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T5-3B-SynQL-Spider-Train-Run-00

Text Generation
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t5
text2text-generation
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T5-3B-SynQL-Spider-Train-Run-00 / README.md
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metadata
license: apache-2.0
pipeline_tag: text-generation
tags:
  - code
datasets:
  - semiotic/SynQL-Spider-Train
language:
  - en
base_model:
  - google-t5/t5-3b

Model Card for T5-3B/SynQL-Spider-Train-Run-00

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: Spider/dev

Evaluation metrics: [Test-Suite-Execution, Execution Accuracy]

Model Data Run Execution Accuracy Test-Suite Execution Accuracy
T5-3B semiotic/SynQL-Spider-Train 00 0.7021 0.5996
T5-3B semiotic/SynQL-Spider-Train 01 0.6992 0.5464
T5-3B semiotic/SynQL-Spider-Train 02 0.7002 0.5861