch/distributed/elastic/agent/server/local_elastic_agent.py:236] Environment variable 'TORCHELASTIC_HEALTH_CHECK_PORT' not found. Do not start health check.
o_act_ckpt/0 [default0]:/fast/home/mihir.mahajan/Projects/crowd-pilot/.uv_venv/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
o_act_ckpt/0 [default0]:  import pynvml  # type: ignore[import]
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:19 api:1251] Disabling try_restore_best_ckpt restoration for adapters
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:19 nemo_logger:162] Experiments will be logged at /fast/project/HFMI_SynergyUnit/tab_model/mihir/logs/qwen3_600m_lora_4k_tokens_no_act_ckpt/2025-11-25_16-11-19
o_act_ckpt/0 [default0]:GPU available: True (cuda), used: True
o_act_ckpt/0 [default0]:TPU available: False, using: 0 TPU cores
o_act_ckpt/0 [default0]:HPU available: False, using: 0 HPUs
o_act_ckpt/0 [default0]:[NeMo W 2025-11-25 16:11:19 nemo_logger:190] "update_logger_directory" is True. Overwriting tensorboard logger "save_dir" to /fast/project/HFMI_SynergyUnit/tab_model/mihir/logs/tb_logs
o_act_ckpt/0 [default0]:[NeMo W 2025-11-25 16:11:19 nemo_logger:209] The Trainer already contains a ModelCheckpoint callback. This will be overwritten.
o_act_ckpt/0 [default0]:[NeMo W 2025-11-25 16:11:19 nemo_logger:239] The checkpoint callback was told to monitor a validation value and trainer's max_steps was set to 1000. Please ensure that max_steps will run for at least 1 epochs to ensure that checkpointing will not error out.
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:19 megatron_strategy:460] Fixing mis-match between ddp-config & mcore-optimizer config
o_act_ckpt/0 [default0]:You are using a CUDA device ('NVIDIA H100 80GB HBM3') that has Tensor Cores. To properly utilize them, you should set `torch.set_float32_matmul_precision('medium' | 'high')` which will trade-off precision for performance. For more details, read https://pytorch.org/docs/stable/generated/torch.set_float32_matmul_precision.html#torch.set_float32_matmul_precision
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:19 megatron_init:449] Rank 0 has data parallel group : [0]
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:19 megatron_init:455] Rank 0 has combined group of data parallel and context parallel : [0]
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:19 megatron_init:460] All data parallel group ranks with context parallel combined: [[0]]
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:19 megatron_init:463] Ranks 0 has data parallel rank: 0
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:19 megatron_init:471] Rank 0 has context parallel group: [0]
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:19 megatron_init:474] All context parallel group ranks: [[0]]
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:19 megatron_init:475] Ranks 0 has context parallel rank: 0
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:19 megatron_init:482] Rank 0 has model parallel group: [0]
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:19 megatron_init:483] All model parallel group ranks: [[0]]
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:19 megatron_init:492] Rank 0 has tensor model parallel group: [0]
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:19 megatron_init:496] All tensor model parallel group ranks: [[0]]
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:19 megatron_init:497] Rank 0 has tensor model parallel rank: 0
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:19 megatron_init:532] Rank 0 has pipeline model parallel group: [0]
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:19 megatron_init:544] Rank 0 has embedding group: [0]
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:19 megatron_init:550] All pipeline model parallel group ranks: [[0]]
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:19 megatron_init:551] Rank 0 has pipeline model parallel rank 0
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:19 megatron_init:552] All embedding group ranks: [[0]]
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:19 megatron_init:553] Rank 0 has embedding rank: 0
o_act_ckpt/0 [default0]:[Gloo] Rank 0 is connected to 0 peer ranks. Expected number of connected peer ranks is : 0
o_act_ckpt/0 [default0]:[Gloo] Rank 0 is connected to 0 peer ranks. Expected number of connected peer ranks is : 0
o_act_ckpt/0 [default0]:[Gloo] Rank 0 is connected to 0 peer ranks. Expected number of connected peer ranks is : 0
o_act_ckpt/0 [default0]:[W1125 16:11:19.504655507 ProcessGroupNCCL.cpp:981] Warning: TORCH_NCCL_AVOID_RECORD_STREAMS is the default now, this environment variable is thus deprecated. (function operator())
o_act_ckpt/0 [default0]:----------------------------------------------------------------------------------------------------
o_act_ckpt/0 [default0]:distributed_backend=nccl
o_act_ckpt/0 [default0]:All distributed processes registered. Starting with 1 processes
o_act_ckpt/0 [default0]:----------------------------------------------------------------------------------------------------
o_act_ckpt/0 [default0]:
o_act_ckpt/0 [default0]:[Gloo] Rank 0 is connected to 0 peer ranks. Expected number of connected peer ranks is : 0
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:20 model_transform:67] Setting up ModelTransform for stage: fit
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:20 model_transform:70] Found model_transform attribute on pl_module
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:20 model_transform:73] Set model_transform to: <function _call_counter.<locals>.wrapper at 0x7f0c102f7640>
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:20 base:373] Use preset vocab_size: 151936, original vocab_size: 151669, dummy tokens: 267.
