Scheduled Commit

data/clustering_battle-112c1ce1-fe57-41e6-8919-4f1859b89f91.jsonl

@@ -1,2 +1,3 @@
 {"tstamp": 1723773356.776, "task_type": "clustering", "type": "rightvote", "models": ["", ""], "ip": "", "0_conv_id": "bb85ed0b1a2346ee98c183269ce62cbb", "0_model_name": "text-embedding-3-large", "0_prompt": ["the major city in US", "Shanghai", "Beijing", "Shenzhen", "Hangzhou", "Seattle", "Boston", "New York", "San Francisco", "Darth Vader", "Yoda", "Squirtle", "Gandalf", "Legolas", "Mickey Mouse", "Donald Duck", "Charizard"], "0_ncluster": 2, "0_output": "", "0_ndim": "3D (press for 2D)", "0_dim_method": "PCA", "0_clustering_method": "KMeans", "1_conv_id": "50788a7548b34a43ba518321a7c900a7", "1_model_name": "nomic-ai/nomic-embed-text-v1.5", "1_prompt": ["the major city in US", "Shanghai", "Beijing", "Shenzhen", "Hangzhou", "Seattle", "Boston", "New York", "San Francisco", "Darth Vader", "Yoda", "Squirtle", "Gandalf", "Legolas", "Mickey Mouse", "Donald Duck", "Charizard"], "1_ncluster": 2, "1_output": "", "1_ndim": "3D (press for 2D)", "1_dim_method": "PCA", "1_clustering_method": "KMeans"}
 {"tstamp": 1723773582.4108, "task_type": "clustering", "type": "leftvote", "models": ["", ""], "ip": "", "0_conv_id": "fc182aada5a1495fac383e3650a06fa7", "0_model_name": "mixedbread-ai/mxbai-embed-large-v1", "0_prompt": ["octagon", "rectangle", "Temple of Artemis", "Colossus of Rhodes", "Statue of Zeus", "Lighthouse of Alexandria", "Hanging Gardens of Babylon", "Pyramids of Giza", "brunette", "black", "blonde", "redhead", "gray", "auburn", "white", "soccer", "basketball", "tennis", "baseball", "cricket", "ruby", "topaz", "diamond"], "0_ncluster": 5, "0_output": "", "0_ndim": "3D (press for 2D)", "0_dim_method": "PCA", "0_clustering_method": "KMeans", "1_conv_id": "353d690256994441a1b2e7f8c1777b52", "1_model_name": "BAAI/bge-large-en-v1.5", "1_prompt": ["octagon", "rectangle", "Temple of Artemis", "Colossus of Rhodes", "Statue of Zeus", "Lighthouse of Alexandria", "Hanging Gardens of Babylon", "Pyramids of Giza", "brunette", "black", "blonde", "redhead", "gray", "auburn", "white", "soccer", "basketball", "tennis", "baseball", "cricket", "ruby", "topaz", "diamond"], "1_ncluster": 5, "1_output": "", "1_ndim": "3D (press for 2D)", "1_dim_method": "PCA", "1_clustering_method": "KMeans"}
+{"tstamp": 1723791451.7309, "task_type": "clustering", "type": "rightvote", "models": ["", ""], "ip": "", "0_conv_id": "eeb16bc223734184aff49ba1cd073ab1", "0_model_name": "sentence-transformers/all-MiniLM-L6-v2", "0_prompt": ["PVC", "acrylic", "polypropylene", "polyethylene", "pruning shears", "wheelbarrow", "rake", "hoe", "trowel", "watering can", "Google Cloud", "IBM Cloud", "Azure", "DigitalOcean", "AWS", "penne", "ravioli", "anchoring bias", "hindsight bias", "confirmation bias", "dunning-kruger effect"], "0_ncluster": 5, "0_output": "", "0_ndim": "3D (press for 2D)", "0_dim_method": "PCA", "0_clustering_method": "KMeans", "1_conv_id": "3f1a9b58bfff4fb38c727bdacaa7a7f9", "1_model_name": "BAAI/bge-large-en-v1.5", "1_prompt": ["PVC", "acrylic", "polypropylene", "polyethylene", "pruning shears", "wheelbarrow", "rake", "hoe", "trowel", "watering can", "Google Cloud", "IBM Cloud", "Azure", "DigitalOcean", "AWS", "penne", "ravioli", "anchoring bias", "hindsight bias", "confirmation bias", "dunning-kruger effect"], "1_ncluster": 5, "1_output": "", "1_ndim": "3D (press for 2D)", "1_dim_method": "PCA", "1_clustering_method": "KMeans"}

data/clustering_individual-112c1ce1-fe57-41e6-8919-4f1859b89f91.jsonl

@@ -8,3 +8,5 @@
