Shawn’s Blog
  • 🗂️ Collections
    • 🖥️ Slides Gallery
    • 💻 LeetCode Notes
    • 🧑‍🍳️ Cooking Ideas
    • 🍱 Cookbook
    • 💬 Language Learning
    • 🎼 Songbook
  • ⚙️ Projects
    • ⚛ Continual Learning Arena
  • 📄 Papers
    • AdaHAT
    • FG-AdaHAT
  • 🎓 CV
    • CV (English)
    • CV (Mandarin)
    • CV (Mandarin, Long Version)
  • About
  1. Multi-Task Learning (MTL)
  2. Output Results
  • Welcome to CLArena
  • Getting Started
  • Configure Pipelines
  • Continual Learning (CL)
    • CL Main Experiment
    • Save and Evaluate Model
    • Full Experiment
    • Output Results
  • Continual Unlearning (CUL)
    • CUL Main Experiment
    • Full Experiment
    • Output Results
  • Multi-Task Learning (MTL)
    • MTL Experiment
    • Save and Evaluate Model
    • Output Results
  • Single-Task Learning (STL)
    • STL Experiment
    • Save and Evaluate Model
    • Output Results
  • Components
    • CL Dataset
    • MTL Dataset
    • STL Dataset
    • CL Algorithm
    • CUL Algorithm
    • MTL Algorithm
    • STL Algorithm
    • Backbone Network
    • Optimizer
    • Learning Rate Scheduler
    • Trainer
    • Metrics
    • Lightning Loggers
    • Callbacks
    • Other Configs
  • Custom Implementation
    • CL Dataset
    • MTL Dataset
    • STL Dataset
    • CL Algorithm
    • CUL Algorithm
    • MTL Algorithm
    • STL Algorithm
    • Backbone Network
    • Callback
  • API Reference
  • FAQs
  1. Multi-Task Learning (MTL)
  2. Output Results

Output Results (MTL)

Modified

October 6, 2025

This page summarizes the output results of multi-task learning experiment and evaluation pipelines. Their existence, file or folder names, and formats can be customized.

The following output results are produced after running multi-task learning experiment or multi-task learning evaluation.

Folder or File Description Customization
<output_dir>/ Contains all output results
  • <output_dir>: Field output_dir in the index config
<acc_save_dir>/ Contains all data and figures of test accuracy metrics
  • To include or exclude these outputs, enable or disable MTLAccuracy metric callback (see Configure Metrics)

  • <acc_save_dir>: Field save_dir in MTLAccuracy. It is recommended to be set as ${output_dir}/results/ to make sure outputs are under <output_dir>/

<acc_save_dir>/acc.csv The original data of test accuracy metrics, stored as CSV format. It contains accuracy of all tasks and average accuracy
  • acc.csv: Field test_acc_csv_name in MTLAccuracy. Default is acc.csv
<acc_save_dir>/acc.png Bar charts for test accuracy of all tasks
  • ave_acc.png: Field test_acc_plot_name in MTLAccuracy

  • To exclude this output, set this field to null or remove this field

<loss_cls_save_dir>/ Contains all data and figures of test classification loss metrics
  • To include or exclude these outputs, enable or disable MTLLoss metric callback (see Configure Metrics)

  • <loss_cls_save_dir>: Field save_dir in MTLLoss. It is recommended to be set as ${output_dir}/results/ to make sure outputs are under <output_dir>/

<loss_cls_save_dir>/loss_cls.csv The original data of test classification loss metrics, stored as CSV format. It contains classification loss of all tasks and average classification loss
  • loss_cls.csv: Field test_loss_cls_csv_name in MTLLoss. Default is loss_cls.csv
<loss_cls_save_dir>/loss_cls.png Bar charts for test classification loss of all tasks
  • ave_loss_cls.png: Field test_loss_cls_csv_name in MTLLoss

  • To exclude this output, set this field to null or remove this field

<output_dir>/lightning_logs/csv/ Training and validation metrics logged to Lightning CSV logger in real time. Please refer to my article about CL metrics to learn about training and validation metrics in continual learning
  • To include or exclude these outputs, enable or disable Lightning CSV logger (see Configure Lightning Loggers)
<output_dir>/lightning_logs/tensorboard Output files for Lightning TensorBoard logger
  • To include or exclude these outputs, enable or disable Lightning TensorBoard logger (see Configure Lightning Loggers)
<output_dir>/lightning_logs/wandb Output files for Lightning Weights & Biases logger
  • To include or exclude these outputs, enable or disable Lightning Weights & Biases logger (see Configure Lightning Loggers)
<samples_save_dir>/ Contains input samples of first batch
  • To include or exclude these outputs, enable or disable SaveFirstBatchImages callback (see Configure Callbacks)

  • <samples_save_dir>: Field save_dir in SaveFirstBatchImages. It is recommended to be set as ${output_dir}/samples/ to make sure outputs are under <output_dir>/

<saved_models_dir>/ Contains saved model
  • To include or exclude these outputs, enable or disable SaveModels (see Configure Callbacks)
  • <saved_models_dir>: Field save_dir in SaveModels. It is recommended to be set as ${output_dir}/saved_model/ to make sure outputs are under <output_dir>/
<profile_dir>/ Contains profiling results
  • To include or exclude these outputs, enable or disable profiler in Trainer (see Configure Trainer(s))
config_tree.log Full copy of the experiment config in tree format
  • To include or exclude this output, set save as true or false in config tree config (see Other Configs)

  • config_tree.log: Field save_path in config tree config. It is recommended to be set as ${output_dir}/ to make sure outputs are under <output_dir>/

console.log Full logs of the console log in text format
  • To include or exclude this output, include or exclude the config field below in Hydra config (see Other Configs)

  • console.log: the filename config in the Hydra config. It is recommended to be set as ${hydra.runtime.output_dir}/ to make sure outputs are under <output_dir>/

    job_logging:
     handlers:
        file:
          filename: ${hydra.runtime.output_dir}/console.log
Back to top
Save and Evaluate Model
Single-Task Learning (STL)
 
 

©️ 2025 Pengxiang Wang. All rights reserved.