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:20 megatron_strategy:472] Copying Trainer's 'max_steps' (1000) to LR scheduler's 'max_steps'.
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:20 num_microbatches_calculator:228] setting number of microbatches to constant 8
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:20 megatron_strategy:1045] Doing selective restore from RestoreConfig(path='/fast/project/HFMI_SynergyUnit/tab_model/data/checkpoints/nemo_converted_weights_qwen3-600m', load_model_state=True, load_optim_state=False, load_artifacts=True)
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:20 pl:411] Loaded sharded_state_dict_metadata from checkpoint: {'distrib_optim_sharding_type': 'fully_sharded_model_space'}
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:20 pl:275] Using <megatron.core.dist_checkpointing.strategies.fully_parallel.FullyParallelLoadStrategyWrapper object at 0x7f0c39f2a290> dist-ckpt load strategy.
o_act_ckpt/0 [default0]:LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]
o_act_ckpt/0 [default0]:[NeMo W 2025-11-25 16:11:20 serialization:184] DEPRECATED: Passing 'checkpoint_dir' as a Path object in load_common_state_dict will no longer be supported in a future release. Please pass it as a string instead.
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:21 pl:297] Global Checkpoint Load : Rank : 0 : Start time : 1764083480.655s : Time spent in load_checkpoint: 1.334s
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:21 megatron_strategy:1050] Restoring model weights from RestoreConfig(path='/fast/project/HFMI_SynergyUnit/tab_model/data/checkpoints/nemo_converted_weights_qwen3-600m', load_model_state=True, load_optim_state=False, load_artifacts=True)
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:21 megatron_strategy:1058] Finished restoring from RestoreConfig(path='/fast/project/HFMI_SynergyUnit/tab_model/data/checkpoints/nemo_converted_weights_qwen3-600m', load_model_state=True, load_optim_state=False, load_artifacts=True), cleaning up.
o_act_ckpt/0 [default0]:
o_act_ckpt/0 [default0]:  | Name   | Type     | Params | Mode 
o_act_ckpt/0 [default0]:--------------------------------------------
o_act_ckpt/0 [default0]:0 | module | GPTModel | 596 M  | train
o_act_ckpt/0 [default0]:--------------------------------------------
o_act_ckpt/0 [default0]:596 M     Trainable params
o_act_ckpt/0 [default0]:0         Non-trainable params
o_act_ckpt/0 [default0]:596 M     Total params
o_act_ckpt/0 [default0]:2,384.200 Total estimated model params size (MB)
o_act_ckpt/0 [default0]:569       Modules in train mode
o_act_ckpt/0 [default0]:0         Modules in eval mode
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.0.self_attention.linear_proj
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.0.self_attention.linear_qkv
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.0.mlp.linear_fc1
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.0.mlp.linear_fc2
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.1.self_attention.linear_proj
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.1.self_attention.linear_qkv
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.1.mlp.linear_fc1
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.1.mlp.linear_fc2
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.2.self_attention.linear_proj
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.2.self_attention.linear_qkv
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.2.mlp.linear_fc1
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.2.mlp.linear_fc2
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.3.self_attention.linear_proj
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.3.self_attention.linear_qkv
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.3.mlp.linear_fc1
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.3.mlp.linear_fc2
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.4.self_attention.linear_proj
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.4.self_attention.linear_qkv
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.4.mlp.linear_fc1
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.4.mlp.linear_fc2
o_act_ckpt/0 [default0]:[NeMo W 2025-11-25 16:11:22 nemo_logging:361] /fast/home/mihir.mahajan/Projects/crowd-pilot/.uv_venv/lib/python3.10/site-packages/lightning/pytorch/trainer/connectors/data_connector.py:424: The 'val_dataloader' does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` to `num_workers=9` in the `DataLoader` to improve performance.
