File size: 49,672 Bytes
b54a891 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540 541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 557 558 559 560 561 562 563 564 565 566 567 568 569 570 571 572 573 574 575 576 577 578 579 580 581 582 583 584 585 586 587 588 589 590 591 592 593 594 595 596 597 598 599 600 601 602 603 604 605 606 607 608 609 610 611 612 613 614 615 616 617 618 619 620 621 622 623 624 625 626 627 628 629 630 631 632 633 634 635 636 637 638 639 640 641 642 643 644 645 646 647 648 649 650 651 652 653 654 655 656 657 658 659 660 661 662 663 664 665 666 667 668 669 670 671 672 673 674 675 676 677 678 679 680 681 682 683 684 685 686 687 688 689 690 691 692 693 694 695 696 697 698 699 700 701 702 703 704 705 706 707 708 709 710 711 712 713 714 715 716 717 718 719 720 721 722 723 724 725 726 727 728 729 730 731 732 733 734 735 736 737 738 739 740 741 742 743 744 745 746 747 748 749 750 751 752 753 754 755 756 757 758 759 760 761 762 763 764 765 766 767 768 769 770 771 772 773 774 775 776 777 778 779 780 781 782 783 784 785 786 787 788 789 790 791 792 793 794 795 796 797 798 799 800 801 802 803 804 805 806 807 808 809 810 811 812 813 814 815 816 817 818 819 820 821 822 823 824 825 826 827 828 829 830 831 832 833 834 835 836 837 838 839 840 841 842 843 844 845 846 847 848 849 850 851 852 853 854 855 856 857 858 859 860 861 862 863 864 865 866 867 868 869 870 871 872 873 874 875 876 877 878 879 880 881 882 883 884 885 886 887 888 889 890 891 892 893 894 895 896 897 898 899 900 901 902 903 904 905 906 907 908 909 910 911 912 913 914 915 916 917 918 919 920 921 922 923 924 925 926 927 928 929 930 931 932 933 934 935 936 937 938 939 940 941 942 943 944 945 946 947 948 949 950 951 952 953 954 955 956 957 958 959 960 961 962 963 964 965 966 967 968 969 970 971 972 973 974 975 976 977 978 979 980 981 982 983 984 985 986 987 988 989 990 991 |
---
base_model: BAAI/bge-base-en-v1.5
datasets: []
language:
- en
library_name: sentence-transformers
license: apache-2.0
metrics:
- cosine_accuracy@1
- cosine_accuracy@3
- cosine_accuracy@5
- cosine_accuracy@10
- cosine_precision@1
- cosine_precision@3
- cosine_precision@5
- cosine_precision@10
- cosine_recall@1
- cosine_recall@3
- cosine_recall@5
- cosine_recall@10
- cosine_ndcg@10
- cosine_mrr@10
- cosine_map@100
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- feature-extraction
- generated_from_trainer
- dataset_size:3305
- loss:MatryoshkaLoss
- loss:MultipleNegativesRankingLoss
widget:
- source_sentence: '
Limitation of Liability
CUSTOMER’S ENTIRE LIABILITY AND PACNET’S EXCLUSIVE REMEDIES AGAINST CUSTOMER FOR
ANY DAMAGES ARISING
FROM ANY ACT OR OMISSION RELATING TO THE SERVICES, REGARDLESS OF THE FORM OF ACTION,
WHETHER IN CONTRACT,
UNDER STATUTE, IN TORT OR OTHERWISE, INCLUDING NEGLIGENCE, WILL BE LIMITED, FOR
EACH EVENT OR SERIES OF
CONNECTED EVENTS, AS FOLLOWS:
FOR PERSONAL INJURY OR DEATH, UNLIMITED, BUT SUBJECT TO PROVEN DIRECT DAMAGES;
AND
FOR ALL OTHER EVENTS, SUBJECT TO A MAXIMUM EQUAL TO THE AGGREGATE MONTHLY SERVICE
CHARGES PAID OR
PAYBALE BY THE CUSTOMER UNDER THE AGREEMENT.
PACNET’S ENTIRE LIABILITY AND CUSTOMER’S EXCLUSIVE REMEDIES AGAINST PACNET OR
ITS AFFILIATES FOR
ANY DAMAGES ARISING FROM ANY ACT OR OMISSION RELATING TO THE AGREEMENT, REGARDLESS
OF THE
FORM OF ACTION, WHETHER IN CONTRACT, UNDER STATUTE, IN TORT OR OTHERWISE, INCLUDING
NEGLIGENCE, WILL BE LIMITED, FOR EACH EVENT OR SERIES OF CONNECTED EVENTS, AS
FOLLOWS:
{i} | FOR PERSONAL INJURY OR DEATH, UNLIMITED, BUT SUBJECT TO PROVEN DIRECT DAMAGES;
(ii) FOR FAILURE TO COMPLY WITH SERVICE LEVELS, TO THE AMOUNT OF CREDITS SET OUT
IN THE
RELEVANT SPECIFIC CONDITIONS OF THE RELEVANT SERVICE; AND
(iii) FOR ALL OTHER EVENTS, SUBJECT TO A MAXIMUM EQUAL TO THE AGGREGATE MONTHLY
SERVICE
CHARGES PAID OR PAYABLE BY THE CUSTOMER UNDER THE AGREEMENT.
.
PACNET WILL IN NO CIRCUMSTANCES BE LIABLE FOR ANY DAMAGES (EXCEPT RESULTING IN
PERSONAL INJURY
OR DEATH) ATTRIBUTABLE TO ANY SERVICE, PRODUCT OR ACTIONS OF ANY PERSON OTHER
THAN PACNET, ITS
EMPLOYEES AND AGENTS.
