---
model-index:
- name: karsar/gte-multilingual-base-hu
results:
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config: hun_Latn-hun_Latn
name: MTEB BelebeleRetrieval (hun_Latn-hun_Latn)
revision: 75b399394a9803252cfec289d103de462763db7c
split: test
type: facebook/belebele
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task:
type: Retrieval
- dataset:
config: hun_Latn-eng_Latn
name: MTEB BelebeleRetrieval (hun_Latn-eng_Latn)
revision: 75b399394a9803252cfec289d103de462763db7c
split: test
type: facebook/belebele
metrics:
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task:
type: Retrieval
- dataset:
config: eng_Latn-hun_Latn
name: MTEB BelebeleRetrieval (eng_Latn-hun_Latn)
revision: 75b399394a9803252cfec289d103de462763db7c
split: test
type: facebook/belebele
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task:
type: Retrieval
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config: eng_Latn-hun_Latn
name: MTEB BibleNLPBitextMining (eng_Latn-hun_Latn)
revision: 264a18480c529d9e922483839b4b9758e690b762
split: train
type: davidstap/biblenlp-corpus-mmteb
metrics:
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value: 76.953125
task:
type: BitextMining
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config: hun_Latn-eng_Latn
name: MTEB BibleNLPBitextMining (hun_Latn-eng_Latn)
revision: 264a18480c529d9e922483839b4b9758e690b762
split: train
type: davidstap/biblenlp-corpus-mmteb
metrics:
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task:
type: BitextMining
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config: default
name: MTEB HunSum2AbstractiveRetrieval (default)
revision: 24e1445c8180d937f0a16f8ae8a62e77cc952e56
split: test
type: SZTAKI-HLT/HunSum-2-abstractive
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task:
type: Retrieval
- dataset:
config: hu
name: MTEB MassiveIntentClassification (hu)
revision: 4672e20407010da34463acc759c162ca9734bca6
split: test
type: mteb/amazon_massive_intent
metrics:
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value: 55.823806321452594
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value: 50.78756643922222
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value: 55.11520680706619
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value: 55.823806321452594
task:
type: Classification
- dataset:
config: hu
name: MTEB MassiveIntentClassification (hu)
revision: 4672e20407010da34463acc759c162ca9734bca6
split: validation
type: mteb/amazon_massive_intent
metrics:
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value: 54.66797835710773
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value: 49.5096347438473
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value: 53.73310190085533
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task:
type: Classification
- dataset:
config: hu
name: MTEB MassiveScenarioClassification (hu)
revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
split: test
type: mteb/amazon_massive_scenario
metrics:
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value: 63.37256220578345
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value: 61.58399629628825
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value: 63.13464436259451
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task:
type: Classification
- dataset:
config: hu
name: MTEB MassiveScenarioClassification (hu)
revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
split: validation
type: mteb/amazon_massive_scenario
metrics:
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value: 62.03148057058534
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value: 60.9893800714451
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value: 61.85509382597554
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value: 62.03148057058534
task:
type: Classification
- dataset:
config: hu
name: MTEB MultiEURLEXMultilabelClassification (hu)
revision: 2aea5a6dc8fdcfeca41d0fb963c0a338930bde5c
split: test
type: mteb/eurlex-multilingual
metrics:
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value: 3.0380000000000003
