--- tags: - sentence-transformers - sentence-similarity - feature-extraction - generated_from_trainer - dataset_size:105064 - loss:CachedGISTEmbedLoss widget: - source_sentence: When was Jacques-Louis David born? sentences: - Jacques-Louis David was born into a prosperous French family in Paris on 30 August 1748. When he was about nine his father was killed in a duel and his mother left him with his well-off architect uncles. They saw to it that he received an excellent education at the Collège des Quatre-Nations, University of Paris, but he was never a good student-- he had a facial tumor that impeded his speech, and he was always preoccupied with drawing. He covered his notebooks with drawings, and he once said, "I was always hiding behind the instructor's chair, drawing for the duration of the class". Soon, he desired to be a painter, but his uncles and mother wanted him to be an architect. He overcame the opposition, and went to learn from François Boucher (1703–1770), the leading painter of the time, who was also a distant relative. Boucher was a Rococo painter, but tastes were changing, and the fashion for Rococo was giving way to a more classical style. Boucher decided that instead of taking over David's tutelage, he would send David to his friend, Joseph-Marie Vien (1716–1809), a painter who embraced the classical reaction to Rococo. There, David attended the Royal Academy, based in what is now the Louvre. - 'Jacques Louis Antoine Marie David (22 December 1930 – 19 December 2018) was a French Roman Catholic bishop. David was born in France and was ordained to the priesthood in 1956. He served as titular bishop of "Girba" and as auxiliary bishop of the Roman Catholic Archdiocese of Bordeaux, France, from 1981 to 1986. He served as bishop of the Roman Catholic Diocese of La Rochelle and Saintes, France, from 1986 to 1996. David served as bishop of the Roman Catholic Diocese of Évreux, France, from 1996 to 2006.' - 'Jérôme David was born in Rome, Italy on 30 June 1823, nominal grandson of the painter Jacques-Louis David, and godson of Jérôme Bonaparte, King of Westphalia and Catharina of Württemberg, his wife. He was the natural son of King Jérôme. His family destined him for the navy, where he served from 1835 to 1837, but he took a dislike to this service and chose to join the army instead. He graduated from the École de Saint-Cyr on 1 October 1844 as second lieutenant of the Zouaves.' - Garneray was born in Paris (on Rue Saint-Andre-des-arts, in the Latin Quarter) on 19 February 1783. He was the elder son of Jean-François Garneray (1755–1837), painter of the king, who was pupil of Jacques-Louis David. At thirteen, he joined the Navy as a seaman, encouraged by his cousin, Beaulieu-Leloup, commander of the frigate "Forte" ("the Stout one"). Garneray sailed from Rochefort to the Indian Ocean with the frigate division under Sercey, to which the "Forte" belonged. - It was moved there from its original location after the artist's death on 25 December 1825 where his body had been resting in the old churchyard of the St. Michael and St. Gudula collegiate church of the Leopold Quarter of Brussels while waiting for posthumous repatriation to France. However, as a notable participant of the Reign of Terror, his body was not accepted for repatriation, and the lead-lined oak casket was left where it was. Thanks to an initiative by Jobard, a monument was erected with the text "À Jacques-Louis David restaurateur de l'école moderne de peinture de France ici dessous" ("To Jacques-Louis David, restorer of the school of modern art of France, buried here"). In 1882 a grandson requested that the monument be moved to a more prominent location and the body was re-buried at the Mayor's circle in the city cemetery of Evere. - source_sentence: Who is the most popular character in Omamori Himari? sentences: - In Japan, "Omamori Himari" has been featured on the Tohan charts, with Volume 4 reaching No. 29 between November 11, 2008 and November 17, 2008 and Volume 5 reaching No. 15 between April 7 and April 13, 2009, the highest ranking to date. - ', also known as for short, is a Japanese manga series written and illustrated by Milan Matra. The story revolves around Yuto Amakawa, an orphan who, on his sixteenth birthday, meets Himari, a cat spirit samurai girl who has sworn an oath to protect Yuto from the various monsters and demons that are out to kill him.' - 'The manga and anime series "Omamori Himari" features an extensive cast of characters by Milan Matra. The series'' storyline focuses on Yuto Amakawa, an orphan who, on the day of his sixteenth birthday, meets Himari, a buxom sword-wielding girl and a cat spirit. Yuto later learns