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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/falsein YAML and--flag true/falsein CLI. - This package uses TRL’s
TRLParser/ HF’sHfArgumentParserunder 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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