LlamaFactory/examples/train_full/mossvl_full_sft.yaml

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1.3 KiB
YAML

### Install model-specific dependencies: `pip install -r requirements/moss-vl.txt`
### model
model_name_or_path: OpenMOSS-Team/MOSS-VL-Instruct-0708
image_max_pixels: 262144
video_max_pixels: 16384
video_fps: 1.0
video_maxlen: 256
use_reentrant_gc: false
trust_remote_code: true
### method
stage: sft
do_train: true
finetuning_type: full
freeze_vision_tower: true
freeze_multi_modal_projector: true
freeze_language_model: false
deepspeed: examples/deepspeed/ds_z3_config.json
### dataset
dataset: mllm_demo,identity,alpaca_en_demo # video: mllm_video_demo
template: moss_vl
cutoff_len: 4096
max_samples: 1000
preprocessing_num_workers: 16
dataloader_num_workers: 4
packing: false
### output
output_dir: saves/moss-vl-11b/full/sft
logging_steps: 10
save_steps: 500
plot_loss: true
overwrite_output_dir: true
save_only_model: false
report_to: none # choices: [none, wandb, tensorboard, swanlab, mlflow]
### train
per_device_train_batch_size: 1
gradient_accumulation_steps: 1
gradient_checkpointing: true
gradient_checkpointing_kwargs:
use_reentrant: false
learning_rate: 1.0e-5
num_train_epochs: 3.0
lr_scheduler_type: cosine
warmup_ratio: 0.1
bf16: true
ddp_timeout: 180000000
resume_from_checkpoint: null
### eval
# val_size: 0.1
# per_device_eval_batch_size: 1
# eval_strategy: steps
# eval_steps: 500