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data/clustering_individual-af410ee3-7691-4d91-abd0-61898a8363dc.jsonl
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{"tstamp": 1739758644.6931, "task_type": "clustering", "type": "chat", "model": "nomic-ai/nomic-embed-text-v1.5", "gen_params": {}, "start": 1739758644.4413, "finish": 1739758644.6931, "ip": "", "conv_id": "b8dc17f9c5b24a1fa5fe30dcfdbf90a4", "model_name": "nomic-ai/nomic-embed-text-v1.5", "prompt": ["jiu-jitsu", "aikido", "taekwondo", "judo", "kayak", "motorboat", "yacht", "cruise ship", "canoe"], "ncluster": 2, "output": "", "ndim": "3D (press for 2D)", "dim_method": "PCA", "clustering_method": "KMeans"}
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{"tstamp": 1739758666.9427, "task_type": "clustering", "type": "chat", "model": "text-embedding-004", "gen_params": {}, "start": 1739758666.6638, "finish": 1739758666.9427, "ip": "", "conv_id": "be28eed2b6384f4e9e33ad45e41c926c", "model_name": "text-embedding-004", "prompt": ["pu-erh", "white", "green", "black", "chamomile", "TikTok", "Twitter", "LinkedIn", "Facebook", "Instagram", "claustrophobia", "nyctophobia", "acrophobia", "arachnophobia", "agoraphobia", "ophidiophobia", "mackerel", "halibut", "trout", "bass", "tuna", "salmon", "cod"], "ncluster": 4, "output": "", "ndim": "3D (press for 2D)", "dim_method": "PCA", "clustering_method": "KMeans"}
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{"tstamp": 1739758666.9427, "task_type": "clustering", "type": "chat", "model": "BAAI/bge-large-en-v1.5", "gen_params": {}, "start": 1739758666.6638, "finish": 1739758666.9427, "ip": "", "conv_id": "796074680ba54227b44c6ea8da10bf5d", "model_name": "BAAI/bge-large-en-v1.5", "prompt": ["pu-erh", "white", "green", "black", "chamomile", "TikTok", "Twitter", "LinkedIn", "Facebook", "Instagram", "claustrophobia", "nyctophobia", "acrophobia", "arachnophobia", "agoraphobia", "ophidiophobia", "mackerel", "halibut", "trout", "bass", "tuna", "salmon", "cod"], "ncluster": 4, "output": "", "ndim": "3D (press for 2D)", "dim_method": "PCA", "clustering_method": "KMeans"}
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{"tstamp": 1739758644.6931, "task_type": "clustering", "type": "chat", "model": "nomic-ai/nomic-embed-text-v1.5", "gen_params": {}, "start": 1739758644.4413, "finish": 1739758644.6931, "ip": "", "conv_id": "b8dc17f9c5b24a1fa5fe30dcfdbf90a4", "model_name": "nomic-ai/nomic-embed-text-v1.5", "prompt": ["jiu-jitsu", "aikido", "taekwondo", "judo", "kayak", "motorboat", "yacht", "cruise ship", "canoe"], "ncluster": 2, "output": "", "ndim": "3D (press for 2D)", "dim_method": "PCA", "clustering_method": "KMeans"}
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{"tstamp": 1739758666.9427, "task_type": "clustering", "type": "chat", "model": "text-embedding-004", "gen_params": {}, "start": 1739758666.6638, "finish": 1739758666.9427, "ip": "", "conv_id": "be28eed2b6384f4e9e33ad45e41c926c", "model_name": "text-embedding-004", "prompt": ["pu-erh", "white", "green", "black", "chamomile", "TikTok", "Twitter", "LinkedIn", "Facebook", "Instagram", "claustrophobia", "nyctophobia", "acrophobia", "arachnophobia", "agoraphobia", "ophidiophobia", "mackerel", "halibut", "trout", "bass", "tuna", "salmon", "cod"], "ncluster": 4, "output": "", "ndim": "3D (press for 2D)", "dim_method": "PCA", "clustering_method": "KMeans"}
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{"tstamp": 1739758666.9427, "task_type": "clustering", "type": "chat", "model": "BAAI/bge-large-en-v1.5", "gen_params": {}, "start": 1739758666.6638, "finish": 1739758666.9427, "ip": "", "conv_id": "796074680ba54227b44c6ea8da10bf5d", "model_name": "BAAI/bge-large-en-v1.5", "prompt": ["pu-erh", "white", "green", "black", "chamomile", "TikTok", "Twitter", "LinkedIn", "Facebook", "Instagram", "claustrophobia", "nyctophobia", "acrophobia", "arachnophobia", "agoraphobia", "ophidiophobia", "mackerel", "halibut", "trout", "bass", "tuna", "salmon", "cod"], "ncluster": 4, "output": "", "ndim": "3D (press for 2D)", "dim_method": "PCA", "clustering_method": "KMeans"}
