metadata
dataset_info:
features:
- name: query
dtype: string
- name: doc
dtype: string
splits:
- name: train
num_bytes: 2351581
num_examples: 1235
- name: test
num_bytes: 8764166
num_examples: 3765
- name: validation
num_bytes: 7168991
num_examples: 3765
download_size: 9353279
dataset_size: 18284738
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
- split: validation
path: data/validation-*
Dataset Card for Apps-Retrieval-TR
Table of Contents
Dataset Description
Apps-Retrieval-TR dataset is obtained by translating the queries of AppsRetrieval into Turkish using GPT4.1.
Dataset Structure
The original dataset only had train and test splits. We applied the following splitting methodology to obtain validation and test splits:
- If a train-val-test split is available, we use the existing divisions as provided.
- For datasets with a train-test split only, we create a val split from the training set, sized to match the test set, and apply this across all models.
- In cases with a train-val split, we reassign the val set as the test split, then generate a new val split from the training data following the approach above.
- In cases with a val-test split, we split validation into train and val sets in 80% and 20% proportions, respectively.
- When only a single combined split is present, we partition the data into train, val, and test sets in 70%, 15%, and 15% proportions, respectively.
Data Fields
- query(string) : Problem definition
- doc(string) : Solution of the problem in form of code.