o_act_ckpt/0 [default0]:    
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.5.self_attention.linear_proj
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.5.self_attention.linear_qkv
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.5.mlp.linear_fc1
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.5.mlp.linear_fc2
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.6.self_attention.linear_proj
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.6.self_attention.linear_qkv
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.6.mlp.linear_fc1
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.6.mlp.linear_fc2
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.7.self_attention.linear_proj
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.7.self_attention.linear_qkv
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.7.mlp.linear_fc1
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.7.mlp.linear_fc2
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.8.self_attention.linear_proj
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.8.self_attention.linear_qkv
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.8.mlp.linear_fc1
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.8.mlp.linear_fc2
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.9.self_attention.linear_proj
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.9.self_attention.linear_qkv
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.9.mlp.linear_fc1
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.9.mlp.linear_fc2
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.10.self_attention.linear_proj
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.10.self_attention.linear_qkv
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.10.mlp.linear_fc1
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.10.mlp.linear_fc2
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.11.self_attention.linear_proj
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.11.self_attention.linear_qkv
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.11.mlp.linear_fc1
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.11.mlp.linear_fc2
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.12.self_attention.linear_proj
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.12.self_attention.linear_qkv
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.12.mlp.linear_fc1
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.12.mlp.linear_fc2
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.13.self_attention.linear_proj
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.13.self_attention.linear_qkv
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.13.mlp.linear_fc1
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.13.mlp.linear_fc2
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.14.self_attention.linear_proj
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.14.self_attention.linear_qkv
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.14.mlp.linear_fc1
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.14.mlp.linear_fc2
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.15.self_attention.linear_proj
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.15.self_attention.linear_qkv
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.15.mlp.linear_fc1
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.15.mlp.linear_fc2
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.16.self_attention.linear_proj
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.16.self_attention.linear_qkv
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.16.mlp.linear_fc1
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.16.mlp.linear_fc2
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.17.self_attention.linear_proj
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.17.self_attention.linear_qkv
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.17.mlp.linear_fc1
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.17.mlp.linear_fc2
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.18.self_attention.linear_proj
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.18.self_attention.linear_qkv
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.18.mlp.linear_fc1
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.18.mlp.linear_fc2
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.19.self_attention.linear_proj
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.19.self_attention.linear_qkv
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.19.mlp.linear_fc1
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.19.mlp.linear_fc2
