crazyjeannot/en-literary-gte-base

SentenceTransformer based on Alibaba-NLP/gte-base-en-v1.5

This is a sentence-transformers model finetuned from Alibaba-NLP/gte-base-en-v1.5. It maps sentences & paragraphs to a 768-dimensional dense vector space and can be used for semantic textual similarity, semantic search, paraphrase mining, text classification, clustering, and more.

Model Details

Model Description

• Model Type: Sentence Transformer
• Base model: Alibaba-NLP/gte-base-en-v1.5
• Maximum Sequence Length: 8192 tokens
• Output Dimensionality: 768 dimensions
• Similarity Function: Cosine Similarity

Model Sources

• Documentation: Sentence Transformers Documentation
• Repository: Sentence Transformers on GitHub
• Hugging Face: Sentence Transformers on Hugging Face

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})
)

Usage

Direct Usage (Sentence Transformers)

First install the Sentence Transformers library:

pip install -U sentence-transformers

Then you can load this model and run inference.

from sentence_transformers import SentenceTransformer

# Download from the 🤗 Hub
model = SentenceTransformer("sentence_transformers_model_id")
# Run inference
sentences = [
    'Tulipson!’ I called out to the Second, who had not been able to get a word in edgeways, ‘I don’t know what the devil’s the matter with the First Mate; but he’ll not find it pay to talk to a crowd like ours, in that sort of fashion, or there’ll be ructions aboard.’  “ ‘Come! come! Jessop! This won’t do! I can’t have you talking like that about the Mate!’ he said, sharply. ‘Let me know what’s to-do, and then go forrard again, the lot of you.’  “ ‘We’d have told you at first, Sir,’ I said, ‘only the Mate wouldn’t give any of us a chance to speak. There’s been an awful accident, Sir. Something’s fallen from aloft, right onto Jock—’  “I stopped suddenly; for there was a loud crying aloft. “ ‘Help! help!',
    '“Love you.”  He sure knows how to pull on my heartstrings that I thought were long gone. “Love you too, kid. Get some sleep.” I shut off the lights and close the door, taking a minute for myself. Shit, this parenting stuff is hard and exhausting. I’m not sure how Hawk did it and was able to found time to be in the club. Music from the main room is muted through the steel door I had installed between the hallway and Jenkins’ bedroom, so he doesn’t hear all the commotion going on. This place is my home, and it’s his home now too, and the members have been good about following my rules. Now that the kid is sleeping, the adults can have a good time. And fuck do I need a good time. I need a real fucking good time.',
    'Dacă nu mă înşel, e marele caic care ne-a depăşit azi- dimineaţa. Dumnezeu ştie cum, dar cred că au fost preveniţi şi vor fi al naibii de bănuitori. Nu va fi o joacă şi nu ne vor cerceta cu mănuşi. Vor fi înarmaţi pînă-n dinţi şi vor căuta scandal. Nu va fi vorba de jumătăţi de măsură. Să fim lămuriţi. Sau se vor scufunda ei, sau ne scufundăm noi, nu putem supravieţui unei inspecţii dat fiind materialul pe care-l avem la bord. Şi, adăugă el blînd, nu-l vom arunca în mare. Repede le explică planul său. Aplecat peste fereastra timoneriei, Stevens simţea vechea durere în stomac şi sîngele fugindu-i din cap.',
]
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]

Training Details

Training Dataset

Unnamed Dataset

• Size: 40,000 training samples
• Columns: sentence_0, sentence_1, and sentence_2
• Approximate statistics based on the first 1000 samples:

  	sentence_0	sentence_1	sentence_2
  type	string	list	list
  details	min: 12 tokens mean: 223.34 tokens max: 8192 tokens	size: 5 elements	size: 5 elements