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{"tstamp": 1739810035.2147, "task_type": "clustering", "type": "chat", "model": "text-embedding-004", "gen_params": {}, "start": 1739810035.1791, "finish": 1739810035.2147, "ip": "", "conv_id": "d3090a81bdf2416f99710a9deb426701", "model_name": "text-embedding-004", "prompt": ["Dog"], "ncluster": 1, "output": "", "ndim": "3D", "dim_method": "PCA", "clustering_method": "KMeans"}
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{"tstamp": 1739810056.7094, "task_type": "clustering", "type": "chat", "model": "nomic-ai/nomic-embed-text-v1.5", "gen_params": {}, "start": 1739810056.6861, "finish": 1739810056.7094, "ip": "", "conv_id": "4970886ebbed49feb909de52923a4c15", "model_name": "nomic-ai/nomic-embed-text-v1.5", "prompt": ["Dog"], "ncluster": 1, "output": "", "ndim": "3D", "dim_method": "PCA", "clustering_method": "KMeans"}
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data/retrieval_individual-af410ee3-7691-4d91-abd0-61898a8363dc.jsonl
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{"tstamp": 1739803764.3633, "task_type": "retrieval", "type": "chat", "model": "GritLM/GritLM-7B", "gen_params": {}, "start": 1739803762.0932, "finish": 1739803764.3633, "ip": "", "conv_id": "2cff8bb07a18474a8ea3ee239186fe23", "model_name": "GritLM/GritLM-7B", "prompt": "์ ํ๋ธ๋ฅผ ๋ณด๋ฉด์ ๊ณต๋ถํ ๋ ์ฌ์ฉํ ์ ์๋ ์ถ์ฒ ๊ณต๋ถ๋ฒ์?", "output": [["์ ํ๋ธ๋ฅผ ๋ณด๋ฉด์ ๊ณต๋ถํ ๋ ์ฌ์ฉํ ์ ์๋ ์ถ์ฒ ๊ณต๋ถ๋ฒ์?", "Active learning\n\nEngaging in deliberate practice: promoting practice focused on learning from errors (Brown, Roediger, & McDaniel, 2014; Ericsson, Krampe, & Tesch-Romer, 1993)\nUsing interleaving: intermixing different problem types\nInducing dual coding: presenting information both verbally and visually (Kosslyn, 1994; Mayer, 2001; Moreno & Valdez, 2005)\nEvoking emotion: generating feelings to enhance recall (Erk et al., 2003; Levine & Pizarro, 2004; McGaugh, 2003, 2004)\nMaxim II: Make and use associations\nPromoting chunking: collecting information into organized units (Brown, Roediger, & McDaniel, 2014; Mayer & Moreno, 2003)\nBuilding on prior associations: connecting new information to previously stored information (Bransford, Brown, & Cocking, 2000; Glenberg & Robertson, 1999; Mayer, 2001)\nPresenting foundational material first: providing basic information as a structural \"spine\" onto which new information can be attached (Bransford, Brown, & Cocking, 2000; Wandersee, Mintzes, & Novak, 1994)\nExploiting appropriate examples: offering examples of the same idea in multiple contexts (Hakel & Halpern, 2005)\nRelying on principles, not rote: explicitly characterizing the dimensions, factors or mechanisms that underlie a phenomenon (Kozma & Russell, 1997; Bransford, Brown, & Cocking, 2000)\nCreating associative chaining: sequencing chunks of information into stories (Bower & Clark, 1969; Graeser, Olde, & Klettke, 2002)\nUsing spaced practice: spreading learning out over time (Brown, Roediger, & McDaniel, 2014; Cepeda et al., 2006, 2008; Cull, 2000)"]], "corpus": "wikipedia"}
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{"tstamp": 1739808138.6647, "task_type": "retrieval", "type": "chat", "model": "Salesforce/SFR-Embedding-2_R", "gen_params": {}, "start": 1739808136.2602, "finish": 1739808138.6647, "ip": "", "conv_id": "fdaa254477b14837b91ed5a9d695c689", "model_name": "Salesforce/SFR-Embedding-2_R", "prompt": "I love cats so much!", "output": [["I love cats so much!", "Cats and the Internet\n\nCats That Look Like Hitler is a satirical website featuring photographs of cats that bear an alleged resemblance to Adolf Hitler. Most of the cats have a large black splotch underneath their nose, much like the dictator's stumpy toothbrush moustache. The site was founded by Koos Plegt and Paul Neve in 2006, and became widely known after being featured on several television programmes across Europe and Australia. The site is now only run by Neve. , the site contained photographs of over 8,000 cats, submitted by owners with digital cameras and Internet access and then approved by Neve as content.