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.
5 Steps
- 1
Install Arena-Hard Auto: Set up your environment and install the Arena-Hard Auto evaluation framework or library.
- 2
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.
- 3
Define Evaluation Configuration: Specify evaluation metrics, reference models, or specific benchmark subsets via a configuration file (e.g., YAML) or command-line arguments.
- 4
Run Automated Benchmark: Execute the Arena-Hard Auto tool with your prepared data and defined configuration to start the evaluation process.
- 5
Interpret Results: Analyze the generated evaluation report, which will contain scores, metrics, and potentially qualitative feedback on your model's performance against the benchmark.
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