 {"tstamp": 1723773612.8322, "task_type": "clustering", "type": "chat", "model": "Salesforce/SFR-Embedding-2_R", "gen_params": {}, "start": 1723773612.6172, "finish": 1723773612.8322, "ip": "", "conv_id": "e877bae0afec4328835afe6e8c2a2595", "model_name": "Salesforce/SFR-Embedding-2_R", "prompt": ["It's official! 1 Bitcoin = $10,000 USD", "Everyone who's trading BTC right now", "Age reversal not only achievable but also possibly imminent: Retro Biosciences", "MicroRNA regrows 90% of lost hair, study finds", "Speech-to-speech translation for a real-world unwritten language", "Seeking the Best Embedding Model: Experiences with the MTEB Arena?"], "ncluster": 5, "output": "", "ndim": "3D (press for 2D)", "dim_method": "PCA", "clustering_method": "KMeans"}
 {"tstamp": 1723773667.1796, "task_type": "clustering", "type": "chat", "model": "GritLM/GritLM-7B", "gen_params": {}, "start": 1723773666.7728, "finish": 1723773667.1796, "ip": "", "conv_id": "00a727e1627f441488bdfbb690744cc8", "model_name": "GritLM/GritLM-7B", "prompt": ["It's official! 1 Bitcoin = $10,000 USD", "Everyone who's trading BTC right now", "Age reversal not only achievable but also possibly imminent: Retro Biosciences", "MicroRNA regrows 90% of lost hair, study finds", "Speech-to-speech translation for a real-world unwritten language", "Seeking the Best Embedding Model: Experiences with the MTEB Arena?"], "ncluster": 5, "output": "", "ndim": "2D (press for 3D)", "dim_method": "PCA", "clustering_method": "KMeans"}
 {"tstamp": 1723773667.1796, "task_type": "clustering", "type": "chat", "model": "Salesforce/SFR-Embedding-2_R", "gen_params": {}, "start": 1723773666.7728, "finish": 1723773667.1796, "ip": "", "conv_id": "e877bae0afec4328835afe6e8c2a2595", "model_name": "Salesforce/SFR-Embedding-2_R", "prompt": ["It's official! 1 Bitcoin = $10,000 USD", "Everyone who's trading BTC right now", "Age reversal not only achievable but also possibly imminent: Retro Biosciences", "MicroRNA regrows 90% of lost hair, study finds", "Speech-to-speech translation for a real-world unwritten language", "Seeking the Best Embedding Model: Experiences with the MTEB Arena?"], "ncluster": 5, "output": "", "ndim": "2D (press for 3D)", "dim_method": "PCA", "clustering_method": "KMeans"}
+{"tstamp": 1723791402.9895, "task_type": "clustering", "type": "chat", "model": "sentence-transformers/all-MiniLM-L6-v2", "gen_params": {}, "start": 1723791402.5942, "finish": 1723791402.9895, "ip": "", "conv_id": "eeb16bc223734184aff49ba1cd073ab1", "model_name": "sentence-transformers/all-MiniLM-L6-v2", "prompt": ["PVC", "acrylic", "polypropylene", "polyethylene", "pruning shears", "wheelbarrow", "rake", "hoe", "trowel", "watering can", "Google Cloud", "IBM Cloud", "Azure", "DigitalOcean", "AWS", "penne", "ravioli", "anchoring bias", "hindsight bias", "confirmation bias", "dunning-kruger effect"], "ncluster": 5, "output": "", "ndim": "3D (press for 2D)", "dim_method": "PCA", "clustering_method": "KMeans"}
+{"tstamp": 1723791402.9895, "task_type": "clustering", "type": "chat", "model": "BAAI/bge-large-en-v1.5", "gen_params": {}, "start": 1723791402.5942, "finish": 1723791402.9895, "ip": "", "conv_id": "3f1a9b58bfff4fb38c727bdacaa7a7f9", "model_name": "BAAI/bge-large-en-v1.5", "prompt": ["PVC", "acrylic", "polypropylene", "polyethylene", "pruning shears", "wheelbarrow", "rake", "hoe", "trowel", "watering can", "Google Cloud", "IBM Cloud", "Azure", "DigitalOcean", "AWS", "penne", "ravioli", "anchoring bias", "hindsight bias", "confirmation bias", "dunning-kruger effect"], "ncluster": 5, "output": "", "ndim": "3D (press for 2D)", "dim_method": "PCA", "clustering_method": "KMeans"}

data/retrieval_battle-112c1ce1-fe57-41e6-8919-4f1859b89f91.jsonl

@@ -1 +1,2 @@
