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Project description

NL2SQLEvaluator

Roadmap

  • Add MySQL database executor
  • Add Precision, Recall, F1 metrics for ambiguity Text2SQL datasets

👷🏼‍♂️ Work in progress

Configuration Guide

🔧 Use a YAML config (with CLI overrides)

Run your experiment with a config file:

nl2sql_eval --config path/to/config.yaml

Example config.yaml

# Core
output_dir: ./outputs
seed: 42

# Dataset
relative_db_base_path: data/bird_dev/dev_databases
dataset_path: simone-papicchio/bird
dataset_name: bird-dev

# Model
model_name: Qwen3-Coder-30B
model: Qwen/Qwen3-Coder-30B-A3B-Instruct
temperature: 0.7
top_p: 0.8
top_k: 20
repetition_penalty: 1.05
max_tokens: 32000

# Weights & Biases
project: text2sql-eval
entity: spapicchio-politecnico-di-torino   # or your team
group: evals
mode: online                               # or "offline" on clusters without net
tags: [eval, seg]
notes: ""
job_type: eval

Override any value from the CLI

Command-line flags take precedence over the YAML:

nl2sql_eval --config config.yaml \
  --output_dir ./outputs/run-42 \
  --mode offline \
  --temperature 0.2 \
  --max_tokens 4096 \
  --tags eval --tags ablation

Notes

  • The config is flat (all keys at top level) so it works smoothly with the parser.
  • Lists (e.g., tags) can be provided in YAML or by repeating the flag in CLI (--tags ... multiple times).
  • Booleans accept true/false in YAML and --flag true/false in CLI.
  • This package uses TRL’s TRLParser / HF’s HfArgumentParser under the hood, so the same configuration behaviors apply.

This package relies on TrlParser so all the configurations available there can be used as well.

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