Evaluation specifics

[piotrmigdalek]

Hi!

I'm trying to evaluate Mistral-7b based model with custom locality and portability data.
For each of 50 edits I have 6 locality prompts and 2 portability ones.

How should I arange the dicts to feed them into an edit function in that case? Will the variable below feeded to portability_inputs work as intended?

portability_inputs = {
    'english': {
        'prompt': df_port['question_en'].tolist(),
        'ground_truth': df_port['label_en'].tolist()
    },
    'polish': {
        'prompt': df_port['question_pl'].tolist(),
        'ground_truth': df_port['label_pl'].tolist()
    }
}

And a technical one, are the metrics calculated after each edit? If yes, is there an option to evaluate everything on the final model after 50 sequential edits?

Thank you :)

[pengzju]

Q1:

• Your usage is correct; just ensure that the number of items in the prompts and ground_truth under each dimension, such as "english" and "polish," are consistent.

• You can also check if the number of metrics recorded in the logs matches the number of input prompts.

Q2:

• I haven't implemented this feature yet, which allows for unified evaluation after full editing, but you can refer to the pseudocode in this Continual Editing  #220. I will improve this feature in the next version. Thank you!

[zxlzr]

Hi, do you have any further questions?