'
sentences:
- Auto Renewal Cancellation Notice Period
- Assignment
- Absolute Maximum Amount of Liability
- source_sentence: '
Subcontracting
(a) The Supplier must not subcontract any of its
obligations under this Agreement, without the
Company''s prior written consent (which will not
be unreasonably withheld).
(b) The Supplier remains fully responsible for acts
and omissions of its subcontractors and Supplier
Personnel in connection with this Agreement or a
Statement of Work as if they were its acts and
omissions.
Personnel
(a) At the Company''s reasonable request the
Supplier must, at its cost, immediately (or by any
date nominated by the Company) remove any
person nominated by the Company from the
performance of the Services and, if requested by
the Company, provide an alternative person
acceptable to the Company (acting reasonably).
(b) The Supplier will not remove (temporarily or
permanently) or replace a Key Personnel without
the Company’s prior written consent (which must
not be unreasonably withheld). Any substitute
personnel must be at least equally qualified for
the duties of the position as the person for whom
they are substituted. The Supplier must use
reasonable endeavours to provide uninterrupted
transition between Key Personnel and their
replacements.
'
sentences:
- Audit Rights
- Severability
- Subcontracting
- source_sentence: All Intellectual Property shall be deemed to be owned by the Employer
and Executive hereby relinquishes any right or claim to any such Intellectual
Property except to the extent necessary to transfer the ownership of any such
Intellectual Property to Employer. Executive shall promptly disclose to the Employer
all Intellectual Property. Without royalty or separate consideration, Executive
hereby assigns and agrees to assign to the Employer (or as otherwise directed
by the Employer) Executive’s full right, title and interest in and to all Intellectual
Property, including without limitation all copyright interests therein. Executive
agrees to cooperate with Employer and to execute any and all applications for
domestic and foreign patents, copyrights or other proprietary rights and to do
such other acts (including, among other things, the execution and delivery of
instruments of further assurance or confirmation) requested by the Employer to
assign the Intellectual Property to the Employer and to permit the Employer to
file, obtain and enforce any patents, copyrights or other proprietary rights in
the Intellectual Property. Executive agrees that Executive’s obligation to cooperate
and to execute, or cause to be executed, when it is in Executive’s power to do
so, any such instrument or paper, will continue after termination of this Agreement.
Executive agrees to make and maintain adequate and current written records of
all Intellectual Property, in the form of notes, sketches, drawings, or reports
relating hereto, which records shall be and remain the property of and available
to the Employer at all times. The parties agree that the Intellectual Property
does not include the items listed in the attached Exhibit A to this Agreement.
sentences:
- General Indemnities
- Intellectual Property Ownership
- Governing Law
- source_sentence: "CBRE\n.\n\nHEVERTECH LTD\n.\n\n.\n \n.\n\nPreferred Supplier\
\ Light/Agreement\n.\n\n.\n \n.\n \n.\n\nAgreement; Number: NMS/16/050 |\n.\n\
\nQUALIFIED SERVICE LEVEL AGREEMENT\nBETWEEN\nCBRE MANAGED SERVICES LIMITED\n\
AND\nHEVERTECH LTDCBRE\n.\n\nHEVERTECH LTD\n.\n\n.\n \n.\n \n.\n\n.\n \n.\n\
\ \n.\n\n.\n \n.\n \n.\n\nPreferred!Supplier Light Agreement\ni]\n.\n\nW\\\
olaclelealelaters Ulin elsiea Niky AeyAOkLY)\n.\n\nTABLE OF CONTENTS:\n.\n\nQualified\
\ Service Level Agreement Pages 03 to 10 inclusive\n.\n\nAppendix 1 — Schedule\
\ of Rates Page\n.\n\nAppendix 2 — Key Contacts and Escalation Process Pages 8\
\ to 9 inclusive\n.\n\nAppendix 3 - Working Capital Scheme Pages 10\n.\n\n.\n\
\ \n.\n\nCBRE Managed Services Lid\nFebruary 2016 Page 2 of LOPreferred Supplier\
\ Light'A greement HEVERTECH LTD\n.\n\nAgreement Number: NMS/16/050\n.\n\n.\n\
\ \n\n\nTHIS AGREEMENT is made on 1° June 2016\nBETWEEN\n\n(1) CBRE Managed Services\
\ Limited (Registered in England No. 1799580) whose registered\noffice is at City\
\ Bridge House, 57 Southwark Street, London, SE1 1RU (“CBRE”); and\n\n(2) Hevertech\
\ Ltd (Registered in England No. 2803522) whose registered office is at: Unit\
\ 2\nTreefield Industrial Estate, Gildersome, Leeds, LS27 7JU (the “Supplier’).\n"
sentences:
- Non Solicitation
- Intellectual Property Infringement Indemnity
- Title of Agreement
- source_sentence: "\nThe management of each individual entity within a suppliers\
\ organization is responsible for\nimplementing the VAT Supplier Code of Conduct\
\ in their respective area of responsibility. They are\nobliged to take all appropriate\