that he is a Demon Slayer and that his family is one of the twelve Demon Slayer families that had slain demons for hundreds of years, and that Himari had sworn an oath set by their ancestors to protect him until his powers awaken. Throughout the series, Yuto, along with his childhood friend Rinko, later encounter other girls who soon take a liking to Yuto: Shizuku, a mizuchi, Lizlet, an artifact spirit, and Kuesu Jinguji, an heiress to the Jinguji Family of Demon Slayers who is revealed to be Yuto''s fiancée. are the demons and spirits based on Japanese mythology and folklore. They once coexisted with the humans until the Demon Slayers arrived and killed most of them. As a result, the surviving ayakashi bear a deep hatred towards the Demon Slayers. Some ayakashi, like Himari and Shizuku, can assume human forms to blend in with society (though Himari comments that most do not like human cities), and some ayakashi can cast barriers and spells using their .' - '"Omamori Himari" has also been featured on Nielsen BookScan''s Best-Selling Graphic Novels List, with Volume 7 debuting at No. 22 between May 14, 2012 and May 20, 2012 before the volume''s official release, No. 14 between May 21, 2012 and May 27, 2012 on its first week of sales, and No. 21 between May 28, 2012 and June 3, 2012 on its second week of sales, selling a total of 1,270 copies.' - are humans with supernatural powers and abilities with the duty to slay ayakashi, which has been their primary purpose for hundreds of years. The Demon Slayers were established by the feudal lords who opposed the ayakashi and because of this, most of the surviving ayakashi bear a grudge against them for their near-extinction. The Demon Slayers consist of twelve families, each family having their own unique powers and abilities, such as the Amakawa Family with their Light Ferry ability and the Jinguji Family with their dark magic. Out of the twelve families in feudal times, less than half of the families remain in existence in present times. Each Demon Slayer family is sorted by rank, with the Jinguji Family being at the bottom (#12) and the Tsuchimikado Family at the top (#1). - source_sentence: Who was the leader of the Upper Canada Rebellion? sentences: - When news of the arrest of the Patriote leaders reached Upper Canada, William Lyon Mackenzie launched an armed rebellion in December 1837. In the meantime, filibusters from the United States, the Hunter Patriots, formed a small militia and attacked Windsor, Upper Canada, to support the Canadian Patriots. This resulted in the declaration of martial law by the Lower Canadian government. - The Upper Canada Rebellion was an insurrection against the oligarchic government of the British colony of Upper Canada (present-day Ontario) in December 1837. While public grievances had existed for years, it was the rebellion in Lower Canada (present-day Quebec) that emboldened rebels in Upper Canada to openly revolt soon after. - Jesse Lloyd (11 January 1786 – 27 September 1838) was the founder of Lloydtown, Ontario and a leader in the Upper Canada Rebellion of 1837. Born in Springfield Township, Pennsylvania, he was the third son of Quakers William Lloyd and Susannah Heacock. The Lloyds, who were United Empire Loyalists, possibly came to Canada at Niagara in 1788 but soon returned to the United States. They likely immigrated permanently to Upper Canada in 1808. Upon arrival, they crossed the Niagara gorge and migrated north to settle in the 10th concession of King Township. - Compared to the Lower Canada Rebellion, the initial portion of the Upper Canada Rebellion was short and disorganized. However, the British government in London was very concerned about the rebellion, especially in light of the strong popular support for the rebels in the United States and the more serious crisis in Lower Canada. Bond Head was recalled in late 1837 and replaced with Sir George Arthur who arrived in Toronto in March 1838. Parliament also sent Lord Durham to become Governor-in-Chief of the British North American colonies, so that Arthur reported to Durham. Durham was assigned to report on the grievances among the British North American colonists and find a way to appease them. His report eventually led to greater autonomy in the Canadian colonies, and the union of Upper and Lower Canada into the Province of Canada in 1840. The populations of Upper and Lower Canada are listed on the Province of Canada wiki, and that of Canada West was not to exceed that of Canada East until 1850. - The Upper Canada Rebellion was an insurrection against the oligarchic government of the Family Compact by W.L. Mackenzie in December 1837. Long term grievances included