Model: NohTow/ModernBERT-base-DPR-fullneg-gte-0.0002
Author: NohTow
Pipeline: sentence-similarity
Library: sentence-transformers
Tags: sentence-transformers, safetensors, modernbert, sentence-similarity, feature-extraction, generated_from_trainer, dataset_size:1770649, loss:CachedMultipleNegativesRankingLoss, dataset:cfli/bge-full-data, arxiv:1908.10084, arxiv:2101.06983, model-index, text-embeddings-inference, endpoints_compatible, region:us
Card metadata: datasets: cfli/bge-full-data
library_name: sentence-transformers
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:1770649, loss:CachedMultipleNegativesRankingLoss
widget: source_sentence: what is the pulse in your wrist called
sentences: Pulse cm up the forearm is suggestive of arteriosclerosis. In coarctation of aorta, femoral pulse may be significantly delayed as compared to radial pulse (unless there is coexisting aortic regurgitation). The delay can also be observed in supravalvar aortic stenosis. Several pulse patterns can be of clinically significance. These include: Chinese medicine has focused on the pulse in the upper limbs for several centuries. The concept of pulse diagnosis is essentially based on palpation and observations of the radial and ulnar volar pulses at the readily accessible wrist. Although the pulse can be felt in multiple places in the head, people, Pulse diagnosis into three positions on each wrist. The first pulse closest to the wrist is the "cun" (inch, 寸) position, the second "guan" (gate, 關), and the third pulse position furthest away from the wrist is the "chi" (foot, 尺). There are several systems of diagnostic interpretation of pulse findings utilised in the Chinese medicine system. Some systems (Cun Kou) utilise overall pulse qualities, looking at changes in the assessed parameters of the pulse to derive one of the traditional 28 pulse types. Other approaches focus on individual pulse positions, looking at changes in the pulse quality and strength within the, Pre-hospital trauma assessment inside of the wrist toward the thumb. For unresponsive adult patients, checking pulse is performed by palpating the carotid artery in the neck. For infants and small children, the pulse is usually assessed in the brachial artery in the upper arm. After confirming that the pulse is present, the final step in the initial assessment for a trauma patient is to check for any gross bleeding and to control it. Should a pulse not be detected, or in the case of a child or infant is present but at a rate less than 60, cardiovascular resuscitation will be commenced. Steps:, Pulse Pulse In medicine, a pulse represents the tactile arterial palpation of the heartbeat by trained fingertips. The pulse may be palpated in any place that allows an artery to be compressed near the surface of the body, such as at the neck (carotid artery), wrist (radial artery), at the groin (femoral artery), behind the knee (popliteal artery), near the ankle joint (posterior tibial artery), and on foot (dorsalis pedis artery). Pulse (or the count of arterial pulse per minute) is equivalent to measuring the heart rate. The heart rate can also be measured by listening to the heart beat by, Pulse diagnosis dosha. The middle finger and ring finger are placed next to the index finger and represents consequently the Pitta and Kapha doshas of the patient. Pulse can be measured in the superficial, middle, and deep levels thus obtaining more information regarding energy imbalance of the patient. The main sites for pulse assessment are the radial arteries in the left and right wrists, where it overlays the styloid process of the radius, between the wrist crease and extending proximal, approximately 5 cm in length (or 1.9 cun, where the forearm is 12 cun). In traditional Chinese medicine, the pulse is divided, Pulse auscultation, traditionally using a stethoscope and counting it for a minute. The radial pulse is commonly measured using three fingers. This has a reason: the finger closest to the heart is used to occlude the pulse pressure, the middle finger is used get a crude estimate of the blood pressure, and the finger most distal to the heart (usually the ring finger) is used to nullify the effect of the ulnar pulse as the two arteries are connected via the palmar arches (superficial and deep). The study of the pulse is known as sphygmology. Claudius Galen was perhaps the first, source_sentence: Diet and Mass Conservation--We weigh as much as we eat?
