---
license: apache-2.0
base_model: Salesforce/codet5-small
tags:
- generated_from_trainer
model-index:
- name: sodabot-sql-sm
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# sql-sodabot-v1.0

This encoder-decoder model is a descendent of [Salesforce/codet5-small](https://huggingface.co/Salesforce/codet5-small), fine-tuned on a modified version of [b-mc2/sql-create-context](https://huggingface.co/datasets/b-mc2/sql-create-context) data. The original [CodeT5](https://github.com/salesforce/CodeT5) was published by Salesfoce Research as an "AI-powered coding assistant to boost the productivity of software developers". The goal of this project is to apply transfer learning in order to appropriate this model for text-to-SQL applications, specifically in the context of generating Socrata SQL ([SoQL](https://dev.socrata.com/docs/queries/)) queries that can be executed on the Socrata Open Data API (e.g., to analyze [NYC Open Data](https://opendata.cityofnewyork.us)).

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 25

### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0