Multiple Choice Question Answering Mcqa On 28
Metriken
Accuracy
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
Modellname | Accuracy | Paper Title | Repository |
|---|---|---|---|
| GPT-NeoX (few-shot, k=3) | 86.4 | BloombergGPT: A Large Language Model for Finance | - |
| OPT 66B (few-shot, k=3) | 91.2 | BloombergGPT: A Large Language Model for Finance | - |
| Gopher-280B (few-shot, k=5) | 50.5 | Scaling Language Models: Methods, Analysis & Insights from Training Gopher | |
| BLOOM 176B (few-shot, k=3) | 91.2 | BloombergGPT: A Large Language Model for Finance | - |
| Chinchilla-70B (few-shot, k=5) | 75.6 | Training Compute-Optimal Large Language Models | |
| PaLM 2 (few-shot, k=3, Direct) | 93.6 | PaLM 2 Technical Report | |
| Bloomberg GPT (few-shot, k=3) | 90.4 | BloombergGPT: A Large Language Model for Finance | - |
| PaLM 2 (few-shot, k=3, CoT) | 94.4 | PaLM 2 Technical Report | |
| PaLM 540B (few-shot, k=3) | 87.2 | BloombergGPT: A Large Language Model for Finance | - |
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