antagonism between Later Loyalists and British Loyalists, political corruption, the collapse of the international financial system and the resultant economic distress, and a growing republican sentiment. While public grievances had existed for years, it was the Rebellion in Lower Canada (present day Quebec) that emboldened rebels in Upper Canada to openly revolt soon after. The Upper Canada Rebellion was largely defeated shortly after it began, although resistance lingered until 1838 (and became more violent) – mainly through the support of the Hunters' Lodges, a secret anti-British, American militia that emerged in states around the Great Lakes. They launched the Patriot War in 1838–39. - source_sentence: Has Lady Shiva appeared in any DC Comics films? sentences: - Following the one-year gap during which "52" takes place, she has reappeared in several of DC Comics' science fiction series. In "Mystery in Space", she is the source of Captain Comet's death and rebirth, a cycle which began when her forces attacked him in "52". In the 2006 "Omega Men" miniseries, Lady Styx appears as the central antagonist, seeking powerful artifacts known as "heartstones" in her attempt to remake the universe and usurp the role of God. Apparently trapped in another dimension, Lady Styx manifests in this series as a giantess. - Lady Shiva (real name Sandra Woosan, or more recently Sandra Wu-San) is a fictional supervillainess and antiheroine appearing in American comic books published by DC Comics. The character was co-created by Dennis O'Neil and Ric Estrada, and first appeared in "Richard Dragon, Kung Fu Fighter". Over time, she has become more closely associated with Batman and related characters, both as an enemy and an ally. She is a martial arts grandmaster and one of the most skilled combatants in the DC Universe. She is an assassin-for-hire, who specializes in killing her targets with her bare hands, and is the mother of Cassandra Cain, a.k.a. Orphan. - Lady Elaine Marsh-Morton, a.k.a. “Lady Vic” or “Lady Victim” is a fictional character in the DC Comics universe. She is an English noblewoman who works secretly as an assassin, bounty hunter, and mercenary. She is employed on a semi-regular basis by Roland Desmond and appears most frequently as an antagonist of Nightwing (Dick Grayson). - 'Cassandra gathered evidence indicating that Lady Shiva was her mother, and sought out Shiva to confirm this. At the time Shiva was the sensei of Nyssa''s new League. When Batgirl arrived she played a key role in the rebirth of Mr. Freeze''s wife Nora Fries as the monstrous Lazara, and several League members died in the resulting chaos. Due to the conflict between their loyalty to Shiva and Nyssa and their near-worship of Batgirl as "the One Who is All" the League split at that point, with several members pledging themselves to Cassandra. Several more members of the League (including all the defectors except one) died when the Mad Dog went on a killing spree. The Mad Dog was successful in killing Batgirl (who gave her life to protect the last of the defected assassins), although she was able to knock him unconscious before perishing. Cassandra was quickly restored to life in a Lazarus Pit by Shiva. The Mad Dog''s fate is unknown. In September 2011, The New 52 rebooted DC''s continuity. In this new timeline, a new character named Mad Dog appeared. This version of the character works as bounty hunter for an unnamed organization that "pays his bills." He is hired to go after the Suicide Squad in order to recover a newborn baby the Squad had kidnapped. Mad Dog knows Deadshot''s secret identity, and is surprised that Deadshot is a member of the Suicide Squad and not incarcerated at Belle Reve. While using thermal vision on his mask to see through smoke, Mad Dog shoots Black Spider in the chest and blows up a diner with Black Spider and El Diablo still inside. Before he can fire any more shots and steal "the package", Harley Quinn releases knockout gas into the room to prevent further gunfire. Mad Dog and his team find Deadshot and Harley at their hideout and chase them inside. Harley has once again turned on the gas to prevent any gunfire from Mad Dog inside the hideout. They evacuate the building, which then explodes. As Mad Dog flees, swearing revenge on Deadshot, he encounters King Shark. When King Shark rejoins his fellow Squad members, he is seen wearing Mad Dog''s necklace, implying that he killed him.' - 'DC gave the Question his own solo series in 1987, written by Dennis O''Neil and primarily drawn by Denys Cowan. The series was published for 36 issues, two annuals, and five "Quarterly" specials. In "The Question" #1, the Question was defeated in