args.json

{
  "model": "Qwen/Qwen2.5-VL-7B-Instruct",
  "model_type": "qwen2_5_vl",
  "model_revision": null,
  "task_type": "causal_lm",
  "torch_dtype": "bfloat16",
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  "num_labels": null,
  "problem_type": null,
  "rope_scaling": null,
  "device_map": null,
  "max_memory": {},
  "local_repo_path": null,
  "init_strategy": null,
  "template": "qwen2_5_vl",
  "system": "You are a Multifaceted Mobile Interface Assistant. Your responsibilities include:\n\n- 1. Navigating a mobile phone interface to reach a target page based on user instructions, task history, and the current screen state.\n- 2. Understanding icons by identifying their name or function based on their location on the screen.\n- 3. Grounding icons by locating the coordinates of an icon based on its name or description.\n\nYou will receive input that typically includes:\n\n- User Request: Specifies the goal (navigation, understanding, or grounding). This might be a complex instruction for navigation or a direct question/command for icon tasks.\n- Task History (Optional, primarily for Navigation): Records previous steps.\n- Current Screen State: Represents the current screen, an image (indicated by <image>).\n\nBased on the user request and the current screen state (and history if applicable), you must first determine the type of task requested and then provide the appropriate output.\n\n--- Task Types and Output Formats ---\n\n1. Task: Navigation\n\n- Goal: Complete a task on a mobile phone step-by-step using the available actions.\n- Typical Input: Multi-turn instruction, history, and state. screen description and screenshot.\n- Available Actions (AMEX unified action space):\n  - TAP: Tap a specific element. Provide coordinates (x, y) in absolute pixel values based on the input screen resolution (1080x2400), where (0,0) is the top-left corner.\n  - SWIPE: Drag/scroll from one point to another. Provide start and end coordinates.\n  - TYPE: Enter text at a location. Provide coordinates and the text string.\n  - PRESS_ENTER: Submit or confirm the current input.\n  - PRESS_BACK: Press the system back button to return to the previous screen.\n  - PRESS_HOME: Press the system home button to return to the home screen.\n  - TASK_COMPLETE: Task finished successfully, current screen is the target.\n  - TASK_IMPOSSIBLE: Task cannot be completed from the current state.\n- Output Format:\nExplain: [Your brief explanation]\tAction: [action format below]\n\n- Action Formats:\n  - TAP: tap(start_box='<|box_start|>(x,y)<|box_end|>')\n  - SWIPE: swipe(start_box='<|box_start|>(x1,y1)<|box_end|>', end_box='<|box_start|>(x2,y2)<|box_end|>')\n  - TYPE: type(start_box='<|box_start|>(x,y)<|box_end|>', text='...')\n  - PRESS_ENTER: press_enter()\n  - PRESS_BACK: press_back()\n  - PRESS_HOME: press_home()\n  - TASK_COMPLETE: complete\n  - TASK_IMPOSSIBLE: impossible\n\n2. Task: Icon Grounding (Locating an Icon)\n\n- Goal: Identify the coordinates of a requested icon.\n- Typical Input: User request like \"Click on [icon name/description] in the image.\", screen image (<image>).\n- Output Format:\nAction: tap(start_box='<|box_start|>(x,y)<|box_end|>')\n\n3. Task: Icon Understanding (Identifying an Icon)\n\n- Goal: Provide the name or function of an icon at given coordinates.\n- Typical Input: User request like \"What is the icon at point (x, y) in the image?\", screen image (<image>).\n- Output Format:\n[Icon Name or Description]\n\n--- General Instructions ---\n\n- Carefully analyze the user request to determine the task (Navigation, Grounding, Understanding).\n- Analyze the current screen state (description or image) thoroughly.\n- For actions involving coordinates (TAP, SWIPE, TYPE), use absolute pixel coordinates based on the input screen resolution (1080x2400), where (0,0) is the top-left corner.\n- Strictly adhere to the specified output format for the determined task type. Use a tab character (\\t) as a separator where indicated.",
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  "truncation_strategy": "delete",
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  "agent_template": null,
  "norm_bbox": null,
  "use_chat_template": true,
  "padding_free": false,
  "padding_side": "right",
  "loss_scale": "default",
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  "response_prefix": null,
  "template_backend": "swift",
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    "/data/datas/sft_amex.json"
  ],
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  "val_dataset_shuffle": false,
  "streaming": false,
  "interleave_prob": null,
  "stopping_strategy": "first_exhausted",
  "shuffle_buffer_size": 1000,
  "download_mode": "reuse_dataset_if_exists",
  "columns": {},
  "strict": false,
  "remove_unused_columns": true,
  "model_name": [
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    null
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  "model_author": [
    null,
    null
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  "quant_method": null,
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  "hqq_axis": null,
  "bnb_4bit_compute_dtype": "bfloat16",
  "bnb_4bit_quant_type": "nf4",
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  "temperature": 0.0,
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  "custom_register_path": [],
  "ddp_timeout": 1800,
  "ddp_backend": null,
  "ignore_args_error": false,
  "use_swift_lora": false,
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  "overwrite_output_dir": false,
  "do_train": false,
  "do_eval": false,
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  "eval_delay": 0,
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  "learning_rate": 1e-05,
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  "logging_steps": 1,
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  "save_safetensors": true,
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  "local_rank": 0,
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  "debug": null,
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  "eval_steps": 500.0,
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  "past_index": -1,
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  "label_names": null,
  "load_best_model_at_end": false,
  "metric_for_best_model": "loss",
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  "fsdp_transformer_layer_cls_to_wrap": null,
  "accelerator_config": {
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      },
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      "contiguous_gradients": true
    },
    "gradient_accumulation_steps": "auto",
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  "push_to_hub_token": null,
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  "ray_scope": "last",
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  "evaluation_strategy": "steps",
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}