Description of task.
The goal of this template is to increase the ease of running evaluations by future contributors and improving automation.
Optional: Description on needed files.
- Date/Time in ISO Format
- [App/Model] (github commit link), version info.
- [Ground Truth/Golds Dataset] (github commit link/or describe where to get).
- [Prediction Dataset] (github commit link/or describe where to get)).
- [Evaluation Script] (github commit link).
Run command or instructionsthat generated the report.
Describe the needed file types. Recommended to use same format as report (above).
How they are inputted - path to local dir, url to a github commit, one by one or by batch? (should be batch)
Where are the needed files - which github dir for golds? (some are not publically accessible).
[!Note]: don't forget to set up a python environment for running the evaluation code.
In the future, to run the evaluation code as a module, run the following command while in the task_dir_name directory:
python3 -m evaluate -g <gold_url> -p <mmif_preds_dir> -r <result_file.txt>
# See `python3 evaluate --help` to check if there have been changes to the run command.
Currently, the run commands may differ, and are generally of this format:
# Example 1
python evaluate.py required-params-args
Format of result if needed.
Explanation of metrics can be in the report.txt or here.
Since different evaluation runs may have different metrics, its suggested to place this in the report.
- Document any special changes that may be needed to run the code
- Document any common errors/issues if they are not already error-handled.
- Document any notable history if needed.