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#     http://www.apache.org/licenses/LICENSE-2.0
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  # Configuration for fine-tuning Gemma 3n VL 4B with MedPix dataset for image description

step_scheduler:
  global_batch_size: 8
  local_batch_size: 1
  ckpt_every_steps: 100
  val_every_steps: 1000  # will run every x number of gradient steps
  max_steps: 1000

dist_env:
  backend: nccl
  timeout_minutes: 10

rng:
  _target_: nemo_automodel.components.training.rng.StatefulRNG
  seed: 42
  ranked: true

model:
  _target_: nemo_automodel.NeMoAutoModelForImageTextToText.from_pretrained
  pretrained_model_name_or_path: google/gemma-3n-e4b-it #HF model id or local path
  torch_dtype: torch.bfloat16
  use_liger_kernel: false
  use_sdpa_patching: false # gemma-3n-e4b-it does not work with sdpa patching
  attn_implementation: eager
  text_config:
    use_cache: true

checkpoint:
  enabled: true
  checkpoint_dir: vlm_checkpoints/
  model_save_format: torch_save
  save_consolidated: False

distributed:
  _target_: nemo_automodel.components.distributed.fsdp2.FSDP2Manager
  dp_size: none
  tp_size: 1
  cp_size: 1
  sequence_parallel: false

loss_fn:
  _target_: nemo_automodel.components.loss.masked_ce.MaskedCrossEntropy

dataset:
  _target_: nemo_automodel.components.datasets.vlm.datasets.make_medpix_dataset
  path_or_dataset: mmoukouba/MedPix-VQA
  split: train[:1000]

dataloader:
  _target_: torchdata.stateful_dataloader.StatefulDataLoader
  num_workers: 0
  pin_memory: true
  collate_fn:
    _target_: nemo_automodel.components.datasets.vlm.collate_fns.default_collate_fn

validation_dataset:
  _target_: nemo_automodel.components.datasets.vlm.datasets.make_medpix_dataset
  path_or_dataset: mmoukouba/MedPix-VQA
  split: validation[:500]

validation_dataloader:
  _target_: torchdata.stateful_dataloader.StatefulDataLoader
  
optimizer:
  _target_: torch.optim.AdamW
  lr: 1e-5
  weight_decay: 0.01
  betas: [0.9, 0.95]

freeze_config:
  freeze_embeddings: true
  freeze_vision_tower: true
  freeze_audio_tower: true
  freeze_language_model: false

# Uncomment and configure for W&B logging
# logger:
#   wandb_project:
#   wandb_entity: 
#   wandb_exp_name:
#   wandb_save_dir:
