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7B_lora_dpo_single_device.yaml
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7B_lora_dpo_single_device.yaml
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# Config for single device LoRA DPO alignment in lora_dpo_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>
#
# To launch on a single device, run the following command from root:
# tune run lora_dpo_single_device --config llama2/7B_lora_dpo_single_device
#
# You can add specific overrides through the command line. For example
# to override the checkpointer directory while launching training
# you can run:
# tune run lora_dpo_single_device --config llama2/7B_lora_dpo_single_device checkpointer.checkpoint_dir=<YOUR_CHECKPOINT_DIR>
#
# This config works only for training on single device.
# Model Arguments
model:
_component_: torchtune.models.llama2.lora_llama2_7b
lora_attn_modules: ['q_proj', 'v_proj']
apply_lora_to_mlp: False
apply_lora_to_output: False
lora_rank: 8
lora_alpha: 16
lora_dropout: 0.0
# Tokenizer
tokenizer:
_component_: torchtune.models.llama2.llama2_tokenizer
path: /tmp/Llama-2-7b-hf/tokenizer.model
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
]
adapter_checkpoint: null
recipe_checkpoint: null
output_dir: /tmp/Llama-2-7b-hf
model_type: LLAMA2
resume_from_checkpoint: False
save_adapter_weights_only: False
# Dataset and Sampler
dataset:
_component_: torchtune.datasets.stack_exchanged_paired_dataset
max_seq_len: 1024
seed: null
shuffle: True
batch_size: 4
# Optimizer and Scheduler
optimizer:
_component_: torch.optim.AdamW
weight_decay: 0.05
lr: 5e-4
lr_scheduler:
_component_: torchtune.modules.get_cosine_schedule_with_warmup
num_warmup_steps: 100
loss:
_component_: torchtune.modules.loss.DPOLoss
beta: 0.1
label_smoothing: 0
# Training
epochs: 1
max_steps_per_epoch: 1000
gradient_accumulation_steps: 16
compile: False
# Logging
output_dir: /tmp/lora_dpo_output/
metric_logger:
_component_: torchtune.utils.metric_logging.DiskLogger
log_dir: ${output_dir}
log_every_n_steps: 1
log_peak_memory_stats: False
# Environment
device: cuda
dtype: bf16
enable_activation_checkpointing: True