| # Optional: run train_sft_qwen3.py under `accelerate launch` instead of `torchrun`. | |
| # The script builds its own FSDP wrapper, so accelerate is used ONLY as a launcher here | |
| # (it sets RANK/LOCAL_RANK/WORLD_SIZE). These fsdp_config values document the exact | |
| # equivalent settings for anyone who prefers accelerate's Accelerator.prepare(). | |
| # | |
| # accelerate launch --config_file accelerate_fsdp_qwen3.yaml train_sft_qwen3.py ... | |
| # | |
| # If you DO switch to Accelerator.prepare(), you must keep: | |
| # * mixed_precision bf16 with fp32 master weights and fp32 gradient reduction | |
| # * FULL_SHARD + transformer-layer wrapping of Qwen3DecoderLayer | |
| # * use_orig_params: true (the weight-decay parameter groups depend on it) | |
| # * accelerator.clip_grad_norm_ AFTER all accumulation micro-steps | |
| # * your own loss normalisation; accelerate's default 1/gradient_accumulation_steps | |
| # is NOT the recipe's per-microbatch token-weighted mean. | |
| compute_environment: LOCAL_MACHINE | |
| distributed_type: FSDP | |
| downcast_bf16: 'no' | |
| machine_rank: 0 | |
| main_training_function: main | |
| mixed_precision: bf16 | |
| num_machines: 1 | |
| num_processes: 8 | |
| rdzv_backend: static | |
| same_network: true | |
| use_cpu: false | |
| enable_cpu_affinity: true | |
| fsdp_config: | |
| fsdp_version: 1 | |
| fsdp_sharding_strategy: FULL_SHARD | |
| fsdp_auto_wrap_policy: TRANSFORMER_BASED_WRAP | |
| fsdp_transformer_layer_cls_to_wrap: Qwen3DecoderLayer | |
| fsdp_backward_prefetch: BACKWARD_PRE | |
| fsdp_forward_prefetch: false | |
| fsdp_use_orig_params: true | |
| fsdp_cpu_ram_efficient_loading: true | |
| fsdp_sync_module_states: true | |
| fsdp_offload_params: false | |
| fsdp_state_dict_type: SHARDED_STATE_DICT | |
| fsdp_activation_checkpointing: false # the script calls gradient_checkpointing_enable itself | |
| fsdp_reshard_after_forward: true | |
| fsdp_limit_all_gathers: true | |