sentences: [This thread](_URL_0_) contains a good comment string based on /u/Redwing999 experience and some written sources on insect obesity., We have two chemicals. One that tells us that we're full and the other that tells us something gives us pleasure. Through evolution, they made sure that the balance wouldn't tip. Now, the latter can override the former. That means you eat cake because it gives you pleasure even though you're full as hell. The balance has tipped and temptation gets in our way. This is one of the reasons for obesity!, This question actually has nothing to do with the law of conservation of mass or energy. You don't take up more mass by exercising; in fact, you technically **lose** mass because you are sweating water and other substances out, as well as converting your food into heat and having this heat escape your body.   It's just that when your muscle fibers are damaged through exercise, they "over-heal" (to put it very unsophisticated-sounding). The food you eat contributes to feeding these growing muscles, which adds more mass to your body. So you *lose* mass through exercising, but more than make up for it with a proper diet., A professor of nutrition went on a diet for 10 weeks, consisting largely of twinkies, oreos, and doritos. While still maintaining multivitamins and a protein shake daily with occasional greens as well to not go completely off the deep end. After the 10 weeks of controlling a steady stream of 1,800 calories a day he lost 27 pounds, lowered his bad cholesterol by 20% and upping his good cholesterol also by 20%. Most weight loss is from a steady intake in a caloric deficit (IE don't eat 1,700 of your daily 1,800 in one meal). If you do this make sure to also grab multivitamins if you don't already have them, and ensure you're getting some protein. Obviously these are also just short term results, and it's not recommended you over indulge in junk food over a balanced diet and daily exercise. Article link here (sorry for ghetto link I'm on my phone) _URL_0_, This is a great question. I hope we get some real answers.  I don't chew my food much, I'm pretty skinny and eat a ton..I always wondered if chewing less makes less nutrients available for absorption, There is a tremendous amount of misinformation surrounding calories and weight. [This blog entry](_URL_0_) does a good job of presenting why people so often get confused with regards to thermodynamics and food. There's a lot to learn, but it's a good start., source_sentence: Are Jett Pangan and Jon Fratelli both from Scotland?
sentences: Gary Lightbody Gary Lightbody (born 15 June 1976) is a Northern Irish singer, songwriter, guitarist and multi-instrumentalist, best known as the lead singer and rhythm guitarist of the Northern Irish-Scottish rock band Snow Patrol., Ray Wilson (musician) Raymond Wilson (born 8 September 1968) is a Scottish musician, best known as vocalist in the post-grunge band Stiltskin, and in Genesis from 1996 to 1998., Peter Frampton Peter Kenneth Frampton (born 22 April 1950) is an English rock musician, singer, songwriter, producer, and guitarist. He was previously associated with the bands Humble Pie and The Herd. At the end of his 'group' career was Frampton's international breakthrough album his live release, "Frampton Comes Alive!" The album sold in the United States more than 8 million copies and spawned several single hits. Since then he has released several major albums. He has also worked with David Bowie and both Matt Cameron and Mike McCready from Pearl Jam, among others., Rob Wainwright (rugby union) Robert Iain Wainwright (born 22 March 1965 in Perth, Scotland) is a former rugby union footballer who was capped 37 times for Scotland (Captain 16 times) and once for the British and Irish Lions. He played flanker., Bert Jansch Herbert "Bert" Jansch (3 November 1943 – 5 October 2011) was a Scottish folk musician and founding member of the band Pentangle. He was born in Glasgow and came to prominence in London in the 1960s, as an acoustic guitarist, as well as a singer-songwriter. He recorded at least 25 albums and toured extensively from the 1960s to the 21st century., Jett Pangan Jett Pangan (born Reginald Pangan on June 21, 1968) is a Filipino singer and guitarist best known for fronting the Filipino rock bands The Dawn, and the now defunct Jett Pangan Group. He is also an actor, appearing in several TV and films, most notably his role in "Tulad ng Dati". He is the half-brother of John Lapus., source_sentence: How can I control my mind from thinking too much?
sentences: Why is it that we always think about anything too much which is not even worth thinking?, When I'm around people I love my mind goes blank. As I get closer to someone it gets worse and worse. How can I change my way of thinking?, Why am I thinking too much?, Why am I thinking too much about everything?, If I keep choosing not to fully think about a concept or grab onto it when it appears in my mind while I am reading or doing something else, am I damaging my brain's ability to understand and act on those things in the future?, How do I keep my mind from thinking too much over a thing?, source_sentence: Who won 23 World Rally Championships, two in particular with the Lancia Delta Group A rally car?