\nEverytime you masturbate... God kills a kitten\n\"Every time you masturbate... God kills a kitten\" is the caption of an image created by a member of the website Fark in 2002. The image features a kitten (subsequently referred to as \"Clichรฉ Kitty\") being chased by two Domos, and has the tagline \"Please, think of the kittens\".\nI Can Has Cheezburger\nIt was created in 2007 by Eric Nakagawa (Cheezburger), a blogger from Hawaii, and his friend Kari Unebasami (Tofuburger). The website is one of the most popular Internet sites of its kind. It received as many as 1,500,000 hits per day at its peak in May 2007. ICHC was instrumental in bringing animal-based image macros and lolspeak into mainstream usage and making Internet memes profitable."]], "corpus": "wikipedia"}
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{"tstamp": 1739808138.6647, "task_type": "retrieval", "type": "chat", "model": "intfloat/e5-mistral-7b-instruct", "gen_params": {}, "start": 1739808136.2602, "finish": 1739808138.6647, "ip": "", "conv_id": "9ad8ec5ace3c40e6ac10c8283b559f65", "model_name": "intfloat/e5-mistral-7b-instruct", "prompt": "I love cats so much!", "output": [["I love cats so much!", "Meow\n\nA meow or miaow is a cat vocalization. Meows may have diverse tones in terms of their sound, and what is heard can vary from being chattered to calls, murmurs, and whispers. Adult cats rarely meow to each other. Thus, an adult cat meowing to human beings is generally considered a post-domestication extension of meowing by kittens: a call for attention. Felines usually communicate with each other via their shared sense of smell, yet with people they often make verbal cues around behavior, such as having a specific sound indicate a desire to go outside."]], "corpus": "wikipedia"}
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{"tstamp": 1739803764.3633, "task_type": "retrieval", "type": "chat", "model": "GritLM/GritLM-7B", "gen_params": {}, "start": 1739803762.0932, "finish": 1739803764.3633, "ip": "", "conv_id": "2cff8bb07a18474a8ea3ee239186fe23", "model_name": "GritLM/GritLM-7B", "prompt": "์ ํ๋ธ๋ฅผ ๋ณด๋ฉด์ ๊ณต๋ถํ ๋ ์ฌ์ฉํ ์ ์๋ ์ถ์ฒ ๊ณต๋ถ๋ฒ์?", "output": [["์ ํ๋ธ๋ฅผ ๋ณด๋ฉด์ ๊ณต๋ถํ ๋ ์ฌ์ฉํ ์ ์๋ ์ถ์ฒ ๊ณต๋ถ๋ฒ์?", "Active learning\n\nEngaging in deliberate practice: promoting practice focused on learning from errors (Brown, Roediger, & McDaniel, 2014; Ericsson, Krampe, & Tesch-Romer, 1993)\nUsing interleaving: intermixing different problem types\nInducing dual coding: presenting information both verbally and visually (Kosslyn, 1994; Mayer, 2001; Moreno & Valdez, 2005)\nEvoking emotion: generating feelings to enhance recall (Erk et al., 2003; Levine & Pizarro, 2004; McGaugh, 2003, 2004)\nMaxim II: Make and use associations\nPromoting chunking: collecting information into organized units (Brown, Roediger, & McDaniel, 2014; Mayer & Moreno, 2003)\nBuilding on prior associations: connecting new information to previously stored information (Bransford, Brown, & Cocking, 2000; Glenberg & Robertson, 1999; Mayer, 2001)\nPresenting foundational material first: providing basic information as a structural \"spine\" onto which new information can be attached (Bransford, Brown, & Cocking, 2000; Wandersee, Mintzes, & Novak, 1994)\nExploiting appropriate examples: offering examples of the same idea in multiple contexts (Hakel & Halpern, 2005)\nRelying on principles, not rote: explicitly characterizing the dimensions, factors or mechanisms that underlie a phenomenon (Kozma & Russell, 1997; Bransford, Brown, & Cocking, 2000)\nCreating associative chaining: sequencing chunks of information into stories (Bower & Clark, 1969; Graeser, Olde, & Klettke, 2002)\nUsing spaced practice: spreading learning out over time (Brown, Roediger, & McDaniel, 2014; Cepeda et al., 2006, 2008; Cull, 2000)"]], "corpus": "wikipedia"}