• Samples:

  sentence_0	sentence_1	sentence_2
  Second: I’m going to avoid you. You’re a jinx. I’m that girl again?’ Fran pointed to the splattered photos beside the cooker. ‘I’m her?’ The nurse was ringing and her dad was calling her name and she was thinking about crying. ‘I’m upset, but it’s fine, I know what to do and now you do too.’ She let Nurse Jen in, The Captain out, and shut the door. Oops, Rosie was still inside. ‘Bye Mrs Collins,’ she said, pushing past. And Fran watched the girl in the cherry-red boots walk towards her father’s forgettable car. [] Vonny was in bed with a sore head, and Nurse Jen was in charge of Gramps for the next four hours, which meant Fran could do anything she wanted. She opened the windows and doors, but there was no breeze.	['She turned on the television, The Love House, turned it off again. Everything was icky, the 91world was yucky, the light was bad. She splashed her face with a tiny amount of water and closed herself in the bedroom to ring Vincent. ‘What’s she got that I haven’t, this Chelsea person?’ she said. ‘Constance.’ ‘Right.’ ‘She’s very nice, and don’t worry, she’s not jealous of you at all.’ ‘That’s … I’m just ringing to say I’ll put Vonny on the three-thirty.’ ‘Cool. You okay?’ ‘I am.’ ‘Love you F Face, talk soon.’ Fran had called to tell Vincent everything, but he wasn’t her listener anymore. She changed into her running gear as quickly as she could and sweated it out along Ryan’s Lane, up and over the monument track, and along North Road. She jumped the fence across from St Michael’s onto the old railway land. It was her favourite run, down that hill, along those long disused lines, then up to The Tree. It was a large oak, and was on the hill beside the Old Reservoir.', 'Gramps had proposed to her mum here, and the two of them had made plans for a new life in the country. Apparently, Sofia said this was the most beautiful view she’d ever seen – and her family was from Tuscany. She remembered Gramps bringing her here when she was five, both of them dressed in black, shoes off, feet in the water. ‘Stuff happens,’ he’d said, fishing rod in hand. ‘Things get interrupted.’ Fran was crying her eyes out. ‘But no, no, no, what are we supposed to do now?’ 92 ‘Have a cry, then make new plans,’ he’d said. He brought her here at sixteen too, quite a few times that year, baby Dante in a pouch on his chest, a fishing rod in his hand, Fran usually crying. And when she was thirty, pregnant, lying down, sighing; her fourteen-year-old son holding a fishing rod beside his beloved Grandpa. [] Fran headed back down the hill and onto the railway tracks, sprinting all the way to the oval, where she stopped to stretch. Sunday lunchtime downtown Ash Mountain: the oval was littered with last night’s bottles and cigarette butts, the soon-to-be-replaced statue of Bert Gallagher had been vomited on by someone who had cancer or had eaten tandoori.', 'The Red Lion carpark was crammed with the vehicles of families having counter meals of chicken parmigiana and peppercorn steak. Fran was hungry. A group of young men with a boat named Red Rocket were getting snacks at Gallagher’s Bakery, on their way to Lake Eildon, probably. And the convent was … the convent was right in front of her. One last stretch and she headed that way. [] Fran expected the elderly nun to take ages to answer the door – the building was an enormous bluestone rectangle with a hall attached – and it was a shock when Sister Mary Margaret appeared almost immediately. 93 ‘Hello?’ ‘Hello! Sister Mary Margaret, do you remember me? I’m Fran Collins – Francesca.’ The same Sidney Nolan was still hanging in the hall, and that was about as welcoming as the place would get. ‘You taught me when I was pregnant.', 'Do you remember Little Dante? Sorry, I’ve just been running.’ ‘Little Dante? He’s enormous! Course I know him. His half-acre feeds me, practically – come look at his miracles. Francesca. Come, come, I was just about to pop on the kettle.’ The zucchini on the kitchen table were impressive – Dante had a knack for enabling things to take off. ‘I can’t stay for tea, sorry. I’ve got to get back to Dad.’ ‘Would you like something other than tea?’ ‘Um, maybe water, thanks.’ Poor Sister Mary Margaret, the lonesome lush. She poured Fran’s water first, then – ‘It’s five o’clock somewhere’ – squeezed herself a reasonable-sized glass of cask rosé, plopping two round ice cubes in it.', '‘I made toffee!’ It was in a lovely tin. Sister Mary Margaret was into pretty containers. This one had cows on it. ‘I’d love to be able to chew it. I can only suck it these days. Take some.’ Sister Mary Margaret put a small piece of toffee in the side of her mouth and did not chew it. ‘Your dad – how’s your dad?’ ‘Terrible.’ Fran’s speech had been disabled by the toffee. ‘No, he’s okay. He can’t move, or do anything. He wants to die.’ ‘I’ll try and get out this week, do some crosswords with him.’ Sister Mary Margaret had shrunk a tad, but still towered over Fran at eighty-something.']	