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EN
Cde Small V1
C
Cde Small V1
Developed by OrcaDB
cde-small-v1 is a small sentence embedding model based on transformer architecture, excelling in multiple text classification, clustering, and retrieval tasks.
Downloads 90.62k
Release Time : 11/8/2024
Model Overview
This model is primarily used for text classification, clustering, and retrieval tasks, supporting English text processing, with strong performance in MTEB benchmark tests.
Model Features
Excellent Multitask Performance
Performs well in various tasks including text classification, clustering, and retrieval
Efficient Small Model
As a small model, it maintains high efficiency while preserving performance
MTEB Benchmark Verified
Comprehensively evaluated on multiple MTEB benchmark datasets
Model Capabilities
Text classification
Text clustering
Information retrieval
Sentence similarity calculation
Text reranking
Use Cases
E-commerce
Amazon Review Classification
Sentiment analysis and classification of Amazon product reviews
Achieved 94.66% accuracy on Amazon polarity classification task
Counterfactual Review Identification
Identifying counterfactual reviews on Amazon
Achieved 87.03% accuracy on Amazon counterfactual classification task
Finance
Bank Customer Service Classification
Classifying bank customer inquiries
Achieved 88.58% accuracy on Banking77 dataset
Academic Research
Paper Clustering
Topic clustering of academic papers
Achieved 48.63 V-measure on arXiv paper clustering task
🚀 cde-small-v1
The cde-small-v1 model is a powerful tool in natural language processing, offering high - performance results across multiple classification, retrieval, clustering, reranking, and semantic textual similarity tasks.
📚 Documentation
Model Performance Metrics
The following table presents the performance of the cde-small-v1 model on various datasets:
| Dataset Name | Task Type | Metrics | Value |
|---|---|---|---|
| MTEB AmazonCounterfactualClassification (en) | Classification | accuracy | 87.02985074626866 |
| MTEB AmazonCounterfactualClassification (en) | Classification | ap | 56.706190238632956 |
| MTEB AmazonCounterfactualClassification (en) | Classification | ap_weighted | 56.706190238632956 |
| MTEB AmazonCounterfactualClassification (en) | Classification | f1 | 81.93161953007674 |
| MTEB AmazonCounterfactualClassification (en) | Classification | f1_weighted | 87.7650174177188 |
| MTEB AmazonCounterfactualClassification (en) | Classification | main_score | 87.02985074626866 |
| MTEB AmazonPolarityClassification (default) | Classification | accuracy | 94.664175 |
| MTEB AmazonPolarityClassification (default) | Classification | ap | 91.68668057762052 |
| MTEB AmazonPolarityClassification (default) | Classification | ap_weighted | 91.68668057762052 |
| MTEB AmazonPolarityClassification (default) | Classification | f1 | 94.65859470333152 |
| MTEB AmazonPolarityClassification (default) | Classification | f1_weighted | 94.65859470333152 |
| MTEB AmazonPolarityClassification (default) | Classification | main_score | 94.664175 |
| MTEB AmazonReviewsClassification (en) | Classification | accuracy | 55.762 |
| MTEB AmazonReviewsClassification (en) | Classification | f1 | 55.06427827477677 |
| MTEB AmazonReviewsClassification (en) | Classification | f1_weighted | 55.06427827477677 |
| MTEB AmazonReviewsClassification (en) | Classification | main_score | 55.762 |
| MTEB ArguAna (default) | Retrieval | main_score | 71.99600000000001 |
| MTEB ArguAna (default) | Retrieval | map_at_1 | 49.004 |