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.20.self_attention.linear_proj
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.20.self_attention.linear_qkv
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.20.mlp.linear_fc1
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.20.mlp.linear_fc2
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.21.self_attention.linear_proj
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.21.self_attention.linear_qkv
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.21.mlp.linear_fc1
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.21.mlp.linear_fc2
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.22.self_attention.linear_proj
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.22.self_attention.linear_qkv
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.22.mlp.linear_fc1
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.22.mlp.linear_fc2
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.23.self_attention.linear_proj
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.23.self_attention.linear_qkv
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.23.mlp.linear_fc1
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.23.mlp.linear_fc2
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.24.self_attention.linear_proj
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.24.self_attention.linear_qkv
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.24.mlp.linear_fc1
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.24.mlp.linear_fc2
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.25.self_attention.linear_proj
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.25.self_attention.linear_qkv
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.25.mlp.linear_fc1
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.25.mlp.linear_fc2
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.26.self_attention.linear_proj
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.26.self_attention.linear_qkv
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.26.mlp.linear_fc1
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.26.mlp.linear_fc2
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.27.self_attention.linear_proj
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.27.self_attention.linear_qkv
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.27.mlp.linear_fc1
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 lora:468] Adding lora to: module.decoder.layers.27.mlp.linear_fc2
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 model_transform:97] After applying model_transform:
o_act_ckpt/0 [default0]:    
o_act_ckpt/0 [default0]:    
o_act_ckpt/0 [default0]:  | Name   | Type     | Params | Mode 
o_act_ckpt/0 [default0]:    
o_act_ckpt/0 [default0]:--------------------------------------------
o_act_ckpt/0 [default0]:    
o_act_ckpt/0 [default0]:0 | module | GPTModel | 613 M  | train
o_act_ckpt/0 [default0]:    
o_act_ckpt/0 [default0]:--------------------------------------------
o_act_ckpt/0 [default0]:    
o_act_ckpt/0 [default0]:17.4 M    Trainable params
o_act_ckpt/0 [default0]:    
o_act_ckpt/0 [default0]:596 M     Non-trainable params
o_act_ckpt/0 [default0]:    
o_act_ckpt/0 [default0]:613 M     Total params
o_act_ckpt/0 [default0]:    
o_act_ckpt/0 [default0]:2,453.930 Total estimated model params size (MB)
o_act_ckpt/0 [default0]:    
o_act_ckpt/0 [default0]:1129      Modules in train mode
o_act_ckpt/0 [default0]:    
o_act_ckpt/0 [default0]:0         Modules in eval mode
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 peft:250] Initializing model parallel
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 megatron_parallel:584]  > number of parameters on (tensor, pipeline) model parallel rank (0 ,0): 613482496
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 megatron_parallel:587]  > number of trainable parameters: 17432576 (2.84% of total)
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 utils:673] Setting up DistributedDataParallel with config DistributedDataParallelConfig(grad_reduce_in_fp32=True, overlap_grad_reduce=False, overlap_param_gather=False, align_param_gather=False, use_distributed_optimizer=True, num_distributed_optimizer_instances=1, check_for_nan_in_grad=True, check_for_large_grads=False, bucket_size=None, pad_buckets_for_high_nccl_busbw=False, average_in_collective=False, fp8_param_gather=False, reuse_grad_buf_for_mxfp8_param_ag=False, use_megatron_fsdp=False, use_custom_fsdp=False, data_parallel_sharding_strategy='no_shard', gradient_reduce_div_fusion=True, suggested_communication_unit_size=None, preserve_fp32_weights=True, keep_fp8_transpose_cache=False, nccl_ub=False, fsdp_double_buffer=False, outer_dp_sharding_strategy='no_shard', disable_symmetric_registration=False, delay_wgrad_compute=False)
