|
SYSTEM = '' |
|
accumulative_counts = 1 |
|
batch_size = 32 |
|
betas = ( |
|
0.9, |
|
0.999, |
|
) |
|
custom_hooks = [ |
|
dict( |
|
tokenizer=dict( |
|
padding_side='right', |
|
pretrained_model_name_or_path='lmsys/vicuna-7b-v1.5', |
|
trust_remote_code=True, |
|
type='transformers.AutoTokenizer.from_pretrained'), |
|
type='xtuner.engine.DatasetInfoHook'), |
|
dict( |
|
evaluation_images='https://llava-vl.github.io/static/images/view.jpg', |
|
evaluation_inputs=[ |
|
'', |
|
], |
|
every_n_iters=500, |
|
image_processor=dict( |
|
pretrained_model_name_or_path='openai/clip-vit-large-patch14-336', |
|
trust_remote_code=True, |
|
type='transformers.CLIPImageProcessor.from_pretrained'), |
|
prompt_template='xtuner.utils.PROMPT_TEMPLATE.vicuna', |
|
system='', |
|
tokenizer=dict( |
|
padding_side='right', |
|
pretrained_model_name_or_path='lmsys/vicuna-7b-v1.5', |
|
trust_remote_code=True, |
|
type='transformers.AutoTokenizer.from_pretrained'), |
|
type='xtuner.engine.EvaluateChatHook'), |
|
] |
|
data_path = './data/llava_data/LLaVA-Pretrain/blip_laion_cc_sbu_558k.json' |
|
dataloader_num_workers = 0 |
|
default_hooks = dict( |
|
checkpoint=dict(interval=1, type='mmengine.hooks.CheckpointHook'), |
|
logger=dict(interval=10, type='mmengine.hooks.LoggerHook'), |
|
param_scheduler=dict(type='mmengine.hooks.ParamSchedulerHook'), |
|
sampler_seed=dict(type='mmengine.hooks.DistSamplerSeedHook'), |
|
timer=dict(type='mmengine.hooks.IterTimerHook')) |
|
env_cfg = dict( |
|
cudnn_benchmark=False, |
|
dist_cfg=dict(backend='nccl'), |
|
mp_cfg=dict(mp_start_method='fork', opencv_num_threads=0)) |
|
evaluation_freq = 500 |
|
evaluation_images = 'https://llava-vl.github.io/static/images/view.jpg' |
|
evaluation_inputs = [ |
|
'', |
|
] |
|
image_folder = './data/llava_data/LLaVA-Pretrain/images' |
|
launcher = 'pytorch' |
|
llava_data_root = './data/llava_data/' |
|
llava_dataset = dict( |
|
data_path='./data/llava_data/LLaVA-Pretrain/blip_laion_cc_sbu_558k.json', |
|
dataset_map_fn='xtuner.dataset.map_fns.llava_map_fn', |
|
image_folder='./data/llava_data/LLaVA-Pretrain/images', |
|
max_length=1472, |
|
pad_image_to_square=False, |
|
image_processor=dict( |
|
pretrained_model_name_or_path='openai/clip-vit-large-patch14-336', |
|
trust_remote_code=True, |
|
type='transformers.CLIPImageProcessor.from_pretrained'), |
|
template_map_fn=dict( |
|
template='xtuner.utils.PROMPT_TEMPLATE.vicuna', |
|
type='xtuner.dataset.map_fns.template_map_fn_factory'), |
|
tokenizer=dict( |
|
padding_side='right', |
|
pretrained_model_name_or_path='lmsys/vicuna-7b-v1.5', |
|
trust_remote_code=True, |
|
type='transformers.AutoTokenizer.from_pretrained'), |
|
type='xtuner.dataset.LLaVADataset') |
|
llm_name_or_path = 'lmsys/vicuna-7b-v1.5' |
|
load_from = None |
|
log_level = 'INFO' |
|
lr = 0.001 |
|
max_epochs = 1 |
|
max_length = 1472 |
|
max_norm = 1 |
|
model = dict( |
|
freeze_llm=True, |
|
freeze_visual_encoder=True, |
|
llm=dict( |
|
pretrained_model_name_or_path='lmsys/vicuna-7b-v1.5', |
|
quantization_config=dict( |
|
bnb_4bit_compute_dtype='torch.float16', |
|
bnb_4bit_quant_type='nf4', |
|
bnb_4bit_use_double_quant=True, |
|
llm_int8_has_fp16_weight=False, |
|
llm_int8_threshold=6.0, |
|
load_in_4bit=True, |
|
load_in_8bit=False, |
|
type='transformers.BitsAndBytesConfig'), |