\ action and provide the required structures and resources to ensure\nthat all\
\ employees in the entity are familiar with the VAT Supplier Code of Conduct and\
\ that its\nprinciples are fully implemented.\n.\n\nAll VAT suppliers are encouraged\
\ to direct any questions they might have with regard to the\ncontents, interpretation\
\ or implementation of the VAT Supplier Code of Conduct to the VAT Strategic\n\
Procurement function.\n.\n\n.\n \n.\n\nDocument created Release\nName Index Date\n\
.\n\n.\n \n.\n\nFile name\n.\n\n.\n \n.\n\n.\n \n.\n\n.\n \n.\n\n.\n \n.\n\nPMS\
\ Document BPO1FO30EA MEY A 18.11.2014\n.\n\n.\n \n.\n\n.\n \n.\n\n.\n \n.\n\n\
.\n \n.\n\n.\n \n.\n\nWAT Strategic Procurement BP01FO30E\n.\n\nVakuumventile\
\ AG Supplier Code of Conduct Page 3 of 3\n.\n\n.\n \n.\n\n.\n \n.\n\n.\n \n.\n\
\nWe, the undersigned, hereby confirm and declare in the name and on behalf of\
\ our company that\n.\n\n1. we have received the VAT Supplier Code of Condex;\n\
.\n\n2. by signing this declaration, we accept and commit to complying with all\
\ rules and requirements as\nlaid out in the VAT Supplier Code of Conduct;\n.\n\
\n3. we accept that this declaration shall be exclusively governed by the material\
\ laws of Switzerland,\nexcluding the UN Law of Sales (CISG).\n.\n\nPlacelDate\
\ —-Singagore. / tone 2077\nCompany Kien Ann Engineering Pe ad\nStreet 3c 500\
\ kovo Cirle\n.\n\nPost codelcity Singapore 627035\n.\n\nName of authorized signatory\
\ Jameson Low\n.\n\nL. Ze\nSignature << : Ly eA\n* fh\n20,\nXn _A\nCETES\n.\n\n\
1. Please sign one (1) original c Of this document.\n2. Please note that only\
\ duly authorized personnel of your company may sign this document.\n3. Please\
\ send the duly signed original copy by conventional mail to:\nVAT VAKUUMVENTILE\
\ AG, SEELISTRASSE 1, STRATEGISCHER EINKAUF, CH-9469 HAAG\n.\n\n.\n \n.\n\n.\n\
\ \n.\n\n.\n \n.\n\nDocument created Release\n.\n\n.\n \n.\n\nFile name\nName\
\ Index Date\n.\n\n.\n \n.\n\n.\n \n.\n\n.\n \n.\n\n.\n \n.\n\n.\n \n.\n\n.\n\
\ \n.\n\n.\n \n.\n\nPMS Document BPO1FO30EA MEY A 18.11.2014\n\n \n\n \n\nAll\
\ business is conducted in compliance with governing national and international\
\ laws and\nregulations. As a matter of principle, we honor agreements and obligations\
\ we have entered into\nvoluntarily. All suppliers are obliged to carefully study\
\ the rules and regulations pertinent to their\narea of responsibility and ensure\
\ full compliance. In case of doubt or queries, they are obliged to\nseek additional\
\ information and guidance from the appropriate channels or persons in charge.\
\ VAT\nhas a zero tolerance policy with regard to violations of its Supplier Code\
\ of Conduct. Violations may\nlead to appropriate action being taken against the\
\ supplier.\n.\n\n2. Fair competition\n"
sentences:
- Absolute Maximum Amount of Liability
- Governing Law
- Third Party Beneficiary
model-index:
- name: BGE base Financial Matryoshka
results:
- task:
type: information-retrieval
name: Information Retrieval
dataset:
name: dim 768
type: dim_768
metrics:
- type: cosine_accuracy@1
value: 0.005502063273727648
name: Cosine Accuracy@1
- type: cosine_accuracy@3
value: 0.02063273727647868
name: Cosine Accuracy@3
- type: cosine_accuracy@5
value: 0.0343878954607978
name: Cosine Accuracy@5
- type: cosine_accuracy@10
value: 0.055020632737276476
name: Cosine Accuracy@10
- type: cosine_precision@1
value: 0.005502063273727648
name: Cosine Precision@1
- type: cosine_precision@3
value: 0.0068775790921595595
name: Cosine Precision@3
- type: cosine_precision@5
value: 0.0068775790921595595
name: Cosine Precision@5
- type: cosine_precision@10
value: 0.005502063273727648
name: Cosine Precision@10
- type: cosine_recall@1
value: 0.005502063273727648
name: Cosine Recall@1
- type: cosine_recall@3
value: 0.02063273727647868
name: Cosine Recall@3
- type: cosine_recall@5
value: 0.0343878954607978
name: Cosine Recall@5
- type: cosine_recall@10
value: 0.055020632737276476
name: Cosine Recall@10
- type: cosine_ndcg@10
value: 0.026159571077284855
name: Cosine Ndcg@10
- type: cosine_mrr@10
value: 0.017443396432392302
name: Cosine Mrr@10
- type: cosine_map@100
value: 0.028690755071459656
name: Cosine Map@100
- task:
type: information-retrieval
name: Information Retrieval
dataset:
name: dim 512
type: dim_512
metrics:
- type: cosine_accuracy@1
value: 0.005502063273727648
name: Cosine Accuracy@1
- type: cosine_accuracy@3
value: 0.023383768913342505
name: Cosine Accuracy@3
- type: cosine_accuracy@5
value: 0.030261348005502064
name: Cosine Accuracy@5
- type: cosine_accuracy@10
value: 0.06327372764786796
name: Cosine Accuracy@10
- type: cosine_precision@1
value: 0.005502063273727648
name: Cosine Precision@1
- type: cosine_precision@3
value: 0.0077945896377808336
