File size: 3,654 Bytes
99b51ef 98c9bf1 99b51ef d6f730f 3540643 fba4518 98c9bf1 3c6d390 98c9bf1 3c6d390 98c9bf1 3c6d390 98c9bf1 3c6d390 98c9bf1 3c6d390 99b51ef fba4518 98c9bf1 99b51ef ca6840e 61a6d06 ca6840e de8f30c ca6840e de8f30c ca6840e de8f30c ca6840e |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 |
---
dataset_info:
- config_name: default
features:
- name: utterance
dtype: string
- name: label
dtype: int64
splits:
- name: train
num_bytes: 715028
num_examples: 10003
- name: test
num_bytes: 204010
num_examples: 3080
download_size: 757238
dataset_size: 919038
- config_name: intents
features:
- name: id
dtype: int64
- name: name
dtype: string
- name: tags
sequence: 'null'
- name: regex_full_match
sequence: 'null'
- name: regex_partial_match
sequence: 'null'
- name: description
dtype: string
splits:
- name: intents
num_bytes: 8957
num_examples: 77
download_size: 7838
dataset_size: 8957
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
- config_name: intents
data_files:
- split: intents
path: intents/intents-*
---
# 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](https://deeppavlov.github.io/AutoIntent/index.html).
## Usage
It is intended to be used with our [AutoIntent Library](https://deeppavlov.github.io/AutoIntent/index.html):
```python
from autointent import Dataset
banking77 = Dataset.from_hub("AutoIntent/banking77")
```
## Source
This dataset is taken from `PolyAI/banking77` and formatted with our [AutoIntent Library](https://deeppavlov.github.io/AutoIntent/index.html):
```python
"""Convert events dataset to autointent internal format and scheme."""
import json
import requests
from datasets import Dataset as HFDataset
from datasets import load_dataset
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:
target_list = classwise_samples[sample["label"]]
if shots_per_intent is not None and len(target_list) >= shots_per_intent:
continue
target_list.append(Sample(utterance=sample["text"], label=sample["label"]))
samples = [sample for samples_from_one_class in classwise_samples for sample in samples_from_one_class]
print(f"{len(samples)=}")
return samples
if __name__ == "__main__":
intents_data = get_intents_data()
banking77 = load_dataset("PolyAI/banking77", trust_remote_code=True)
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}
)
```
|