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value: 27.32839484028383
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value: 41.09644076719448
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value: 3.0380000000000003
task:
type: MultilabelClassification
- dataset:
config: arb_Arab-hun_Latn
name: MTEB NTREXBitextMining (arb_Arab-hun_Latn)
revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
split: test
type: mteb/NTREX
metrics:
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value: 83.07461191787682
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value: 78.97012184944082
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value: 78.97012184944082
- type: precision
value: 77.16324486730095
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value: 83.07461191787682
task:
type: BitextMining
- dataset:
config: ben_Beng-hun_Latn
name: MTEB NTREXBitextMining (ben_Beng-hun_Latn)
revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
split: test
type: mteb/NTREX
metrics:
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value: 81.2719078617927
- type: f1
value: 76.6133724396118
- type: main_score
value: 76.6133724396118
- type: precision
value: 74.5247633354794
- type: recall
value: 81.2719078617927
task:
type: BitextMining
- dataset:
config: deu_Latn-hun_Latn
name: MTEB NTREXBitextMining (deu_Latn-hun_Latn)
revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
split: test
type: mteb/NTREX
metrics:
- type: accuracy
value: 90.78617926890335
- type: f1
value: 88.27073944249707
- type: main_score
value: 88.27073944249707
- type: precision
value: 87.1056584877316
- type: recall
value: 90.78617926890335
task:
type: BitextMining
- dataset:
config: ell_Grek-hun_Latn
name: MTEB NTREXBitextMining (ell_Grek-hun_Latn)
revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
split: test
type: mteb/NTREX
metrics:
- type: accuracy
value: 89.08362543815723
- type: f1
value: 86.19429143715574
- type: main_score
value: 86.19429143715574
- type: precision
value: 84.85728592889333
- type: recall
value: 89.08362543815723
task:
type: BitextMining
- dataset:
config: eng_Latn-hun_Latn
name: MTEB NTREXBitextMining (eng_Latn-hun_Latn)
revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
split: test
type: mteb/NTREX
metrics:
- type: accuracy
value: 93.23985978968453
- type: f1
value: 91.4087798364213
- type: main_score
value: 91.4087798364213
- type: precision
value: 90.57753296611585
- type: recall
value: 93.23985978968453
task:
type: BitextMining
- dataset:
config: fas_Arab-hun_Latn
name: MTEB NTREXBitextMining (fas_Arab-hun_Latn)
revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
split: test
type: mteb/NTREX
metrics:
- type: accuracy
value: 86.37956935403105
- type: f1
value: 82.8442663995994
- type: main_score
value: 82.8442663995994
- type: precision
value: 81.2635620096812
- type: recall
value: 86.37956935403105
task:
type: BitextMining
- dataset:
config: fin_Latn-hun_Latn
name: MTEB NTREXBitextMining (fin_Latn-hun_Latn)
revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
split: test
type: mteb/NTREX
metrics:
- type: accuracy
value: 85.42814221331997
- type: f1
value: 81.80031952690942
- type: main_score
value: 81.80031952690942
- type: precision
value: 80.1235186112502
- type: recall
value: 85.42814221331997
task:
type: BitextMining
- dataset:
config: fra_Latn-hun_Latn
name: MTEB NTREXBitextMining (fra_Latn-hun_Latn)
revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
split: test
type: mteb/NTREX
metrics:
- type: accuracy
value: 90.83625438157236
- type: f1
value: 88.31079953263227
- type: main_score
value: 88.31079953263227
- type: precision
value: 87.11817726589885
- type: recall
value: 90.83625438157236
task:
type: BitextMining
- dataset:
config: heb_Hebr-hun_Latn
name: MTEB NTREXBitextMining (heb_Hebr-hun_Latn)
revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
split: test
type: mteb/NTREX
metrics:
- type: accuracy
value: 81.32198297446169
- type: f1
value: 76.4972458688032
- type: main_score
value: 76.4972458688032
- type: precision
value: 74.3578462932494
- type: recall
value: 81.32198297446169
task:
type: BitextMining
- dataset:
config: hin_Deva-hun_Latn
name: MTEB NTREXBitextMining (hin_Deva-hun_Latn)
revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
split: test
type: mteb/NTREX
metrics:
- type: accuracy
value: 86.37956935403105
- type: f1
value: 82.83341679185445
- type: main_score
value: 82.83341679185445
- type: precision
value: 81.21563297326942
- type: recall
value: 86.37956935403105
task:
type: BitextMining
- dataset:
config: hun_Latn-arb_Arab
name: MTEB NTREXBitextMining (hun_Latn-arb_Arab)
revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
split: test
type: mteb/NTREX
metrics:
- type: accuracy
value: 82.22333500250375
- type: f1
value: 77.76760378663232
- type: main_score
value: 77.76760378663232
- type: precision
value: 75.81634356296348
- type: recall
value: 82.22333500250375
task:
type: BitextMining
- dataset:
config: hun_Latn-ben_Beng
name: MTEB NTREXBitextMining (hun_Latn-ben_Beng)
revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
split: test
type: mteb/NTREX
metrics:
- type: accuracy
value: 77.56634952428642
- type: f1
value: 72.28537250319926
- type: main_score
value: 72.28537250319926
- type: precision
value: 70.02032811121445
- type: recall
value: 77.56634952428642
task:
type: BitextMining
- dataset:
config: hun_Latn-deu_Latn
name: MTEB NTREXBitextMining (hun_Latn-deu_Latn)
revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
split: test
type: mteb/NTREX
metrics:
- type: accuracy
value: 91.4371557336004
- type: f1
value: 89.27391086629945
- type: main_score
value: 89.27391086629945
- type: precision
value: 88.24904022700719
- type: recall
value: 91.4371557336004
task:
type: BitextMining
- dataset:
config: hun_Latn-ell_Grek
name: MTEB NTREXBitextMining (hun_Latn-ell_Grek)
revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
split: test
type: mteb/NTREX
metrics:
- type: accuracy
value: 88.3825738607912
- type: f1
value: 85.36900588978705
- type: main_score
value: 85.36900588978705
- type: precision
value: 83.98848272408614
- type: recall
value: 88.3825738607912
task:
type: BitextMining
- dataset:
config: hun_Latn-eng_Latn
name: MTEB NTREXBitextMining (hun_Latn-eng_Latn)
revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
split: test
type: mteb/NTREX
metrics:
- type: accuracy
value: 94.2914371557336
- type: f1
value: 92.68903355032549
- type: main_score
value: 92.68903355032549
- type: precision
value: 91.92121515606743
- type: recall
value: 94.2914371557336
task:
type: BitextMining
- dataset:
config: hun_Latn-fas_Arab
name: MTEB NTREXBitextMining (hun_Latn-fas_Arab)
revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
split: test
type: mteb/NTREX
metrics:
- type: accuracy
value: 84.72709063595393
- type: f1
value: 80.81622433650475
- type: main_score
value: 80.81622433650475
- type: precision
value: 79.05524954097814
- type: recall
value: 84.72709063595393
task:
type: BitextMining
- dataset:
config: hun_Latn-fin_Latn
name: MTEB NTREXBitextMining (hun_Latn-fin_Latn)
revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
split: test
type: mteb/NTREX
metrics:
- type: accuracy
value: 83.57536304456686
- type: f1
value: 79.32338984667477
- type: main_score
value: 79.32338984667477
- type: precision
value: 77.45833035267187
- type: recall
value: 83.57536304456686
task:
type: BitextMining
- dataset:
config: hun_Latn-fra_Latn
name: MTEB NTREXBitextMining (hun_Latn-fra_Latn)
revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
split: test
type: mteb/NTREX
metrics:
- type: accuracy
value: 90.48572859288933
- type: f1
value: 87.94954336266304
- type: main_score
value: 87.94954336266304
- type: precision
value: 86.75429811383744
- type: recall
value: 90.48572859288933
task:
type: BitextMining
- dataset:
config: hun_Latn-heb_Hebr
name: MTEB NTREXBitextMining (hun_Latn-heb_Hebr)
revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
split: test
type: mteb/NTREX
metrics:
- type: accuracy
value: 77.21582373560341
- type: f1
value: 71.82277384330463
- type: main_score
value: 71.82277384330463
- type: precision
value: 69.55856403653098
- type: recall
value: 77.21582373560341
task:
type: BitextMining
- dataset:
config: hun_Latn-hin_Deva
name: MTEB NTREXBitextMining (hun_Latn-hin_Deva)
revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
split: test
type: mteb/NTREX
metrics:
- type: accuracy
value: 84.77716574862293
- type: f1
value: 80.97423913648251
- type: main_score
value: 80.97423913648251
- type: precision
value: 79.27265898848273
- type: recall
value: 84.77716574862293
task:
type: BitextMining
- dataset:
config: hun_Latn-ind_Latn
name: MTEB NTREXBitextMining (hun_Latn-ind_Latn)
revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
split: test
type: mteb/NTREX
metrics:
- type: accuracy
value: 90.0350525788683
- type: f1
value: 87.28592889334
- type: main_score
value: 87.28592889334
- type: precision
value: 85.99732932732432
- type: recall
value: 90.0350525788683
task:
type: BitextMining
- dataset:
config: hun_Latn-jpn_Jpan
name: MTEB NTREXBitextMining (hun_Latn-jpn_Jpan)
revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
split: test
type: mteb/NTREX
metrics:
- type: accuracy
value: 84.37656484727091
- type: f1
value: 80.59017097074182
- type: main_score
value: 80.59017097074182
- type: precision
value: 78.94508429310633
- type: recall
value: 84.37656484727091
task:
type: BitextMining
- dataset:
config: hun_Latn-kor_Hang
name: MTEB NTREXBitextMining (hun_Latn-kor_Hang)
revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
split: test
type: mteb/NTREX
metrics:
- type: accuracy
value: 80.77115673510265
- type: f1
value: 76.35683684256543
- type: main_score
value: 76.35683684256543
- type: precision
value: 74.47361699114327
- type: recall
value: 80.77115673510265
task:
type: BitextMining
- dataset:
config: hun_Latn-lav_Latn
name: MTEB NTREXBitextMining (hun_Latn-lav_Latn)
revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
split: test
type: mteb/NTREX
metrics:
- type: accuracy
value: 76.81522283425137
- type: f1
value: 71.24067052960392
- type: main_score
value: 71.24067052960392
- type: precision
value: 68.94003703968652
- type: recall
value: 76.81522283425137
task:
type: BitextMining
- dataset:
config: hun_Latn-lit_Latn
name: MTEB NTREXBitextMining (hun_Latn-lit_Latn)
revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
split: test
type: mteb/NTREX
metrics:
- type: accuracy
value: 77.3159739609414
- type: f1
value: 71.92622266733433
- type: main_score
value: 71.92622266733433
- type: precision
value: 69.58461501776473
- type: recall
value: 77.3159739609414
task:
type: BitextMining
- dataset:
config: hun_Latn-nld_Latn
name: MTEB NTREXBitextMining (hun_Latn-nld_Latn)
revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
split: test
type: mteb/NTREX
metrics:
- type: accuracy
value: 90.98647971957938
- type: f1
value: 88.5027541311968
- type: main_score
value: 88.5027541311968
- type: precision
value: 87.33683859122017
- type: recall
value: 90.98647971957938
task:
type: BitextMining
- dataset:
config: hun_Latn-pol_Latn
name: MTEB NTREXBitextMining (hun_Latn-pol_Latn)
revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
split: test
type: mteb/NTREX
metrics:
- type: accuracy
value: 88.43264897346019
- type: f1
value: 85.33896082218565
- type: main_score
value: 85.33896082218565
- type: precision
value: 83.90919712902688
- type: recall
value: 88.43264897346019
task:
type: BitextMining
- dataset:
config: hun_Latn-por_Latn
name: MTEB NTREXBitextMining (hun_Latn-por_Latn)
revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
split: test
type: mteb/NTREX
metrics:
- type: accuracy
value: 90.68602904356536
- type: f1
value: 88.09046903688868
- type: main_score
value: 88.09046903688868
- type: precision
value: 86.88449340677683
- type: recall
value: 90.68602904356536
task:
type: BitextMining
- dataset:
config: hun_Latn-rus_Cyrl
name: MTEB NTREXBitextMining (hun_Latn-rus_Cyrl)
revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
split: test
type: mteb/NTREX
metrics:
- type: accuracy
value: 90.0350525788683
- type: f1
value: 87.35770322149892
- type: main_score
value: 87.35770322149892
- type: precision
value: 86.10832916040727
- type: recall
value: 90.0350525788683
task:
type: BitextMining
