### model
model_name_or_path: meta-llama/Llama-3.2-1B-Instruct

### method
stage: sft
do_train: true
finetuning_type: lora  # full or lora
dataset: alpaca_en_demo
template: llama3
cutoff_len: 2048
preprocessing_num_workers: 8
# disable_shuffling: true  # keep sample order aligned with HF baseline

### output
output_dir: saves/mbridge/llama3_sft
logging_steps: 1
overwrite_output_dir: true

### train
per_device_train_batch_size: 1
gradient_accumulation_steps: 1
num_train_epochs: 3
max_steps: 1000  # when set, overrides num_train_epochs for Megatron Bridge schedule
save_steps: 3000
learning_rate: 5.0e-6
lr_scheduler_type: cosine
warmup_steps: 10
adam_beta1: 0.9
adam_beta2: 0.999
weight_decay: 0.0
max_grad_norm: 1.0
bf16: true

### megatron bridge parallelism
tensor_model_parallel_size: 1
pipeline_model_parallel_size: 1
context_parallel_size: 1
expert_model_parallel_size: 1
# virtual_pipeline_model_parallel_size: 2
sequence_parallel: false

### megatron bridge optimizer / overlap
use_distributed_optimizer: true
overlap_param_gather: true
overlap_grad_reduce: true
mixed_precision: bf16_mixed

### megatron bridge activation recompute (optional)
# recompute_granularity: full
# recompute_method: uniform
# recompute_num_layers: 1

### megatron bridge model kernels (optional; None keeps provider defaults)
# bias_activation_fusion: true
# apply_rope_fusion: true
# masked_softmax_fusion: true
# cross_entropy_loss_fusion: true

### megatron bridge MoE (optional)
# moe_grouped_gemm: true
# moe_token_dispatcher_type: alltoall

### megatron bridge data / checkpoint
use_packed_sequences: false
# megatron_pretrained_checkpoint: /path/to/megatron_ckpt
export_hf_on_finish: false  # disable for short loss-comparison runs (avoids checkpoint OOM)
# extra_config: '{"train.train_iters": 5, "logger.log_interval": 1}'