training_config.yml

model:
  _component_: models.lora_mmllama3_8b
  lora_attn_modules:
  - q_proj
  - v_proj
  apply_lora_to_mlp: false
  apply_lora_to_output: false
  lora_rank: 16
  lora_alpha: 32
  perception_tokens: 2
  use_clip: false
tokenizer:
  _component_: models.a2a_tokenizer
  path: models/tokenizer.model
freeze_layers:
  _component_: torchtune.utils.Freeze_Layers
  num_layers: 8
checkpointer:
  _component_: torchtune.utils.FullModelMetaCheckpointer
  checkpoint_dir: tiresome5/
  checkpoint_files:
  - meta_model_0.pt
  adapter_checkpoint: null
  recipe_checkpoint: null
  output_dir: output_checkpoints/experiment_1
  model_type: LLAMA3
use_freeze_layers: true
resume_from_checkpoint: false
interim_checkpoint_steps: 20000
interim_gen_steps: null
max_new_tokens: 100
temperature: 0.6
top_k: 225
dataset:
  _component_: ds.EvenBatcher
  buffer_size: 1000
  dataset:
    _component_: ds.RoundRobinDataset
    datasets:
    - _component_: ds.CaptionInstructDataset
      dataset_path: ds/sam_llava/output.parquet
      train_on_input: false
seed: null
shuffle: true
batch_size: 4
optimizer:
  _component_: torch.optim.AdamW
  weight_decay: 0.0001
  lr: 0.0001
  betas:
  - 0.9
  - 0.998
lr_scheduler:
  _component_: torchtune.modules.get_cosine_schedule_with_warmup
  num_warmup_steps: 500
loss:
  _component_: torch.nn.CrossEntropyLoss
grad_clip:
  _component_: torch.nn.utils.clip_grad_norm
  max_norm: 2.0
  norm_type: 2
epochs: 6
max_steps_per_epoch: null
gradient_accumulation_steps: 32
compile: true
output_dir: /tmp/lora_finetune_output
metric_logger:
  _component_: torchtune.utils.metric_logging.DiskLogger
  log_dir: ${output_dir}
log_every_n_steps: null
device: cuda
dtype: bf16
enable_activation_checkpointing: false
profiler:
  _component_: torchtune.utils.profiler
  enabled: true
inference:
  prompt_template: 'Video:

    {video}

    Caption the previous video.'
  max_new_tokens: 300
  temperature: 0.6
  top_k: 300
  quantizer: null
gradient-accumulation-steps: 32