- dataset:
config: hun_Latn-spa_Latn
name: MTEB NTREXBitextMining (hun_Latn-spa_Latn)
revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
split: test
type: mteb/NTREX
metrics:
- type: accuracy
value: 92.58888332498748
- type: f1
value: 90.64763812385245
- type: main_score
value: 90.64763812385245
- type: precision
value: 89.75880487397765
- type: recall
value: 92.58888332498748
task:
type: BitextMining
- dataset:
config: hun_Latn-swa_Latn
name: MTEB NTREXBitextMining (hun_Latn-swa_Latn)
revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
split: test
type: mteb/NTREX
metrics:
- type: accuracy
value: 72.60891337005508
- type: f1
value: 66.62728580605396
- type: main_score
value: 66.62728580605396
- type: precision
value: 64.22842597229177
- type: recall
value: 72.60891337005508
task:
type: BitextMining
- dataset:
config: hun_Latn-swe_Latn
name: MTEB NTREXBitextMining (hun_Latn-swe_Latn)
revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
split: test
type: mteb/NTREX
metrics:
- type: accuracy
value: 89.03355032548824
- type: f1
value: 86.01569020196962
- type: main_score
value: 86.01569020196962
- type: precision
value: 84.59105324653648
- type: recall
value: 89.03355032548824
task:
type: BitextMining
- dataset:
config: hun_Latn-tam_Taml
name: MTEB NTREXBitextMining (hun_Latn-tam_Taml)
revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
split: test
type: mteb/NTREX
metrics:
- type: accuracy
value: 74.66199298948423
- type: f1
value: 68.7971639999682
- type: main_score
value: 68.7971639999682
- type: precision
value: 66.36091041323891
- type: recall
value: 74.66199298948423
task:
type: BitextMining
- dataset:
config: hun_Latn-tur_Latn
name: MTEB NTREXBitextMining (hun_Latn-tur_Latn)
revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
split: test
type: mteb/NTREX
metrics:
- type: accuracy
value: 87.08062093139709
- type: f1
value: 83.79736271073277
- type: main_score
value: 83.79736271073277
- type: precision
value: 82.33278489162315
- type: recall
value: 87.08062093139709
task:
type: BitextMining
- dataset:
config: hun_Latn-vie_Latn
name: MTEB NTREXBitextMining (hun_Latn-vie_Latn)
revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
split: test
type: mteb/NTREX
metrics:
- type: accuracy
value: 89.78467701552329
- type: f1
value: 87.0288766483058
- type: main_score
value: 87.0288766483058
- type: precision
value: 85.76781839425806
- type: recall
value: 89.78467701552329
task:
type: BitextMining
- dataset:
config: hun_Latn-zho_Hant
name: MTEB NTREXBitextMining (hun_Latn-zho_Hant)
revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
split: test
type: mteb/NTREX
metrics:
- type: accuracy
value: 87.33099649474211
- type: f1
value: 84.02103154732097
- type: main_score
value: 84.02103154732097
- type: precision
value: 82.51877816725089
- type: recall
value: 87.33099649474211
task:
type: BitextMining
- dataset:
config: hun_Latn-zul_Latn
name: MTEB NTREXBitextMining (hun_Latn-zul_Latn)
revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
split: test
type: mteb/NTREX
metrics:
- type: accuracy
value: 51.92789183775663
- type: f1
value: 43.912175926815536
- type: main_score
value: 43.912175926815536
- type: precision
value: 41.09881091478487
- type: recall
value: 51.92789183775663
task:
type: BitextMining
- dataset:
config: ind_Latn-hun_Latn
name: MTEB NTREXBitextMining (ind_Latn-hun_Latn)
revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
split: test
type: mteb/NTREX
metrics:
- type: accuracy
value: 90.1352028042063
- type: f1
value: 87.51722822328732
- type: main_score
value: 87.51722822328732
- type: precision
value: 86.31280253713905
- type: recall
value: 90.1352028042063
task:
type: BitextMining
- dataset:
config: jpn_Jpan-hun_Latn
name: MTEB NTREXBitextMining (jpn_Jpan-hun_Latn)
revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
split: test
type: mteb/NTREX
metrics:
- type: accuracy
value: 84.37656484727091
- type: f1
value: 80.56084126189283
- type: main_score
value: 80.56084126189283
- type: precision
value: 78.84743782340176
- type: recall
value: 84.37656484727091
task:
type: BitextMining
