To Reproduce Steps to reproduce the behavior:

1. Simply attempt to run training for the first time, by running `ilab model train -enable-serving-output --strategy lab-multiphase  -phased-phase1-data ~/.local/share/instructlab/datasets/knowledge_train_msgs_2024-12-17T21
   _14_00.jsonl   --phased-phase2-data ~/skills-15k.jsonl`
2. output:

~~~~~~~~~~~~_{STARTING MULTI-PHASE TRAINING}~~~~~~~~~~~~
Running phased training with '2' epochs.
Note: 7 epochs is the recommended amount for optimal performance.
No training journal found. Will initialize at: '/var/home/cloud-user/.local/share/instructlab/phased/journalfile.yaml'
Metadata (checkpoints, the training journal) may have been saved from a previous training run.
By default, training will resume from this metadata if it exists.
Alternatively, the metadata can be cleared, and training can start from scratch.

Would you like to START TRAINING FROM THE BEGINNING?
'y' clears metadata to start new training, 'N' tries to resume:  [y/N]: y

Expected behavior

• Omit the question and omit the attempt to resume if it's the first attempt.

Device Info (please complete the following information):

• Hardware Specs: [p5.48xlarge AWS instance]
• OS Version: [Red Hat Enterprise Linux release 9.4]
• InstructLab Version: [0.21.2]
• Provide the output of these two commands:
  • sudo bootc status --format json | jq .status.booted.image.image.image
    • registry.redhat.io/rhelai1/bootc-nvidia-rhel9:1.3
  • ilab system info 

  • Platform:                                 
      sys.version: 3.11.7 (main, Oct  9 2024, 00:00:00) [GCC 11.4.1 20231218 (Red Hat 11.4.1-3)]
      sys.platform: linux        
      os.name: posix                                                
      platform.release: 5.14.0-427.42.1.el9_4.x86_64
      platform.machine: x86_64  
      platform.node: ip-10-0-26-215.us-east-2.compute.internal
      platform.python_version: 3.11.7                               
      os-release.ID: rhel                     
      os-release.VERSION_ID: 9.4
      os-release.PRETTY_NAME: Red Hat Enterprise Linux 9.4 (Plow)
      memory.total: 1999.96 GB                                       
      memory.available: 1987.32 GB            
      memory.used: 3.48 GB      
                                 
    InstructLab:                                                     
      instructlab.version: 0.21.2             
      instructlab-dolomite.version: 0.2.0
      instructlab-eval.version: 0.4.1
      instructlab-quantize.version: 0.1.0                  
      instructlab-schema.version: 0.4.1
      instructlab-sdg.version: 0.6.1
      instructlab-training.version: 0.6.1
     
    Torch:                                                                                                                                                                                        
      torch.version: 2.4.1                                                                                                                                                                        
      torch.backends.cpu.capability: AVX2                                                                                                                                                         
      torch.version.cuda: 12.4                                                                                                                                                                    
      torch.version.hip: None                                                                                                                                                                     
      torch.cuda.available: True                                                                                                                                                                  
      torch.backends.cuda.is_built: True                                                                                                                                                          
      torch.backends.mps.is_built: False                                                                                                                                                          
      torch.backends.mps.is_available: False
      torch.cuda.bf16: True
      torch.cuda.current.device: 0
      torch.cuda.0.name: NVIDIA H100 80GB HBM3
      torch.cuda.0.free: 78.6 GB
      torch.cuda.0.total: 79.1 GB
      torch.cuda.0.capability: 9.0 (see https://developer.nvidia.com/cuda-gpus#compute)
      torch.cuda.1.name: NVIDIA H100 80GB HBM3
      torch.cuda.1.free: 78.6 GB
      torch.cuda.1.total: 79.1 GB
      torch.cuda.1.capability: 9.0 (see https://developer.nvidia.com/cuda-gpus#compute)
      torch.cuda.2.name: NVIDIA H100 80GB HBM3
      torch.cuda.2.free: 78.6 GB
      torch.cuda.2.total: 79.1 GB
      torch.cuda.2.capability: 9.0 (see https://developer.nvidia.com/cuda-gpus#compute)
      torch.cuda.3.name: NVIDIA H100 80GB HBM3
      torch.cuda.3.free: 78.6 GB
      torch.cuda.3.total: 79.1 GB
      torch.cuda.3.capability: 9.0 (see https://developer.nvidia.com/cuda-gpus#compute)
      torch.cuda.4.name: NVIDIA H100 80GB HBM3
      torch.cuda.4.free: 78.6 GB
      torch.cuda.4.total: 79.1 GB
      torch.cuda.4.capability: 9.0 (see https://developer.nvidia.com/cuda-gpus#compute)
      torch.cuda.5.name: NVIDIA H100 80GB HBM3
      torch.cuda.5.free: 78.6 GB
      torch.cuda.5.total: 79.1 GB
      torch.cuda.5.capability: 9.0 (see https://developer.nvidia.com/cuda-gpus#compute)
      torch.cuda.6.name: NVIDIA H100 80GB HBM3
      torch.cuda.6.free: 78.6 GB
      torch.cuda.6.total: 79.1 GB
      torch.cuda.6.capability: 9.0 (see https://developer.nvidia.com/cuda-gpus#compute)   torch.cuda.7.name: NVIDIA H100 80GB HBM3
      torch.cuda.7.free: 78.6 GB
      torch.cuda.7.total: 79.1 GB
      torch.cuda.7.capability: 9.0 (see https://developer.nvidia.com/cuda-gpus#compute)llama_cpp_python:
      llama_cpp_python.version: 0.2.79
      llama_cpp_python.supports_gpu_offload: True