sentences: Lancia Delta Group A The Lancia Delta Group A is a Group A rally car built for the Martini Lancia by Lancia to compete in the World Rally Championship. It is based upon the Lancia Delta road car and replaced the Lancia Delta S4. The car was introduced for the 1987 World Rally Championship season and dominated the World Rally Championship, scoring 46 WRC victories overall and winning the constructors' championship a record six times in a row from 1987 to 1992, in addition to drivers' championship titles for Juha Kankkunen (1987 and 1991) and Miki Biasion (1988 and 1989), making Lancia the most successful marque in the history of the WRC and the Delta the most successful car., Luis Moya Luis Rodríguez Moya, better known as Luis Moya (born 23 September 1960 in La Coruña, Spain) is a now-retired rally co-driver, synonymous with driver Carlos Sainz. He is the third most successful co-driver in the history of the World Rally Championship (WRC), after Daniel Elena and Timo Rautiainen, 2016 World Rally Championship-3 The 2016 World Rally Championship-3 was the fourth season of the World Rally Championship-3, an auto racing championship recognized by the Fédération Internationale de l'Automobile, ran in support of the World Rally Championship. It was created when the Group R class of rally car was introduced in 2013. The Championship was composed of fourteen rallies, and drivers and teams had to nominate a maximum of six events. The best five results counted towards the championship., 2015 Rally Catalunya The 2015 Rally Catalunya (formally the 51º Rally RACC Catalunya – Costa Daurada) was the twelfth round of the 2015 World Rally Championship. The race was held over four days between 22 October and 25 October 2015, and operated out of Salou, Catalonia, Spain. Volkswagen's Andreas Mikkelsen won the race, his first win in the World Rally Championship., Lancia Rally 037 The Lancia Rally ("Tipo 151", also known as the Lancia Rally 037, Lancia 037 or Lancia-Abarth #037 from its Abarth project code "037") was a mid-engine sports car and rally car built by Lancia in the early 1980s to compete in the FIA Group B World Rally Championship. Driven by Markku Alén, Attilio Bettega, and Walter Röhrl, the car won Lancia the manufacturers' world championship in the 1983 season. It was the last rear-wheel drive car to win the WRC., John Lund (racing driver) John Lund (born 12 January 1954) is a BriSCA Formula 1 Stock Cars racing driver from Rimington, Lancashire who races under number 53. Lund is one of the most successful stock car drivers of all time and holds the current record for the most World Championship wins.
model-index: name: SentenceTransformer
results: task: type: information-retrieval
name: Information Retrieval
dataset: name: NanoClimateFEVER
type: NanoClimateFEVER
metrics: type: cosine_accuracy@1
value: 0.22
name: Cosine Accuracy@1
verified: no, type: cosine_accuracy@3
value: 0.52
name: Cosine Accuracy@3
verified: no, type: cosine_accuracy@5
value: 0.6
name: Cosine Accuracy@5
verified: no, type: cosine_accuracy@10
value: 0.64
name: Cosine Accuracy@10
verified: no, type: cosine_precision@1
value: 0.22
name: Cosine Precision@1
verified: no, type: cosine_precision@3
value: 0.20666666666666667
name: Cosine Precision@3
verified: no, type: cosine_precision@5
value: 0.14400000000000002
name: Cosine Precision@5
verified: no, type: cosine_precision@10
value: 0.084
name: Cosine Precision@10
verified: no, type: cosine_recall@1
value: 0.08833333333333332
name: Cosine Recall@1