- dataset:
config: kor_Hang-hun_Latn
name: MTEB NTREXBitextMining (kor_Hang-hun_Latn)
revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
split: test
type: mteb/NTREX
metrics:
- type: accuracy
value: 83.47521281922884
- type: f1
value: 79.41519421990128
- type: main_score
value: 79.41519421990128
- type: precision
value: 77.57350311181057
- type: recall
value: 83.47521281922884
task:
type: BitextMining
- dataset:
config: lav_Latn-hun_Latn
name: MTEB NTREXBitextMining (lav_Latn-hun_Latn)
revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
split: test
type: mteb/NTREX
metrics:
- type: accuracy
value: 82.12318477716575
- type: f1
value: 78.18656556262967
- type: main_score
value: 78.18656556262967
- type: precision
value: 76.41879485895511
- type: recall
value: 82.12318477716575
task:
type: BitextMining
- dataset:
config: lit_Latn-hun_Latn
name: MTEB NTREXBitextMining (lit_Latn-hun_Latn)
revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
split: test
type: mteb/NTREX
metrics:
- type: accuracy
value: 81.67250876314472
- type: f1
value: 77.52628943415122
- type: main_score
value: 77.52628943415122
- type: precision
value: 75.62426973794024
- type: recall
value: 81.67250876314472
task:
type: BitextMining
- dataset:
config: nld_Latn-hun_Latn
name: MTEB NTREXBitextMining (nld_Latn-hun_Latn)
revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
split: test
type: mteb/NTREX
metrics:
- type: accuracy
value: 91.03655483224837
- type: f1
value: 88.62404718188392
- type: main_score
value: 88.62404718188392
- type: precision
value: 87.50584209647806
- type: recall
value: 91.03655483224837
task:
type: BitextMining
- dataset:
config: pol_Latn-hun_Latn
name: MTEB NTREXBitextMining (pol_Latn-hun_Latn)
revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
split: test
type: mteb/NTREX
metrics:
- type: accuracy
value: 88.73309964947421
- type: f1
value: 85.63869613944726
- type: main_score
value: 85.63869613944726
- type: precision
value: 84.21799365715239
- type: recall
value: 88.73309964947421
task:
type: BitextMining
- dataset:
config: por_Latn-hun_Latn
name: MTEB NTREXBitextMining (por_Latn-hun_Latn)
revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
split: test
type: mteb/NTREX
metrics:
- type: accuracy
value: 91.03655483224837
- type: f1
value: 88.54782173259889
- type: main_score
value: 88.54782173259889
- type: precision
value: 87.39108662994491
- type: recall
value: 91.03655483224837
task:
type: BitextMining
- dataset:
config: rus_Cyrl-hun_Latn
name: MTEB NTREXBitextMining (rus_Cyrl-hun_Latn)
revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
split: test
type: mteb/NTREX
metrics:
- type: accuracy
value: 88.88332498748123
- type: f1
value: 85.8447194601426
- type: main_score
value: 85.8447194601426
- type: precision
value: 84.45751961275246
- type: recall
value: 88.88332498748123
task:
type: BitextMining
- dataset:
config: spa_Latn-hun_Latn
name: MTEB NTREXBitextMining (spa_Latn-hun_Latn)
revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
split: test
type: mteb/NTREX
metrics:
- type: accuracy
value: 92.13820731096645
- type: f1
value: 89.933233183108
- type: main_score
value: 89.933233183108
- type: precision
value: 88.92004673677182
- type: recall
value: 92.13820731096645
task:
type: BitextMining
- dataset:
config: swa_Latn-hun_Latn
name: MTEB NTREXBitextMining (swa_Latn-hun_Latn)
revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
split: test
type: mteb/NTREX
metrics:
- type: accuracy
value: 75.7636454682023
- type: f1
value: 71.19297994610965
- type: main_score
value: 71.19297994610965
- type: precision
value: 69.29461652796655
- type: recall
value: 75.7636454682023
task:
type: BitextMining
- dataset:
config: swe_Latn-hun_Latn
name: MTEB NTREXBitextMining (swe_Latn-hun_Latn)
revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
split: test
type: mteb/NTREX
metrics:
- type: accuracy
value: 89.83475212819229
- type: f1
value: 87.25779144907837
- type: main_score
value: 87.25779144907837
- type: precision
value: 86.05408112168253
- type: recall
value: 89.83475212819229
task:
type: BitextMining
