mini_full.yaml

# Config for multi-device full finetuning in full_finetune_distributed.py
# using a Phi3 Mini 4K Instruct
#
# This config assumes that you've run the following command before launching
# this run:
#   tune download microsoft/Phi-3-mini-4k-instruct --output-dir /tmp/Phi-3-mini-4k-instruct --ignore-patterns None --hf-token <HF_TOKEN>
#
# Run this config on 4 GPUs using the following:
#  tune run --nproc_per_node 4 full_finetune_distributed --config phi3/mini_full
#
# You can add specific overrides through the command line. For example
# to override the checkpointer directory while launching training
# you can run:
#   tune run --nproc_per_node 4 full_finetune_distributed --config phi3/mini_full checkpointer.checkpoint_dir=<YOUR_CHECKPOINT_DIR>
#
# This config works best when the model is being fine-tuned on 2+ GPUs.
# Single device full finetuning requires more memory optimizations. It's
# best to use mini_low_memory.yaml for those cases

# Model arguments
model:
  _component_: torchtune.models.phi3.phi3_mini

# Tokenizer
tokenizer:
  _component_: torchtune.models.phi3.phi3_mini_tokenizer
  path: /tmp/Phi-3-mini-4k-instruct/tokenizer.model

# Checkpointer
checkpointer:
  _component_: torchtune.utils.FullModelHFCheckpointer
  checkpoint_dir: /tmp/Phi-3-mini-4k-instruct
  checkpoint_files: [
    model-00001-of-00002.safetensors,
    model-00002-of-00002.safetensors
  ]
  recipe_checkpoint: null
  output_dir: /tmp/Phi-3-mini-4k-instruct
  model_type: PHI3_MINI
resume_from_checkpoint: False

# Dataset
dataset:
  _component_: torchtune.datasets.alpaca_cleaned_dataset
seed: null
shuffle: True

# Fine-tuning arguments
epochs: 1
max_steps_per_epoch: null
batch_size: 2
gradient_accumulation_steps: 16
optimizer:
  _component_: torch.optim.AdamW
  lr: 5e-6
loss:
  _component_: torch.nn.CrossEntropyLoss

# Training env
device: cuda

# Memory management
enable_activation_checkpointing: True
memory_efficient_fsdp_wrap: False
dtype: bf16

# Logging
output_dir: /tmp/phi3_full_finetune_output
metric_logger:
  _component_: torchtune.utils.metric_logging.DiskLogger
  log_dir: /tmp/Phi-3-mini-4k-instruct/logs
log_every_n_steps: 1
log_peak_memory_stats: False