['“Nice work, Amber. I can’t believe that you didn’t do your book report. Couldn’t you find a book to match your interests? Did the library lend out the last copy of Where’s Spot?” She picks up some cold noodles with sesame sauce on them and chopsticks them into her mouth. “Are you enjoying your lunch? Worms with worm doodoo, isn’t it? Mmmmmmm, good.” Hannah puts the chopsticks down for a minute, and then she picks them up again. “You are just so immature, Amber. Late growing up\xa0. .', 'Лицето му внезапно помрачня. — Какво има? — попита Бартън разтревожено. — Какво се е случило? — Илюзо-преобразователят — Кристофър се подпря уморено на края на масата. Той вдигна уреда. — Забравил беше да си го сложиш. Кристофър засили лампата. — Значи не е от илюзо-преобразователя — проговори той след известно мълчание. Изглеждаше ужасно състарен и съкрушен, говореше едва едва.', 'It wasn’t long before I realized I had left Paphos without getting gas. I now understood that I wasn’t traveling on Pennsylvania’s I-80, but I still expected to see tall Mobil signs in the distance. In a hilltop village I stopped and used my Greek to ask a man who was walking down the street, “Where can I buy gas?” (I’d practiced.) He got in the car and directed me to the kafeneíon—the coffeehouse—whose patrons came out to give me directions and ended up forming a phalanx around the car and escorting me, on foot, to the garage, while I drove slowly, as if on parade. Instead of in underground tanks with a pump, the gasoline was stored in cans that came in two sizes, small and large. I picked the large one, the proprietor poured it into my tank, I paid in lira, and the men of the village whose coffee I had interrupted all waved goodbye as I pulled back onto the road. So far, the only signs of war I had seen were a refugee camp outside Limassol and a lot of poured-concrete buildings under construction to house people relocating from the Turkish sector. An old man with his arm in a sling was hitchhiking in the opposite direction, and I turned around to give him a ride. I felt so rich here in Cyprus, in my little yellow Fiat with its tank full of gas, that I could not pass up an old man who needed a lift. As soon as he got in the car, the old man whipped off the sling—there was nothing wrong with his arm. Back in his village, where I had been tempted to stop anyway, he wanted to buy me a Coke.', 'The number of bacteria on earth is estimated to be 5,000,000,000,000,000,000,000,000,000,000. This is five million trillion trillion, or 5 × 10 to the 30th power.⁹ Bacteria are the most social of the microbial world, but they don’t often win popularity contests. Bacteria can live in a wide variety of environments, including inside our bodies, where they help us with our biological processes like digesting food. Bacteria often encourage other friendlies to join their tribe and work together for the greater good. But like any social clique, some types of bacteria can be toxic, bad-mouthing each other and recruiting outcasts to soldier up for an invasion. The havoc these nasty tribes wreak include serious diseases like pneumonia (culprit: Streptococcus pneumoniae), meningitis (violator: Haemophilus influenzae), strep throat (perpetrator: Group A Streptococcus), food poisoning (invader: Escherichia coli and Salmonella), and other infections.¹⁰ But here’s the thing: both good and bad bacteria coexist, and it’s when the bad bacteria start rallying their peeps to outnumber the good that causes havoc, and can become a menace as prolific as COVID-19. [Image] You Are a Superorganism So you think you’re human? Made of blood, cells, flesh, thoughts, and emotions? Think again. Humans are superorganisms, with literally trillions of microbes taking up residence inside your body, on your skin, and in your hair.', '2. Suitable. 3. Excited. 2. How we must sanctify God in this ordinance. 1. Something is required before. 1. Habitual.']
  Or they may go the rest of their lives out of a wrong motive and never attain all that God wants for them. If the parents are not filled with the joy, blessing and anointing of the Lord, it is very difficult for the children to be so filled. Is not rather the fast that I have chosen, to loose the bands of wickedness, to undo the ties of oppression, to release into freedom those who are broken, and that ye break every yoke? (Isaiah 58:6). As Christians, we must be sure in our families and in our corporate expression of Christianity, that we are not legalistic, making heavier yokes and more chains for everyone. That is our human, natural way of doing things. When there is a problem or an abuse, we make more rules to ensure it doesn’t happen again and put everyone in a strait jacket removing more liberty from the Holy Spirit. God intended for the Jews to be a people who would live in freedom with liberty to express themselves to Him, to worship and honor Him. Over the centuries, they adde...	