| MTEB ArguAna (default) | Retrieval | map_at_10 | 64.741 |
| MTEB ArguAna (default) | Retrieval | map_at_100 | 65.045 |
| MTEB ArguAna (default) | Retrieval | map_at_1000 | 65.048 |
| MTEB ArguAna (default) | Retrieval | map_at_20 | 64.999 |
| MTEB ArguAna (default) | Retrieval | map_at_3 | 61.344 |
| MTEB ArguAna (default) | Retrieval | map_at_5 | 63.595 |
| MTEB ArguAna (default) | Retrieval | mrr_at_1 | 50.71123755334281 |
| MTEB ArguAna (default) | Retrieval | mrr_at_10 | 65.32688703741336 |
| MTEB ArguAna (default) | Retrieval | mrr_at_100 | 65.63793917015693 |
| MTEB ArguAna (default) | Retrieval | mrr_at_1000 | 65.64038101143724 |
| MTEB ArguAna (default) | Retrieval | mrr_at_20 | 65.59178002869953 |
| MTEB ArguAna (default) | Retrieval | mrr_at_3 | 61.960644855381695 |
| MTEB ArguAna (default) | Retrieval | mrr_at_5 | 64.12636320531058 |
| MTEB ArguAna (default) | Retrieval | nauc_map_at_1000_diff1 | 15.961240220366024 |
| MTEB ArguAna (default) | Retrieval | nauc_map_at_1000_max | -7.44765810583741 |
| MTEB ArguAna (default) | Retrieval | nauc_map_at_1000_std | -17.07167824225605 |
| MTEB ArguAna (default) | Retrieval | nauc_map_at_100_diff1 | 15.965616911760689 |
| MTEB ArguAna (default) | Retrieval | nauc_map_at_100_max | -7.440609797442297 |
| MTEB ArguAna (default) | Retrieval | nauc_map_at_100_std | -17.069175070766125 |
| MTEB ArguAna (default) | Retrieval | nauc_map_at_10_diff1 | 16.0053641689455 |
| MTEB ArguAna (default) | Retrieval | nauc_map_at_10_max | -7.292003400856069 |
| MTEB ArguAna (default) | Retrieval | nauc_map_at_10_std | -17.21891231777586 |
| MTEB ArguAna (default) | Retrieval | nauc_map_at_1_diff1 | 16.775859614223965 |
| MTEB ArguAna (default) | Retrieval | nauc_map_at_1_max | -10.812150486389175 |
| MTEB ArguAna (default) | Retrieval | nauc_map_at_1_std | -18.447209756110635 |
| MTEB ArguAna (default) | Retrieval | nauc_map_at_20_diff1 | 16.00477985164213 |
| MTEB ArguAna (default) | Retrieval | nauc_map_at_20_max | -7.344399709169316 |
| MTEB ArguAna (default) | Retrieval | nauc_map_at_20_std | -17.011815937847548 |
| MTEB ArguAna (default) | Retrieval | nauc_map_at_3_diff1 | 15.730294091913994 |
| MTEB ArguAna (default) | Retrieval | nauc_map_at_3_max | -7.13902722192326 |
| MTEB ArguAna (default) | Retrieval | nauc_map_at_3_std | -16.846251134000045 |
| MTEB ArguAna (default) | Retrieval | nauc_map_at_5_diff1 | 15.952653874864062 |
| MTEB ArguAna (default) | Retrieval | nauc_map_at_5_max | -6.730509527119155 |
| MTEB ArguAna (default) | Retrieval | nauc_map_at_5_std | -16.586379153220353 |
| MTEB ArguAna (default) | Retrieval | nauc_mrr_at_1000_diff1 | 10.221278338563085 |
| MTEB ArguAna (default) | Retrieval | nauc_mrr_at_1000_max | -10.513831642963527 |
| MTEB ArguAna (default) | Retrieval | nauc_mrr_at_1000_std | -16.340880407651863 |
| MTEB ArguAna (default) | Retrieval | nauc_mrr_at_100_diff1 | 10.226217465992063 |
| MTEB ArguAna (default) | Retrieval | nauc_mrr_at_100_max | -10.506478667638874 |
| MTEB ArguAna (default) | Retrieval | nauc_mrr_at_100_std | -16.33847358633176 |
| MTEB ArguAna (default) | Retrieval | nauc_mrr_at_10_diff1 | 10.293491655887369 |
| MTEB ArguAna (default) | Retrieval | nauc_mrr_at_10_max | -10.357229664747909 |
| MTEB ArguAna (default) | Retrieval | nauc_mrr_at_10_std | -16.496874845739885 |
| MTEB ArguAna (default) | Retrieval | nauc_mrr_at_1_diff1 | 12.049863016253427 |
| MTEB ArguAna (default) | Retrieval | nauc_mrr_at_1_max | -11.968579522299635 |
| MTEB ArguAna (default) | Retrieval | nauc_mrr_at_1_std | -16.65245790056632 |