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 utils:694] Number of buckets for gradient all-reduce / reduce-scatter: 1
o_act_ckpt/0 [default0]:    Params for bucket 1 (17432576 elements, 17432576 padded size):
o_act_ckpt/0 [default0]:    	module.decoder.layers.26.mlp.linear_fc1.adapter.linear_out.weight
o_act_ckpt/0 [default0]:    	module.decoder.layers.22.mlp.linear_fc2.adapter.linear_in.weight
o_act_ckpt/0 [default0]:    	module.decoder.layers.14.mlp.linear_fc2.adapter.linear_in.weight
o_act_ckpt/0 [default0]:    	module.decoder.layers.12.mlp.linear_fc1.adapter.linear_in.weight
o_act_ckpt/0 [default0]:    	module.decoder.layers.9.self_attention.linear_qkv.adapter.linear_out.weight
o_act_ckpt/0 [default0]:    	module.decoder.layers.6.self_attention.linear_proj.adapter.linear_out.weight
o_act_ckpt/0 [default0]:    	module.decoder.layers.2.self_attention.linear_qkv.adapter.linear_in.weight
o_act_ckpt/0 [default0]:    	module.decoder.layers.20.self_attention.linear_qkv.adapter.linear_in.weight
o_act_ckpt/0 [default0]:    	module.decoder.layers.22.self_attention.linear_proj.adapter.linear_in.weight
o_act_ckpt/0 [default0]:    	module.decoder.layers.18.mlp.linear_fc1.adapter.linear_out.weight
o_act_ckpt/0 [default0]:    	module.decoder.layers.13.self_attention.linear_qkv.adapter.linear_in.weight
o_act_ckpt/0 [default0]:    	module.decoder.layers.8.self_attention.linear_qkv.adapter.linear_out.weight
o_act_ckpt/0 [default0]:    	module.decoder.layers.26.self_attention.linear_qkv.adapter.linear_out.weight
o_act_ckpt/0 [default0]:    	module.decoder.layers.24.self_attention.linear_proj.adapter.linear_out.weight
o_act_ckpt/0 [default0]:    	module.decoder.layers.20.mlp.linear_fc2.adapter.linear_out.weight
o_act_ckpt/0 [default0]:    	module.decoder.layers.16.self_attention.linear_proj.adapter.linear_out.weight
o_act_ckpt/0 [default0]:    	module.decoder.layers.14.self_attention.linear_qkv.adapter.linear_out.weight
o_act_ckpt/0 [default0]:    	module.decoder.layers.13.mlp.linear_fc2.adapter.linear_out.weight
o_act_ckpt/0 [default0]:    	module.decoder.layers.12.self_attention.linear_qkv.adapter.linear_in.weight
o_act_ckpt/0 [default0]:    	module.decoder.layers.10.mlp.linear_fc1.adapter.linear_out.weight
o_act_ckpt/0 [default0]:    	module.decoder.layers.5.mlp.linear_fc2.adapter.linear_in.weight
o_act_ckpt/0 [default0]:    	module.decoder.layers.21.mlp.linear_fc1.adapter.linear_in.weight
o_act_ckpt/0 [default0]:    	module.decoder.layers.18.self_attention.linear_qkv.adapter.linear_out.weight
o_act_ckpt/0 [default0]:    	module.decoder.layers.5.self_attention.linear_proj.adapter.linear_in.weight
o_act_ckpt/0 [default0]:    	module.decoder.layers.2.mlp.linear_fc1.adapter.linear_out.weight
o_act_ckpt/0 [default0]:    	module.decoder.layers.27.mlp.linear_fc1.adapter.linear_out.weight
o_act_ckpt/0 [default0]:    	module.decoder.layers.23.mlp.linear_fc2.adapter.linear_in.weight
o_act_ckpt/0 [default0]:    	module.decoder.layers.15.mlp.linear_fc2.adapter.linear_in.weight
o_act_ckpt/0 [default0]:    	module.decoder.layers.10.self_attention.linear_qkv.adapter.linear_out.weight
o_act_ckpt/0 [default0]:    	module.decoder.layers.7.self_attention.linear_proj.adapter.linear_out.weight
o_act_ckpt/0 [default0]:    	module.decoder.layers.4.self_attention.linear_proj.adapter.linear_in.weight
o_act_ckpt/0 [default0]:    	module.decoder.layers.1.mlp.linear_fc1.adapter.linear_out.weight
o_act_ckpt/0 [default0]:    	module.decoder.layers.23.self_attention.linear_proj.adapter.linear_in.weight
o_act_ckpt/0 [default0]:    	module.decoder.layers.21.self_attention.linear_qkv.adapter.linear_in.weight
o_act_ckpt/0 [default0]:    	module.decoder.layers.19.mlp.linear_fc1.adapter.linear_out.weight
o_act_ckpt/0 [default0]:    	module.decoder.layers.15.self_attention.linear_proj.adapter.linear_in.weight
o_act_ckpt/0 [default0]:    	module.decoder.layers.12.mlp.linear_fc2.adapter.linear_in.weight
o_act_ckpt/0 [default0]:    	module.decoder.layers.4.mlp.linear_fc1.adapter.linear_in.weight
o_act_ckpt/0 [default0]:    	module.decoder.layers.27.self_attention.linear_qkv.adapter.linear_out.weight
o_act_ckpt/0 [default0]:    	module.decoder.layers.21.mlp.linear_fc2.adapter.linear_out.weight
o_act_ckpt/0 [default0]:    	module.decoder.layers.17.self_attention.linear_proj.adapter.linear_out.weight
o_act_ckpt/0 [default0]:    	module.decoder.layers.11.mlp.linear_fc1.adapter.linear_out.weight
o_act_ckpt/0 [default0]:    	module.decoder.layers.6.mlp.linear_fc2.adapter.linear_in.weight
