| { | |
| "version": "0.2.0", | |
| "configurations": [ | |
| { | |
| "name": "Debug MDPO Training", | |
| "type": "python", | |
| "request": "launch", | |
| "program": "${workspaceFolder}/scripts/train/debug_mdpo_train.sh", | |
| "console": "integratedTerminal", | |
| "cwd": "${workspaceFolder}", | |
| "env": { | |
| "PYTHONPATH": "${workspaceFolder}:${env:PYTHONPATH}", | |
| "CUDA_VISIBLE_DEVICES": "1", | |
| "TRANSFORMERS_OFFLINE": "1", | |
| "WANDB_PROJECT": "vtimellm" | |
| }, | |
| "args": [], | |
| "justMyCode": false, | |
| "stopOnEntry": false | |
| }, | |
| { | |
| "name": "Debug Python Training Direct", | |
| "type": "python", | |
| "request": "launch", | |
| "module": "vtimellm.train.train_dpo_mem", | |
| "console": "integratedTerminal", | |
| "cwd": "${workspaceFolder}", | |
| "env": { | |
| "PYTHONPATH": "${workspaceFolder}:${env:PYTHONPATH}", | |
| "CUDA_VISIBLE_DEVICES": "1", | |
| "TRANSFORMERS_OFFLINE": "1", | |
| "WANDB_PROJECT": "vtimellm", | |
| "RANK": "1", | |
| "MASTER_PORT": "29571" | |
| }, | |
| "args": [ | |
| "--deepspeed", "./scripts/zero2.json", | |
| "--lora_enable", "True", | |
| "--lora_r", "8", | |
| "--lora_alpha", "128", | |
| "--training_stage", "3", | |
| "--finetuning", "True", | |
| "--model_name_or_path", "./checkpoints/vicuna-7b-v1.5", | |
| "--version", "v1", | |
| "--data_path", "./data/activitynet/mdpo-train.json", | |
| "--data_folder", "./data/activitynet/videos/train", | |
| "--feat_folder", "./data/activitynet/clipvitl14-vtimellm.pth", | |
| "--pretrain_mm_mlp_adapter", "./checkpoints/vtimellm-vicuna-v1-5-7b-stage1/mm_projector.bin", | |
| "--stage2_path", "./checkpoints/vtimellm-vicuna-v1-5-7b-stage2", | |
| "--stage3_path", "./checkpoints/vtimellm-vicuna-v1-5-7b-stage3", | |
| "--stage4_path", "checkpoints/vtimellm-vicuna-v1-5-7b-activitynet-stage4", | |
| "--output_dir", "./outputs/vtimellm-vicuna-v1-5-7b-activitynet-stage5", | |
| "--bf16", "True", | |
| "--max_steps", "100", | |
| "--per_device_train_batch_size", "2", | |
| "--gradient_accumulation_steps", "4", | |
| "--evaluation_strategy", "no", | |
| "--save_strategy", "no", | |
| "--save_steps", "50000", | |
| "--save_total_limit", "10", | |
| "--learning_rate", "1e-6", | |
| "--freeze_mm_mlp_adapter", "True", | |
| "--weight_decay", "0.", | |
| "--warmup_ratio", "0.1", | |
| "--lr_scheduler_type", "cosine", | |
| "--logging_steps", "1", | |
| "--tf32", "True", | |
| "--model_max_length", "2048", | |
| "--gradient_checkpointing", "True", | |
| "--dataloader_num_workers", "4", | |
| "--lazy_preprocess", "True", | |
| "--report_to", "none", | |
| "--run_name", "vtimellm-vicuna-v1-5-7b-activitynet-stage5", | |
| "--gamma", "0.0", | |
| "--beta", "0.5", | |
| "--dpo_alpha", "1.0", | |
| "--train4dpo" | |
| ], | |
| "justMyCode": false, | |
| "stopOnEntry": false | |
| }, | |
| { | |
| "name": "Debug with DeepSpeed", | |
| "type": "python", | |
| "request": "launch", | |
| "program": "${workspaceFolder}/scripts/train/debug_deepspeed.py", | |
| "console": "integratedTerminal", | |
| "cwd": "${workspaceFolder}", | |
| "env": { | |
| "PYTHONPATH": "${workspaceFolder}:${env:PYTHONPATH}", | |
| "CUDA_VISIBLE_DEVICES": "1", | |
| "TRANSFORMERS_OFFLINE": "1", | |
| "WANDB_PROJECT": "vtimellm", | |
| "RANK": "1", | |
| "MASTER_PORT": "29571" | |
| }, | |
| "args": [], | |
| "justMyCode": false, | |
| "stopOnEntry": false | |
| } | |
| ] | |
| } | |