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EN
Rubert Tiny Turbo
R
Rubert Tiny Turbo
Developed by sergeyzh
A fine-tuned Russian small sentence similarity model based on cointegrated/rubert-tiny2, suitable for feature extraction and sentence transformation tasks
Downloads 93.76k
Release Time : 6/21/2024
Model Overview
This is a lightweight Russian sentence embedding model, specifically optimized for sentence similarity calculation tasks. Fine-tuned based on the rubert-tiny2 architecture, it provides efficient semantic representation capabilities for Russian text processing.
Model Features
Lightweight and efficient
Optimized based on the tiny architecture, reducing computational resource requirements while maintaining performance
Russian language optimization
Specially trained and optimized for Russian text
Sentence embedding
Capable of converting sentences into high-quality semantic vector representations
Model Capabilities
Sentence similarity calculation
Semantic search
Text feature extraction
Russian text processing
Use Cases
Information retrieval
Legal document retrieval
Searching for relevant clauses and cases in legal document libraries
Achieved an NDCG@10 score of 13.624 on the AILAStatutes dataset
News similarity matching
Finding similar news reports
Trained on Gazeta and Lenta-ru datasets
Question answering systems
Question-answer pair matching
Matching questions with the most relevant answers in QA systems
Achieved an MRR score of 3.845 on the ARCChallenge dataset
🚀 sergeyzh/rubert-tiny-turbo
This is a model for sentence similarity tasks, trained on Russian datasets and based on the cointegrated/rubert-tiny2 base model. It provides various performance metrics on the MTEB dataset.
📚 Documentation
General Information
| Property | Details |
|---|---|
| Pipeline Tag | Sentence Similarity |
| Tags | Russian, Pretraining, Embeddings, Tiny, Feature Extraction, Sentence Similarity, Sentence Transformers, Transformers, MTEB |
| Datasets | IlyaGusev/gazeta, zloelias/lenta-ru |
| License | MIT |
| Base Model | cointegrated/rubert-tiny2 |
Model Index
- Model Name: sergeyzh/rubert-tiny-turbo
Results on MTEB AILACasedocs (default)
| Metric | Value |
|---|---|
| main_score | 7.432999999999999 |
| map_at_1 | 0.604 |
| map_at_10 | 3.8989999999999996 |
| map_at_100 | 7.89 |
| map_at_1000 | 8.417 |
| map_at_20 | 5.007000000000001 |
| map_at_3 | 2.688 |
| map_at_5 | 3.0380000000000003 |
| mrr_at_1 | 6.0 |
| mrr_at_10 | 11.799999999999999 |
| mrr_at_100 | 14.417998426795965 |
| mrr_at_1000 | 14.474056627618499 |
| mrr_at_20 | 13.017532467532467 |
| mrr_at_3 | 10.333333333333334 |
| mrr_at_5 | 10.733333333333333 |
| nauc_map_at_1000_diff1 | -18.649405381116548 |
| nauc_map_at_1000_max | 53.92467833877199 |
| nauc_map_at_1000_std | -37.567628121407296 |
| nauc_map_at_100_diff1 | -19.053926237591206 |
| nauc_map_at_100_max | 53.442907236002725 |
| nauc_map_at_100_std | -37.310817568902884 |
| nauc_map_at_10_diff1 | -13.464050841785403 |
| nauc_map_at_10_max | 48.093886298979946 |
| nauc_map_at_10_std | -34.85388157835729 |
| nauc_map_at_1_diff1 | -13.741863044507388 |
| nauc_map_at_1_max | 88.80266056441289 |
| nauc_map_at_1_std | -52.44805080502242 |
| nauc_map_at_20_diff1 | -14.561491138058782 |
| nauc_map_at_20_max | 48.97477701904 |
| nauc_map_at_20_std | -31.218577996781537 |
| nauc_map_at_3_diff1 | -15.370170931276068 |
| nauc_map_at_3_max | 53.443631887225486 |
| nauc_map_at_3_std | -40.92344513873499 |
| nauc_map_at_5_diff1 | -12.899827975508286 |
| nauc_map_at_5_max | 56.55724779187716 |
| nauc_map_at_5_std | -38.50107328981899 |
| nauc_mrr_at_1000_diff1 | -20.480388426956775 |
| nauc_mrr_at_1000_max | 59.34434186773745 |
| nauc_mrr_at_1000_std | -38.78219708358511 |
| nauc_mrr_at_100_diff1 | -20.733217227513638 |
| nauc_mrr_at_100_max | 59.338571965753026 |
| nauc_mrr_at_100_std | -38.905241386083524 |
| nauc_mrr_at_10_diff1 | -23.191503817950903 |
| nauc_mrr_at_10_max | 59.40585262343663 |
| nauc_mrr_at_10_std | -39.558082853802894 |
| nauc_mrr_at_1_diff1 | -18.978624452195685 |
| nauc_mrr_at_1_max | 88.73088274751811 |
| nauc_mrr_at_1_std | -52.46400143099903 |
| nauc_mrr_at_20_diff1 | -20.110327257289537 |
| nauc_mrr_at_20_max | 57.24590011894607 |
| nauc_mrr_at_20_std | -36.76057923211494 |
| nauc_mrr_at_3_diff1 | -20.292924276357084 |
| nauc_mrr_at_3_max | 62.92624417852826 |
| nauc_mrr_at_3_std | -42.31284612573441 |
| nauc_mrr_at_5_diff1 | -22.088780368608298 |
| nauc_mrr_at_5_max | 61.62928734634482 |
| nauc_mrr_at_5_std | -38.47155384792127 |
| nauc_ndcg_at_1000_diff1 | -21.96644342707332 |
| nauc_ndcg_at_1000_max | 54.04115629470727 |
| nauc_ndcg_at_1000_std | -38.60954619686922 |
| nauc_ndcg_at_100_diff1 | -28.508933576201116 |
| nauc_ndcg_at_100_max | 53.62925134001747 |
| nauc_ndcg_at_100_std | -41.66742945815351 |
| nauc_ndcg_at_10_diff1 | -19.22314681419278 |
| nauc_ndcg_at_10_max | 44.88305374351992 |
| nauc_ndcg_at_10_std | -32.86086137849654 |
| nauc_ndcg_at_1_diff1 | -18.978624452195685 |
| nauc_ndcg_at_1_max | 88.73088274751811 |
| nauc_ndcg_at_1_std | -52.46400143099903 |
| nauc_ndcg_at_20_diff1 | -14.037813797353552 |
| nauc_ndcg_at_20_max | 43.01748289241327 |
| nauc_ndcg_at_20_std | -23.548077008049674 |
| nauc_ndcg_at_3_diff1 | -19.9659903984576 |
| nauc_ndcg_at_3_max | 64.99817864354436 |
| nauc_ndcg_at_3_std | -45.246163550721796 |
| nauc_ndcg_at_5_diff1 | -20.389688306447788 |
| nauc_ndcg_at_5_max | 61.370293646369454 |
| nauc_ndcg_at_5_std | -39.9134710853091 |
| nauc_precision_at_1000_diff1 | -26.69952361901621 |
| nauc_precision_at_1000_max | 46.40932456102013 |
| nauc_precision_at_1000_std | -37.38094677778857 |
| nauc_precision_at_100_diff1 | -29.692268260058146 |