 {"tstamp": 1723753523.5083, "task_type": "retrieval", "type": "leftvote", "models": ["", ""], "ip": "", "0_conv_id": "b14193e665104bc4b30c0a458d9b7246", "0_model_name": "BAAI/bge-large-en-v1.5", "0_prompt": "are boxer engines hard to work on?", "0_output": [["are boxer engines hard to work on?", "Stackoverflow Stackexchange\n\nQ: Boxer semantic parser download I was curious if anyone knew of a separate repository (or if you have your own version or a C&C tool login that I could use) of the Boxer semantic parser? I'm trying to download this from the developer's website (http://svn.ask.it.usyd.edu.au/trac/candc/wiki/Installation) but everytime I register, it says that 1) there's an error with my registration but I don't know what else to fill or 2) it leads to me a page where it says script failed..\nAnyways, let me know what you all think. I wasn't sure which forum to post this on (this could also fall under the software recommendations, open source stackexchange sites, and many others) so I apologize if this is in the wrong site. Thanks.\n\nA: I too, was not able to download the source files from the link. I got in touch with Dr. Valerio Basile. He pointed me to his github repository (https://github.com/valeriobasile/learningbyreading). Check out the ext/candc folder under it. You can get the source files of C&C and Boxer form there.\n"]], "0_corpus": "stackexchange", "1_conv_id": "594fd72b72774c0cac4a9b8631687431", "1_model_name": "jinaai/jina-embeddings-v2-base-en", "1_prompt": "are boxer engines hard to work on?", "1_output": [["are boxer engines hard to work on?", "Stackoverflow Stackexchange\n\nQ: How to find Xpath? is there any easy way to find xpath ?\n<span class=\"r5\">5</span><a href=\"http://google.com\">Google</a>\n\nwhat will be the xpath of r5 ?\nThanks..\n\nA: span[@class='r5']\n"]], "1_corpus": "stackexchange"}
+{"tstamp": 1723791388.0058, "task_type": "retrieval", "type": "tievote", "models": ["", ""], "ip": "", "0_conv_id": "662f485da4de41c982f0d841cd30746c", "0_model_name": "intfloat/e5-mistral-7b-instruct", "0_prompt": "Which test was devised to determine whether robots can think?", "0_output": [["Which test was devised to determine whether robots can think?", "Turing test\n\nThe Turing test, originally called the imitation game by Alan Turing in 1950, is a test of a machine's ability to exhibit intelligent behaviour equivalent to, or indistinguishable from, that of a human. Turing proposed that a human evaluator would judge natural language conversations between a human and a machine designed to generate human-like responses. The evaluator would be aware that one of the two partners in conversation was a machine, and all participants would be separated from one another. The conversation would be limited to a text-only channel, such as a computer keyboard and screen, so the result would not depend on the machine's ability to render words as speech. If the evaluator could not reliably tell the machine from the human, the machine would be said to have passed the test. The test results would not depend on the machine's ability to give correct answers to questions, only on how closely its answers resembled those a human would give. Since the Turing test is a test of indistinguishability in performance capacity, the verbal version generalizes naturally to all of human performance capacity, verbal as well as nonverbal (robotic)."]], "0_corpus": "wikipedia", "1_conv_id": "3970f00f0b604f659ba5151b6d889559", "1_model_name": "Salesforce/SFR-Embedding-2_R", "1_prompt": "Which test was devised to determine whether robots can think?", "1_output": [["Which test was devised to determine whether robots can think?", "Turing test\n\nThe Turing test, originally called the imitation game by Alan Turing in 1950, is a test of a machine's ability to exhibit