Common Sense Reasoning On Big Bench Sports
評価指標
Accuracy
評価結果
このベンチマークにおける各モデルのパフォーマンス結果
モデル名 | Accuracy | Paper Title | Repository |
|---|---|---|---|
| OPT 66B (few-shot, k=3) | 54.4 | BloombergGPT: A Large Language Model for Finance | - |
| GPT-NeoX (few-shot, k=3) | 53.2 | BloombergGPT: A Large Language Model for Finance | - |
| Bloomberg GPT (few-shot, k=3) | 62.8 | BloombergGPT: A Large Language Model for Finance | - |
| Chinchilla-70B (few-shot, k=5) | 71 | Training Compute-Optimal Large Language Models | |
| PaLM 2(few-shot, k=3, CoT) | 98 | PaLM 2 Technical Report | |
| Gopher-280B (few-shot, k=5) | 54.9 | Scaling Language Models: Methods, Analysis & Insights from Training Gopher | |
| PaLM 540B (few-shot, k=3) | 80.4 | BloombergGPT: A Large Language Model for Finance | - |
| PaLM 2 (few-shot, k=3, Direct) | 90.8 | PaLM 2 Technical Report |
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