personal combat, first by the martial arts mercenary Lady Shiva. He was then beaten nearly to death by the villain''s hired thugs, shot in the head with a pellet gun, and thrown into the river to drown. Lady Shiva then rescued him for reasons of her own and gave him directions to meet wheelchair-bound Richard Dragon as soon as he recovered enough to get out of bed. Once there, Sage learned both martial arts and eastern philosophy. When he returned to the city, he resumed his journalist and superhero careers with adventures that tended to illustrate various philosophic points. To further illustrate those ideas, Dennis O''Neil had a reading recommendation in the letters page of each issue.' - source_sentence: When were bluebonnets named the state flower of Texas? sentences: - The bluebonnet is the state flower of Texas. - Miller served as campaign manager for U.S. Senator Charles A. Culberson, and was elected to the Texas Senate in 1898 to support Culberson's candidacy. As a State Senator in 1901, Miller authored and sponsored Senate Concurrent Resolution 10, which made the bluebonnet the Texas State flower. He did so as a gesture of respect to the wife of longtime Texas lawyer, Sawnie Robertson, in whose firm Miller read law when he first came to Texas. Mrs. Robertson had always remarked that the bluebonnet was her favorite flower. In 1911, he was appointed a Judge of the Criminal District Court in Dallas County and Miller was reelected in 1915. In 1916, Miller was elected to a vacant State Representative seat in Dallas as a Democrat. Miller was a vocal opponent of the Ku Klux Klan. He was also an early opponent of women's suffrage in Texas, one of the most vocal at the time. However, he changed his mind when the Dallas Equal Suffrage Association (DESA) provided over 10,000 signatures from Dallas women supporting suffrage. He even became the chair of the woman suffrage caucus. - The second major festival hosted in Ennis is the Bluebonnet Trails Festival, celebrating the state flower of Texas and the vibrant bloom of wildflowers in the surrounding countryside. The event attracts tens of thousands of tourists each year to events including sightseeing excursions and a festival in downtown. The festival is held on the third weekend of April, and the Bluebonnet Trails are hosted for the entire month. First hosted along the Kachina Prairie Park's historic mile-long trail system in 1938, the Bluebonnet Trails have since expanded into a route map of several dozen miles along rural farm roads throughout the surrounding countryside east and northeast of the city. The routes for these sightseeing excursions have been officially hosted and mapped out by the Ennis Garden Club since 1951. To commemorate the popularity of the Bluebonnet Trails Festival and the efforts made to celebrate and preserve the state flower of Texas, Ennis was designated by the 1997 Texas State Legislature as the "Official Bluebonnet City of Texas" and home to the "Official Bluebonnet Trail of Texas." - 'Bluebonnet is a name given to any number of blue-flowered species of the genus "Lupinus" predominantly found in southwestern United States and is collectively the state flower of Texas. The shape of the petals on the flower resembles the bonnet worn by pioneer women to shield them from the sun. Species often called bluebonnets include:On March 7, 1901, "Lupinus subcarnosus" became the only species of bluebonnet recognized as the state flower of Texas; however, "Lupinus texensis" emerged as the favorite of most Texans. So, in 1971, the Texas Legislature made any similar species of "Lupinus" that could be found in Texas the state flower.' - Lupinus texensis, the Texas bluebonnet or Texas lupine is a species of lupine endemic to Texas. With other related species of lupines also called bluebonnets, it is the state flower of Texas. pipeline_tag: sentence-similarity library_name: sentence-transformers --- # SentenceTransformer This is a [sentence-transformers](https://www.SBERT.net) model trained. It maps sentences & paragraphs to a 1024-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 - **Maximum Sequence Length:** 1024 tokens - **Output Dimensionality:** 1024 dimensions - **Similarity Function:** Cosine Similarity ### 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': 1024, 'do_lower_case': False}) with Transformer model: XLMRobertaModel (1): Pooling({'word_embedding_dimension': 1024, '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("sentence_transformers_model_id") # Run inference sentences = [ 'When were bluebonnets named the state flower of Texas?', 'Bluebonnet is a name given to any number of blue-flowered species of the genus "Lupinus" predominantly found in southwestern United States and is collectively the state flower of Texas. The shape of the petals on the flower resembles the bonnet worn by pioneer women to shield them from the sun.