Fine-tuning/result.txt

(base) [root@localhost ~]# docker exec finetune-trainer tail -200 /tmp/train_33166c59-034d-4afd-92ba-ff6bece676dc.log
[remote_train] === Training job started: 33166c59-034d-4afd-92ba-ff6bece676dc ===
[remote_train] model_id=Qwen/Qwen3.5-0.8B, model_type=text
[remote_train] dataset_path=/root/Fine-tuning/backend/data/datasets/data.jsonl
[remote_train] config={"model_id": "Qwen/Qwen3.5-0.8B", "model_type": "text", "dataset_id": "3d5f8808-e71a-449d-94e9-c61c4881b2cf", "peft_method": "adalora", "epochs": 3, "batch_size": 16, "gradient_accumulation": 4, "lear
[remote_train] Dataset file exists: /root/Fine-tuning/backend/data/datasets/data.jsonl
[remote_train] Step 1: Preprocessing dataset...
[remote_train]   task_type=sft, template=auto
[remote_train]   output_path=/root/Fine-tuning/backend/data/processed/33166c59-034d-4afd-92ba-ff6bece676dc_processed.jsonl
[remote_train]   Selecting engine for model_type=text...
[remote_train]   Engine loaded: TextEngine
[remote_train]   PEFT method: adalora
[remote_train]   Running preprocess_dataset...
[remote_train]   Preprocessing done, output: /root/Fine-tuning/backend/data/processed/33166c59-034d-4afd-92ba-ff6bece676dc_processed.jsonl
[remote_train] Step 2: Loading model: Qwen/Qwen3.5-0.8B...
[remote_train]   Quantization: None
Current Triton version 3.0.0 is below the recommended 3.2.0 version. Errors may occur and these issues will not be fixed. Please consider upgrading Triton.
Current Python version 3.10 is below the recommended 3.11 version. It is recommended to upgrade to Python 3.11 or higher for the best experience.
torch.compile is not available in Python 3.10, using identity decorator instead
/opt/conda/lib/python3.10/site-packages/torchvision/datapoints/__init__.py:12: UserWarning: The torchvision.datapoints and torchvision.transforms.v2 namespaces are still Beta. While we do not expect major breaking changes, some APIs may still change according to user feedback. Please submit any feedback you may have in this issue: https://github.com/pytorch/vision/issues/6753, and you can also check out https://github.com/pytorch/vision/issues/7319 to learn more about the APIs that we suspect might involve future changes. You can silence this warning by calling torchvision.disable_beta_transforms_warning().
  warnings.warn(_BETA_TRANSFORMS_WARNING)
/opt/conda/lib/python3.10/site-packages/torchvision/transforms/v2/__init__.py:54: UserWarning: The torchvision.datapoints and torchvision.transforms.v2 namespaces are still Beta. While we do not expect major breaking changes, some APIs may still change according to user feedback. Please submit any feedback you may have in this issue: https://github.com/pytorch/vision/issues/6753, and you can also check out https://github.com/pytorch/vision/issues/7319 to learn more about the APIs that we suspect might involve future changes. You can silence this warning by calling torchvision.disable_beta_transforms_warning().
  warnings.warn(_BETA_TRANSFORMS_WARNING)
Loading weights: 100%|██████████| 320/320 [00:06<00:00, 49.85it/s]
[remote_train]   Model loaded successfully
[remote_train] Step 3: Building PEFT config...
[remote_train]   PEFT config built
[remote_train] Step 4: Starting training...