| MTEB ArguAna (default) | Retrieval | nauc_mrr_at_20_diff1 | 10.276109067921565 |
| MTEB ArguAna (default) | Retrieval | nauc_mrr_at_20_max | -10.404100283652397 |
| MTEB ArguAna (default) | Retrieval | nauc_mrr_at_20_std | -16.282098762560164 |
| MTEB ArguAna (default) | Retrieval | nauc_mrr_at_3_diff1 | 10.338008940592475 |
| MTEB ArguAna (default) | Retrieval | nauc_mrr_at_3_max | -10.123508259477648 |
| MTEB ArguAna (default) | Retrieval | nauc_mrr_at_3_std | -16.218834894850918 |
| MTEB ArguAna (default) | Retrieval | nauc_mrr_at_5_diff1 | 10.114375457049043 |
| MTEB ArguAna (default) | Retrieval | nauc_mrr_at_5_max | -9.987361588255437 |
| MTEB ArguAna (default) | Retrieval | nauc_mrr_at_5_std | -15.723897501895118 |
| MTEB ArguAna (default) | Retrieval | nauc_ndcg_at_1000_diff1 | 16.00889445347496 |
| MTEB ArguAna (default) | Retrieval | nauc_ndcg_at_1000_max | -6.746746500535893 |
| MTEB ArguAna (default) | Retrieval | nauc_ndcg_at_1000_std | -16.567047531839382 |
| MTEB ArguAna (default) | Retrieval | nauc_ndcg_at_100_diff1 | 16.10719535312808 |
| MTEB ArguAna (default) | Retrieval | nauc_ndcg_at_100_max | -6.59354665730934 |
| MTEB ArguAna (default) | Retrieval | nauc_ndcg_at_100_std | -16.513298001700566 |
| MTEB ArguAna (default) | Retrieval | nauc_ndcg_at_10_diff1 | 16.396485814351973 |
| MTEB ArguAna (default) | Retrieval | nauc_ndcg_at_10_max | -5.7111859345525895 |
| MTEB ArguAna (default) | Retrieval | nauc_ndcg_at_10_std | -17.13416103510026 |
| MTEB ArguAna (default) | Retrieval | nauc_ndcg_at_1_diff1 | 16.775859614223965 |
| MTEB ArguAna (default) | Retrieval | nauc_ndcg_at_1_max | -10.812150486389175 |
| MTEB ArguAna (default) | Retrieval | nauc_ndcg_at_1_std | -18.447209756110635 |
| MTEB ArguAna (default) | Retrieval | nauc_ndcg_at_20_diff1 | 16.414235526534497 |
| MTEB ArguAna (default) | Retrieval | nauc_ndcg_at_20_max | -5.890463457153039 |
| MTEB ArguAna (default) | Retrieval | nauc_ndcg_at_20_std | -16.124783371499017 |
| MTEB ArguAna (default) | Retrieval | nauc_ndcg_at_3_diff1 | 15.683431770601713 |
| MTEB ArguAna (default) | Retrieval | nauc_ndcg_at_3_max | -5.546675513691499 |
| MTEB ArguAna (default) | Retrieval | nauc_ndcg_at_3_std | -15.973244504586676 |
| MTEB ArguAna (default) | Retrieval | nauc_ndcg_at_5_diff1 | 16.193847874581166 |
| MTEB ArguAna (default) | Retrieval | nauc_ndcg_at_5_max | -4.471638454091411 |
| MTEB ArguAna (default) | Retrieval | nauc_ndcg_at_5_std | -15.517824617814629 |
| MTEB ArguAna (default) | Retrieval | nauc_precision_at_1000_diff1 | 3.170440311533737 |
| MTEB ArguAna (default) | Retrieval | nauc_precision_at_1000_max | 25.521992526080666 |
| MTEB ArguAna (default) | Retrieval | nauc_precision_at_1000_std | 68.4373013145641 |
| MTEB ArguAna (default) | Retrieval | nauc_precision_at_100_diff1 | 30.283338663457897 |
| MTEB ArguAna (default) | Retrieval | nauc_precision_at_100_max | 44.33747104624998 |
| MTEB ArguAna (default) | Retrieval | nauc_precision_at_100_std | 42.28887350925609 |
| MTEB ArguAna (default) | Retrieval | nauc_precision_at_10_diff1 | 23.390956301235633 |
| MTEB ArguAna (default) | Retrieval | nauc_precision_at_10_max | 15.468288261126773 |
| MTEB ArguAna (default) | Retrieval | nauc_precision_at_10_std | -18.2942744669977 |
| MTEB ArguAna (default) | Retrieval | nauc_precision_at_1_diff1 | 16.775859614223965 |
| MTEB ArguAna (default) | Retrieval | nauc_precision_at_1_max | -10.812150486389175 |
| MTEB ArguAna (default) | Retrieval | nauc_precision_at_1_std | -18.447209756110635 |