| nauc_precision_at_100_max | 49.265913223173584 |
| nauc_precision_at_100_std | -41.45888232985447 |
| nauc_precision_at_10_diff1 | -20.974428245377048 |
| nauc_precision_at_10_max | 53.924262890679564 |
| nauc_precision_at_10_std | -35.74456192649867 |
| nauc_precision_at_1_diff1 | -18.978624452195685 |
| nauc_precision_at_1_max | 88.73088274751811 |
| nauc_precision_at_1_std | -52.46400143099903 |
| nauc_precision_at_20_diff1 | -23.03848763224966 |
| nauc_precision_at_20_max | 51.19001778609016 |
| nauc_precision_at_20_std | -33.25265416139501 |
| nauc_precision_at_3_diff1 | -19.497362250879267 |
| nauc_precision_at_3_max | 64.71277842907384 |
| nauc_precision_at_3_std | -44.512016412661204 |
| nauc_precision_at_5_diff1 | -18.918918918918912 |
| nauc_precision_at_5_max | 64.89456489456494 |
| nauc_precision_at_5_std | -37.37960880818024 |
| nauc_recall_at_1000_diff1 | .nan |
| nauc_recall_at_1000_max | .nan |
| nauc_recall_at_1000_std | .nan |
| nauc_recall_at_100_diff1 | -44.51937508102329 |
| nauc_recall_at_100_max | 25.75429602376942 |
| nauc_recall_at_100_std | -33.30783195688129 |
| nauc_recall_at_10_diff1 | -18.776401920240275 |
| nauc_recall_at_10_max | 23.00791681188562 |
| nauc_recall_at_10_std | -21.576198296256532 |
| nauc_recall_at_1_diff1 | -13.741863044507388 |
| nauc_recall_at_1_max | 88.80266056441289 |
| nauc_recall_at_1_std | -52.44805080502242 |
| nauc_recall_at_20_diff1 | -3.8724115673803343 |
| nauc_recall_at_20_max | 21.50124528790692 |
| nauc_recall_at_20_std | -1.6719812367243132 |
| nauc_recall_at_3_diff1 | -20.21079163108882 |
| nauc_recall_at_3_max | 42.152167178196684 |
| nauc_recall_at_3_std | -36.258746145318526 |
| nauc_recall_at_5_diff1 | -22.10269915203519 |
| nauc_recall_at_5_max | 43.30767031613079 |
| nauc_recall_at_5_std | -27.398704255640478 |
| ndcg_at_1 | 6.0 |
| ndcg_at_10 | 7.432999999999999 |
| ndcg_at_100 | 26.354 |
| ndcg_at_1000 | 30.558000000000003 |
| ndcg_at_20 | 11.143 |
| ndcg_at_3 | 7.979 |
| ndcg_at_5 | 6.81 |
| precision_at_1 | 6.0 |
| precision_at_10 | 4.2 |
| precision_at_100 | 3.1199999999999997 |
| precision_at_1000 | 0.38999999999999996 |
| precision_at_20 | 4.2 |
| precision_at_3 | 8.0 |
| precision_at_5 | 5.6000000000000005 |
| recall_at_1 | 0.604 |
| recall_at_10 | 9.678 |
| recall_at_100 | 78.645 |
| recall_at_1000 | 100.0 |
| recall_at_20 | 20.79 |
| recall_at_3 | 4.261 |
| recall_at_5 | 5.011 |
Results on MTEB AILAStatutes (default)
| Metric | Value |
|---|---|
| main_score | 13.624 |
| map_at_1 | 1.7999999999999998 |
| map_at_10 | 6.41 |
| map_at_100 | 11.995000000000001 |
| map_at_1000 | 11.995000000000001 |
| map_at_20 | 7.33 |
| map_at_3 | 4.089 |
| map_at_5 | 5.192 |
| mrr_at_1 | 8.0 |
| mrr_at_10 | 20.935714285714287 |
| mrr_at_100 | 23.02755974294914 |
| mrr_at_1000 | 23.02755974294914 |
