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1.1 KiB
1.1 KiB
Finetuning the base model with LoRA adaptor
WANDB_MODE=disabled python hyperlora/intx_sft.py configs/default.yaml --model_name_or_path=meta-llama/Llama-3.2-1B-Instruct --num_train_epochs=50 --per_device_train_batch_size=128 --per_device_eval_batch_size=128 --exp_setup=lora --train_ds_name=data/raw_datasets/context_numbers_small
HyperLoRA w/ context_numbers_10
WANDB_MODE=disabled run python hyperlora/intx_sft.py configs/context_numbers_10.yaml --model_name_or_path=meta-llama/Llama-3.2-1B-Instruct --num_train_epochs=100 --per_device_train_batch_size=64 --per_device_eval_batch_size=64 --exp_setup=hyper_lora --aggregator_type=perceiver --target_modules=down_proj,up_proj
HyperLoRA w/ context_numbers_128
WANDB_MODE=disabled run python hyperlora/intx_sft.py configs/context_numbers_128.yaml --model_name_or_path=meta-llama/Llama-3.2-1B-Instruct --num_train_epochs=10 --per_device_train_batch_size=64 --per_device_eval_batch_size=8 --exp_setup=hyper_lora --aggregator_type=perceiver --target_modules=down_proj