verified: no, type: cosine_recall@3
value: 0.26666666666666666
name: Cosine Recall@3
verified: no, type: cosine_recall@5
value: 0.30833333333333335
name: Cosine Recall@5
verified: no, type: cosine_recall@10
value: 0.35666666666666663
name: Cosine Recall@10
verified: no, type: cosine_ndcg@10
value: 0.2839842522559327
name: Cosine Ndcg@10
verified: no, type: cosine_mrr@10
value: 0.37471428571428567
name: Cosine Mrr@10
verified: no, type: cosine_map@100
value: 0.2232144898031751
name: Cosine Map@100
verified: no, task: type: information-retrieval
name: Information Retrieval
dataset: name: NanoDBPedia
type: NanoDBPedia
metrics: type: cosine_accuracy@1
value: 0.7
name: Cosine Accuracy@1
verified: no, type: cosine_accuracy@3
value: 0.74
name: Cosine Accuracy@3
verified: no, type: cosine_accuracy@5
value: 0.8
name: Cosine Accuracy@5
verified: no, type: cosine_accuracy@10
value: 0.86
name: Cosine Accuracy@10
verified: no, type: cosine_precision@1
value: 0.7
name: Cosine Precision@1
verified: no, type: cosine_precision@3
value: 0.48
name: Cosine Precision@3
verified: no, type: cosine_precision@5
value: 0.43200000000000005
name: Cosine Precision@5
verified: no, type: cosine_precision@10
value: 0.3760000000000001
name: Cosine Precision@10
verified: no, type: cosine_recall@1
value: 0.07263002775640012
name: Cosine Recall@1
verified: no, type: cosine_recall@3
value: 0.11337585016033845
name: Cosine Recall@3
verified: no, type: cosine_recall@5
value: 0.15857516982468162
name: Cosine Recall@5
verified: no, type: cosine_recall@10
value: 0.23454122344078535
name: Cosine Recall@10
verified: no, type: cosine_ndcg@10
value: 0.4732884231947513
name: Cosine Ndcg@10
verified: no, type: cosine_mrr@10
value: 0.738888888888889
name: Cosine Mrr@10
verified: no, type: cosine_map@100
value: 0.334802367685341
name: Cosine Map@100
verified: no, task: type: information-retrieval
name: Information Retrieval
dataset: name: NanoFEVER
type: NanoFEVER
metrics: type: cosine_accuracy@1
value: 0.88
name: Cosine Accuracy@1
verified: no, type: cosine_accuracy@3
value: 0.96
name: Cosine Accuracy@3
verified: no, type: cosine_accuracy@5
value: 1
name: Cosine Accuracy@5
verified: no, type: cosine_accuracy@10
value: 1
name: Cosine Accuracy@10
verified: no, type: cosine_precision@1
value: 0.88
name: Cosine Precision@1
verified: no, type: cosine_precision@3
value: 0.33333333333333326
name: Cosine Precision@3
verified: no, type: cosine_precision@5
value: 0.20799999999999996
name: Cosine Precision@5
verified: no, type: cosine_precision@10
value: 0.10799999999999998
name: Cosine Precision@10
verified: no, type: cosine_recall@1
value: 0.8266666666666667
name: Cosine Recall@1
verified: no, type: cosine_recall@3
value: 0.9233333333333333
name: Cosine Recall@3
verified: no, type: cosine_recall@5
value: 0.9533333333333333
name: Cosine Recall@5
verified: no, type: cosine_recall@10
value: 0.9733333333333333
name: Cosine Recall@10
verified: no, type: cosine_ndcg@10
value: 0.920250305861268
name: Cosine Ndcg@10
verified: no, type: cosine_mrr@10
value: 0.9266666666666665
name: Cosine Mrr@10
verified: no, type: cosine_map@100
value: 0.8908062417949636
name: Cosine Map@100
verified: no, task: type: information-retrieval
name: Information Retrieval
dataset: name: NanoFiQA2018
type: NanoFiQA2018
metrics: type: cosine_accuracy@1
value: 0.46
name: Cosine Accuracy@1
verified: no, type: cosine_accuracy@3
value: 0.62
name: Cosine Accuracy@3
verified: no, type: cosine_accuracy@5
value: 0.68
name: Cosine Accuracy@5
verified: no, type: cosine_accuracy@10
value: 0.74
