learned_hands_courts
- Task Description: Classify if a user post implicates legal issues related to courts.
- Task Type: Binary classification
- Document Type: legal question
- Number of Samples: 198
- Input Length Range: 54-1235 tokens
- Evaluation Metrics: accuracy (maximize), balanced_accuracy (maximize), f1_macro (maximize), f1_micro (maximize), valid_predictions_ratio (maximize)
- Tags: court law, issue spotting
- Paper: LegalBench: A Collaboratively Built Benchmark for Measuring Legal Reasoning in Large Language Models
- Dataset Download: https://hazyresearch.stanford.edu/legalbench/
7 submissions
| Rank | Model | accuracy | balanced_accuracy | f1_macro | f1_micro | valid_predictions_ratio | Date | Results |
|---|---|---|---|---|---|---|---|---|
| 1 | claude-3-5-haiku-20241022 | 0.589 | 0.589 | 0.546 | 0.589 | 1.000 | 2025-08-01 | View |
| 2 | meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo | 0.539 | 0.539 | 0.436 | 0.539 | 0.938 | 2025-07-25 | View |
| 3 | claude-3-haiku-20240307 | 0.532 | 0.527 | 0.445 | 0.532 | 0.990 | 2025-07-25 | View |
| 4 | meta-llama/Meta-Llama-3.1-405B-Instruct-Turbo | 0.510 | 0.510 | 0.408 | 0.510 | 1.000 | 2025-08-01 | View |
| 5 | gpt-4o-mini | 0.495 | 0.495 | 0.331 | 0.495 | 1.000 | 2025-07-02 | View |
| 6 | gpt-4.1-nano | 0.484 | 0.484 | 0.445 | 0.484 | 1.000 | 2025-07-03 | View |
| 7 | google/gemma-2-27b-it | 0.474 | 0.474 | 0.330 | 0.474 | 1.000 | 2025-07-24 | View |