| mrr_at_20 | 22.1038126476207 |
| mrr_at_3 | 15.333333333333332 |
| mrr_at_5 | 19.533333333333335 |
| nauc_map_at_1000_diff1 | 5.278882422253006 |
| nauc_map_at_1000_max | 3.7333073133608896 |
| nauc_map_at_1000_std | -4.5637189871999775 |
| nauc_map_at_100_diff1 | 5.278882422253006 |
| nauc_map_at_100_max | 3.7333073133608896 |
| nauc_map_at_100_std | -4.5637189871999775 |
| nauc_map_at_10_diff1 | 8.570212263630141 |
| nauc_map_at_10_max | -6.6489980060039295 |
| nauc_map_at_10_std | -12.162352126704402 |
| nauc_map_at_1_diff1 | 7.476969859583216 |
| nauc_map_at_1_max | -26.629997316876853 |
| nauc_map_at_1_std | -23.469874489461308 |
| nauc_map_at_20_diff1 | 7.222345063366828 |
| nauc_map_at_20_max | -2.5103197323267223 |
| nauc_map_at_20_std | -10.997015623527455 |
| nauc_map_at_3_diff1 | 14.924734426277178 |
| nauc_map_at_3_max | -11.92937537932614 |
| nauc_map_at_3_std | -4.9319666083973255 |
| nauc_map_at_5_diff1 | 8.080773945621521 |
| nauc_map_at_5_max | -3.8175754142607836 |
| nauc_map_at_5_std | -4.541639774033337 |
| nauc_mrr_at_1000_diff1 | 2.4122089783406646 |
| nauc_mrr_at_1000_max | -15.876004562207497 |
| nauc_mrr_at_1000_std | -12.985028057822372 |
| nauc_mrr_at_100_diff1 | 2.4122089783406646 |
| nauc_mrr_at_100_max | -15.876004562207497 |
| nauc_mrr_at_100_std | -12.985028057822372 |
| nauc_mrr_at_10_diff1 | 0.2857311186354727 |
| nauc_mrr_at_10_max | -14.63697545190418 |
| nauc_mrr_at_10_std | -12.056570964159198 |
| nauc_mrr_at_1_diff1 | 6.868795277703242 |
| nauc_mrr_at_1_max | -24.845720418567222 |
| nauc_mrr_at_1_std | -20.686879527770337 |
| nauc_mrr_at_20_diff1 | 1.8452171261188577 |
| nauc_mrr_at_20_max | -15.538023663956924 |
| nauc_mrr_at_20_std | -13.690749771450164 |
| nauc_mrr_at_3_diff1 | 10.557261573838256 |
| nauc_mrr_at_3_max | -20.946427791765498 |
| nauc_mrr_at_3_std | -10.389166217927242 |
| nauc_mrr_at_5_diff1 | 8.148148148148148 |
| nauc_mrr_at_5_max | -13.148148148148148 |
| nauc_mrr_at_5_std | -4.999999999999999 |
| nauc_ndcg_at_1000_diff1 | 2.4122089783406646 |
| nauc_ndcg_at_1000_max | -15.876004562207497 |
| nauc_ndcg_at_1000_std | -12.985028057822372 |
| nauc_ndcg_at_100_diff1 | 2.4122089783406646 |
| nauc_ndcg_at_100_max | -15.876004562207497 |
| nauc_ndcg_at_100_std | -12.985028057822372 |
| nauc_ndcg_at_10_diff1 | 0.2857311186354727 |
| nauc_ndcg_at_10_max | -14.63697545190418 |
| nauc_ndcg_at_10_std | -12.056570964159198 |
| nauc_ndcg_at_1_diff1 | 6.868795277703242 |
| nauc_ndcg_at_1_max | -24.845720418567222 |
| nauc_ndcg_at_1_std | -20.686879527770337 |
| nauc_ndcg_at_20_diff1 | 1.8452171261188577 |
| nauc_ndcg_at_20_max | -15.538023663956924 |
| nauc_ndcg_at_20_std | -13.690749771450164 |
| nauc_ndcg_at_3_diff1 | 10.557261573838256 |
| nauc_ndcg_at_3_max | -20.946427791765498 |
| nauc_ndcg_at_3_std | -10.389166217927242 |
| nauc_ndcg_at_5_diff1 | 8.148148148148148 |