name: Cosine Accuracy@10
verified: no, type: cosine_precision@1
value: 0.46
name: Cosine Precision@1
verified: no, type: cosine_precision@3
value: 0.2866666666666667
name: Cosine Precision@3
verified: no, type: cosine_precision@5
value: 0.22399999999999995
name: Cosine Precision@5
verified: no, type: cosine_precision@10
value: 0.13399999999999998
name: Cosine Precision@10
verified: no, type: cosine_recall@1
value: 0.24452380952380953
name: Cosine Recall@1
verified: no, type: cosine_recall@3
value: 0.4037936507936508
name: Cosine Recall@3
verified: no, type: cosine_recall@5
value: 0.4890396825396825
name: Cosine Recall@5
verified: no, type: cosine_recall@10
value: 0.5964206349206349
name: Cosine Recall@10
verified: no, type: cosine_ndcg@10
value: 0.49008883369308526
name: Cosine Ndcg@10
verified: no, type: cosine_mrr@10
value: 0.5513333333333333
name: Cosine Mrr@10
verified: no, type: cosine_map@100
value: 0.4201188803513742
name: Cosine Map@100
verified: no, task: type: information-retrieval
name: Information Retrieval
dataset: name: NanoHotpotQA
type: NanoHotpotQA
metrics: type: cosine_accuracy@1
value: 0.82
name: Cosine Accuracy@1
verified: no, type: cosine_accuracy@3
value: 0.94
name: Cosine Accuracy@3
verified: no, type: cosine_accuracy@5
value: 0.94
name: Cosine Accuracy@5
verified: no, type: cosine_accuracy@10
value: 0.96
name: Cosine Accuracy@10
verified: no, type: cosine_precision@1
value: 0.82
name: Cosine Precision@1
verified: no, type: cosine_precision@3
value: 0.38666666666666655
name: Cosine Precision@3
verified: no, type: cosine_precision@5
value: 0.24799999999999997
name: Cosine Precision@5
verified: no, type: cosine_precision@10
value: 0.132
name: Cosine Precision@10
verified: no, type: cosine_recall@1
value: 0.41
name: Cosine Recall@1
verified: no, type: cosine_recall@3
value: 0.58
name: Cosine Recall@3
verified: no, type: cosine_recall@5
value: 0.62
name: Cosine Recall@5
verified: no, type: cosine_recall@10
value: 0.66
name: Cosine Recall@10
verified: no, type: cosine_ndcg@10
value: 0.6699619900438456
name: Cosine Ndcg@10
verified: no, type: cosine_mrr@10
value: 0.8795238095238095
name: Cosine Mrr@10
verified: no, type: cosine_map@100
value: 0.5983592359151276
name: Cosine Map@100
verified: no, task: type: information-retrieval
name: Information Retrieval
dataset: name: NanoMSMARCO
type: NanoMSMARCO
metrics: type: cosine_accuracy@1
value: 0.34
name: Cosine Accuracy@1
verified: no, type: cosine_accuracy@3
value: 0.6
name: Cosine Accuracy@3
verified: no, type: cosine_accuracy@5
value: 0.72
name: Cosine Accuracy@5
verified: no, type: cosine_accuracy@10
value: 0.82
name: Cosine Accuracy@10
verified: no, type: cosine_precision@1
value: 0.34
name: Cosine Precision@1
verified: no, type: cosine_precision@3
value: 0.2
name: Cosine Precision@3
verified: no, type: cosine_precision@5
value: 0.14400000000000002
name: Cosine Precision@5
verified: no, type: cosine_precision@10
value: 0.08199999999999999
name: Cosine Precision@10
verified: no, type: cosine_recall@1
value: 0.34
name: Cosine Recall@1
verified: no, type: cosine_recall@3
value: 0.6
name: Cosine Recall@3
verified: no, type: cosine_recall@5
value: 0.72
name: Cosine Recall@5
verified: no, type: cosine_recall@10
value: 0.82
name: Cosine Recall@10
verified: no, type: cosine_ndcg@10
value: 0.5747097116234108
name: Cosine Ndcg@10
verified: no, type: cosine_mrr@10
value: 0.4967380952380951
name: Cosine Mrr@10
verified: no, type: cosine_map@100
value: 0.5049567742199321
name: Cosine Map@100
verified: no, task: type: information-retrieval
