DeepPavlov/banking77_ru

Russian banking77

This is a text classification dataset. It is intended for machine learning research and experimentation.

This dataset is obtained via formatting another publicly available data to be compatible with our AutoIntent Library.

Usage

It is intended to be used with our AutoIntent Library:

from autointent import Dataset

banking77_ru = Dataset.from_hub("AutoIntent/banking77_ru")

Source

This dataset is taken from github private repository LadaNikitina/RuBanking77 and formatted with our AutoIntent Library:

"""Convert banking77 dataset to autointent internal format and scheme."""  # noqa: INP001

import json

import requests
from datasets import Dataset as HFDataset
from datasets import load_from_disk

from autointent import Dataset
from autointent.schemas import Intent, Sample


def get_intents_data(github_file: str | None = None) -> list[Intent]:
    """Load specific json from HF repo."""
    github_file = github_file or "https://huggingface.co/datasets/PolyAI/banking77/resolve/main/dataset_infos.json"
    raw_text = requests.get(github_file, timeout=5).text
    dataset_description = json.loads(raw_text)
    intent_names = dataset_description["default"]["features"]["label"]["names"]
    return [Intent(id=i, name=name) for i, name in enumerate(intent_names)]


def convert_banking77(
    banking77_split: HFDataset, intents_data: list[Intent], shots_per_intent: int | None = None
) -> list[Sample]:
    """Convert one split into desired format."""
    all_labels = sorted(banking77_split.unique("label"))
    n_classes = len(intents_data)
    if all_labels != list(range(n_classes)):
        msg = "Something's wrong"
        raise ValueError(msg)

    classwise_samples = [[] for _ in range(n_classes)]

    for sample in banking77_split:
        txt, intent_id = sample["text"], sample["label"]
        target_list = classwise_samples[intent_id]
        if shots_per_intent is not None and len(target_list) >= shots_per_intent:
            continue
        target_list.append({"utterance": txt, "label": intent_id})

    return [Sample(**sample) for samples_from_one_class in classwise_samples for sample in samples_from_one_class]


if __name__ == "__main__":
    intents_data = get_intents_data()

    # load dataset
    # ! git clone git@github.com:LadaNikitina/RuBanking77 "data/RuBanking77"
    # ! rm -rf data/RuBanking77/.git
    banking77 = load_from_disk("data/RuBanking77")

    train_samples = convert_banking77(banking77["train"], intents_data=intents_data)
    test_samples = convert_banking77(banking77["test"], intents_data=intents_data)

    banking77_converted = Dataset.from_dict({"train": train_samples, "test": test_samples, "intents": intents_data})