Map: 100%|██████████| 60/60 [00:00<00:00, 2165.49 examples/s]
[remote_train] ERROR: Please specify `target_modules` or `target_parameters`in `peft_config`
[remote_train] Traceback (most recent call last):
  File "/root/Fine-tuning/backend/app/engines/remote_train.py", line 172, in run_training
    adapter_path = await engine.train(
  File "/root/Fine-tuning/backend/app/engines/text_engine.py", line 198, in train
    self._model = get_peft_model(self._model, peft_config)
  File "/opt/conda/lib/python3.10/site-packages/peft/mapping_func.py", line 122, in get_peft_model
    return MODEL_TYPE_TO_PEFT_MODEL_MAPPING[peft_config.task_type](
  File "/opt/conda/lib/python3.10/site-packages/peft/peft_model.py", line 1955, in __init__
    super().__init__(model, peft_config, adapter_name, **kwargs)
  File "/opt/conda/lib/python3.10/site-packages/peft/peft_model.py", line 129, in __init__
    self.base_model = cls(model, {adapter_name: peft_config}, adapter_name)
  File "/opt/conda/lib/python3.10/site-packages/peft/tuners/adalora/model.py", line 69, in __init__
    super().__init__(model, config, adapter_name, **kwargs)
  File "/opt/conda/lib/python3.10/site-packages/peft/tuners/tuners_utils.py", line 315, in __init__
    self.inject_adapter(self.model, adapter_name, low_cpu_mem_usage=low_cpu_mem_usage, state_dict=state_dict)
  File "/opt/conda/lib/python3.10/site-packages/peft/tuners/tuners_utils.py", line 815, in inject_adapter
    peft_config = self._prepare_adapter_config(peft_config, model_config)
  File "/opt/conda/lib/python3.10/site-packages/peft/tuners/lora/model.py", line 570, in _prepare_adapter_config
    raise ValueError("Please specify `target_modules` or `target_parameters`in `peft_config`")
ValueError: Please specify `target_modules` or `target_parameters`in `peft_config`

[remote_train] === Training job failed: 33166c59-034d-4afd-92ba-ff6bece676dc ===
Traceback (most recent call last):
  File "/opt/conda/lib/python3.10/runpy.py", line 196, in _run_module_as_main
    return _run_code(code, main_globals, None,
  File "/opt/conda/lib/python3.10/runpy.py", line 86, in _run_code
    exec(code, run_globals)
  File "/root/Fine-tuning/backend/app/engines/remote_train.py", line 213, in <module>
    main()
  File "/root/Fine-tuning/backend/app/engines/remote_train.py", line 209, in main
    asyncio.run(run_training(job_id, model_id, model_type, dataset_id, config))
  File "/opt/conda/lib/python3.10/asyncio/runners.py", line 44, in run
    return loop.run_until_complete(main)
  File "/opt/conda/lib/python3.10/asyncio/base_events.py", line 649, in run_until_complete
    return future.result()
  File "/root/Fine-tuning/backend/app/engines/remote_train.py", line 172, in run_training
    adapter_path = await engine.train(
  File "/root/Fine-tuning/backend/app/engines/text_engine.py", line 198, in train
    self._model = get_peft_model(self._model, peft_config)
  File "/opt/conda/lib/python3.10/site-packages/peft/mapping_func.py", line 122, in get_peft_model
    return MODEL_TYPE_TO_PEFT_MODEL_MAPPING[peft_config.task_type](
  File "/opt/conda/lib/python3.10/site-packages/peft/peft_model.py", line 1955, in __init__
    super().__init__(model, peft_config, adapter_name, **kwargs)
  File "/opt/conda/lib/python3.10/site-packages/peft/peft_model.py", line 129, in __init__
    self.base_model = cls(model, {adapter_name: peft_config}, adapter_name)
  File "/opt/conda/lib/python3.10/site-packages/peft/tuners/adalora/model.py", line 69, in __init__
    super().__init__(model, config, adapter_name, **kwargs)
  File "/opt/conda/lib/python3.10/site-packages/peft/tuners/tuners_utils.py", line 315, in __init__
    self.inject_adapter(self.model, adapter_name, low_cpu_mem_usage=low_cpu_mem_usage, state_dict=state_dict)
  File "/opt/conda/lib/python3.10/site-packages/peft/tuners/tuners_utils.py", line 815, in inject_adapter
    peft_config = self._prepare_adapter_config(peft_config, model_config)
  File "/opt/conda/lib/python3.10/site-packages/peft/tuners/lora/model.py", line 570, in _prepare_adapter_config
    raise ValueError("Please specify `target_modules` or `target_parameters`in `peft_config`")
ValueError: Please specify `target_modules` or `target_parameters`in `peft_config`