o_act_ckpt/0 [default0]:    	module.decoder.layers.1.self_attention.linear_qkv.adapter.linear_out.weight
o_act_ckpt/0 [default0]:    	module.decoder.layers.24.mlp.linear_fc2.adapter.linear_in.weight
o_act_ckpt/0 [default0]:    	module.decoder.layers.22.mlp.linear_fc1.adapter.linear_in.weight
o_act_ckpt/0 [default0]:    	module.decoder.layers.19.self_attention.linear_qkv.adapter.linear_out.weight
o_act_ckpt/0 [default0]:    	module.decoder.layers.14.mlp.linear_fc1.adapter.linear_in.weight
o_act_ckpt/0 [default0]:    	module.decoder.layers.6.self_attention.linear_proj.adapter.linear_in.weight
o_act_ckpt/0 [default0]:    	module.decoder.layers.4.self_attention.linear_qkv.adapter.linear_in.weight
o_act_ckpt/0 [default0]:    	module.decoder.layers.3.mlp.linear_fc1.adapter.linear_out.weight
o_act_ckpt/0 [default0]:    	module.decoder.layers.16.mlp.linear_fc2.adapter.linear_in.weight
o_act_ckpt/0 [default0]:    	module.decoder.layers.11.self_attention.linear_qkv.adapter.linear_out.weight
o_act_ckpt/0 [default0]:    	module.decoder.layers.8.self_attention.linear_proj.adapter.linear_out.weight
o_act_ckpt/0 [default0]:    	module.decoder.layers.4.mlp.linear_fc2.adapter.linear_out.weight
o_act_ckpt/0 [default0]:    	module.decoder.layers.26.self_attention.linear_proj.adapter.linear_out.weight
o_act_ckpt/0 [default0]:    	module.decoder.layers.24.self_attention.linear_proj.adapter.linear_in.weight
o_act_ckpt/0 [default0]:    	module.decoder.layers.22.self_attention.linear_qkv.adapter.linear_in.weight
o_act_ckpt/0 [default0]:    	module.decoder.layers.20.mlp.linear_fc1.adapter.linear_out.weight
o_act_ckpt/0 [default0]:    	module.decoder.layers.16.self_attention.linear_proj.adapter.linear_in.weight
o_act_ckpt/0 [default0]:    	module.decoder.layers.14.self_attention.linear_qkv.adapter.linear_in.weight
o_act_ckpt/0 [default0]:    	module.decoder.layers.13.mlp.linear_fc1.adapter.linear_out.weight
o_act_ckpt/0 [default0]:    	module.decoder.layers.8.mlp.linear_fc2.adapter.linear_in.weight
o_act_ckpt/0 [default0]:    	module.decoder.layers.5.mlp.linear_fc1.adapter.linear_in.weight
o_act_ckpt/0 [default0]:    	module.decoder.layers.3.self_attention.linear_qkv.adapter.linear_out.weight
o_act_ckpt/0 [default0]:    	module.decoder.layers.22.mlp.linear_fc2.adapter.linear_out.weight
o_act_ckpt/0 [default0]:    	module.decoder.layers.18.self_attention.linear_proj.adapter.linear_out.weight
o_act_ckpt/0 [default0]:    	module.decoder.layers.14.mlp.linear_fc2.adapter.linear_out.weight
o_act_ckpt/0 [default0]:    	module.decoder.layers.12.mlp.linear_fc1.adapter.linear_out.weight
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o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 peft:254] Setting up optimizers
o_act_ckpt/0 [default0]:[NeMo I 2025-11-25 16:11:22 utils:673] Setting up optimizer with config OptimizerConfig(optimizer='adam', lr=0.0001, min_lr=None, decoupled_lr=None, decoupled_min_lr=None, weight_decay=0.1, fp8_recipe='delayed', fp16=False, bf16=True, reuse_grad_buf_for_mxfp8_param_ag=False, params_dtype=torch.bfloat16, use_precision_aware_optimizer=False, store_param_remainders=True, main_grads_dtype=torch.float32, main_params_dtype=torch.float32, exp_avg_dtype=torch.float32, exp_avg_sq_dtype=torch.float32, loss_scale=None, initial_loss_scale=4294967296, min_loss_scale=1.0, loss_scale_window=1000, hysteresis=2, adam_beta1=0.9, adam_beta2=0.98, adam_eps=1e-05, sgd_momentum=0.9, use_distributed_optimizer=True, overlap_param_gather=False, overlap_param_gather_with_optimizer_step=False, use_megatron_fsdp=False, optimizer_cpu_offload=False, optimizer_offload_fraction=0.0, use_torch_optimizer_for_cpu_offload=False, overlap_cpu_optimizer_d2h_h2d=False, pin_cpu_grads=True, pin_cpu_params=True, clip_grad=1.0, log_num_zeros_in_grad=False, barrier_with_L1_time=False, timers=None, config_logger_dir='')
o_act_ckpt/0 [default0]:[NeMo W 2025-11-25 16:11:29 nemo_logging:361] /fast/home/mihir.mahajan/Projects/crowd-pilot/.uv_venv/lib/python3.10/site-packages/lightning/pytorch/trainer/connectors/logger_connector/result.py:431: It is recommended to use `self.log('global_batch_size', ..., sync_dist=True)` when logging on epoch level in distributed setting to accumulate the metric across devices.
o_act_ckpt/0 [default0]:    
o_act_ckpt/0 [default0]:[NeMo W 2025-11-25 16:11:29 nemo_logging:361] /fast/home/mihir.mahajan/Projects/crowd-pilot/.uv_venv/lib/python3.10/site-packages/lightning/pytorch/trainer/connectors/logger_connector/result.py:431: It is recommended to use `self.log('val_loss', ..., sync_dist=True)` when logging on epoch level in distributed setting to accumulate the metric across devices.
