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https://github.com/hiyouga/LLaMA-Factory.git
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49 lines
1.0 KiB
YAML
49 lines
1.0 KiB
YAML
# pip install git+https://github.com/hiyouga/transformers.git@llama4_train
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### model
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model_name_or_path: meta-llama/Llama-4-Scout-17B-16E-Instruct
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trust_remote_code: true
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### method
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stage: sft
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do_train: true
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finetuning_type: lora
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lora_rank: 8
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lora_target: all
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deepspeed: examples/deepspeed/ds_z3_config.json # choices: [ds_z0_config.json, ds_z2_config.json, ds_z3_config.json]
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### dataset
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dataset: mllm_demo,identity,alpaca_en_demo
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template: llama4
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cutoff_len: 2048
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max_samples: 1000
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overwrite_cache: true
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preprocessing_num_workers: 16
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dataloader_num_workers: 4
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### output
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output_dir: saves/llama4-8b/lora/sft
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logging_steps: 10
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save_steps: 500
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plot_loss: true
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overwrite_output_dir: true
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save_only_model: false
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### train
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per_device_train_batch_size: 1
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gradient_accumulation_steps: 8
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learning_rate: 1.0e-4
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num_train_epochs: 3.0
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lr_scheduler_type: cosine
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warmup_ratio: 0.1
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bf16: true
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ddp_timeout: 180000000
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resume_from_checkpoint: null
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### eval
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# eval_dataset: alpaca_en_demo
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# val_size: 0.1
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# per_device_eval_batch_size: 1
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# eval_strategy: steps
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# eval_steps: 500
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