intelligent behaviour equivalent to, or indistinguishable from, that of a human. Turing proposed that a human evaluator would judge natural language conversations between a human and a machine designed to generate human-like responses. The evaluator would be aware that one of the two partners in conversation was a machine, and all participants would be separated from one another. The conversation would be limited to a text-only channel, such as a computer keyboard and screen, so the result would not depend on the machine's ability to render words as speech. If the evaluator could not reliably tell the machine from the human, the machine would be said to have passed the test. The test results would not depend on the machine's ability to give correct answers to questions, only on how closely its answers resembled those a human would give. Since the Turing test is a test of indistinguishability in performance capacity, the verbal version generalizes naturally to all of human performance capacity, verbal as well as nonverbal (robotic)."]], "1_corpus": "wikipedia"}

data/retrieval_individual-112c1ce1-fe57-41e6-8919-4f1859b89f91.jsonl

@@ -18,3 +18,5 @@
 {"tstamp": 1723771194.3153, "task_type": "retrieval", "type": "chat", "model": "BM25", "gen_params": {}, "start": 1723771194.116, "finish": 1723771194.3153, "ip": "", "conv_id": "7ff8b3884a7f4436ab8adb972c8625dd", "model_name": "BM25", "prompt": "西新潟中央病院の院長", "output": [["西新潟中央病院の院長", "List of Desert Island Discs episodes\n\nThe BBC Radio 4 programme Desert Island Discs invites castaways to choose eight pieces of music, a book (in addition to the Bible – or a religious text appropriate to that person's beliefs – and the Complete Works of Shakespeare) and a luxury item that they would take to an imaginary desert island, where they will be marooned indefinitely. The rules state that the chosen luxury item must not be anything animate or indeed anything that enables the castaway to escape from the island, for instance a radio set, sailing yacht or aeroplane. The choices of book and luxury can sometimes give insight into the guest's life, and the choices of guests are listed here."]], "corpus": "wikipedia"}
 {"tstamp": 1723790306.8291, "task_type": "retrieval", "type": "chat", "model": "nomic-ai/nomic-embed-text-v1.5", "gen_params": {}, "start": 1723790306.5127, "finish": 1723790306.8291, "ip": "", "conv_id": "ddf630809c204474b13b2b8a29068af0", "model_name": "nomic-ai/nomic-embed-text-v1.5", "prompt": "Which test was devised to determine whether robots can think?", "output": [["Which test was devised to determine whether robots can think?", "Turing test\n\nThe Turing test, originally called the imitation game by Alan Turing in 1950, is a test of a machine's ability to exhibit intelligent behaviour equivalent to, or indistinguishable from, that of a human. Turing proposed that a human evaluator would judge natural language conversations between a human and a machine designed to generate human-like responses. The evaluator would be aware that one of the two partners in conversation was a machine, and all participants would be separated from one another. The conversation would be limited to a text-only channel, such as a computer keyboard and screen, so the result would not depend on the machine's ability to render words as speech. If the evaluator could not reliably tell the machine from the human, the machine would be said to have passed the test. The test results would not depend on the machine's ability to give correct answers to questions, only on how closely its answers resembled those a human would give. Since the Turing test is a test of indistinguishability in performance capacity, the verbal version generalizes naturally to all of human performance capacity, verbal as well as nonverbal (robotic)."]], "corpus": "wikipedia"}