- dataset:
config: tam_Taml-hun_Latn
name: MTEB NTREXBitextMining (tam_Taml-hun_Latn)
revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
split: test
type: mteb/NTREX
metrics:
- type: accuracy
value: 78.01702553830746
- type: f1
value: 72.70886488462853
- type: main_score
value: 72.70886488462853
- type: precision
value: 70.39064549204758
- type: recall
value: 78.01702553830746
task:
type: BitextMining
- dataset:
config: tur_Latn-hun_Latn
name: MTEB NTREXBitextMining (tur_Latn-hun_Latn)
revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
split: test
type: mteb/NTREX
metrics:
- type: accuracy
value: 87.33099649474211
- type: f1
value: 84.28094522736485
- type: main_score
value: 84.28094522736485
- type: precision
value: 82.89100317142379
- type: recall
value: 87.33099649474211
task:
type: BitextMining
- dataset:
config: vie_Latn-hun_Latn
name: MTEB NTREXBitextMining (vie_Latn-hun_Latn)
revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
split: test
type: mteb/NTREX
metrics:
- type: accuracy
value: 89.23385077616425
- type: f1
value: 86.38290769487564
- type: main_score
value: 86.38290769487564
- type: precision
value: 85.08763144717074
- type: recall
value: 89.23385077616425
task:
type: BitextMining
- dataset:
config: zho_Hant-hun_Latn
name: MTEB NTREXBitextMining (zho_Hant-hun_Latn)
revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
split: test
type: mteb/NTREX
metrics:
- type: accuracy
value: 86.52979469203805
- type: f1
value: 82.964446670005
- type: main_score
value: 82.964446670005
- type: precision
value: 81.4104490068436
- type: recall
value: 86.52979469203805
task:
type: BitextMining
- dataset:
config: zul_Latn-hun_Latn
name: MTEB NTREXBitextMining (zul_Latn-hun_Latn)
revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
split: test
type: mteb/NTREX
metrics:
- type: accuracy
value: 54.98247371056585
- type: f1
value: 48.79136275731169
- type: main_score
value: 48.79136275731169
- type: precision
value: 46.53637850035387
- type: recall
value: 54.98247371056585
task:
type: BitextMining
- dataset:
config: rom-hun
name: MTEB RomaTalesBitextMining (rom-hun)
revision: f4394dbca6845743cd33eba77431767b232ef489
split: test
type: kardosdrur/roma-tales
metrics:
- type: accuracy
value: 10.69767441860465
- type: f1
value: 6.300343882963222
- type: main_score
value: 6.300343882963222
- type: precision
value: 5.2912513842746405
- type: recall
value: 10.69767441860465
task:
type: BitextMining
- dataset:
config: hun_Latn
name: MTEB SIB200Classification (hun_Latn)
revision: a74d7350ea12af010cfb1c21e34f1f81fd2e615b
split: test
type: mteb/sib200
metrics:
- type: accuracy
value: 70.7843137254902
- type: f1
value: 69.54715341688494
- type: f1_weighted
value: 70.80982490835149
- type: main_score
value: 70.7843137254902
task:
type: Classification
- dataset:
config: hun_Latn
name: MTEB SIB200Classification (hun_Latn)
revision: a74d7350ea12af010cfb1c21e34f1f81fd2e615b
split: train
type: mteb/sib200
metrics:
- type: accuracy
value: 71.04136947218261
- type: f1
value: 69.53067958950989
- type: f1_weighted
value: 71.08855534234819
- type: main_score
value: 71.04136947218261
task:
type: Classification
- dataset:
config: hun_Latn
name: MTEB SIB200Classification (hun_Latn)
revision: a74d7350ea12af010cfb1c21e34f1f81fd2e615b
split: validation
type: mteb/sib200
metrics:
- type: accuracy
value: 67.77777777777779
- type: f1
value: 65.81682696212664
- type: f1_weighted
value: 68.15630936254685
- type: main_score
value: 67.77777777777779
task:
type: Classification
- dataset:
config: hun_Latn
name: MTEB SIB200ClusteringS2S (hun_Latn)
revision: a74d7350ea12af010cfb1c21e34f1f81fd2e615b
split: test
type: mteb/sib200
metrics:
- type: main_score
value: 37.555486757695725
- type: v_measure
value: 37.555486757695725
- type: v_measure_std
value: 5.704486435014278
task:
type: Clustering
- dataset:
config: hun-eng
name: MTEB Tatoeba (hun-eng)
revision: 69e8f12da6e31d59addadda9a9c8a2e601a0e282
split: test
type: mteb/tatoeba-bitext-mining
metrics:
- type: accuracy
value: 80.9
- type: f1
value: 76.77888888888889
- type: main_score
value: 76.77888888888889
