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Arena-Hard Auto

Automate the evaluation of large language models for instruction-following and open-ended generation. Use Arena-Hard Auto, a benchmark derived from Chatbot Arena, to quickly assess and compare model performance against established standards.

intermediate30 min5 steps

The play

Install Arena-Hard Auto
Set up your environment and install the Arena-Hard Auto evaluation framework or library.
Prepare Evaluation Data
Format your model's prompts and outputs into the required input structure, typically a JSONL file with prompts and corresponding model responses.
Define Evaluation Configuration
Specify evaluation metrics, reference models, or specific benchmark subsets via a configuration file (e.g., YAML) or command-line arguments.
Run Automated Benchmark
Execute the Arena-Hard Auto tool with your prepared data and defined configuration to start the evaluation process.
Interpret Results
Analyze the generated evaluation report, which will contain scores, metrics, and potentially qualitative feedback on your model's performance against the benchmark.

Starter code

arena-hard-auto run --data-file your_model_outputs.jsonl --config default_eval.yaml --output-file evaluation_report.json

Source

Articlelmarena.ai