name: Information Retrieval
dataset: name: NanoNFCorpus
type: NanoNFCorpus
metrics: type: cosine_accuracy@1
value: 0.36
name: Cosine Accuracy@1
verified: no, type: cosine_accuracy@3
value: 0.5
name: Cosine Accuracy@3
verified: no, type: cosine_accuracy@5
value: 0.56
name: Cosine Accuracy@5
verified: no, type: cosine_accuracy@10
value: 0.62
name: Cosine Accuracy@10
verified: no, type: cosine_precision@1
value: 0.36
name: Cosine Precision@1
verified: no, type: cosine_precision@3
value: 0.2933333333333333
name: Cosine Precision@3
verified: no, type: cosine_precision@5
value: 0.296
name: Cosine Precision@5
verified: no, type: cosine_precision@10
value: 0.22
name: Cosine Precision@10
verified: no, type: cosine_recall@1
value: 0.015576651798182985
name: Cosine Recall@1
verified: no, type: cosine_recall@3
value: 0.03488791186499473
name: Cosine Recall@3
verified: no, type: cosine_recall@5
value: 0.06408574388859087
name: Cosine Recall@5
verified: no, type: cosine_recall@10
value: 0.07971201227506045
name: Cosine Recall@10
verified: no, type: cosine_ndcg@10
value: 0.25470834876894616
name: Cosine Ndcg@10
verified: no, type: cosine_mrr@10
value: 0.4443888888888889
name: Cosine Mrr@10
verified: no, type: cosine_map@100
value: 0.09234660597563751
name: Cosine Map@100
verified: no, task: type: information-retrieval
name: Information Retrieval
dataset: name: NanoNQ
type: NanoNQ
metrics: type: cosine_accuracy@1
value: 0.46
name: Cosine Accuracy@1
verified: no, type: cosine_accuracy@3
value: 0.66
name: Cosine Accuracy@3
verified: no, type: cosine_accuracy@5
value: 0.7
name: Cosine Accuracy@5
verified: no, type: cosine_accuracy@10
value: 0.78
name: Cosine Accuracy@10
verified: no, type: cosine_precision@1
value: 0.46
name: Cosine Precision@1
verified: no, type: cosine_precision@3
value: 0.22
name: Cosine Precision@3
verified: no, type: cosine_precision@5
value: 0.14400000000000002
name: Cosine Precision@5
verified: no, type: cosine_precision@10
value: 0.08399999999999999
name: Cosine Precision@10
verified: no, type: cosine_recall@1
value: 0.45
name: Cosine Recall@1
verified: no, type: cosine_recall@3
value: 0.61
name: Cosine Recall@3
verified: no, type: cosine_recall@5
value: 0.66
name: Cosine Recall@5
verified: no, type: cosine_recall@10
value: 0.75
name: Cosine Recall@10
verified: no, type: cosine_ndcg@10
value: 0.6060972125930784
name: Cosine Ndcg@10
verified: no, type: cosine_mrr@10
value: 0.569079365079365
name: Cosine Mrr@10
verified: no, type: cosine_map@100
value: 0.5645161933196003
name: Cosine Map@100
verified: no, task: type: information-retrieval
name: Information Retrieval
dataset: name: NanoQuoraRetrieval
type: NanoQuoraRetrieval
metrics: type: cosine_accuracy@1
value: 0.94
name: Cosine Accuracy@1
verified: no, type: cosine_accuracy@3
value: 0.98
name: Cosine Accuracy@3
verified: no, type: cosine_accuracy@5
value: 0.98
name: Cosine Accuracy@5
verified: no, type: cosine_accuracy@10
value: 1
name: Cosine Accuracy@10
verified: no, type: cosine_precision@1
value: 0.94
name: Cosine Precision@1
verified: no, type: cosine_precision@3
value: 0.40666666666666657
name: Cosine Precision@3
verified: no, type: cosine_precision@5
value: 0.25199999999999995
name: Cosine Precision@5
verified: no, type: cosine_precision@10
value: 0.13599999999999998
name: Cosine Precision@10
verified: no, type: cosine_recall@1
value: 0.8173333333333332
name: Cosine Recall@1
verified: no, type: cosine_recall@3
value: 0.9453333333333334
name: Cosine Recall@3
verified: no, type: cosine_recall@5
value: 0.956