|
torch_dtype='torch.float16', |
|
trust_remote_code=True, |
|
type='transformers.AutoModelForCausalLM.from_pretrained'), |
|
type='xtuner.model.LLaVAModel', |
|
visual_encoder=dict( |
|
pretrained_model_name_or_path='openai/clip-vit-large-patch14-336', |
|
type='transformers.CLIPVisionModel.from_pretrained')) |
|
optim_type = 'torch.optim.AdamW' |
|
optim_wrapper = dict( |
|
optimizer=dict( |
|
betas=( |
|
0.9, |
|
0.999, |
|
), |
|
lr=0.001, |
|
type='torch.optim.AdamW', |
|
weight_decay=0), |
|
type='DeepSpeedOptimWrapper') |
|
param_scheduler = [ |
|
dict( |
|
begin=0, |
|
by_epoch=True, |
|
convert_to_iter_based=True, |
|
end=0.03, |
|
start_factor=1e-05, |
|
type='mmengine.optim.LinearLR'), |
|
dict( |
|
T_max=1, |
|
begin=0.03, |
|
by_epoch=True, |
|
convert_to_iter_based=True, |
|
eta_min=0.0, |
|
type='mmengine.optim.CosineAnnealingLR'), |
|
] |
|
image_processor = dict( |
|
pretrained_model_name_or_path='openai/clip-vit-large-patch14-336', |
|
trust_remote_code=True, |
|
type='transformers.CLIPImageProcessor.from_pretrained') |
|
prompt_template = 'xtuner.utils.PROMPT_TEMPLATE.vicuna' |
|
randomness = dict(deterministic=False, seed=None) |
|
resume = False |
|
runner_type = 'FlexibleRunner' |
|
strategy = dict( |
|
config=dict( |
|
bf16=dict(enabled=True), |
|
fp16=dict(enabled=False, initial_scale_power=16), |
|
gradient_accumulation_steps='auto', |
|
gradient_clipping='auto', |
|
train_micro_batch_size_per_gpu='auto', |
|
zero_allow_untested_optimizer=True, |
|
zero_force_ds_cpu_optimizer=False, |
|
zero_optimization=dict(overlap_comm=True, stage=2)), |
|
exclude_frozen_parameters=True, |
|
gradient_accumulation_steps=1, |
|
gradient_clipping=1, |
|
train_micro_batch_size_per_gpu=32, |
|
type='xtuner.engine.DeepSpeedStrategy') |
|
tokenizer = dict( |
|
padding_side='right', |
|
pretrained_model_name_or_path='lmsys/vicuna-7b-v1.5', |
|
trust_remote_code=True, |
|
type='transformers.AutoTokenizer.from_pretrained') |
|
train_cfg = dict(by_epoch=True, max_epochs=1, val_interval=1) |
|
train_dataloader = dict( |
|
batch_size=32, |
|
collate_fn=dict(type='xtuner.dataset.collate_fns.default_collate_fn'), |
|
dataset=dict( |
|
data_path= |
|
'./data/llava_data/LLaVA-Pretrain/blip_laion_cc_sbu_558k.json', |
|
dataset_map_fn='xtuner.dataset.map_fns.llava_map_fn', |
|
image_folder='./data/llava_data/LLaVA-Pretrain/images', |
|
max_length=1472, |
|
pad_image_to_square=False, |
|
image_processor=dict( |
|
pretrained_model_name_or_path='openai/clip-vit-large-patch14-336', |
|
trust_remote_code=True, |
|
type='transformers.CLIPImageProcessor.from_pretrained'), |
|
template_map_fn=dict( |
|
template='xtuner.utils.PROMPT_TEMPLATE.vicuna', |
|
type='xtuner.dataset.map_fns.template_map_fn_factory'), |
|
tokenizer=dict( |
|
padding_side='right', |
|
pretrained_model_name_or_path='lmsys/vicuna-7b-v1.5', |
|
trust_remote_code=True, |
|
type='transformers.AutoTokenizer.from_pretrained'), |
|
type='xtuner.dataset.LLaVADataset'), |
|
num_workers=0, |
|
sampler=dict(shuffle=True, type='mmengine.dataset.DefaultSampler')) |
|
visual_encoder_name_or_path = 'openai/clip-vit-large-patch14-336' |
|
visualizer = None |
|
warmup_ratio = 0.03 |
|
weight_decay = 0 |
|
work_dir = './work_dirs/llava_vicuna_7b_v15_clip_vit_large_p14_336_e1_gpu8_pretrain' |
|
|