Open vincent507cpu opened 2 months ago
@vincent507cpu Can you provide more information? For example, configuration files, whether any changes were made, etc.
@hhaAndroid Thank you for your help. I only changed Part 1:
#######################################################################
# PART 1 Settings #
#######################################################################
# Model
llm_name_or_path = '/root/autodl-tmp/Models/Meta-Llama-3-8B-Instruct'
visual_encoder_name_or_path = '/root/autodl-tmp/Models/clip-vit-large-patch14-336'
# Data
data_root = '/root/autodl-tmp/'
data_path = data_root + 'Data/model_finetuning/llava_finetune_pretrain.json'
image_folder = data_root + 'Data/MultiModalQA/final_dataset_images'
prompt_template = PROMPT_TEMPLATE.llama3_chat
max_length = int(2048 - (336 / 14)**2)
# Scheduler & Optimizer
batch_size = 1 # per_device
accumulative_counts = 256
dataloader_num_workers = 0
max_epochs = 3
optim_type = AdamW
lr = 1e-3
betas = (0.9, 0.999)
weight_decay = 0
max_norm = 1 # grad clip
warmup_ratio = 0.03
# Save
save_steps = 50000
save_total_limit = 2 # Maximum checkpoints to keep (-1 means unlimited)
# Evaluate the generation performance during the training
evaluation_freq = 50000
SYSTEM = ''
evaluation_images = image_folder + '/6ce6de9d60f9b58cd4f925db4642f96b.jpg'
evaluation_inputs = ['Please describe this picture']
I'm using MultimodalQA dataset, text (image caption) is generalized by ChatGPT-4o.
Hi @hhaAndroid, finetune has a similar error.
NPROC_PER_NODE=1 xtuner train /root/autodl-tmp/GitHub/xtuner/xtuner/configs/llava/llama3_8b_instruct_clip_vit_large_p14_336/finetune/llava_llama3_8b_instruct_qlora_clip_vit_large_p14_336_e1_gpu1_finetune.py --deepspeed deepspeed_zero3
#######################################################################
# PART 1 Settings #
#######################################################################
# Model
llm_name_or_path = '/root/autodl-tmp/Models/Meta-Llama-3-8B-Instruct'
visual_encoder_name_or_path = '/root/autodl-tmp/Models/clip-vit-large-patch14-336'
# Specify the pretrained pth
pretrained_pth = '/root/autodl-tmp/Models/llava-llama-3-8b-v1_1-pretrain/iter_9742.pth' # noqa: E501
data_root = '/root/autodl-tmp/' data_path = data_root + 'Data/model_finetuning/llava_finetune_pretrain.json' image_folder = data_root + 'Data/MultiModalQA/final_dataset_images' prompt_template = PROMPT_TEMPLATE.llama3_chat max_length = int(2048 - (336 / 14)**2)
batch_size = 1 # per_device accumulative_counts = 128 dataloader_num_workers = 0 max_epochs = 3 optim_type = AdamW lr = 2e-4 betas = (0.9, 0.999) weight_decay = 0 max_norm = 1 # grad clip warmup_ratio = 0.03
save_steps = 50000 save_total_limit = 2 # Maximum checkpoints to keep (-1 means unlimited)
evaluation_freq = 50000 SYSTEM = ''
evaluation_images = image_folder + '/6ce6de9d60f9b58cd4f925db4642f96b.jpg' evaluation_inputs = ['请描述一下这张照片', 'Please describe this picture']
- error message:
Traceback (most recent call last): File "/root/miniconda3/lib/python3.10/site-packages/mmengine/runner/_flexible_runner.py", line 1271, in call_hook getattr(hook, fn_name)(self, kwargs) File "/root/miniconda3/lib/python3.10/site-packages/xtuner/engine/hooks/evaluate_chat_hook.py", line 230, in before_train self._generate_samples(runner, max_new_tokens=50) File "/root/miniconda3/lib/python3.10/site-packages/xtuner/engine/hooks/evaluate_chat_hook.py", line 216, in _generate_samples self._eval_images(runner, model, device, max_new_tokens, File "/root/miniconda3/lib/python3.10/site-packages/xtuner/engine/hooks/evaluate_chat_hook.py", line 148, in _eval_images generation_output = model.generate( File "/root/miniconda3/lib/python3.10/site-packages/peft/peft_model.py", line 1491, in generate outputs = self.base_model.generate(*args, *kwargs) File "/root/miniconda3/lib/python3.10/site-packages/torch/utils/_contextlib.py", line 115, in decorate_context return func(args, kwargs) File "/root/miniconda3/lib/python3.10/site-packages/transformers/generation/utils.py", line 1758, in generate result = self._sample( File "/root/miniconda3/lib/python3.10/site-packages/transformers/generation/utils.py", line 2390, in _sample model_kwargs = self._get_initial_cache_position(input_ids, model_kwargs) File "/root/miniconda3/lib/python3.10/site-packages/transformers/generation/utils.py", line 1321, in _get_initial_cache_position past_length = model_kwargs["past_key_values"][0][0].shape[2] TypeError: 'NoneType' object is not subscriptable
If you have a chance, please look into it. Thank you very much!
可以看看这个,https://github.com/InternLM/xtuner/issues/834 transformers版本的问题,我安装4.39.1,问题就解决了 @vincent507cpu
@KimWu1994 非常感谢!
Any help would be greatly appreciated!