['They would meticulously keep these rules and think they were serving God, yet the blessing of God had left them long ago. Their rule-keeping was so extreme that when Jesus Christ walked among them, healed the blind, raised the dead, and did miracles they had never imagined, they did not give glory to God because Jesus was not interested in all their petty rules and regulations. He had come to share the heart of God with them, and they rejected it because it was foreign to the gilded cage of legalism they had surrounded themselves with. We must be continually on our guard so the same thing does not happen to us. We need to look for chains and yokes, making sure we are not creating bondages. We cannot be saying, “Well, since this happened to me, and I had this negative experience, I had better make sure there is no way anyone else can get hurt by this. Therefore, we will have this and that rule,” and thereby, we add to the Word of God. At the end of the Bible in the book of Revelation, there is a terrible curse on anyone who would add to or take away from the Word of God. Obviously, we need order. Our churches and families are not to be totally uncontrolled.', 'But we must have divine order, God-ordained order, and not some other order we devised as a substitute for God’s order. We must be sure to shoulder our God-ordained responsibilities. If you are the head of the household, your responsibility is to guarantee that your household is run according to God’s order, not according to rules you made up or learned somewhere. Likewise, if you are part of the leadership of a church, it is your responsibility to be participating in God’s order and not some other kind of order. Is it not to share thy bread with the hungry and that thou bring the poor that are cast out into thy house? when thou seest the naked, that thou cover him; and that thou not hide thyself from thy brother? Then shall thy light break forth as the morning, and thine health shall spring forth speedily: and thy righteousness shall go before thee; the glory of the LORD shall gather thee. Then shalt thou call, and thou shalt hear the LORD; thou shalt cry, and he shall say, Here I am. If thou take away from the midst of thee the yoke, the putting forth of the finger, and speaking vanity (Isaiah 58:7-9). As I travel across this continent, I hear many prayers in churches, and most people want great things from God.', '“Lord, heal our land. Lord, heal me when I’m sick. Lord, we don’t have enough money. Lord, save our schools.” Rarely do I see spectacular, clear-cut answers to prayer where the power of God has descended and there is a distinct difference between those who are serving God and those who are not. If God’s conditions have not been met by those who claim to belong to Him, we have not allowed the Lord to work in and through us. ...to share thy bread with the hungry and that thou bring the poor that are cast out to thy house. One time when we were very poor, growing up on a missionary base, my Dad started to apply some of these promises and meet some of the conditions. He had a whole book of all of the promises in Scripture. He would get down on his knees and ask the Lord what He wanted him to do to meet some of these conditions and activate God’s promises. Dad did some “strange” things for which he was severely criticized.', 'One occurred when we were to host a big banquet for the government dignitaries who were in charge of the Ministry of Government. The missionaries were about to be kicked out of the country, so the mission wanted to give the leaders of the government a favorable impression of the mission base. An airplane was sent to fly the dignitaries from the capital city to the missionary compound. Buying food and supplies for a special banquet drained the mission public relations fund. Everyone got out their best lace tablecloths and china. The banquet centered at our house because my dad was in charge of the technical work for the mission. It was his job to handle the government dignitaries. My mom and some of the ladies who were the best cooks among the missionary wives prepared a special dinner. We took our living room furniture out and put extra tables in our living room and dining room. But then the Director of our mission called with a report that there was bad weather, and the trip had been canceled and put off a week.', 'So there we were with this exquisite banquet and no invited guests. The Director wanted to know if our family could eat all the food and then pay the public relations fund back. Dad and Ricardo had just been reading in their Bibles where it said that if the wedding guests who had been invited did not come, you were to go out into the highways and byways and compel them to come in. Ricardo felt that this was what we should do. There were a lot of poor neighbors outside the gates of the mission compound. We were not supposed to be working with them because we had only been chartered to work with Indians, and many of our missionary coworkers feared that if we worked with these needy Spanish speakers, we would jeopardize our government contract. So we had been sitting there allowing horrendous need to occur right at our very gate. Dad informed the Director that in regard to the banquet, we were going to do what the Bible said and round up all the poor, hungry neighbors and feed them. Then Dad went out with the mission vehicles and loaded up the poor people and brought them to our house where he sat them down at the tables with the lace tablecloths and the fine china, and we served them the banquet. I can still remember serving at that banquet when a little old guy (I have never seen before or since) came hobbling up the hill to ask if we could give him a drink of water.']	