\nSpecies often called bluebonnets include:On March 7, 1901, "Lupinus subcarnosus" became the only species of bluebonnet recognized as the state flower of Texas; however, "Lupinus texensis" emerged as the favorite of most Texans. So, in 1971, the Texas Legislature made any similar species of "Lupinus" that could be found in Texas the state flower.', 'The second major festival hosted in Ennis is the Bluebonnet Trails Festival, celebrating the state flower of Texas and the vibrant bloom of wildflowers in the surrounding countryside. The event attracts tens of thousands of tourists each year to events including sightseeing excursions and a festival in downtown. The festival is held on the third weekend of April, and the Bluebonnet Trails are hosted for the entire month. First hosted along the Kachina Prairie Park\'s historic mile-long trail system in 1938, the Bluebonnet Trails have since expanded into a route map of several dozen miles along rural farm roads throughout the surrounding countryside east and northeast of the city. The routes for these sightseeing excursions have been officially hosted and mapped out by the Ennis Garden Club since 1951. To commemorate the popularity of the Bluebonnet Trails Festival and the efforts made to celebrate and preserve the state flower of Texas, Ennis was designated by the 1997 Texas State Legislature as the "Official Bluebonnet City of Texas" and home to the "Official Bluebonnet Trail of Texas."', ] embeddings = model.encode(sentences) print(embeddings.shape) # [3, 1024] # Get the similarity scores for the embeddings similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] ``` ## Training Details ### Training Dataset #### Unnamed Dataset * Size: 105,064 training samples * Columns: anchor, positive, negative, negative_2, negative_3, and negative_4 * Approximate statistics based on the first 1000 samples: | | anchor | positive | negative | negative_2 | negative_3 | negative_4 | |:--------|:----------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | string | string | string | string | | details | | | | | | | * Samples: | anchor | positive | negative | negative_2 | negative_3 | negative_4 | |:------------------------------------------------------|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| | When was quantum field theory developed? | The third thread in the development of quantum field theory was the need to handle the statistics of many-particle systems consistently and with ease. In 1927, Pascual Jordan tried to extend the canonical quantization of fields to the many-body wave functions of identical particles using a formalism which is known as statistical transformation theory; this procedure is now sometimes called second quantization. In 1928, Jordan and Eugene Wigner found that the quantum field describing electrons, or other fermions, had to be expanded using anti-commuting creation and annihilation operators due to the Pauli exclusion principle (see Jordan–Wigner transformation). This thread of development was incorporated into many-body theory and strongly influenced condensed matter physics and nuclear physics. | The application of the new quantum theory to electromagnetism resulted in quantum field theory, which was developed starting around 1930. Quantum field theory has driven the development of more sophisticated formulations of quantum mechanics, of which the ones presented here are simple special cases. | Two classic text-books from the 1960s, James D. Bjorken, Sidney David Drell, "Relativistic Quantum Mechanics" (1964) and J. J. Sakurai, "Advanced Quantum Mechanics" (1967), thoroughly developed the Feynman graph expansion techniques using physically intuitive and practical methods following from the correspondence principle, without worrying about the technicalities involved in deriving the Feynman rules from the superstructure of quantum field theory itself. Although both Feynman's heuristic and pictorial style of dealing with the infinities, as well as the formal methods of Tomonaga and Schwinger, worked extremely well, and gave spectacularly accurate answers, the true analytical nature of the question of "renormalizability", that is, whether ANY theory formulated as a "quantum field theory" would give finite answers, was not worked-out until much later, when the urgency of trying to formulate finite theories for the strong and electro-weak (and gravitational interactions) demanded i... | It was evident from the beginning that a proper quantum