name: Cosine Recall@5
verified: no, type: cosine_recall@10
value: 0.9933333333333334
name: Cosine Recall@10
verified: no, type: cosine_ndcg@10
value: 0.9593808852823181
name: Cosine Ndcg@10
verified: no, type: cosine_mrr@10
value: 0.9625
name: Cosine Mrr@10
verified: no, type: cosine_map@100
value: 0.9422896825396825
name: Cosine Map@100
verified: no, task: type: information-retrieval
name: Information Retrieval
dataset: name: NanoSCIDOCS
type: NanoSCIDOCS
metrics: type: cosine_accuracy@1
value: 0.48
name: Cosine Accuracy@1
verified: no, type: cosine_accuracy@3
value: 0.66
name: Cosine Accuracy@3
verified: no, type: cosine_accuracy@5
value: 0.74
name: Cosine Accuracy@5
verified: no, type: cosine_accuracy@10
value: 0.86
name: Cosine Accuracy@10
verified: no, type: cosine_precision@1
value: 0.48
name: Cosine Precision@1
verified: no, type: cosine_precision@3
value: 0.33333333333333326
name: Cosine Precision@3
verified: no, type: cosine_precision@5
value: 0.276
name: Cosine Precision@5
verified: no, type: cosine_precision@10
value: 0.20199999999999996
name: Cosine Precision@10
verified: no, type: cosine_recall@1
value: 0.10166666666666668
name: Cosine Recall@1
verified: no, type: cosine_recall@3
value: 0.20666666666666664
name: Cosine Recall@3
verified: no, type: cosine_recall@5
value: 0.2846666666666667
name: Cosine Recall@5
verified: no, type: cosine_recall@10
value: 0.41566666666666663
name: Cosine Recall@10
verified: no, type: cosine_ndcg@10
value: 0.3972031938693105
name: Cosine Ndcg@10
verified: no, type: cosine_mrr@10
value: 0.5927698412698412
name: Cosine Mrr@10
verified: no, type: cosine_map@100
value: 0.304253910983743
name: Cosine Map@100
verified: no, task: type: information-retrieval
name: Information Retrieval
dataset: name: NanoArguAna
type: NanoArguAna
metrics: type: cosine_accuracy@1
value: 0.26
name: Cosine Accuracy@1
verified: no, type: cosine_accuracy@3
value: 0.64
name: Cosine Accuracy@3
verified: no, type: cosine_accuracy@5
value: 0.8
name: Cosine Accuracy@5
verified: no, type: cosine_accuracy@10
value: 0.9
name: Cosine Accuracy@10
verified: no, type: cosine_precision@1
value: 0.26
name: Cosine Precision@1
verified: no, type: cosine_precision@3
value: 0.21333333333333335
name: Cosine Precision@3
verified: no, type: cosine_precision@5
value: 0.16
name: Cosine Precision@5
verified: no, type: cosine_precision@10
value: 0.08999999999999998
name: Cosine Precision@10
verified: no, type: cosine_recall@1
value: 0.26
name: Cosine Recall@1
verified: no, type: cosine_recall@3
value: 0.64
name: Cosine Recall@3
verified: no, type: cosine_recall@5
value: 0.8
name: Cosine Recall@5
verified: no, type: cosine_recall@10
value: 0.9
name: Cosine Recall@10
verified: no, type: cosine_ndcg@10
value: 0.5855962294470597
name: Cosine Ndcg@10
verified: no, type: cosine_mrr@10
value: 0.48385714285714276
name: Cosine Mrr@10
verified: no, type: cosine_map@100
value: 0.48932444805879344
name: Cosine Map@100
verified: no, task: type: information-retrieval
name: Information Retrieval
dataset: name: NanoSciFact
type: NanoSciFact
metrics: type: cosine_accuracy@1
value: 0.34
name: Cosine Accuracy@1
verified: no, type: cosine_accuracy@3
value: 0.48
name: Cosine Accuracy@3
verified: no, type: cosine_accuracy@5
value: 0.54
name: Cosine Accuracy@5
verified: no, type: cosine_accuracy@10
value: 0.6
name: Cosine Accuracy@10
verified: no, type: cosine_precision@1
value: 0.34
name: Cosine Precision@1
verified: no, type: cosine_precision@3
value: 0.18
name: Cosine Precision@3
verified: no, type: cosine_precision@5