name: Cosine Precision@3
- type: cosine_precision@5
value: 0.006052269601100413
name: Cosine Precision@5
- type: cosine_precision@10
value: 0.006327372764786796
name: Cosine Precision@10
- type: cosine_recall@1
value: 0.005502063273727648
name: Cosine Recall@1
- type: cosine_recall@3
value: 0.023383768913342505
name: Cosine Recall@3
- type: cosine_recall@5
value: 0.030261348005502064
name: Cosine Recall@5
- type: cosine_recall@10
value: 0.06327372764786796
name: Cosine Recall@10
- type: cosine_ndcg@10
value: 0.02862375490125008
name: Cosine Ndcg@10
- type: cosine_mrr@10
value: 0.01840243662802122
name: Cosine Mrr@10
- type: cosine_map@100
value: 0.029291334425024487
name: Cosine Map@100
- task:
type: information-retrieval
name: Information Retrieval
dataset:
name: dim 256
type: dim_256
metrics:
- type: cosine_accuracy@1
value: 0.0068775790921595595
name: Cosine Accuracy@1
- type: cosine_accuracy@3
value: 0.02200825309491059
name: Cosine Accuracy@3
- type: cosine_accuracy@5
value: 0.03576341127922971
name: Cosine Accuracy@5
- type: cosine_accuracy@10
value: 0.06602475928473177
name: Cosine Accuracy@10
- type: cosine_precision@1
value: 0.0068775790921595595
name: Cosine Precision@1
- type: cosine_precision@3
value: 0.007336084364970197
name: Cosine Precision@3
- type: cosine_precision@5
value: 0.007152682255845944
name: Cosine Precision@5
- type: cosine_precision@10
value: 0.006602475928473177
name: Cosine Precision@10
- type: cosine_recall@1
value: 0.0068775790921595595
name: Cosine Recall@1
- type: cosine_recall@3
value: 0.02200825309491059
name: Cosine Recall@3
- type: cosine_recall@5
value: 0.03576341127922971
name: Cosine Recall@5
- type: cosine_recall@10
value: 0.06602475928473177
name: Cosine Recall@10
- type: cosine_ndcg@10
value: 0.03032191705264531
name: Cosine Ndcg@10
- type: cosine_mrr@10
value: 0.019712451693194466
name: Cosine Mrr@10
- type: cosine_map@100
value: 0.03142394630610729
name: Cosine Map@100
- task:
type: information-retrieval
name: Information Retrieval
dataset:
name: dim 128
type: dim_128
metrics:
- type: cosine_accuracy@1
value: 0.001375515818431912
name: Cosine Accuracy@1
- type: cosine_accuracy@3
value: 0.017881705639614855
name: Cosine Accuracy@3
- type: cosine_accuracy@5
value: 0.02200825309491059
name: Cosine Accuracy@5
- type: cosine_accuracy@10
value: 0.061898211829436035
name: Cosine Accuracy@10
- type: cosine_precision@1
value: 0.001375515818431912
name: Cosine Precision@1
- type: cosine_precision@3
value: 0.0059605685465382845
name: Cosine Precision@3
- type: cosine_precision@5
value: 0.004401650618982119
name: Cosine Precision@5
- type: cosine_precision@10
value: 0.0061898211829436054
name: Cosine Precision@10
- type: cosine_recall@1
value: 0.001375515818431912
name: Cosine Recall@1
- type: cosine_recall@3
value: 0.017881705639614855
name: Cosine Recall@3
- type: cosine_recall@5
value: 0.02200825309491059
name: Cosine Recall@5
- type: cosine_recall@10
value: 0.061898211829436035
name: Cosine Recall@10
- type: cosine_ndcg@10
value: 0.02519373355892647
name: Cosine Ndcg@10
- type: cosine_mrr@10
value: 0.01444837448963996
name: Cosine Mrr@10
- type: cosine_map@100
value: 0.027157891073425876
name: Cosine Map@100
- task:
type: information-retrieval
name: Information Retrieval
dataset:
name: dim 64
type: dim_64
metrics:
- type: cosine_accuracy@1
value: 0.005502063273727648
name: Cosine Accuracy@1
- type: cosine_accuracy@3
value: 0.02888583218707015
name: Cosine Accuracy@3
- type: cosine_accuracy@5
value: 0.0453920220082531
name: Cosine Accuracy@5
- type: cosine_accuracy@10
value: 0.0687757909215956
name: Cosine Accuracy@10
- type: cosine_precision@1
value: 0.005502063273727648
name: Cosine Precision@1
- type: cosine_precision@3
value: 0.009628610729023383
name: Cosine Precision@3
- type: cosine_precision@5
value: 0.009078404401650619
name: Cosine Precision@5
- type: cosine_precision@10
value: 0.0068775790921595595
name: Cosine Precision@10
- type: cosine_recall@1
value: 0.005502063273727648
name: Cosine Recall@1
- type: cosine_recall@3
value: 0.02888583218707015
name: Cosine Recall@3
- type: cosine_recall@5
value: 0.0453920220082531
name: Cosine Recall@5
- type: cosine_recall@10
value: 0.0687757909215956
name: Cosine Recall@10
- type: cosine_ndcg@10
value: 0.033131660986050276
name: Cosine Ndcg@10
- type: cosine_mrr@10
value: 0.022215672146896348
name: Cosine Mrr@10
- type: cosine_map@100
value: 0.033485590251952455
name: Cosine Map@100
---
# BGE base Financial Matryoshka
This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [BAAI/bge-base-en-v1.5](https://huggingface.co/BAAI/bge-base-en-v1.5). It maps sentences & paragraphs to a 768-dimensional dense vector space and can be used for semantic textual similarity, semantic search, paraphrase mining, text classification, clustering, and more.
