apiche

Apiche's group workspace

Group: fix_metrics

1-3

of 3

Tags

Notes

Author

apiche

State

Crashed

Start time

July 19th, 2025 9:25:38 PM

Runtime

18m 53s

Tracked hours

6m 38s

Run path

apiche/pipeline-rl/fix_metrics_finetune

Linux-5.15.0-1067-nvidia-x86_64-with-glibc2.39

Python version

CPython 3.11.11

Git repository

git clone git@github.com:ServiceNow/pipelinerl.git

Git state

git checkout -b "fix_metrics/finetune" 0d1db7f606744d8a4387cab3dbcdaeeceab613ac

Command

pipelinerl/entrypoints/run_finetune.py --config-dir results/fix_metrics/conf --config-name exp_config output_dir=results/fix_metrics hydra.run.dir=results/fix_metrics/finetune +me.weight_update_group_init_method=tcp://localhost:9000 +me.weight_update_group_world_size=3 +me.llm_urls=http://localhost:8080+http://localhost:8081

System Hardware

CPU count	112
Logical CPU count	224
GPU count	4
GPU type	NVIDIA H100 80GB HBM3

W&B CLI Version

0.19.11

Group

fix_metrics

Config parameters are your model's inputs. Learn more

▶
Config parameters:{} 178 keys
- _cpu:
  "False"
- _mixed_precision:
  "no"
- accelerate_config:
  null
- actor.discount_factor:
  1
- actor.llm_max_rollouts:
  64
- actor.log_each_n_secs:
  0
- actor.problem_queue_size:
  64
- actor.result_queue_size:
  64
- actor.rollout_policy:
  "pipelinerl.domains.math.generate_math_rollout"
- actor.rollout_workers:
  1
- actor.shared_memory_entry_size:
  10,000,000
- actor.system_prompt:
  "Please reason step by step, and put your final answer within \boxed{}."
- actor.task_template:
  "{task}"
- actor.throughput_window_size:
  50
- attempts:
  8
- backend:
  "nccl"
- dataset_loader:
  "pipelinerl.domains.math.load_datasets"
- debug:
  "False"
- debug.mode:
  ""
- debug.place_inference_workers:
  true
- debug.streams_from:
  null
- debug.use_existing_llms:
  false
- deepspeed_config:
  "deepspeed_stage3_bf16"
- deepspeed_plugins:
  "DeepSpeedPlugin(hf_ds_config=<accelerate.utils.deepspeed.HfDeepSpeedConfig object at 0x7ffc785963d0>, gradient_accumulation_steps=1, gradient_clipping='auto', zero_stage=3, is_train_batch_min=True, offload_optimizer_device='none', offload_param_device='none', offload_optimizer_nvme_path='none', offload_param_nvme_path='none', zero3_init_flag=True, zero3_save_16bit_model=True, transformer_moe_cls_names=None, enable_msamp=False, msamp_opt_level='O1')"
- device:
  "cuda:0"
- distributed_type:
  "DistributedType.DEEPSPEED"
- dynamo_plugin:
  "TorchDynamoPlugin(backend=<DynamoBackend.NO: 'NO'>, mode='default', fullgraph=False, dynamic=False, options=None, disable=False)"
- environment._target_:
  "pipelinerl.domains.math.MathEnvironment"
- eval_every_n_versions:
  78,000
- finetune.also_save_steps:[] 0 items
- finetune.attn_implementation:
  "flash_attention_2"
- finetune.auto_device_map:
  false
- finetune.config_name:
  "Qwen/Qwen2.5-1.5B-Instruct"
- finetune.cuda_empty_cache:
  true
- finetune.data:
  null
- finetune.eval_callback._target_:
  "tapeagents.finetune.eval.dummy_eval_callback"
- finetune.eval_callback.config_name:
  ""
- finetune.force_restart:
  false
- finetune.gradient_accumulation_passes:
  256
- finetune.gradient_checkpointing:
  true
- finetune.gradient_clipping_threshold:
  0.3
- finetune.input:
  "training_data"
- finetune.interrupt_train_steps:
  -1
- finetune.keep_intermediate_checkpoints:
  true
- finetune.learning_rate:
  0.000001
- finetune.load_as_bf16:
  true
- world.environment_start_port:
  7,777
- world.finetune_fraction:
  4
- world.preprocessor_fraction:
  0
- world.replicas:
  1

Summary metrics are your model's outputs. Learn more

Summary metrics:{} 0 keys

This run produced these artifacts as outputs. Total: 1. Learn more

wandb-history

run-fix_metrics_finetune-history:v0