treatment of the electromagnetic field had to somehow incorporate Einstein's relativity theory, which had grown out of the study of classical electromagnetism. This need to put together relativity and quantum mechanics was the second major motivation in the development of quantum field theory. Pascual Jordan and Wolfgang Pauli showed in 1928 that quantum fields could be made to behave in the way predicted by special relativity during coordinate transformations (specifically, they showed that the field commutators were Lorentz invariant). A further boost for quantum field theory came with the discovery of the Dirac equation, which was originally formulated and interpreted as a single-particle equation analogous to the Schrödinger equation, but unlike the Schrödinger equation, the Dirac equation satisfies both the Lorentz invariance, that is, the requirements of special relativity, and the rules of quantum mechanics.
The Dirac equa... | Through the works of Born, Heisenberg, and Pascual Jordan in 1925-1926, a quantum theory of the free electromagnetic field (one with no interactions with matter) was developed via canonical quantization by treating the electromagnetic field as a set of quantum harmonic oscillators. With the exclusion of interactions, however, such a theory was yet incapable of making quantitative predictions about the real world. | | Was there a year 0? | Cassini gave the following reasons for using a year 0:
Fred Espanak of NASA lists 50 phases of the moon within year 0, showing that it is a full year, not an instant in time. Jean Meeus gives the following explanation:
Although he used the usual French terms "avant J.-C." (before Jesus Christ) and "après J.-C." (after Jesus Christ) to label years elsewhere in his book, the Byzantine historian Venance Grumel used negative years (identified by a minus sign, −) to label BC years and unsigned positive years to label AD years in a table. He did so possibly to save space and put no year 0 between them. | Games Def Interceptions Fumbles Sacks & Tackles
Year Age Tm Pos No. G GS Int Yds TD Lng PD FF Fmb FR Yds TD Sk Tkl Ast Sfty AV
2004 23 NWE ss 42 13 2 0 0 0 0 2 1 0 1 0 0 15 8 2
2005 24 IND 36 16 0 1 0 1 0 0 8 2 1
2006 25 IND ss 36 10 1 0 0 0 0 2 11 0 1
Career 39 3 0 0 0 0 4 2 0 2 0 0 34 10 4
2 yrs IND 26 1 0 0 0 0 2 1 0 1 0 0 19 2 2
1 yr NWE 13 2 0 0 0 0 2 1 0 1 0 0 15 8 2
After pleading guilty in January 2008 to drug charges in Virginia Beach, VA stemming from a March 2007 incident, Reid was initially sentenced to two years in prison for possessing marijuana with the intent to distribute but had the sentence suspended with the agreement he would stay out of trouble for two years. His license was also suspended for six months and ordered to attend drug treatment and counseling. | This enzyme belongs to the family of oxidoreductases, specifically those acting on paired donors, with O2 as oxidant and incorporation or reduction of oxygen. The oxygen incorporated need not be derived from O2 with 2-oxoglutarate as one donor, and incorporation of one atom o oxygen into each donor. The systematic name of this enzyme class is N6,N6,N6-trimethyl-L-lysine,2-oxoglutarate:oxygen oxidoreductase (3-hydroxylating). Other names in common use include trimethyllysine alpha-ketoglutarate dioxygenase, TML-alpha-ketoglutarate dioxygenase, TML hydroxylase, 6-N,6-N,6-N-trimethyl-L-lysine,2-oxoglutarate:oxygen oxidoreductase, and (3-hydroxylating). This enzyme participates in lysine degradation and L-carnitine biosynthesis and requires the presence of iron and ascorbate. | ㅜ is one of the Korean hangul. The Unicode for ㅜ is U+315C. | ㅌ is one of the Korean hangul. The Unicode for ㅌ is U+314C. | | When is the dialectical method used? | The Dialect Test was created by A.J. Ellis in February 1879, and was used in the fieldwork for his work "On Early English Pronunciation". It stands as one of the earliest methods of identifying vowel sounds and features of speech. The aim was to capture the main vowel sounds of an individual dialect by listening to the reading of a short passage. All the categories of West Saxon words and vowels were included in the test so that comparisons could be made with the historic West Saxon speech as well as with various other dialects. | Karl Popper has attacked the dialectic repeatedly. In 1937, he wrote and delivered a paper entitled "What Is Dialectic?" in which he attacked the dialectical method for its willingness "to put up with contradictions". Popper concluded the essay with these words: "The whole development of dialectic should be a warning against the dangers inherent in philosophical system-building. It should remind us that philosophy should not