## Model Details
### Model Description
- **Model Type:** Sentence Transformer
- **Base model:** [BAAI/bge-base-en-v1.5](https://huggingface.co/BAAI/bge-base-en-v1.5) <!-- at revision a5beb1e3e68b9ab74eb54cfd186867f64f240e1a -->
- **Maximum Sequence Length:** 512 tokens
- **Output Dimensionality:** 768 tokens
- **Similarity Function:** Cosine Similarity
<!-- - **Training Dataset:** Unknown -->
- **Language:** en
- **License:** apache-2.0
### Model Sources
- **Documentation:** [Sentence Transformers Documentation](https://sbert.net)
- **Repository:** [Sentence Transformers on GitHub](https://github.com/UKPLab/sentence-transformers)
- **Hugging Face:** [Sentence Transformers on Hugging Face](https://huggingface.co/models?library=sentence-transformers)
### Full Model Architecture
```
SentenceTransformer(
(0): Transformer({'max_seq_length': 512, 'do_lower_case': True}) with Transformer model: BertModel
(1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_cls_token': True, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True})
(2): Normalize()
)
```
## Usage
### Direct Usage (Sentence Transformers)
First install the Sentence Transformers library:
```bash
pip install -U sentence-transformers
```
Then you can load this model and run inference.
```python
from sentence_transformers import SentenceTransformer
# Download from the 🤗 Hub
model = SentenceTransformer("RishuD7/exigent-moreepoch-bge-base-financial-matryoshka")
# Run inference
sentences = [
'\nThe management of each individual entity within a suppliers organization is responsible for\nimplementing the VAT Supplier Code of Conduct in their respective area of responsibility. They are\nobliged to take all appropriate action and provide the required structures and resources to ensure\nthat all employees in the entity are familiar with the VAT Supplier Code of Conduct and that its\nprinciples are fully implemented.\n.\n\nAll VAT suppliers are encouraged to direct any questions they might have with regard to the\ncontents, interpretation or implementation of the VAT Supplier Code of Conduct to the VAT Strategic\nProcurement function.\n.\n\n.\n \n.\n\nDocument created Release\nName Index Date\n.\n\n.\n \n.\n\nFile name\n.\n\n.\n \n.\n\n.\n \n.\n\n.\n \n.\n\n.\n \n.\n\nPMS Document BPO1FO30EA MEY A 18.11.2014\n.\n\n.\n \n.\n\n.\n \n.\n\n.\n \n.\n\n.\n \n.\n\n.\n \n.\n\nWAT Strategic Procurement BP01FO30E\n.\n\nVakuumventile AG Supplier Code of Conduct Page 3 of 3\n.\n\n.\n \n.\n\n.\n \n.\n\n.\n \n.\n\nWe, the undersigned, hereby confirm and declare in the name and on behalf of our company that\n.\n\n1. we have received the VAT Supplier Code of Condex;\n.\n\n2. by signing this declaration, we accept and commit to complying with all rules and requirements as\nlaid out in the VAT Supplier Code of Conduct;\n.\n\n3. we accept that this declaration shall be exclusively governed by the material laws of Switzerland,\nexcluding the UN Law of Sales (CISG).\n.\n\nPlacelDate —-Singagore. / tone 2077\nCompany Kien Ann Engineering Pe ad\nStreet 3c 500 kovo Cirle\n.\n\nPost codelcity Singapore 627035\n.\n\nName of authorized signatory Jameson Low\n.\n\nL. Ze\nSignature << : Ly eA\n* fh\n20,\nXn _A\nCETES\n.\n\n1. Please sign one (1) original c Of this document.\n2. Please note that only duly authorized personnel of your company may sign this document.\n3. Please send the duly signed original copy by conventional mail to:\nVAT VAKUUMVENTILE AG, SEELISTRASSE 1, STRATEGISCHER EINKAUF, CH-9469 HAAG\n.\n\n.\n \n.\n\n.\n \n.\n\n.\n \n.\n\nDocument created Release\n.\n\n.\n \n.\n\nFile name\nName Index Date\n.\n\n.\n \n.\n\n.\n \n.\n\n.\n \n.\n\n.\n \n.\n\n.\n \n.\n\n.\n \n.\n\n.\n \n.\n\nPMS Document BPO1FO30EA MEY A 18.11.2014\n\n \n\n \n\nAll business is conducted in compliance with governing national and international laws and\nregulations. As a matter of principle, we honor agreements and obligations we have entered into\nvoluntarily. All suppliers are obliged to carefully study the rules and regulations pertinent to their\narea of responsibility and ensure full compliance. In case of doubt or queries, they are obliged to\nseek additional information and guidance from the appropriate channels or persons in charge. VAT\nhas a zero tolerance policy with regard to violations of its Supplier Code of Conduct. Violations may\nlead to appropriate action being taken against the supplier.\n.\n\n2. Fair competition\n',
'Governing Law',
'Absolute Maximum Amount of Liability',
]
embeddings = model.encode(sentences)
print(embeddings.shape)
# [3, 768]
# Get the similarity scores for the embeddings
similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [3, 3]
```
<!--
### Direct Usage (Transformers)
<details><summary>Click to see the direct usage in Transformers</summary>
</details>
-->
<!--
### Downstream Usage (Sentence Transformers)
You can finetune this model on your own dataset.
