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run_id: 0911_libero_object_augsteps_0_wo_flash_attention_wo_augsteps_two_view_action_chunk_8_pretrained_vlm_20k
run_root_dir: ./playground/Checkpoints
seed: 42
trackers:
- jsonl
- wandb
wandb_entity: michaelyu-1101-fudanuniversity
wandb_project: Internvla
is_debug: false
framework:
framework_py: DinoQFormerACT
qwenvl:
base_vlm: /mnt/phwfile/efm_t/zhuyangkun_tmp_need_del/exp/exp_08_09/manip_sys2_qwen25_3b_onevision_molmo_a0all_refsp20/checkpoint-20000/
attn_implementation: flash_attention_2
vl_hidden_dim: 2048
dino:
dino_backbone: dinov2_vitl14
layer_qformer:
qformer_end_layer: 37
qformer_start_layer: 36
num_query_tokens: 64
grad_scale: 0.5
action_model:
action_model_type: DiT-B
action_hidden_dim: 768
action_dim: 7
use_ema: false
future_action_window_size: 7
past_action_window_size: 0
repeated_diffusion_steps: 8
reduce_in_full_precision: true
datasets:
vlm_data:
dataformat: llava_json
dataset_use: asv2_conversation_en,asv2_detailed_description_en,asv2_region_captioning_en,coco_internvl_longcap_en,coco_karpathy_train_567_en,coco_negative_gpt4o_en,coco_poetry_zh,coco_rem_en_zh,cocorem_exist_yorn_en,cocotextv2_en,cocotextv2_gpt4o_en,okvqa_en,refcoco_grounding_aug_en,refcoco_grounding_en,tallyqa_coco_en,toloka_grounding_aug_en,vqav2_en,vsr_en
eval_dataset: aokvqa_cauldron_llava_format
data_flatten: false
base_interval: 2
max_pixels: 50176
min_pixels: 784
fix_image_size:
- 224
- 224
model_max_length: 1024
model_type: qwen2.5vl
per_device_batch_size: 4
vla_data:
dataset_py: lerobot_libero
data_root_dir: playground/Datasets/LEROBOT_LIBERO_DATA
data_mix: libero_object
action_type: delta_qpos
CoT_prompt: Your task is {instruction}. To identify the key objects for your task.
Locate their bounding boxes in [x1,y1,x2,y2] format.
CoT_answer: bbox
default_image_resolution:
- 3
- 224
- 224
per_device_batch_size: 16
load_all_data_for_training: true
obs:
- image_0
trainer:
epochs: 100
max_train_steps: 100000
num_warmup_steps: 5000
save_interval: 10000
eval_interval: 1000
learning_rate:
base: 2.5e-05
lr_scheduler_type: cosine_with_min_lr
scheduler_specific_kwargs:
min_lr: 1.0e-06
freeze_modules: ''
loss_scale:
vla: 1.0
vlm: 0.1
max_grad_norm: 1.0
warmup_ratio: 0.1
weight_decay: 0.0
logging_frequency: 10
gradient_clipping: 1.0
gradient_accumulation_steps: 1
optimizer:
name: AdamW
betas:
- 0.9
- 0.95
eps: 1.0e-08
weight_decay: 1.0e-08
is_resume: false
resume_epoch: null
resume_step: null
enable_gradient_checkpointing: true
enable_mixed_precision_training: true
output_dir: ./playground/Checkpoints/0911_libero_object_augsteps_0_wo_flash_attention_wo_augsteps_two_view_action_chunk_8_pretrained_vlm_20k