be made a basis for any sort of scientific system and that philosophers should be much more modest in their claims. One task which they can fulfill quite usefully is the study of the critical methods of science" (Ibid., p. 335). | He was one of the first to apply Labovian methods in Britain with his research in 1970-1 on the speech of Bradford, Halifax and Huddersfield. He concluded that the speech detailed in most of dialectology (e.g. A. J. Ellis, the Survey of English Dialects) had virtually disappeared, having found only one speaker out of his sample of 106 speakers who regularly used dialect. However, he found that differences in speech persisted as an indicator of social class, age and gender. This PhD dissertation was later adapted into a book, "Dialect and Accent in Industrial West Yorkshire". The work was criticised by Graham Shorrocks on the grounds that the sociolinguistic methods used were inappropriate for recording the traditional vernacular and that there was an inadequate basis for comparison with earlier dialect studies in West Yorkshire. | The Institute also attempted to reformulate dialectics as a concrete method. The use of such a dialectical method can be traced back to the philosophy of Hegel, who conceived dialectic as the tendency of a notion to pass over into its own negation as the result of conflict between its inherent contradictory aspects. In opposition to previous modes of thought, which viewed things in abstraction, each by itself and as though endowed with fixed properties, Hegelian dialectic has the ability to consider ideas according to their movement and change in time, as well as according to their interrelations and interactions. | For Marx, dialectics is not a formula for generating predetermined outcomes but is a method for the empirical study of social processes in terms of interrelations, development, and transformation. In his introduction to the Penguin edition of Marx's "Capital", Ernest Mandel writes, "When the dialectical method is applied to the study of economic problems, economic phenomena are not viewed separately from each other, by bits and pieces, but in their inner connection as an integrated totality, structured around, and by, a basic predominant mode of production." | * Loss: [CachedGISTEmbedLoss](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#cachedgistembedloss) with these parameters: ```json {'guide': SentenceTransformer( (0): Transformer({'max_seq_length': 1024, 'do_lower_case': False}) with Transformer model: XLMRobertaModel (1): Pooling({'word_embedding_dimension': 1024, '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() ), 'temperature': 0.01} ``` ### Training Hyperparameters #### Non-Default Hyperparameters - `per_device_train_batch_size`: 1024 - `learning_rate`: 3e-05 - `weight_decay`: 0.01 - `num_train_epochs`: 8 - `warmup_ratio`: 0.05 - `bf16`: True - `batch_sampler`: no_duplicates #### All Hyperparameters
Click to expand - `overwrite_output_dir`: False - `do_predict`: False - `eval_strategy`: no - `prediction_loss_only`: True - `per_device_train_batch_size`: 1024 - `per_device_eval_batch_size`: 8 - `per_gpu_train_batch_size`: None - `per_gpu_eval_batch_size`: None - `gradient_accumulation_steps`: 1 - `eval_accumulation_steps`: None - `torch_empty_cache_steps`: None - `learning_rate`: 3e-05 - `weight_decay`: 0.01 - `adam_beta1`: 0.9 - `adam_beta2`: 0.999 - `adam_epsilon`: 1e-08 - `max_grad_norm`: 1.0 - `num_train_epochs`: 8 - `max_steps`: -1 - `lr_scheduler_type`: linear - `lr_scheduler_kwargs`: {} - `warmup_ratio`: 0.05 - `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`: None - `local_rank`: 0 - `ddp_backend`: None - `tpu_num_cores`: None - `tpu_metrics_debug`: False - `debug`: [] - `dataloader_drop_last`: True - `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`: False - `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 - `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`: None - `hub_always_push`: False - `gradient_checkpointing`: False - `gradient_checkpointing_kwargs`: None - `include_inputs_for_metrics`: False - `include_for_metrics`: [] - `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 - `eval_on_start`: False - `use_liger_kernel`: False - `eval_use_gather_object`: False - `average_tokens_across_devices`: False - `prompts`: None - `batch_sampler`: no_duplicates - `multi_dataset_batch_sampler`: proportional