["The answer is 50. So, what does Python do if you multiply the alphabet ‘a’ by 10? This is what happens: >>> print(10 * 'a') aaaaaaaaaa Most programmers use this approach if they want to have some spaces within the string, especially when they are displaying the string in the shell as a message. For example, how would you print a letter in the shell? You should select File4New Window and enter the code in the section below: spaces = ' ' * 25 print('%s 12 Butts Wynd' % spaces) print('%s Twinklebottom Heath' % spaces) print('%s West Snoring' % spaces) print() print() print('Dear Sir') print() print('I wish to report that tiles are missing from the') print('outside toilet roof.') print('I think it was bad wind the other night that blew them away.') print() print('Regards') print('Malcolm Dithering') Once the code has been typed in, you should choose the option File4Save to save the code. Save the code using the name myletter. The first line in the code above will instruct Python to create a variable space by using the space character 25. You can then use that space character in the next three lines of the code. This will help you align the text in the right format. You can fill the screen using annoying messages by using the multiplication operation.", 'Even though Lara had grown up in the past year—falling in love, having sex, finding the seeds of her confidence—she was still only fifteen years old. Still young enough to believe that her parents possessed magical powers; that they could fix anything. The whole way home, she played this scene in her head, as if repetition could make it real. She would walk through the door, and her parents would say, Thank God you’re here, Larochka. There’s been some terrible mix-up. But when she entered the apartment, her parents were immersed in a game of canasta, like any ordinary Tuesday night. Without glancing up from her cards, Irina said, “Were you warm enough in that jacket, Lara?” “Join us, darling,” Fyodor said. “Your mother is walloping me. Help me fend her off.” “Lara?” Irina said, finally looking up. “Lara, what’s wrong?” ------------------------------------------------------------------------ The burial took place a few days later, in a cemetery in a distant corner of the city.', 'Tonight she would talk to the others and together they would find a way to give Leila a funeral – and not just any funeral, but the finest funeral this manic old city had ever seen. This Manic Old City Istanbul was an illusion. A magician’s trick gone wrong. Istanbul was a dream that existed solely in the minds of hashish eaters. In truth, there was no Istanbul. There were multiple Istanbuls – struggling, competing, clashing, each perceiving that, in the end, only one could survive. There was, for instance, an ancient Istanbul designed to be crossed on foot or by boat – the city of itinerant dervishes, fortune-tellers, matchmakers, seafarers, cotton fluffers, rug beaters and porters with wicker baskets on their backs … There was modern Istanbul – an urban sprawl overrun with cars and motorcycles whizzing back and forth, construction trucks laden with building materials for more shopping centres, skyscrapers, industrial sites … Imperial Istanbul versus plebeian Istanbul; global Istanbul versus parochial Istanbul; cosmopolitan Istanbul versus philistine Istanbul; heretical Istanbul versus pious Istanbul; macho Istanbul versus a feminine Istanbul that adopted Aphrodite – goddess of desire and also of strife – as its symbol and protector … Then there was the Istanbul of those who had left long ago, sailing to faraway ports. For them this city would always be a metropolis made of memories, myths and messianic longings, forever elusive like a lover’s face receding in the mist. All these Istanbuls lived and breathed inside one another, like matryoshka dolls that had come to life. But even if a wicked wizard managed to separate them and put them side by side, nowhere in this vast line-up would he find a part of the city more desired, demonized and denounced than one particular neighbourhood: Pera.', '“You ready for this fire?” he asked. She groaned. “If you had any idea how sore I am after today, you’d never have agreed to this.” He held out his hand to help her up. “Do you want to beg off?” “And let Paul and Nikki think I’m out of shape?” She groaned again. “No way.” She placed her hand in his and let him pull her to her feet. They stood with only a few inches separating them. In any other circumstances John would have stepped back, but neither of them moved. Their eyes met and he studied her, looking for some indication of what she was thinking, what she was feeling. He read the question on her face and knew it was a reflection of his own doubts. He hadn’t kissed another woman since Lorraine, hadn’t even been tempted.', 'They kept staring at me as if they knew me. I ignored them, but noticed it went on during the whole time they were there. They didn't say anything that day, but when they returned the next day, Galen approached me. He told me I looked just like his wife, Hester. I told him I once had a daughter named Hester but she'd been sold away as a baby." Galen continued at that point. "Then I asked her her name. When she told me her name was Frances, I didn't dare even think she might be Hester's mother for fear it would not be the true Frances." "When he asked my full name and I responded, he went so still I began to fear he'd suffered some type of fit." Galen replied with a smile, "I thought I had. My heart fairly froze in my chest when she told me her name was Frances Wyatt Donaldson." Hester asked, "So do you have to return to Charleston?" Frances glanced over at Galen, then back. "I really don't know. Thanks to your extravagant husband I am no longer in bondage.']
