LLaMA-Factory/examples/extras/loraplus/llama3_lora_sft.yaml
hiyouga 3318b6e188 update examples
Former-commit-id: dae83f419919305cb23bb2b9da1277a1616179c5
2024-05-13 20:39:36 +08:00

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YAML

# model
model_name_or_path: meta-llama/Meta-Llama-3-8B-Instruct
# method
stage: sft
do_train: true
finetuning_type: lora
lora_target: q_proj,v_proj
loraplus_lr_ratio: 16.0
# dataset
dataset: identity,alpaca_gpt4_en
template: llama3
cutoff_len: 1024
max_samples: 1000
overwrite_cache: true
preprocessing_num_workers: 16
# output
output_dir: saves/llama3-8b/lora/sft
logging_steps: 10
save_steps: 500
plot_loss: true
overwrite_output_dir: true
# train
per_device_train_batch_size: 1
gradient_accumulation_steps: 8
learning_rate: 0.0001
num_train_epochs: 3.0
lr_scheduler_type: cosine
warmup_steps: 0.1
fp16: true
# eval
val_size: 0.1
per_device_eval_batch_size: 1
evaluation_strategy: steps
eval_steps: 500