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{"tstamp": 1739808138.6647, "task_type": "retrieval", "type": "chat", "model": "Salesforce/SFR-Embedding-2_R", "gen_params": {}, "start": 1739808136.2602, "finish": 1739808138.6647, "ip": "", "conv_id": "fdaa254477b14837b91ed5a9d695c689", "model_name": "Salesforce/SFR-Embedding-2_R", "prompt": "I love cats so much!", "output": [["I love cats so much!", "Cats and the Internet\n\nCats That Look Like Hitler is a satirical website featuring photographs of cats that bear an alleged resemblance to Adolf Hitler. Most of the cats have a large black splotch underneath their nose, much like the dictator's stumpy toothbrush moustache. The site was founded by Koos Plegt and Paul Neve in 2006, and became widely known after being featured on several television programmes across Europe and Australia. The site is now only run by Neve. , the site contained photographs of over 8,000 cats, submitted by owners with digital cameras and Internet access and then approved by Neve as content.\nEverytime you masturbate... God kills a kitten\n\"Every time you masturbate... God kills a kitten\" is the caption of an image created by a member of the website Fark in 2002. The image features a kitten (subsequently referred to as \"Clichรฉ Kitty\") being chased by two Domos, and has the tagline \"Please, think of the kittens\".\nI Can Has Cheezburger\nIt was created in 2007 by Eric Nakagawa (Cheezburger), a blogger from Hawaii, and his friend Kari Unebasami (Tofuburger). The website is one of the most popular Internet sites of its kind. It received as many as 1,500,000 hits per day at its peak in May 2007. ICHC was instrumental in bringing animal-based image macros and lolspeak into mainstream usage and making Internet memes profitable."]], "corpus": "wikipedia"}
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{"tstamp": 1739808138.6647, "task_type": "retrieval", "type": "chat", "model": "intfloat/e5-mistral-7b-instruct", "gen_params": {}, "start": 1739808136.2602, "finish": 1739808138.6647, "ip": "", "conv_id": "9ad8ec5ace3c40e6ac10c8283b559f65", "model_name": "intfloat/e5-mistral-7b-instruct", "prompt": "I love cats so much!", "output": [["I love cats so much!", "Meow\n\nA meow or miaow is a cat vocalization. Meows may have diverse tones in terms of their sound, and what is heard can vary from being chattered to calls, murmurs, and whispers. Adult cats rarely meow to each other. Thus, an adult cat meowing to human beings is generally considered a post-domestication extension of meowing by kittens: a call for attention. Felines usually communicate with each other via their shared sense of smell, yet with people they often make verbal cues around behavior, such as having a specific sound indicate a desire to go outside."]], "corpus": "wikipedia"}
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{"tstamp": 1739809998.9332, "task_type": "retrieval", "type": "chat", "model": "BM25", "gen_params": {}, "start": 1739809997.7196, "finish": 1739809998.9332, "ip": "", "conv_id": "8f3414cc74b24ce1b6176861a1f093ae", "model_name": "BM25", "prompt": "Dog", "output": [["Dog", "List of films: D\n\nDodge City (1939) Dodgeball: A True Underdog Story (2004)\nDodsworth (1936)\nDoes It Pay? (1923)\nDog: (2001 & 2022)\nThe Dog: (1992 & 2013)\nDog Altogether (2007)\nDog Bite Dog (2006)\nDog Day (1984)\nDog Day Afternoon (1975)\nDog Days: (1925, 1970, 2001 & 2018)\nDog Days of Summer (2007)\nDog Daze: (1937 & 1939)\nA Dog in a Drawer (1982)\nDog Eat Dog: (1964, 2001, 2008, 2016 & 2018)\nDog Factory (1904)\nA Dog of Flanders: (1935, 1959 & 1999)\nDog Gone: (1926, 2008 & 2023)\nDog Gone People (1960)\nDog Heaven (1927)\nDog It Down (2012)\nDog Jack (2010)\nDog Nail Clipper (2004)\nDog Park (1998)\nDog Pound (2010)\nDog Pounded (1954)\nDog Shy (1926)\nDog Soldiers (2002)\nDog Star Man (1961)\nDog Tags (2008)\nDog Tales (1958)\nThe Dog Who Stopped the War (1984)\nThe Dog Who Wouldn't Be Quiet (2021)\nA Dog's Breakfast (2006)\nDog's Dialogue (1977)\nDog's Heads (1955)\nA Dog's Journey (2019)\nDog's Life (2013)\nA Dog's Life (1918)\nA Dog's Purpose (2017)\nA Dog's Will (2000)\nDogfight (1991)\nDoggie March (1963)\nDoggone Cats (1947)\nDoggone Tired (1949)\nDoghead (2006)\nDoghouse (2009)\nDogma (1999)\nDogs: (1976 & 2016)\nThe Dogs (1979)\nDogs Don't Wear Pants (2019)\nDogs in Space (1987)"]], "corpus": "wikipedia"}
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