Model Card for T5-3B/SynQL-KaggleDBQA-Train-Run-01

Model Context

Example metadata can be found below, context represents the prompt that is presented to the model. Database schemas follow the encoding method proposed by Shaw et al (2020).

"query": "SELECT count(*) FROM singer",
"question": "How many singers do we have?",
"context": "How many singers do we have? | concert_singer | stadium : stadium_id, location, name, capacity, highest, lowest, average | singer : singer_id, name, country, song_name, song_release_year, age, is_male | concert : concert_id, concert_name, theme, stadium_id, year | singer_in_concert : concert_id, singer_id",
"db_id": "concert_singer",

Model Results

Evaluation set: KaggleDBQA/test

Evaluation metrics: [Execution Accuracy]

Model Data Run Execution Accuracy
T5-3B semiotic/SynQL-KaggleDBQA 00 0.3514
T5-3B semiotic/SynQL-KaggleDBQA 01 0.3514
T5-3B semiotic/SynQL-KaggleDBQA 02 0.3514
Downloads last month
10
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for semiotic/T5-3B-SynQL-KaggleDBQA-Train-Run-01

Base model

google-t5/t5-3b
Finetuned
(12)
this model

Dataset used to train semiotic/T5-3B-SynQL-KaggleDBQA-Train-Run-01