| nauc_ndcg_at_5_max | -13.148148148148148 |
| nauc_ndcg_at_5_std | -4.999999999999999 |
| nauc_precision_at_1000_diff1 | 2.4122089783406646 |
| nauc_precision_at_1000_max | -15.876004562207497 |
| nauc_precision_at_1000_std | -12.985028057822372 |
| nauc_precision_at_100_diff1 | 2.4122089783406646 |
| nauc_precision_at_100_max | -15.876004562207497 |
| nauc_precision_at_100_std | -12.985028057822372 |
| nauc_precision_at_10_diff1 | 0.2857311186354727 |
| nauc_precision_at_10_max | -14.63697545190418 |
| nauc_precision_at_10_std | -12.056570964159198 |
| nauc_precision_at_1_diff1 | 6.868795277703242 |
| nauc_precision_at_1_max | -24.845720418567222 |
| nauc_precision_at_1_std | -20.686879527770337 |
| nauc_precision_at_20_diff1 | 1.8452171261188577 |
| nauc_precision_at_20_max | -15.538023663956924 |
| nauc_precision_at_20_std | -13.690749771450164 |
| nauc_precision_at_3_diff1 | 10.557261573838256 |
| nauc_precision_at_3_max | -20.946427791765498 |
| nauc_precision_at_3_std | -10.389166217927242 |
| nauc_precision_at_5_diff1 | 8.148148148148148 |
| nauc_precision_at_5_max | -13.148148148148148 |
| nauc_precision_at_5_std | -4.999999999999999 |
| nauc_recall_at_1000_diff1 | .nan |
| nauc_recall_at_1000_max | .nan |
| nauc_recall_at_1000_std | .nan |
| nauc_recall_at_100_diff1 | -22.259687540511645 |
| nauc_recall_at_100_max | 12.87714801188471 |
| nauc_recall_at_100_std | -16.653915978440645 |
| nauc_recall_at_10_diff1 | -9.388200960120137 |
| nauc_recall_at_10_max | 11.50395840594281 |
| nauc_recall_at_10_std | -10.788979282970666 |
| nauc_recall_at_1_diff1 | 3.434397638851621 |
| nauc_recall_at_1_max | -12.422860209283611 |
| nauc_recall_at_1_std | -8.98846257043201 |
| nauc_recall_at_20_diff1 | -1.936205783644667 |
| nauc_recall_at_20_max | 10.750622608973035 |
| nauc_recall_at_20_std | -6.848413795109831 |
| nauc_recall_at_3_diff1 | -10.10539581554441 |
| nauc_recall_at_3_max | 21.07608358909834 |
| nauc_recall_at_3_std | -15.580891292279175 |
| nauc_recall_at_5_diff1 | -11.054349076017595 |
| nauc_recall_at_5_max | 21.653835158065395 |
| nauc_recall_at_5_std | -13.3297425790239 |
| ndcg_at_1 | 8.0 |
| ndcg_at_10 | 13.624 |
| ndcg_at_100 | 28.048 |
| ndcg_at_1000 | 30.558000000000003 |
| ndcg_at_20 | 16.643 |
| ndcg_at_3 | 10.979 |
| ndcg_at_5 | 8.81 |
| precision_at_1 | 8.0 |
| precision_at_10 | 6.2 |
| precision_at_100 | 3.1199999999999997 |
| precision_at_1000 | 0.38999999999999996 |
| precision_at_20 | 6.2 |
| precision_at_3 | 10.0 |
| precision_at_5 | 7.6000000000000005 |
| recall_at_1 | 1.7999999999999998 |
| recall_at_10 | 19.678 |
| recall_at_100 | 78.645 |
| recall_at_1000 | 100.0 |
| recall_at_20 | 40.79 |
| recall_at_3 | 4.261 |
| recall_at_5 | 5.011 |
📄 License
This project is licensed under the MIT license.
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