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7B_full_low_memory.yaml
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7B_full_low_memory.yaml
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# Config for single device full finetuning in full_finetune_single_device.py
# using a Llama2 7B model
#
# This config assumes that you've run the following command before launching
# this run:
# tune download meta-llama/Llama-2-7b-hf --output-dir /tmp/Llama-2-7b-hf --hf-token <HF_TOKEN>
#
# The default config uses an optimizer from bitsandbytes. If you do not have it installed,
# you can install it with
# pip install bitsandbytes
#
# To launch on a single device, run the following command from root:
# tune run full_finetune_single_device --config llama2/7B_full_low_memory
#
# You can add specific overrides through the command line. For example
# to override the checkpointer directory while launching training
# you can run:
# tune run full_finetune_single_device --config llama2/7B_full_low_memory checkpointer.checkpoint_dir=<YOUR_CHECKPOINT_DIR>
#
# This config works only for training on single device.
# Tokenizer
tokenizer:
_component_: torchtune.models.llama2.llama2_tokenizer
path: /tmp/Llama-2-7b-hf/tokenizer.model
# Dataset
dataset:
_component_: torchtune.datasets.alpaca_dataset
seed: null
shuffle: True
# Model Arguments
model:
_component_: torchtune.models.llama2.llama2_7b
checkpointer:
_component_: torchtune.utils.FullModelHFCheckpointer
checkpoint_dir: /tmp/Llama-2-7b-hf
checkpoint_files: [
pytorch_model-00001-of-00002.bin,
pytorch_model-00002-of-00002.bin
]
recipe_checkpoint: null
output_dir: /tmp/Llama-2-7b-hf
model_type: LLAMA2
resume_from_checkpoint: False
# Fine-tuning arguments
batch_size: 2
epochs: 3
optimizer:
_component_: bitsandbytes.optim.PagedAdamW
lr: 2e-5
optimizer_in_bwd: True
loss:
_component_: torch.nn.CrossEntropyLoss
max_steps_per_epoch: null
gradient_accumulation_steps: 1
compile: False
# Training environment
device: cuda
# Memory management
enable_activation_checkpointing: True
# Reduced precision
dtype: bf16
# Logging
metric_logger:
_component_: torchtune.utils.metric_logging.DiskLogger
log_dir: ${output_dir}
output_dir: /tmp/alpaca-llama2-finetune
log_every_n_steps: 1
log_peak_memory_stats: False