  ------------------------------------------------------------------------ MARGUERITE LAI, Dance Revivalist The va’a were the backbone of our culture. Our canoes were the centre of daily life. Our villages were named for the va’a. It means everyone pulling together and working together. It’s a broader metaphor for Polynesian society. ------------------------------------------------------------------------ These vessels were central to Tahitian society. The open catamarans were carved using tools made of coral, stone and human bone, and cracks sealed with sap and resin from breadfruit trees. Planking was bound together with rope made of coconut fibre, and sails were woven from pandanus leaves. Cook had no concerns about the seaworthiness of Polynesian vessels. When he visited Tonga, he was particularly impressed by the double-hulled canoes he saw there.	['And they were speedy. He noted that they could reach seven miles an hour in a light breeze, which far outpaced Cook’s own vessels. In a fine example of nautical one-upmanship, in New Zealand waters a Māori canoe approached the Endeavour and a warrior on board called out to the men on board, ‘Are you alright? Are you sick? Why are you going so slowly?’ When told the ship was under full sail and travelling at top speed, the Māori sailors fell about themselves laughing before taking off again across the waves. As the means by which Polynesians interacted with their world, the canoe was a pillar of traditional Tahitian society. Watching the Tahitians and their brethren negotiate their way across the waves, Cook recognised kindred spirits. Like him, these people were sailors. ------------------------------------------------------------------------ MATAHI TUTAVAI The big canoes would go out to other islands. They not only found those islands, they also went back and forth between them.', 'We have family ties with Hawai‘i, with Aotearoa, with Samoa, Tonga. To us, the ocean wasn’t a barrier, it was a highway. We knew how to use it. ------------------------------------------------------------------------ They handled their canoes ‘very dextrously’, said Cook: ‘I believe [they] perform long and distant voyages in them, otherwise they could not have the knowledge of the islands in these seas they seem to have.’ But the Polynesian ships were, in virtually every way, completely unlike the converted collier James Cook sailed into the Pacific. The newly minted lieutenant would have felt right at home in the coal-carting vessel formerly known as the Earl of Pembroke. Cook learnt to sail on Whitby ‘cats’, as they were called. ------------------------------------------------------------------------ DAVID PRYCE, Sailor and Adventurer You look at the shape of the Endeavour – well, it is pretty much as close to your bathtub as you can get. It wasn’t a very manoeuvrable ship. ------------------------------------------------------------------------ With their flat bottoms, massive space below deck and square bows, the British ships weren’t much chop when it came to speed. But the ship renamed HM Bark Endeavour – ‘bark’ being the term used for those vessels that didn’t easily fit the British Navy’s classification system – was just the ticket for long-distance voyaging.', 'Its ‘bluff’ bow was much stronger than a pointy hull, and its flat bottom and shallow draught meant it could be floated off troublesome reefs or shoals a great deal more easily than if it had a pointy bow. It may not have set any speed records, but as events later in the voyage would prove, the Endeavour was well chosen for the conditions. In any other vessel, Cook’s great Pacific adventure might have gone no further than his first voyage. What the high priest of ’Oro and navigator, Tupaia, thought of Cook’s cumbersome vessel as he climbed on board in 1769 off the shores of Tahiti, we’ll never know. But thanks to the various journals kept by the crew of the Endeavour, we do know something about the man who left his ancestral home on Ra’iatea and set out to sea with a boatload of noisome British sailors. Born around 1725, Tupaia was an ’arioi and was blessed with all the traits that membership of the exclusive class of priests and priestesses entailed. He was statuesque and physically imposing, highly intelligent and charismatic, and a savvy diplomat. The ship’s master, Robert Molyneux, deemed Tupaia to be: ‘infinitely superior in every respect to any other Indian we have met with, he has