LLaMA-Factory/examples/train_full/llama3_full_sft.yaml
hoshi-hiyouga ca78ba964d [model] add models (#7054)
* add qwen25vl awq models

* add moonlight

Former-commit-id: ec1a1bc1184d13188029e19c1d4e7de68707aaf6
2025-02-24 22:05:13 +08:00

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YAML

### model
model_name_or_path: meta-llama/Meta-Llama-3-8B-Instruct
trust_remote_code: true
### method
stage: sft
do_train: true
finetuning_type: full
deepspeed: examples/deepspeed/ds_z3_config.json # choices: [ds_z0_config.json, ds_z2_config.json, ds_z3_config.json]
### dataset
dataset: identity,alpaca_en_demo
template: llama3
cutoff_len: 2048
max_samples: 1000
overwrite_cache: true
preprocessing_num_workers: 16
### output
output_dir: saves/llama3-8b/full/sft
logging_steps: 10
save_steps: 500
plot_loss: true
overwrite_output_dir: true
### train
per_device_train_batch_size: 1
gradient_accumulation_steps: 2
learning_rate: 1.0e-5
num_train_epochs: 3.0
lr_scheduler_type: cosine
warmup_ratio: 0.1
bf16: true
ddp_timeout: 180000000
### eval
# eval_dataset: alpaca_en_demo
# val_size: 0.1
# per_device_eval_batch_size: 1
# eval_strategy: steps
# eval_steps: 500