<details><summary>Click to expand</summary>
</details>
-->
<!--
### Out-of-Scope Use
*List how the model may foreseeably be misused and address what users ought not to do with the model.*
-->
## Evaluation
### Metrics
#### Information Retrieval
* Dataset: `dim_768`
* Evaluated with [<code>InformationRetrievalEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.InformationRetrievalEvaluator)
| Metric | Value |
|:--------------------|:-----------|
| cosine_accuracy@1 | 0.0055 |
| cosine_accuracy@3 | 0.0206 |
| cosine_accuracy@5 | 0.0344 |
| cosine_accuracy@10 | 0.055 |
| cosine_precision@1 | 0.0055 |
| cosine_precision@3 | 0.0069 |
| cosine_precision@5 | 0.0069 |
| cosine_precision@10 | 0.0055 |
| cosine_recall@1 | 0.0055 |
| cosine_recall@3 | 0.0206 |
| cosine_recall@5 | 0.0344 |
| cosine_recall@10 | 0.055 |
| cosine_ndcg@10 | 0.0262 |
| cosine_mrr@10 | 0.0174 |
| **cosine_map@100** | **0.0287** |
#### Information Retrieval
* Dataset: `dim_512`
* Evaluated with [<code>InformationRetrievalEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.InformationRetrievalEvaluator)
| Metric | Value |
|:--------------------|:-----------|
| cosine_accuracy@1 | 0.0055 |
| cosine_accuracy@3 | 0.0234 |
| cosine_accuracy@5 | 0.0303 |
| cosine_accuracy@10 | 0.0633 |
| cosine_precision@1 | 0.0055 |
| cosine_precision@3 | 0.0078 |
| cosine_precision@5 | 0.0061 |
| cosine_precision@10 | 0.0063 |
| cosine_recall@1 | 0.0055 |
| cosine_recall@3 | 0.0234 |
| cosine_recall@5 | 0.0303 |
| cosine_recall@10 | 0.0633 |
| cosine_ndcg@10 | 0.0286 |
| cosine_mrr@10 | 0.0184 |
| **cosine_map@100** | **0.0293** |
#### Information Retrieval
* Dataset: `dim_256`
* Evaluated with [<code>InformationRetrievalEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.InformationRetrievalEvaluator)
| Metric | Value |
|:--------------------|:-----------|
| cosine_accuracy@1 | 0.0069 |
| cosine_accuracy@3 | 0.022 |
| cosine_accuracy@5 | 0.0358 |
| cosine_accuracy@10 | 0.066 |
| cosine_precision@1 | 0.0069 |
| cosine_precision@3 | 0.0073 |
| cosine_precision@5 | 0.0072 |
| cosine_precision@10 | 0.0066 |
| cosine_recall@1 | 0.0069 |
| cosine_recall@3 | 0.022 |
| cosine_recall@5 | 0.0358 |
| cosine_recall@10 | 0.066 |
| cosine_ndcg@10 | 0.0303 |
| cosine_mrr@10 | 0.0197 |
| **cosine_map@100** | **0.0314** |
#### Information Retrieval
* Dataset: `dim_128`
* Evaluated with [<code>InformationRetrievalEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.InformationRetrievalEvaluator)
| Metric | Value |
|:--------------------|:-----------|
| cosine_accuracy@1 | 0.0014 |
| cosine_accuracy@3 | 0.0179 |
| cosine_accuracy@5 | 0.022 |
| cosine_accuracy@10 | 0.0619 |
| cosine_precision@1 | 0.0014 |
| cosine_precision@3 | 0.006 |
| cosine_precision@5 | 0.0044 |
| cosine_precision@10 | 0.0062 |
| cosine_recall@1 | 0.0014 |
| cosine_recall@3 | 0.0179 |
| cosine_recall@5 | 0.022 |
| cosine_recall@10 | 0.0619 |
| cosine_ndcg@10 | 0.0252 |
| cosine_mrr@10 | 0.0144 |
| **cosine_map@100** | **0.0272** |
#### Information Retrieval
* Dataset: `dim_64`
* Evaluated with [<code>InformationRetrievalEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.InformationRetrievalEvaluator)
| Metric | Value |
|:--------------------|:-----------|
| cosine_accuracy@1 | 0.0055 |
| cosine_accuracy@3 | 0.0289 |
| cosine_accuracy@5 | 0.0454 |
| cosine_accuracy@10 | 0.0688 |
| cosine_precision@1 | 0.0055 |
| cosine_precision@3 | 0.0096 |
| cosine_precision@5 | 0.0091 |
| cosine_precision@10 | 0.0069 |
| cosine_recall@1 | 0.0055 |
| cosine_recall@3 | 0.0289 |
| cosine_recall@5 | 0.0454 |
| cosine_recall@10 | 0.0688 |
| cosine_ndcg@10 | 0.0331 |
| cosine_mrr@10 | 0.0222 |
| **cosine_map@100** | **0.0335** |
<!--
## Bias, Risks and Limitations
*What are the known or foreseeable issues stemming from this model? You could also flag here known failure cases or weaknesses of the model.*
-->
<!--
### Recommendations
*What are recommendations with respect to the foreseeable issues? For example, filtering explicit content.*
-->
## Training Details
### Training Dataset
#### Unnamed Dataset
* Size: 3,305 training samples
* Columns: <code>positive</code> and <code>anchor</code>
* Approximate statistics based on the first 1000 samples:
| | positive | anchor |
|:--------|:--------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------|
| type | string | string |
| details | <ul><li>min: 123 tokens</li><li>mean: 353.07 tokens</li><li>max: 512 tokens</li></ul> | <ul><li>min: 3 tokens</li><li>mean: 5.37 tokens</li><li>max: 8 tokens</li></ul> |
* Samples:
| positive | anchor |
|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:--------------------------------------------------|
| <code>In no event shall CBRE, Client, or their respective affiliates incur liability under this agreement or otherwise relating to the Services beyond the insurance proceeds available with respect to the particular matter under the Insurance Policies required to be carried by CBRE AND Client under Article 6 above including, if applicable, proceeds of self-insurance. Each party shall and shall cause its affiliates to look solely to such insurance proceeds (and any such proceeds paid through self-insurance) to satisfy its claims against the released parties and agrees that it shall have no right of recovery beyond such proceeds; provided, however, that if insurance proceeds under such policies are not paid because a party has failed to maintain such policies, comply with policy requirements or, in the case of self-insurance, unreasonably denied a claim, such party shall be liable for the amounts that otherwise would have been payable under such policies had such party maintained such policies, complied with the policy requirement or not unreasonably denied such claim, as the case may be.</code> | <code>Absolute Maximum Amount of Liability</code> |
