--- task_categories: - translation --- # AutoTrain Dataset for project: xx ## Dataset Description This dataset has been automatically processed by AutoTrain for project xx. ### Languages The BCP-47 code for the dataset's language is unk. ## Dataset Structure ### Data Instances A sample from this dataset looks as follows: ```json [ { "feat_db_id": "department_management", "target": "SELECT count(*) FROM head WHERE age > 56", "source": "How many heads of the departments are older than 56 ?", "feat_query_toks": [ "SELECT", "count", "(", "*", ")", "FROM", "head", "WHERE", "age", ">", "56" ], "feat_query_toks_no_value": [ "select", "count", "(", "*", ")", "from", "head", "where", "age", ">", "value" ], "feat_question_toks": [ "How", "many", "heads", "of", "the", "departments", "are", "older", "than", "56", "?" ] }, { "feat_db_id": "department_management", "target": "SELECT name , born_state , age FROM head ORDER BY age", "source": "List the name, born state and age of the heads of departments ordered by age.", "feat_query_toks": [ "SELECT", "name", ",", "born_state", ",", "age", "FROM", "head", "ORDER", "BY", "age" ], "feat_query_toks_no_value": [ "select", "name", ",", "born_state", ",", "age", "from", "head", "order", "by", "age" ], "feat_question_toks": [ "List", "the", "name", ",", "born", "state", "and", "age", "of", "the", "heads", "of", "departments", "ordered", "by", "age", "." ] } ] ``` ### Dataset Fields The dataset has the following fields (also called "features"): ```json { "feat_db_id": "Value(dtype='string', id=None)", "target": "Value(dtype='string', id=None)", "source": "Value(dtype='string', id=None)", "feat_query_toks": "Sequence(feature=Value(dtype='string', id=None), length=-1, id=None)", "feat_query_toks_no_value": "Sequence(feature=Value(dtype='string', id=None), length=-1, id=None)", "feat_question_toks": "Sequence(feature=Value(dtype='string', id=None), length=-1, id=None)" } ``` ### Dataset Splits This dataset is split into a train and validation split. The split sizes are as follow: | Split name | Num samples | | ------------ | ------------------- | | train | 1001 | | valid | 1001 |