value: 0.128
name: Cosine Precision@5
verified: no, type: cosine_precision@10
value: 0.07
name: Cosine Precision@10
verified: no, type: cosine_recall@1
value: 0.305
name: Cosine Recall@1
verified: no, type: cosine_recall@3
value: 0.47
name: Cosine Recall@3
verified: no, type: cosine_recall@5
value: 0.54
name: Cosine Recall@5
verified: no, type: cosine_recall@10
value: 0.6
name: Cosine Recall@10
verified: no, type: cosine_ndcg@10
value: 0.45719389021878065
name: Cosine Ndcg@10
verified: no, type: cosine_mrr@10
value: 0.4177460317460317
name: Cosine Mrr@10
verified: no, type: cosine_map@100
value: 0.41560718364765603
name: Cosine Map@100
verified: no, task: type: information-retrieval
name: Information Retrieval
dataset: name: NanoTouche2020
type: NanoTouche2020
metrics: type: cosine_accuracy@1
value: 0.4897959183673469
name: Cosine Accuracy@1
verified: no, type: cosine_accuracy@3
value: 0.8367346938775511
name: Cosine Accuracy@3
verified: no, type: cosine_accuracy@5
value: 0.8979591836734694
name: Cosine Accuracy@5
verified: no, type: cosine_accuracy@10
value: 0.9795918367346939
name: Cosine Accuracy@10
verified: no, type: cosine_precision@1
value: 0.4897959183673469
name: Cosine Precision@1
verified: no, type: cosine_precision@3
value: 0.5034013605442177
name: Cosine Precision@3
verified: no, type: cosine_precision@5
value: 0.4653061224489797
name: Cosine Precision@5
verified: no, type: cosine_precision@10
value: 0.36122448979591837
name: Cosine Precision@10
verified: no, type: cosine_recall@1
value: 0.03552902483256089
name: Cosine Recall@1
verified: no, type: cosine_recall@3
value: 0.10751588484963115
name: Cosine Recall@3
verified: no, type: cosine_recall@5
value: 0.16516486949441941
name: Cosine Recall@5
verified: no, type: cosine_recall@10
value: 0.24301991055992778
name: Cosine Recall@10
verified: no, type: cosine_ndcg@10
value: 0.4179864214131331
name: Cosine Ndcg@10
verified: no, type: cosine_mrr@10
value: 0.6742306446388079
name: Cosine Mrr@10
verified: no, type: cosine_map@100
value: 0.30799309847167516
name: Cosine Map@100
verified: no, task: type: nano-beir
name: Nano BEIR
dataset: name: NanoBEIR mean
type: NanoBEIR_mean
metrics: type: cosine_accuracy@1
value: 0.519215070643642
name: Cosine Accuracy@1
verified: no, type: cosine_accuracy@3
value: 0.7028257456828885
name: Cosine Accuracy@3
verified: no, type: cosine_accuracy@5
value: 0.7659968602825747
name: Cosine Accuracy@5
verified: no, type: cosine_accuracy@10
value: 0.8276609105180532
name: Cosine Accuracy@10
verified: no, type: cosine_precision@1
value: 0.519215070643642
name: Cosine Precision@1
verified: no, type: cosine_precision@3
value: 0.31103087388801676
name: Cosine Precision@3
verified: no, type: cosine_precision@5
value: 0.2401004709576139
name: Cosine Precision@5
verified: no, type: cosine_precision@10
value: 0.1599403453689168
name: Cosine Precision@10
verified: no, type: cosine_recall@1
value: 0.30517380876238104
name: Cosine Recall@1
verified: no, type: cosine_recall@3
value: 0.4539671767437396
name: Cosine Recall@3
verified: no, type: cosine_recall@5
value: 0.5168614460831313
name: Cosine Recall@5
verified: no, type: cosine_recall@10
value: 0.5863610600920313
name: Cosine Recall@10
verified: no, type: cosine_ndcg@10
value: 0.5454192075588399
name: Cosine Ndcg@10
verified: no, type: cosine_mrr@10
value: 0.6240336149111658
name: Cosine Mrr@10
verified: no, type: cosine_map@100
value: 0.4683530086743616
name: Cosine Map@100
verified: no
Likes: 2 | All-time downloads: 236
Created: 2024-12-22 16:33:01