| MTEB ArguAna (default) | Retrieval | nauc_precision_at_20_diff1 | 37.14254275219614 |
| MTEB ArguAna (default) | Retrieval | nauc_precision_at_20_max | 46.984729023754824 |
| MTEB ArguAna (default) | Retrieval | nauc_precision_at_20_std | 22.763524786900717 |
| MTEB ArguAna (default) | Retrieval | nauc_precision_at_3_diff1 | 15.651406928218881 |
| MTEB ArguAna (default) | Retrieval | nauc_precision_at_3_max | 0.7775458885343681 |
| MTEB ArguAna (default) | Retrieval | nauc_precision_at_3_std | -12.438132482295773 |
| MTEB ArguAna (default) | Retrieval | nauc_precision_at_5_diff1 | 18.10074574210355 |
| MTEB ArguAna (default) | Retrieval | nauc_precision_at_5_max | 9.373350504221532 |
| MTEB ArguAna (default) | Retrieval | nauc_precision_at_5_std | -9.13125987784625 |
| MTEB ArguAna (default) | Retrieval | nauc_recall_at_1000_diff1 | 3.1704403115262325 |
| MTEB ArguAna (default) | Retrieval | nauc_recall_at_1000_max | 25.521992526077756 |
| MTEB ArguAna (default) | Retrieval | nauc_recall_at_1000_std | 68.4373013145603 |
| MTEB ArguAna (default) | Retrieval | nauc_recall_at_100_diff1 | 30.283338663455616 |
| MTEB ArguAna (default) | Retrieval | nauc_recall_at_100_max | 44.337471046250556 |
| MTEB ArguAna (default) | Retrieval | nauc_recall_at_100_std | 42.28887350925341 |
| MTEB ArguAna (default) | Retrieval | nauc_recall_at_10_diff1 | 23.390956301235168 |
| MTEB ArguAna (default) | Retrieval | nauc_recall_at_10_max | 15.468288261126578 |
| MTEB ArguAna (default) | Retrieval | nauc_recall_at_10_std | -18.294274466997873 |
| MTEB ArguAna (default) | Retrieval | nauc_recall_at_1_diff1 | 16.775859614223965 |
| MTEB ArguAna (default) | Retrieval | nauc_recall_at_1_max | -10.812150486389175 |
| MTEB ArguAna (default) | Retrieval | nauc_recall_at_1_std | -18.447209756110635 |
| MTEB ArguAna (default) | Retrieval | nauc_recall_at_20_diff1 | 37.14254275219513 |
| MTEB ArguAna (default) | Retrieval | nauc_recall_at_20_max | 46.98472902375421 |
| MTEB ArguAna (default) | Retrieval | nauc_recall_at_20_std | 22.763524786899644 |
| MTEB ArguAna (default) | Retrieval | nauc_recall_at_3_diff1 | 15.65140692821902 |
| MTEB ArguAna (default) | Retrieval | nauc_recall_at_3_max | 0.7775458885343522 |
| MTEB ArguAna (default) | Retrieval | nauc_recall_at_3_std | -12.43813248229578 |
| MTEB ArguAna (default) | Retrieval | nauc_recall_at_5_diff1 | 18.10074574210355 |
| MTEB ArguAna (default) | Retrieval | nauc_recall_at_5_max | 9.373350504221595 |
| MTEB ArguAna (default) | Retrieval | nauc_recall_at_5_std | -9.131259877846116 |
| MTEB ArguAna (default) | Retrieval | ndcg_at_1 | 49.004 |
| MTEB ArguAna (default) | Retrieval | ndcg_at_10 | 71.99600000000001 |
| MTEB ArguAna (default) | Retrieval | ndcg_at_100 | 73.173 |
| MTEB ArguAna (default) | Retrieval | ndcg_at_1000 | 73.214 |
| MTEB ArguAna (default) | Retrieval | ndcg_at_20 | 72.91 |
| MTEB ArguAna (default) | Retrieval | ndcg_at_3 | 65.21900000000001 |
| MTEB ArguAna (default) | Retrieval | ndcg_at_5 | 69.284 |
| MTEB ArguAna (default) | Retrieval | precision_at_1 | 49.004 |
| MTEB ArguAna (default) | Retrieval | precision_at_10 | 9.452 |
| MTEB ArguAna (default) | Retrieval | precision_at_100 | 0.9939999999999999 |
| MTEB ArguAna (default) | Retrieval | precision_at_1000 | 0.1 |
| MTEB ArguAna (default) | Retrieval | precision_at_20 | 4.904 |
| MTEB ArguAna (default) | Retrieval | precision_at_3 | 25.462 |
| MTEB ArguAna (default) | Retrieval | precision_at_5 | 17.255000000000003 |
| MTEB ArguAna (default) | Retrieval | recall_at_1 | 49.004 |
