peft_config = LoraConfig(
r=4, # TODO: play with this number
lora_alpha=8, # TODO: play with this number
target_modules=['q_proj', 'v_proj', 'k_proj'],
lora_dropout=0.05,
bias="none",
task_type="CAUSAL_LM" # TODO: you need to figure this out. HINT https://github.com/huggingface/peft/blob/3d2bf9a8b261ed2960f26e61246cf0aa624a6115/src/peft/utils/peft_types.py#L67
)
training_args = TrainingArguments(
per_device_train_batch_size=2,
gradient_accumulation_steps=2,
gradient_checkpointing =False,
max_grad_norm= 0.3,
num_train_epochs=3, # TODO: play with this number
save_steps= 100,
learning_rate=0.0003, # TODO: play with this number
bf16=True,
save_total_limit=3,
logging_steps=10,
output_dir='./sft_models',
optim="adamw_torch",
lr_scheduler_type="cosine",
warmup_ratio=0.05,
remove_unused_columns=False,
report_to="none",
)
generate_max_length: int = 64
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