I get a disk full error while running a Model training job using Azure ML SDK launched from Azure DevOps. I created a custom environment inside the Azure ML Workspace and used it.

I am using azure CLI tasks in Azure DevOps to launch these training jobs. How can I resolve the disk full issue?

Error Message shown in the DevOps Training Online Task:

"error": {
        "code": "UserError",
        "message": "{\"Compliant\":\"Disk full while running job. Please consider reducing amount of data accessed, or upgrading VM SKU. Total space: 14045 MB, available space: 1103 MB.\"}\n{\n  \"code\": \"DiskFullError\",\n  \"target\": \"\",\n  \"category\": \"UserError\",\n  \"error_details\": []\n}",
        "messageParameters": {},
        "details": []
    },

The .runconfig file for the training job:

 framework: Python
 script: cnn_training.py
 communicator: None
 autoPrepareEnvironment: true
 maxRunDurationSeconds:
 nodeCount: 1
 environment:
   name: cnn_training
   python:
     userManagedDependencies: true
     interpreterPath: python
   docker:
     enabled: true
     baseImage: 54646eeace594cf19143dad3c7f31661.azurecr.io/azureml/azureml_b17300b63a1c2abb86b2e774835153ee
     sharedVolumes: true
     gpuSupport: false
     shmSize: 2g
     arguments: []
 history:
   outputCollection: true
   snapshotProject: true
   directoriesToWatch:
   - logs
 dataReferences:
   workspaceblobstore:
     dataStoreName: workspaceblobstore
     pathOnDataStore: dataname
     mode: download
     overwrite: true
     pathOnCompute:

Is there an additional configuration to be done for the disk full issue? Any Changes to be made in the .runconfig file?