| MTEB ArguAna (default) | Retrieval | recall_at_10 | 94.523 |
| MTEB ArguAna (default) | Retrieval | recall_at_100 | 99.36 |
| MTEB ArguAna (default) | Retrieval | recall_at_1000 | 99.644 |
| MTEB ArguAna (default) | Retrieval | recall_at_20 | 98.08 |
| MTEB ArguAna (default) | Retrieval | recall_at_3 | 76.387 |
| MTEB ArguAna (default) | Retrieval | recall_at_5 | 86.273 |
| MTEB ArxivClusteringP2P (default) | Clustering | main_score | 48.629569816593516 |
| MTEB ArxivClusteringP2P (default) | Clustering | v_measure | 48.629569816593516 |
| MTEB ArxivClusteringP2P (default) | Clustering | v_measure_std | 14.01810149072028 |
| MTEB ArxivClusteringS2S (default) | Clustering | main_score | 40.52366904677561 |
| MTEB ArxivClusteringS2S (default) | Clustering | v_measure | 40.52366904677561 |
| MTEB ArxivClusteringS2S (default) | Clustering | v_measure_std | 14.375876773823757 |
| MTEB AskUbuntuDupQuestions (default) | Reranking | main_score | 61.27347206107508 |
| MTEB AskUbuntuDupQuestions (default) | Reranking | map | 61.27347206107508 |
| MTEB AskUbuntuDupQuestions (default) | Reranking | mrr | 74.49105219188321 |
| MTEB AskUbuntuDupQuestions (default) | Reranking | nAUC_map_diff1 | 13.442645655149457 |
| MTEB AskUbuntuDupQuestions (default) | Reranking | nAUC_map_max | 25.013363268430027 |
| MTEB AskUbuntuDupQuestions (default) | Reranking | nAUC_map_std | 17.60175231611674 |
| MTEB AskUbuntuDupQuestions (default) | Reranking | nAUC_mrr_diff1 | 25.217675209249435 |
| MTEB AskUbuntuDupQuestions (default) | Reranking | nAUC_mrr_max | 32.37381560372622 |
| MTEB AskUbuntuDupQuestions (default) | Reranking | nAUC_mrr_std | 22.584922632508412 |
| MTEB BIOSSES (default) | STS | cosine_pearson | 89.09452267906886 |
| MTEB BIOSSES (default) | STS | cosine_spearman | 86.73450642504955 |
| MTEB BIOSSES (default) | STS | euclidean_pearson | 87.1275130552617 |
| MTEB BIOSSES (default) | STS | euclidean_spearman | 86.93812552248012 |
| MTEB BIOSSES (default) | STS | main_score | 86.73450642504955 |
| MTEB BIOSSES (default) | STS | manhattan_pearson | 86.79403606129864 |
| MTEB BIOSSES (default) | STS | manhattan_spearman | 86.76824213349957 |
| MTEB BIOSSES (default) | STS | pearson | 89.09452267906886 |
| MTEB BIOSSES (default) | STS | spearman | 86.73450642504955 |
| MTEB Banking77Classification (default) | Classification | accuracy | 88.58116883116884 |
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GTE Multilingual Base is a multilingual sentence embedding model supporting over 50 languages, suitable for tasks like sentence similarity calculation.
Text Embedding Transformers Supports Multiple Languages
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Polybert
polyBERT is a chemical language model designed to achieve fully machine-driven ultrafast polymer informatics. It maps PSMILES strings into 600-dimensional dense fingerprints to numerically represent polymer chemical structures.
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kuelumbus
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Bert Base Turkish Cased Mean Nli Stsb Tr
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A sentence embedding model based on Turkish BERT, optimized for semantic similarity tasks
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GIST Small Embedding V0
MIT
A text embedding model fine-tuned based on BAAI/bge-small-en-v1.5, trained with the MEDI dataset and MTEB classification task datasets, optimized for query encoding in retrieval tasks.
Text Embedding
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