Distributed Muon Optimizer (#3264)
* init * working * updating configs * removing unneeded files * lint * comments * lint * fix regex match * bump contribs version * comments * fixing tests and imports * muon imports in test v2 * test cleanup * bump contribs version --------- Co-authored-by: Salman Mohammadi <“salman.mohammadi@outlook.com”>
This commit is contained in:
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examples/qwen2/adamw-pretrain-fsdp2.yaml
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examples/qwen2/adamw-pretrain-fsdp2.yaml
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base_model: Qwen/Qwen2.5-0.5B
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model_type: AutoModelForCausalLM
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tokenizer_type: AutoTokenizer
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# Use random initialization for fair comparison
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reinit_weights: true
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load_in_8bit: false
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load_in_4bit: false
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strict: false
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# Pretraining dataset
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pretraining_dataset:
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- path: allenai/c4
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name: en
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type: pretrain
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split: train
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dataset_prepared_path:
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val_set_size: 0.0
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output_dir: ./outputs/compare-adamw-pretrain
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sequence_len: 2048
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sample_packing: true
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pad_to_sequence_len: true
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wandb_project: dist_muon
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wandb_entity:
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wandb_watch:
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wandb_name: adamw
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wandb_log_model:
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gradient_accumulation_steps: 1
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micro_batch_size: 4
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num_epochs: 1
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max_steps: 305
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# AdamW optimizer settings (standard LR for AdamW)
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optimizer: adamw_torch_fused
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learning_rate: 0.0002
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weight_decay: 0.01
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lr_scheduler: cosine
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train_on_inputs: true
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group_by_length: false
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bf16: auto
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fp16: false
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tf32: false
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gradient_checkpointing: false
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logging_steps: 1
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flash_attention: true
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warmup_steps: 10
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evals_per_epoch: 0
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saves_per_epoch: 1
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# Reproducibility
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seed: 42
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fsdp_config:
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fsdp_version: 2
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fsdp_offload_params: false
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fsdp_state_dict_type: FULL_STATE_DICT
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fsdp_transformer_layer_cls_to_wrap: Qwen2DecoderLayer
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fsdp_auto_wrap_policy: TRANSFORMER_BASED_WRAP
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fsdp_cpu_ram_efficient_loading: false
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fsdp_reshard_after_forward: true
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special_tokens:
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70
examples/qwen2/muon-pretrain-fsdp2.yaml
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70
examples/qwen2/muon-pretrain-fsdp2.yaml
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base_model: Qwen/Qwen2.5-0.5B
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model_type: AutoModelForCausalLM
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tokenizer_type: AutoTokenizer
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# Use random initialization for fair comparison
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reinit_weights: true
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load_in_8bit: false
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load_in_4bit: false
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strict: false
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# Pretraining dataset
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pretraining_dataset:
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- path: allenai/c4
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name: en
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type: pretrain
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split: train
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dataset_prepared_path:
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val_set_size: 0.0
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output_dir: ./outputs/compare-muon-pretrain
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sequence_len: 2048
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sample_packing: true
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pad_to_sequence_len: true
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wandb_project: dist_muon
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wandb_entity:
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wandb_watch:
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wandb_name: muon
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wandb_log_model:
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gradient_accumulation_steps: 1
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micro_batch_size: 4
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num_epochs: 1
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max_steps: 305
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# Muon optimizer settings
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optimizer: muon
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learning_rate: 0.02
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weight_decay: 0.01
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lr_scheduler: cosine
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train_on_inputs: true
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group_by_length: false
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bf16: auto
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fp16: false
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tf32: false
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gradient_checkpointing: false
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logging_steps: 1
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flash_attention: true
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warmup_steps: 10
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evals_per_epoch: 0
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saves_per_epoch: 1
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# Reproducibility
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seed: 42
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fsdp_config:
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fsdp_version: 2
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fsdp_offload_params: false
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fsdp_state_dict_type: FULL_STATE_DICT
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fsdp_transformer_layer_cls_to_wrap: Qwen2DecoderLayer
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fsdp_auto_wrap_policy: TRANSFORMER_BASED_WRAP
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fsdp_cpu_ram_efficient_loading: false
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fsdp_reshard_after_forward: true
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special_tokens:
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