o_act_ckpt/0 [default0]:    
o_act_ckpt/0 [default0]:[NeMo W 2025-11-25 16:11:29 nemo_logging:361] /fast/home/mihir.mahajan/Projects/crowd-pilot/.uv_venv/lib/python3.10/site-packages/lightning/pytorch/trainer/connectors/data_connector.py:424: The 'train_dataloader' does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` to `num_workers=9` in the `DataLoader` to improve performance.
o_act_ckpt/0 [default0]:    
o_act_ckpt/0 [default0]:[NeMo W 2025-11-25 16:11:47 rerun_state_machine:1300] Implicit initialization of Rerun State Machine!
o_act_ckpt/0 [default0]:[NeMo W 2025-11-25 16:11:47 rerun_state_machine:238] RerunStateMachine initialized in mode disabled
o_act_ckpt/0 [default0]:Training epoch 0, iteration 0/999 | lr: 1.961e-06 | global_batch_size: 32 | global_step: 0 | reduced_train_loss: 1.102 | train_step_timing in s: 17.34
o_act_ckpt/0 [default0]:Training epoch 0, iteration 1/999 | lr: 3.922e-06 | global_batch_size: 32 | global_step: 1 | reduced_train_loss: 1.087 | train_step_timing in s: 4.244 | consumed_samples: 64
o_act_ckpt/0 [default0]:Training epoch 0, iteration 2/999 | lr: 5.882e-06 | global_batch_size: 32 | global_step: 2 | reduced_train_loss: 1.026 | train_step_timing in s: 4.013 | consumed_samples: 96
o_act_ckpt/0 [default0]:Training epoch 0, iteration 3/999 | lr: 7.843e-06 | global_batch_size: 32 | global_step: 3 | reduced_train_loss: 1.266 | train_step_timing in s: 3.894 | consumed_samples: 128
o_act_ckpt/0 [default0]:Training epoch 0, iteration 4/999 | lr: 9.804e-06 | global_batch_size: 32 | global_step: 4 | reduced_train_loss: 1.182 | train_step_timing in s: 3.951 | consumed_samples: 160
o_act_ckpt/0 [default0]:Training epoch 0, iteration 5/999 | lr: 1.176e-05 | global_batch_size: 32 | global_step: 5 | reduced_train_loss: 0.9192 | train_step_timing in s: 5.901 | consumed_samples: 192
o_act_ckpt/0 [default0]:Training epoch 0, iteration 6/999 | lr: 1.373e-05 | global_batch_size: 32 | global_step: 6 | reduced_train_loss: 0.8988 | train_step_timing in s: 5.441 | consumed_samples: 224
o_act_ckpt/0 [default0]:Training epoch 0, iteration 7/999 | lr: 1.569e-05 | global_batch_size: 32 | global_step: 7 | reduced_train_loss: 1.042 | train_step_timing in s: 5.421 | consumed_samples: 256
o_act_ckpt/0 [default0]:Training epoch 0, iteration 8/999 | lr: 1.765e-05 | global_batch_size: 32 | global_step: 8 | reduced_train_loss: 0.9566 | train_step_timing in s: 5.616 | consumed_samples: 288
o_act_ckpt/0 [default0]:Training epoch 0, iteration 9/999 | lr: 1.961e-05 | global_batch_size: 32 | global_step: 9 | reduced_train_loss: 0.8992 | train_step_timing in s: 5.258 | consumed_samples: 320
o_act_ckpt/0 [default0]:Training epoch 0, iteration 10/999 | lr: 2.157e-05 | global_batch_size: 32 | global_step: 10 | reduced_train_loss: 0.904 | train_step_timing in s: 4.551 | consumed_samples: 352
o_act_ckpt/0 [default0]:Training epoch 0, iteration 11/999 | lr: 2.353e-05 | global_batch_size: 32 | global_step: 11 | reduced_train_loss: 0.725 | train_step_timing in s: 4.067 | consumed_samples: 384
o_act_ckpt/0 [default0]:Training epoch 0, iteration 12/999 | lr: 2.549e-05 | global_batch_size: 32 | global_step: 12 | reduced_train_loss: 0.6793 | train_step_timing in s: 4.005 | consumed_samples: 416
o_act_ckpt/0 [default0]:Training epoch 0, iteration 13/999 | lr: 2.745e-05 | global_batch_size: 32 | global_step: 13 | reduced_train_loss: 0.7737 | train_step_timing in s: 3.97 | consumed_samples: 448