### Training Logs
Click to expand | Epoch | Step | Training Loss | |:------:|:----:|:-------------:| | 0.04 | 1 | 0.1495 | | 0.08 | 2 | 0.1625 | | 0.12 | 3 | 0.1622 | | 0.16 | 4 | 0.1877 | | 0.2 | 5 | 0.1561 | | 0.24 | 6 | 0.1495 | | 0.28 | 7 | 0.1502 | | 0.32 | 8 | 0.1634 | | 0.36 | 9 | 0.1592 | | 0.4 | 10 | 0.1744 | | 0.44 | 11 | 0.1503 | | 0.48 | 12 | 0.1618 | | 0.52 | 13 | 0.1863 | | 0.56 | 14 | 0.1782 | | 0.6 | 15 | 0.1599 | | 0.64 | 16 | 0.1513 | | 0.68 | 17 | 0.1608 | | 0.72 | 18 | 0.1771 | | 0.76 | 19 | 0.1595 | | 0.8 | 20 | 0.1701 | | 0.84 | 21 | 0.1426 | | 0.88 | 22 | 0.1749 | | 0.92 | 23 | 0.1591 | | 0.96 | 24 | 0.1735 | | 1.0 | 25 | 0.174 | | 1.04 | 26 | 0.1246 | | 1.08 | 27 | 0.114 | | 1.12 | 28 | 0.1176 | | 1.16 | 29 | 0.1206 | | 1.2 | 30 | 0.1202 | | 1.24 | 31 | 0.1197 | | 1.28 | 32 | 0.1134 | | 1.32 | 33 | 0.1155 | | 1.3600 | 34 | 0.0978 | | 1.4 | 35 | 0.1197 | | 1.44 | 36 | 0.1038 | | 1.48 | 37 | 0.1254 | | 1.52 | 38 | 0.1083 | | 1.56 | 39 | 0.1192 | | 1.6 | 40 | 0.1026 | | 1.6400 | 41 | 0.1041 | | 1.6800 | 42 | 0.1139 | | 1.72 | 43 | 0.1045 | | 1.76 | 44 | 0.0997 | | 1.8 | 45 | 0.1183 | | 1.8400 | 46 | 0.0952 | | 1.88 | 47 | 0.0941 | | 1.92 | 48 | 0.1075 | | 1.96 | 49 | 0.1093 | | 2.0 | 50 | 0.0975 | | 2.04 | 51 | 0.0839 | | 2.08 | 52 | 0.0795 | | 2.12 | 53 | 0.0809 | | 2.16 | 54 | 0.0798 | | 2.2 | 55 | 0.0698 | | 2.24 | 56 | 0.0878 | | 2.2800 | 57 | 0.0807 | | 2.32 | 58 | 0.0748 | | 2.36 | 59 | 0.0796 | | 2.4 | 60 | 0.0846 | | 2.44 | 61 | 0.0821 | | 2.48 | 62 | 0.0831 | | 2.52 | 63 | 0.0826 | | 2.56 | 64 | 0.0667 | | 2.6 | 65 | 0.0792 | | 2.64 | 66 | 0.0688 | | 2.68 | 67 | 0.0774 | | 2.7200 | 68 | 0.077 | | 2.76 | 69 | 0.0746 | | 2.8 | 70 | 0.0738 | | 2.84 | 71 | 0.0772 | | 2.88 | 72 | 0.0853 | | 2.92 | 73 | 0.0643 | | 2.96 | 74 | 0.0775 | | 3.0 | 75 | 0.0686 | | 3.04 | 76 | 0.0499 | | 3.08 | 77 | 0.056 | | 3.12 | 78 | 0.0607 | | 3.16 | 79 | 0.0616 | | 3.2 | 80 | 0.0528 | | 3.24 | 81 | 0.0585 | | 3.2800 | 82 | 0.0597 | | 3.32 | 83 | 0.0655 | | 3.36 | 84 | 0.0634 | | 3.4 | 85 | 0.0568 | | 3.44 | 86 | 0.06 | | 3.48 | 87 | 0.0581 | | 3.52 | 88 | 0.0499 | | 3.56 | 89 | 0.0524 | | 3.6 | 90 | 0.0593 | | 3.64 | 91 | 0.0558 | | 3.68 | 92 | 0.0497 | | 3.7200 | 93 | 0.057 | | 3.76 | 94 | 0.0526 | | 3.8 | 95 | 0.0615 | | 3.84 | 96 | 0.0532 | | 3.88 | 97 | 0.0514 | | 3.92 | 98 | 0.0569 | | 3.96 | 99 | 0.053 | | 4.0 | 100 | 0.0546 | | 4.04 | 101 | 0.0457 | | 4.08 | 102 | 0.0445 | | 4.12 | 103 | 0.0466 | | 4.16 | 104 | 0.0485 | | 4.2 | 105 | 0.0434 | | 4.24 | 106 | 0.0474 | | 4.28 | 107 | 0.0495 | | 4.32 | 108 | 0.0443 | | 4.36 | 109 | 0.0471 | | 4.4 | 110 | 0.0429 | | 4.44 | 111 | 0.0511 | | 4.48 | 112 | 0.037 | | 4.52 | 113 | 0.047 | | 4.5600 | 114 | 0.0466 | | 4.6 | 115 | 0.0451 | | 4.64 | 116 | 0.0466 | | 4.68 | 117 | 0.0358 | | 4.72 | 118 | 0.0386 | | 4.76 | 119 | 0.0474 | | 4.8 | 120 | 0.0417 | | 4.84 | 121 | 0.0433 | | 4.88 | 122 | 0.0477 | | 4.92 | 123 | 0.0513 | | 4.96 | 124 | 0.0468 | | 5.0 | 125 | 0.0387 | | 5.04 | 126 | 0.0425 | | 5.08 | 127 | 0.0393 | | 5.12 | 128 | 0.0418 | | 5.16 | 129 | 0.0414 | | 5.2 | 130 | 0.0355 | | 5.24 | 131 | 0.0423 | | 5.28 | 132 | 0.0369 | | 5.32 | 133 | 0.0319 | | 5.36 | 134 | 0.0395 | | 5.4 | 135 | 0.0417 | | 5.44 | 136 | 0.0366 | | 5.48 | 137 | 0.0419 | | 5.52 | 138 | 0.0382 | | 5.5600 | 139 | 0.0379 | | 5.6 | 140 | 0.0382 | | 5.64 | 141 | 0.0382 | | 5.68 | 142 | 0.0365 | | 5.72 | 143 | 0.0377 | | 5.76 | 144 | 0.0362 | | 5.8 | 145 | 0.0311 | | 5.84 | 146 | 0.0408 | | 5.88 | 147 | 0.0367 | | 5.92 | 148 | 0.0386 | | 5.96 | 149 | 0.039 | | 6.0 | 150 | 0.0402 | | 6.04 | 151 | 0.038 | | 6.08 | 152 | 0.0395 | | 6.12 | 153 | 0.0351 | | 6.16 | 154 | 0.0377 | | 6.2 | 155 | 0.0387 | | 6.24 | 156 | 0.0306 | | 6.28 | 157 | 0.038 | | 6.32 | 158 | 0.0404 | | 6.36 | 159 | 0.0356 | | 6.4 | 160 | 0.0256 | | 6.44 | 161 | 0.0336 | | 6.48 | 162 | 0.0332 | | 6.52 | 163 | 0.0324 | | 6.5600 | 164 | 0.0345 | | 6.6 | 165 | 0.0374 | | 6.64 | 166 | 0.0335 | | 6.68 | 167 | 0.0313 | | 6.72 | 168 | 0.0348 | | 6.76 | 169 | 0.0386 | | 6.8 | 170 | 0.035 | | 6.84 | 171 | 0.0354 | | 6.88 | 172 | 0.0319 | | 6.92 | 173 | 0.0303 | | 6.96 | 174 | 0.0312 | | 7.0 | 175 | 0.0368 | | 7.04 | 176 | 0.0297 | | 7.08 | 177 | 0.031 | | 7.12 | 178 | 0.0315 | | 7.16 | 179 | 0.034 | | 7.2 | 180 | 0.0415 | | 7.24 | 181 | 0.0338 | | 7.28 | 182 | 0.0296 | | 7.32 | 183 | 0.0299 | | 7.36 | 184 | 0.0305 | | 7.4 | 185 | 0.0318 | | 7.44 | 186 | 0.0303 | | 7.48 | 187 | 0.0302 | | 7.52 | 188 | 0.0323 | | 7.5600 | 189 | 0.031 | | 7.6 | 190 | 0.0343 | | 7.64 | 191 | 0.0344 | | 7.68 | 192 | 0.0407 | | 7.72 | 193 | 0.0332 | | 7.76 | 194 | 0.0298 | | 7.8 | 195 | 0.0301 | | 7.84 | 196 | 0.0296 | | 7.88 | 197 | 0.0342 | | 7.92 | 198 | 0.0316 | | 7.96 | 199 | 0.0307 | | 8.0 | 200 | 0.034 |
### Framework Versions - Python: 3.10.12 - Sentence Transformers: 3.4.1 - Transformers: 4.49.0 - PyTorch: 2.5.1+cu124 - Accelerate: 1.4.0 - Datasets: 2.21.0 - Tokenizers: 0.21.0 ## 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", } ```