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IEETA/
BioASQ-14B

Name: BioASQ-14B
Availability: InStock

information-retrieval

apache-2.0

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BioASQ Phase A Reranker Models

Fine-tuned rerankers for biomedical document retrieval, trained on BioASQ data. All models are cross-encoders fine-tuned from publicly available base models.

Loading a model

python

from transformers import AutoTokenizer, AutoModelForSequenceClassification

subfolder = "nvidia-llama-nemotron-rerank-1b-v2-E2-S4-Mmulti_neg_pairwise-Linfonce-FullData"
tokenizer = AutoTokenizer.from_pretrained("IEETA/BioASQ-14B", subfolder=subfolder)
model = AutoModelForSequenceClassification.from_pretrained("IEETA/BioASQ-14B", subfolder=subfolder)

For nvidia/llama-nemotron variants, also copy llama_bidirectional_model.py from the subfolder and pass trust_remote_code=True.

outputs-E5-Pairwise — Shifter sampler, 5 epochs, pairwise

Model	Path	map-bioasq@10
nvidia/llama-nemotron-rerank-1b-v2	`nvidia-llama-nemotron-rerank-1b-v2-E5-Pairwise`	0.9970
BAAI/bge-reranker-v2-m3	`BAAI-bge-reranker-v2-m3-E5-Pairwise`	0.6824
BAAI/bge-reranker-base	`BAAI-bge-reranker-base-E5-Pairwise`	0.6686
nboost/pt-biobert-base-msmarco	`nboost-pt-biobert-base-msmarco-E5-Pairwise`	0.6608
cross-encoder/ms-marco-MiniLM-L-6-v2	`cross-encoder-ms-marco-MiniLM-L-6-v2-E5-Pairwise`	0.6373
ncbi/MedCPT-Cross-Encoder	`ncbi-MedCPT-Cross-Encoder-E5-Pairwise`	0.6404
michiyasunaga/BioLinkBERT-base	`michiyasunaga-BioLinkBERT-base-E5-Pairwise`	0.6403
monologg/biobert_v1.1_pubmed	`monologg-biobert_v1.1_pubmed-E5-Pairwise`	0.6346
microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext	`microsoft-BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext-E5-Pairwise`	0.6291
pritamdeka/S-PubMedBert-MS-MARCO	`pritamdeka-S-PubMedBert-MS-MARCO-E5-Pairwise`	0.5985
allenai/specter2_base	`allenai-specter2_base-E5-Pairwise`	0.5912
dmis-lab/biobert-base-cased-v1.2	`dmis-lab-biobert-base-cased-v1.2-E5-Pairwise`	0.5848
cross-encoder/ms-marco-electra-base	`cross-encoder-ms-marco-electra-base-E5-Pairwise`	0.5654
emilyalsentzer/Bio_ClinicalBERT	`emilyalsentzer-Bio_ClinicalBERT-E5-Pairwise`	0.4587
cambridgeltl/SapBERT-from-PubMedBERT-fulltext	`cambridgeltl-SapBERT-from-PubMedBERT-fulltext-E5-Pairwise`	0.2594

outputs — Experiments

Model	Characteristics	Path	map-bioasq@10
nvidia/llama-nemotron-rerank-1b-v2	E2-S4, multi_neg_pairwise, InfoNCE, FullData	`nvidia-llama-nemotron-rerank-1b-v2-E2-S4-Mmulti_neg_pairwise-Linfonce-FullData`	0.9995
nvidia/llama-nemotron-rerank-1b-v2	E2, pairwise (13B1+13B2)	`nvidia-llama-nemotron-rerank-1b-v2_llama-E2-Pairwise`	0.9970
BAAI/bge-reranker-v2-m3	E2-S1, pairwise, FullData, shifter	`BAAI-bge-reranker-v2-m3-E2-S1-Mpairwise-FullDataTrue`	0.6705
BAAI/bge-reranker-base	E2-S1, pairwise, FullData, shifter	`BAAI-bge-reranker-base-E2-S1-Mpairwise-FullDataTrue`	0.6489
nboost/pt-biobert-base-msmarco	E2-S1, pairwise, FullData, shifter	`nboost-pt-biobert-base-msmarco-E2-S1-Mpairwise-FullDataTrue`	0.6274
ncbi/MedCPT-Cross-Encoder	E2-S1, pairwise, FullData, shifter	`ncbi-MedCPT-Cross-Encoder-E2-S1-Mpairwise-FullDataTrue`	0.6251
michiyasunaga/BioLinkBERT-base	E2-S1, pairwise, FullData, shifter	`michiyasunaga-BioLinkBERT-base-E2-S1-Mpairwise-FullDataTrue`	0.6178
microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext	E2-S1, pairwise, FullData, shifter	`microsoft-BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext-E2-S1-Mpairwise-FullDataTrue`	0.6153
cross-encoder/ms-marco-MiniLM-L-6-v2	E3-S8, multi_neg_pairwise	`cross-encoder-ms-marco-MiniLM-L-6-v2-E3-S8-Mmulti_neg_pairwise`	0.6098
monologg/biobert_v1.1_pubmed	E2-S1, pairwise, FullData, shifter	`monologg-biobert_v1.1_pubmed-E2-S1-Mpairwise-FullDataTrue`	0.6053
cross-encoder/ms-marco-MiniLM-L-6-v2	E2-S1, pairwise, FullData, shifter	`cross-encoder-ms-marco-MiniLM-L-6-v2-E2-S1-Mpairwise-FullDataTrue`	0.5944
pritamdeka/S-PubMedBert-MS-MARCO	E2-S1, pairwise, FullData, shifter	`pritamdeka-S-PubMedBert-MS-MARCO-E2-S1-Mpairwise-FullDataTrue`	0.5839
michiyasunaga/BioLinkBERT-large	E2-S1, pairwise, FullData, shifter	`michiyasunaga-BioLinkBERT-large-E2-S1-Mpairwise-FullDataTrue`	0.5781
ncbi/MedCPT-Cross-Encoder	E3-S1, pairwise, FullData, shifter	`ncbi-MedCPT-Cross-Encoder-E3-S1-Mpairwise-FullDataTrue`	0.5766