| <code>4. Rent. <br>4.01 From and after the Commencement Date, Tenant shall pay Landlord, without any<br>setoff or deduction, unless expressly set forth in this Lease, all Base Rent and Additional Rent<br>due for the Term (collectively referred to as "Rent"). "Additional Rent" means all sums<br>(exclusive of Base Rent) that Tenant is required to pay Landlord under this Lease. Tenant shall<br>pay and be liable for all rental, sales and use taxes (but excluding income taxes), if any,<br>imposed upon or measured by Rent. Base Rent and recurring monthly charges of Additional<br>Rent shall be due and payable in advance on the first day of each calendar month without<br>notice or demand, provided that the installment of Base Rent attributable to the first (1st) full<br>calendar month of the Term following the Abatement Period shall be due concurrently with the<br>execution of this Lease by Tenant. All other items of Rent shall be due and payable on or<br>before thirty (30) days after billing by Landlord. Rent shall be made payable to the entity, and<br>sent to the address, that Landlord designates and shall be made by good and sufficient check or<br>by other means acceptable to Landlord. Landlord may return to Tenant, at any time within<br>fifteen (15) days after receiving same, any payment of Rent (a) made following any Default<br>(irrespective of whether Landlord has commenced the exercise of any remedy), or (b) that is<br>less than the amount due. Each such returned payment (whether made by returning Tenant's<br>actual check, or by issuing a refund in the event Tenant's check was deposited) shall be<br>conclusively presumed not to have been received or approved by Landlord. If Tenant does not<br>pay any Rent when due hereunder, Tenant shall pay Landlord an administration fee in the<br>amount of five percent (5%) of the past due amount. In addition, past due Rent shall accrue<br>interest at a rate equal to the lesser of (i) twelve percent (12%) per annum or (ii) the maximum<br>legal rate, and Tenant shall pay Landlord a fee for any checks returned by Tenant's bank for<br>any reason. Notwithstanding the foregoing, no such late charge or of interest shall be imposed<br>with respect to the first (1st) late payment in any calendar year, but not with respect to more<br>than three (3) such late payments during the initial Term of this Lease. </code> | <code>Late Payment Charges</code> |
| <code>Term This Agreement shall come into force and shall last unlimited from such date. Either Party may however terminate this Agreement at any time by giving upon thirty (30) days' written notice to the other Party. The Receiving Party's obligations contained in this Agreement to keep confidential and restrict use of the Disclosing Party's Confidential Information shall sur- vive for a period of five (5) years from the date of its termination for any reason whatsoever. lX. Contractual penalty<br>For the purposes of this Non-Disclosure Agreement, " Confidential Information" includes all technical and/or commercial and/or financial information in the field designated in section 1., which a contracting Party (hereinafter referred to as the "EQ€i1gPedy") makes, or has made, accessible to the other contracting Party (hereinafter referred to as the ".&eiyi!g Partv") in oral, written, tangible or other form (e.9. disk, data carrier) directly or indirectly, in- cluding but not limited to, drawings, models, components, and other material. Confidential In- formation is to be identified as such. Orally communicated or visually, information having been designated as confidential at the time of disclosure will be confirmed as such in writing by the Disclosing Party within 30 (thirty) days from such disclosure being understood thatlhe ./A information will be considered Confidential Information during that period of 30 (thirty) days. /L t'-4 PF 0233 (September 2016) page 1 of 5 ä =.<br> PFEIFFER F<br>.<br> F<br>.<br> VACUUM<br></code> | <code>Termination for Convenience</code> |
* Loss: [<code>MatryoshkaLoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#matryoshkaloss) with these parameters:
```json
{
"loss": "MultipleNegativesRankingLoss",
"matryoshka_dims": [
768,
512,
256,
128,
64
],
"matryoshka_weights": [
1,
1,
1,
1,
1
],
"n_dims_per_step": -1
}
```
### Training Hyperparameters
#### Non-Default Hyperparameters
- `eval_strategy`: epoch
- `per_device_train_batch_size`: 32
- `per_device_eval_batch_size`: 16
- `gradient_accumulation_steps`: 16
- `learning_rate`: 2e-05
- `num_train_epochs`: 10
- `lr_scheduler_type`: cosine
- `warmup_ratio`: 0.1
- `bf16`: True
- `tf32`: True
- `load_best_model_at_end`: True
- `optim`: adamw_torch_fused
- `batch_sampler`: no_duplicates
#### All Hyperparameters
<details><summary>Click to expand</summary>
- `overwrite_output_dir`: False
- `do_predict`: False
- `eval_strategy`: epoch
- `prediction_loss_only`: True
- `per_device_train_batch_size`: 32
- `per_device_eval_batch_size`: 16
- `per_gpu_train_batch_size`: None
- `per_gpu_eval_batch_size`: None