o_act_ckpt/0 [default0]:Training epoch 0, iteration 14/999 | lr: 2.941e-05 | global_batch_size: 32 | global_step: 14 | reduced_train_loss: 0.7973 | train_step_timing in s: 4.049 | consumed_samples: 480
o_act_ckpt/0 [default0]:Training epoch 0, iteration 15/999 | lr: 3.137e-05 | global_batch_size: 32 | global_step: 15 | reduced_train_loss: 0.7062 | train_step_timing in s: 3.992 | consumed_samples: 512
o_act_ckpt/0 [default0]:Training epoch 0, iteration 16/999 | lr: 3.333e-05 | global_batch_size: 32 | global_step: 16 | reduced_train_loss: 0.7138 | train_step_timing in s: 4.0 | consumed_samples: 544
o_act_ckpt/0 [default0]:Training epoch 0, iteration 17/999 | lr: 3.529e-05 | global_batch_size: 32 | global_step: 17 | reduced_train_loss: 0.6756 | train_step_timing in s: 4.113 | consumed_samples: 576
o_act_ckpt/0 [default0]:Training epoch 0, iteration 18/999 | lr: 3.725e-05 | global_batch_size: 32 | global_step: 18 | reduced_train_loss: 0.6332 | train_step_timing in s: 3.954 | consumed_samples: 608
o_act_ckpt/0 [default0]:Training epoch 0, iteration 19/999 | lr: 3.922e-05 | global_batch_size: 32 | global_step: 19 | reduced_train_loss: 0.586 | train_step_timing in s: 4.047 | consumed_samples: 640
o_act_ckpt/0 [default0]:Training epoch 0, iteration 20/999 | lr: 4.118e-05 | global_batch_size: 32 | global_step: 20 | reduced_train_loss: 0.8439 | train_step_timing in s: 3.96 | consumed_samples: 672
o_act_ckpt/0 [default0]:Training epoch 0, iteration 21/999 | lr: 4.314e-05 | global_batch_size: 32 | global_step: 21 | reduced_train_loss: 0.5813 | train_step_timing in s: 4.025 | consumed_samples: 704
o_act_ckpt/0 [default0]:Training epoch 0, iteration 22/999 | lr: 4.51e-05 | global_batch_size: 32 | global_step: 22 | reduced_train_loss: 0.6473 | train_step_timing in s: 4.023 | consumed_samples: 736
o_act_ckpt/0 [default0]:Training epoch 0, iteration 23/999 | lr: 4.706e-05 | global_batch_size: 32 | global_step: 23 | reduced_train_loss: 0.6277 | train_step_timing in s: 4.028 | consumed_samples: 768
o_act_ckpt/0 [default0]:Training epoch 0, iteration 24/999 | lr: 4.902e-05 | global_batch_size: 32 | global_step: 24 | reduced_train_loss: 0.7789 | train_step_timing in s: 3.999 | consumed_samples: 800
o_act_ckpt/0 [default0]:Training epoch 0, iteration 25/999 | lr: 5.098e-05 | global_batch_size: 32 | global_step: 25 | reduced_train_loss: 0.5815 | train_step_timing in s: 3.99 | consumed_samples: 832
o_act_ckpt/0 [default0]:Training epoch 0, iteration 26/999 | lr: 5.294e-05 | global_batch_size: 32 | global_step: 26 | reduced_train_loss: 0.6122 | train_step_timing in s: 4.028 | consumed_samples: 864[default0]:
o_act_ckpt/0 [default0]:Training epoch 0, iteration 27/999 | lr: 5.49e-05 | global_batch_size: 32 | global_step: 27 | reduced_train_loss: 0.4993 | train_step_timing in s: 4.061 | consumed_samples: 896
o_act_ckpt/0 [default0]:Training epoch 0, iteration 28/999 | lr: 5.686e-05 | global_batch_size: 32 | global_step: 28 | reduced_train_loss: 0.5572 | train_step_timing in s: 4.349 | consumed_samples: 928
o_act_ckpt/0 [default0]:Training epoch 0, iteration 29/999 | lr: 5.882e-05 | global_batch_size: 32 | global_step: 29 | reduced_train_loss: 0.5877 | train_step_timing in s: 4.013 | consumed_samples: 960
o_act_ckpt/0 [default0]:Validation: iteration 1/0