fix: Add Touche2020v3 and JMTEB

[Samoed]

Checklist

• Run tests locally to make sure nothing is broken using make test.
• Run the formatter to format the code using make lint.

Adding datasets checklist

Reason for dataset addition: #749 #1170

• I have run the following models on the task (adding the results to the pr). These can be run using the mteb -m {model_name} -t {task_name} command.
  • facebook/contriver
    • Touche2020v3.json
  • intfloat/multilingual-e5-small
    JMTEB leaderboard to compare. I ran MrTidyRetrieval only for Bengali, as the Japanese version has 7M documents in context to encode. Overall, the results are similar, with the main difference caused by that JMTEB doesn't include titles.
    • MrTidyRetrieval.json
    • ESCIReranking.json
    • JaqketRetrieval.json
• I have checked that the performance is neither trivial (both models gain close to perfect scores) nor random (both models gain close to random scores).
• If the dataset is too big (e.g. >2048 examples), considering using self.stratified_subsampling() under dataset_transform()
• I have filled out the metadata object in the dataset file (find documentation on it here).
• Run tests locally to make sure nothing is broken using make test.
• Run the formatter to format the code using make lint.

[KennethEnevoldsen]

Wonderful thanks for doing this!

We should also add JMTEB to the benchmarks.py file

[Samoed]

@KennethEnevoldsen runner hanged up. Found this issue in python action actions/setup-python#806