- type: precision
value: 74.9825
- type: recall
value: 80.9
task:
type: BitextMining
tags:
- mteb
---
base_model: Alibaba-NLP/gte-multilingual-base
language:
- hu
library_name: sentence-transformers
license: apache-2.0
# gte-multilingual-base-hu
This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [Alibaba-NLP/gte-multilingual-base](https://huggingface.co/Alibaba-NLP/gte-multilingual-base) on the train dataset. 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:** [Alibaba-NLP/gte-multilingual-base](https://huggingface.co/Alibaba-NLP/gte-multilingual-base)
- **Maximum Sequence Length:** 8192 tokens
- **Output Dimensionality:** 768 tokens
- **Similarity Function:** Cosine Similarity
- **Training Dataset:**
- train
- **Language:** hu
- **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': 8192, 'do_lower_case': False}) with Transformer model: NewModel
(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("karsar/gte-multilingual-base-hu")
# Run inference
sentences = [
'Az emberek alszanak.',
'Egy apa és a fia ölelgeti alvás közben.',
'Egy csoport ember ül egy nyitott, térszerű területen, mögötte nagy bokrok és egy sor viktoriánus stÃlusú épület, melyek közül sokat a kép jobb oldalán lévÅ‘ erÅ‘s elmosódás tesz kivehetetlenné.',
]
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]
```
## Evaluation
### Metrics
#### Triplet
* Dataset: `all-nli-dev`
* Evaluated with [TripletEvaluator
](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.TripletEvaluator)
| Metric | Value |
|:-------------------|:-----------|
| cosine_accuracy | 0.9676 |
| dot_accuracy | 0.0324 |
| manhattan_accuracy | 0.9688 |
| euclidean_accuracy | 0.9676 |
| **max_accuracy** | **0.9688** |
#### Triplet
* Dataset: `all-nli-test`
* Evaluated with [TripletEvaluator
](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.TripletEvaluator)
| Metric | Value |
|:-------------------|:-----------|
| cosine_accuracy | 0.9718 |
| dot_accuracy | 0.0282 |
| manhattan_accuracy | 0.9726 |
| euclidean_accuracy | 0.9718 |
| **max_accuracy** | **0.9726** |
## Training Details
### Training Dataset
#### train
* Dataset: train
* Size: 1,044,013 training samples
* Columns: anchor
, positive
, and negative
* Approximate statistics based on the first 1000 samples:
| | anchor | positive | negative |
|:--------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|
| type | string | string | string |
| details |
Egy lóháton ülő ember átugrik egy lerombolt repülőgép felett.
| Egy ember a szabadban, lóháton.
| Egy ember egy étteremben van, és omlettet rendel.
|
| Gyerekek mosolyogva és integetett a kamera
| Gyermekek vannak jelen
| A gyerekek homlokot rántanak
|
| Egy fiú ugrál a gördeszkát a közepén egy piros hÃd.
| A fiú gördeszkás trükköt csinál.
| A fiú korcsolyázik a járdán.
|
* Loss: [MultipleNegativesRankingLoss
](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#multiplenegativesrankingloss) with these parameters:
```json
{
"scale": 20.0,
"similarity_fct": "cos_sim"
}
```
### Evaluation Dataset
#### train
* Dataset: train
* Size: 5,000 evaluation samples
* Columns: anchor
, positive
, and negative
* Approximate statistics based on the first 1000 samples:
| | anchor | positive | negative |
|:--------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|
| type | string | string | string |
| details | Egy lóháton ülő ember átugrik egy lerombolt repülőgép felett.
| Egy ember a szabadban, lóháton.
| Egy ember egy étteremben van, és omlettet rendel.
|
| Gyerekek mosolyogva és integetett a kamera
| Gyermekek vannak jelen
| A gyerekek homlokot rántanak
|
| Egy fiú ugrál a gördeszkát a közepén egy piros hÃd.
| A fiú gördeszkás trükköt csinál.
| A fiú korcsolyázik a járdán.
|
* Loss: [MultipleNegativesRankingLoss
](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#multiplenegativesrankingloss) with these parameters:
```json
{
"scale": 20.0,
"similarity_fct": "cos_sim"
}
```
### Training Hyperparameters
#### Non-Default Hyperparameters
- `eval_strategy`: steps
- `num_train_epochs`: 1
- `warmup_ratio`: 0.1
- `bf16`: True
- `batch_sampler`: no_duplicates
#### All Hyperparameters