Question Answering On Fiqa 2018 Beir
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nDCG@10
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
Modellname | nDCG@10 | Paper Title | Repository |
|---|---|---|---|
| monoT5-3B | 0.513 | No Parameter Left Behind: How Distillation and Model Size Affect Zero-Shot Retrieval | |
| BM25+CE | 0.347 | BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Models | |
| SGPT-BE-5.8B | 0.372 | SGPT: GPT Sentence Embeddings for Semantic Search | |
| SGPT-CE-6.1B | 0.401 | SGPT: GPT Sentence Embeddings for Semantic Search |
0 of 4 row(s) selected.