- `gradient_accumulation_steps`: 16
- `eval_accumulation_steps`: None
- `learning_rate`: 2e-05
- `weight_decay`: 0.0
- `adam_beta1`: 0.9
- `adam_beta2`: 0.999
- `adam_epsilon`: 1e-08
- `max_grad_norm`: 1.0
- `num_train_epochs`: 10
- `max_steps`: -1
- `lr_scheduler_type`: cosine
- `lr_scheduler_kwargs`: {}
- `warmup_ratio`: 0.1
- `warmup_steps`: 0
- `log_level`: passive
- `log_level_replica`: warning
- `log_on_each_node`: True
- `logging_nan_inf_filter`: True
- `save_safetensors`: True
- `save_on_each_node`: False
- `save_only_model`: False
- `restore_callback_states_from_checkpoint`: False
- `no_cuda`: False
- `use_cpu`: False
- `use_mps_device`: False
- `seed`: 42
- `data_seed`: None
- `jit_mode_eval`: False
- `use_ipex`: False
- `bf16`: True
- `fp16`: False
- `fp16_opt_level`: O1
- `half_precision_backend`: auto
- `bf16_full_eval`: False
- `fp16_full_eval`: False
- `tf32`: True
- `local_rank`: 0
- `ddp_backend`: None
- `tpu_num_cores`: None
- `tpu_metrics_debug`: False
- `debug`: []
- `dataloader_drop_last`: False
- `dataloader_num_workers`: 0
- `dataloader_prefetch_factor`: None
- `past_index`: -1
- `disable_tqdm`: False
- `remove_unused_columns`: True
- `label_names`: None
- `load_best_model_at_end`: True
- `ignore_data_skip`: False
- `fsdp`: []
- `fsdp_min_num_params`: 0
- `fsdp_config`: {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}
- `fsdp_transformer_layer_cls_to_wrap`: None
- `accelerator_config`: {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None}
- `deepspeed`: None
- `label_smoothing_factor`: 0.0
- `optim`: adamw_torch_fused
- `optim_args`: None
- `adafactor`: False
- `group_by_length`: False
- `length_column_name`: length
- `ddp_find_unused_parameters`: None
- `ddp_bucket_cap_mb`: None
- `ddp_broadcast_buffers`: False
- `dataloader_pin_memory`: True
- `dataloader_persistent_workers`: False
- `skip_memory_metrics`: True
- `use_legacy_prediction_loop`: False
- `push_to_hub`: False
- `resume_from_checkpoint`: None
- `hub_model_id`: None
- `hub_strategy`: every_save
- `hub_private_repo`: False
- `hub_always_push`: False
- `gradient_checkpointing`: False
- `gradient_checkpointing_kwargs`: None
- `include_inputs_for_metrics`: False
- `eval_do_concat_batches`: True
- `fp16_backend`: auto
- `push_to_hub_model_id`: None
- `push_to_hub_organization`: None
- `mp_parameters`:
- `auto_find_batch_size`: False
- `full_determinism`: False
- `torchdynamo`: None
- `ray_scope`: last
- `ddp_timeout`: 1800
- `torch_compile`: False
- `torch_compile_backend`: None
- `torch_compile_mode`: None
- `dispatch_batches`: None
- `split_batches`: None
- `include_tokens_per_second`: False
- `include_num_input_tokens_seen`: False
- `neftune_noise_alpha`: None
- `optim_target_modules`: None
- `batch_eval_metrics`: False
- `batch_sampler`: no_duplicates
- `multi_dataset_batch_sampler`: proportional
</details>
### Training Logs
| Epoch | Step | Training Loss | dim_128_cosine_map@100 | dim_256_cosine_map@100 | dim_512_cosine_map@100 | dim_64_cosine_map@100 | dim_768_cosine_map@100 |
|:----------:|:------:|:-------------:|:----------------------:|:----------------------:|:----------------------:|:---------------------:|:----------------------:|
| 1.5385 | 10 | 8.1013 | - | - | - | - | - |
| 3.0769 | 20 | 0.87 | - | - | - | - | - |
| 4.6154 | 30 | 0.2172 | - | - | - | - | - |
| 6.1538 | 40 | 0.0 | - | - | - | - | - |
| **7.3846** | **48** | **-** | **0.0272** | **0.0313** | **0.0293** | **0.0333** | **0.0285** |
| 1.2692 | 50 | 1.4329 | - | - | - | - | - |
| 2.8077 | 60 | 2.9916 | 0.0272 | 0.0314 | 0.0293 | 0.0335 | 0.0287 |
* The bold row denotes the saved checkpoint.
### Framework Versions
- Python: 3.10.12
- Sentence Transformers: 3.0.1
- Transformers: 4.41.2
- PyTorch: 2.1.2+cu121
- Accelerate: 0.32.1
- Datasets: 2.19.1
- Tokenizers: 0.19.1
## Citation
### BibTeX
#### Sentence Transformers
```bibtex
@inproceedings{reimers-2019-sentence-bert,
title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks",
author = "Reimers, Nils and Gurevych, Iryna",
booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing",
month = "11",
year = "2019",
publisher = "Association for Computational Linguistics",
url = "https://arxiv.org/abs/1908.10084",
}
```
#### MatryoshkaLoss
```bibtex
@misc{kusupati2024matryoshka,
title={Matryoshka Representation Learning},
author={Aditya Kusupati and Gantavya Bhatt and Aniket Rege and Matthew Wallingford and Aditya Sinha and Vivek Ramanujan and William Howard-Snyder and Kaifeng Chen and Sham Kakade and Prateek Jain and Ali Farhadi},
year={2024},
eprint={2205.13147},
archivePrefix={arXiv},
primaryClass={cs.LG}
}
```
#### MultipleNegativesRankingLoss
```bibtex
@misc{henderson2017efficient,
title={Efficient Natural Language Response Suggestion for Smart Reply},
author={Matthew Henderson and Rami Al-Rfou and Brian Strope and Yun-hsuan Sung and Laszlo Lukacs and Ruiqi Guo and Sanjiv Kumar and Balint Miklos and Ray Kurzweil},
year={2017},
eprint={1705.00652},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
```
<!--
## Glossary
*Clearly define terms in order to be accessible across audiences.*
-->
<!--
## Model Card Authors
*Lists the people who create the model card, providing recognition and accountability for the detailed work that goes into its construction.*
-->
<!--
## Model Card Contact
*Provides a way for people who have updates to the Model Card, suggestions, or questions, to contact the Model Card authors.*
--> |