conceived so strong a friendship for Mr Banks that he is determined to visit Britannia’. It was true that Joseph Banks formed a particularly close relationship with Tupaia, so much so that he harboured ambitions to take him back to England and keep him. Much like an exotic pet.', '------------------------------------------------------------------------ SIR JOSEPH BANKS Thank heaven I have a sufficiency and I do not know why I may not keep him as a curiosity, as well as some of my neighbours do lions and tigers at a larger expense than he will probably ever put me to; the amusement I shall have in his future conversation and the benefit he will be of to this ship, as well as what he may be if another should be sent into these seas, will I think fully repay me. ------------------------------------------------------------------------ Banks also knew it would be a boon to have Tupaia on board as a translator and local mediator when they encountered other Pacific Islanders. Even before the Endeavour arrived in Tahiti, he had been contemplating the benefits that a local guide would offer. ------------------------------------------------------------------------ SIR JOSEPH BANKS [We should] persuade one of them to come with us who may serve as an interpreter, and give us an opportunity hereafter of landing wherever we please without running the risk of being obliged to commit the cruelties which the Spaniards and most others who have been in these seas have often brought themselves under the dreadful necessity of being guilty of, for guilty I must call it. ------------------------------------------------------------------------ As for Tupaia, his motivations for embarking with Cook and his men were crystal clear. ------------------------------------------------------------------------ RICHARD ARIIHAU TUHEIAVA Tupaia did follow Cook because he wanted to discover how things were outside of this country. He had a personal quest. He was not simply being used by James Cook. Tupaia had his own ambitions too. He had a very high level of wisdom and spiritual training – more so than James Cook.', 'But he had no ship. He needed Cook to travel across the ocean and see the islands beyond. ------------------------------------------------------------------------ In the intertribal wars, Tupaia had been driven from his homeland, Ra’iatea, by a rival group from Bora Bora. He relocated to Tahiti, where he aligned himself with Queen Purea and became her advisor and lover. Naturally, he was keen to take his home back. He must have known that an alliance with the British and their impressive weapons certainly wouldn’t hurt his ambitions. Before the Endeavour set sail on the next leg of its voyage, Tupaia directed the ship to Ra’iatea and what we now know to be one of the most significant historical sites in the Pacific: Taputapuatea Marae. ------------------------------------------------------------------------ RICHARD ARIIHAU TUHEIAVA It was where the most beautiful ocean-going journeys of all time began. Celestial navigation was an art, but also a lifestyle. Taputapuatea was the navigational hub of all these people – these heroes – who crossed the ocean without any instruments, and returned to this place they considered their homeland.']	['Preheat the oven to 300 ° F. Line a circular 9-inch cake pan on baking paper and spray with oil of choice. 2. Sift the almond flour, cocoa powder, baking soda, erythritol and salt into a medium bowl and mix everything until it is smooth. 3. Add the vanilla extract and coconut oil and mix until the dough turns into crumbs. 4. Add the egg and mix until the cookie dough starts to stick and form a ball. 5. Put the dough into a separated cake pan and lightly press the dough with your fingers until it evenly covers the bottom of the pan.', '"Wh-what do you want?" Ciaran had rehearsed what he was going to say to the man, plotted it with Fallon. What would Ciaran of the Mist say? What would he do? What would most terrorize this craven cur with the dagger at his throat? Yet as Ciaran stared down into that bloated face with its eyes gluttonous from selfish pleasure, every speech vanished from his brain, leaving only a red haze of rage. "Who am I?" Ciaran echoed. "I am your worst nightmare—the reason you keep that pathetic pistol beneath your pillow at night, set guards at your doors. Did you really believe such paltry measures could keep me away?" Was it possible for the man to blanch any whiter? "J-James?" Butler stammered, shrinking back. "No!', 'В колата се чувствуваше в стихията си. Отсега нататък окото му няма да мигне. Виждал бе същото на война. То променяше човек повече, отколкото загубата на девствеността. Страхът изчезваше като опериран. На негово място израстваше нещо друго. Най-важното в един мъж. Онова, което го правеше да бъде мъж. И жените го усещаха. Липсата на този проклет страх.', 'No. What were you thinking? I wasn't thinking. I was finally doing something. Yeah. Something stupid. Don't tell me you're on their side now. I was walking fast. Link struggled to keep up with me. "You're gonna start a fight, aren't you?', '39 48. 40 49. 41 50. 42 51. 43 52. 44 53. 45 54. 46 55. 47 56. 48 57.']

• Loss: TripletLoss with these parameters:

  {
      "distance_metric": "TripletDistanceMetric.EUCLIDEAN",
      "triplet_margin": 0.5
  }
  

Training Hyperparameters

Non-Default Hyperparameters

• per_device_train_batch_size: 1
• per_device_eval_batch_size: 1
• num_train_epochs: 1
• multi_dataset_batch_sampler: round_robin

All Hyperparameters

Click to expand

• overwrite_output_dir: False
• do_predict: False
• eval_strategy: no
• prediction_loss_only: True
• per_device_train_batch_size: 1
• per_device_eval_batch_size: 1
• 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: 5e-05
• weight_decay: 0.0
• adam_beta1: 0.9
• adam_beta2: 0.999
• adam_epsilon: 1e-08
• max_grad_norm: 1
• num_train_epochs: 1
• max_steps: -1
• lr_scheduler_type: linear
• lr_scheduler_kwargs: {}
• warmup_ratio: 0.0
• 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: False
• 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: False
• dataloader_num_workers: 0
• dataloader_prefetch_factor: None
• past_index: -1
• disable_tqdm: False
• remove_unused_columns: True
• label_names: None
• load_best_model_at_end: 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}
• tp_size: 0
• 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: batch_sampler
• multi_dataset_batch_sampler: round_robin

Training Logs

Epoch	Step	Training Loss
0.025	500	0.016
0.05	1000	0.0126
0.075	1500	0.0076
0.1	2000	0.0105
0.125	2500	0.0044
0.15	3000	0.0088
0.175	3500	0.0069
0.2	4000	0.0019
0.225	4500	0.0122
0.25	5000	0.0098
0.275	5500	0.0092
0.3	6000	0.0079
0.325	6500	0.0078
0.35	7000	0.0133
0.375	7500	0.0108
0.4	8000	0.0046
0.425	8500	0.0084
0.45	9000	0.0111
0.475	9500	0.0102
0.5	10000	0.0081
0.525	10500	0.0046
0.55	11000	0.0045
0.575	11500	0.001
0.6	12000	0.0045
0.625	12500	0.0057
0.65	13000	0.0057
0.675	13500	0.0062
0.7	14000	0.0045
0.725	14500	0.0089
0.75	15000	0.0028
0.775	15500	0.0017
0.8	16000	0.0082
0.825	16500	0.01
0.85	17000	0.0091
0.875	17500	0.0032
0.9	18000	0.0016
0.925	18500	0.0028
0.95	19000	0.0027
0.975	19500	0.0009
1.0	20000	0.0012

Framework Versions

• Python: 3.11.2
• Sentence Transformers: 3.4.1
• Transformers: 4.50.1
• PyTorch: 2.6.0+cu124
• Accelerate: 1.5.2
• Datasets: 3.4.1
• Tokenizers: 0.21.1

Citation

BibTeX

Sentence Transformers

@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",
}

TripletLoss

@misc{hermans2017defense,
    title={In Defense of the Triplet Loss for Person Re-Identification},
    author={Alexander Hermans and Lucas Beyer and Bastian Leibe},
    year={2017},
    eprint={1703.07737},
    archivePrefix={arXiv},
    primaryClass={cs.CV}
}