 {"tstamp": 1723790306.8291, "task_type": "retrieval", "type": "chat", "model": "Salesforce/SFR-Embedding-2_R", "gen_params": {}, "start": 1723790306.5127, "finish": 1723790306.8291, "ip": "", "conv_id": "f0e372accad042f689ee55ed61777ffb", "model_name": "Salesforce/SFR-Embedding-2_R", "prompt": "Which test was devised to determine whether robots can think?", "output": [["Which test was devised to determine whether robots can think?", "Turing test\n\nThe Turing test, originally called the imitation game by Alan Turing in 1950, is a test of a machine's ability to exhibit intelligent behaviour equivalent to, or indistinguishable from, that of a human. Turing proposed that a human evaluator would judge natural language conversations between a human and a machine designed to generate human-like responses. The evaluator would be aware that one of the two partners in conversation was a machine, and all participants would be separated from one another. The conversation would be limited to a text-only channel, such as a computer keyboard and screen, so the result would not depend on the machine's ability to render words as speech. If the evaluator could not reliably tell the machine from the human, the machine would be said to have passed the test. The test results would not depend on the machine's ability to give correct answers to questions, only on how closely its answers resembled those a human would give. Since the Turing test is a test of indistinguishability in performance capacity, the verbal version generalizes naturally to all of human performance capacity, verbal as well as nonverbal (robotic)."]], "corpus": "wikipedia"}
+{"tstamp": 1723791377.5674, "task_type": "retrieval", "type": "chat", "model": "intfloat/e5-mistral-7b-instruct", "gen_params": {}, "start": 1723791377.1803, "finish": 1723791377.5674, "ip": "", "conv_id": "662f485da4de41c982f0d841cd30746c", "model_name": "intfloat/e5-mistral-7b-instruct", "prompt": "Which test was devised to determine whether robots can think?", "output": [["Which test was devised to determine whether robots can think?", "Turing test\n\nThe Turing test, originally called the imitation game by Alan Turing in 1950, is a test of a machine's ability to exhibit intelligent behaviour equivalent to, or indistinguishable from, that of a human. Turing proposed that a human evaluator would judge natural language conversations between a human and a machine designed to generate human-like responses. The evaluator would be aware that one of the two partners in conversation was a machine, and all participants would be separated from one another. The conversation would be limited to a text-only channel, such as a computer keyboard and screen, so the result would not depend on the machine's ability to render words as speech. If the evaluator could not reliably tell the machine from the human, the machine would be said to have passed the test. The test results would not depend on the machine's ability to give correct answers to questions, only on how closely its answers resembled those a human would give. Since the Turing test is a test of indistinguishability in performance capacity, the verbal version generalizes naturally to all of human performance capacity, verbal as well as nonverbal (robotic)."]], "corpus": "wikipedia"}
+{"tstamp": 1723791377.5674, "task_type": "retrieval", "type": "chat", "model": "Salesforce/SFR-Embedding-2_R", "gen_params": {}, "start": 1723791377.1803, "finish": 1723791377.5674, "ip": "", "conv_id": "3970f00f0b604f659ba5151b6d889559", "model_name": "Salesforce/SFR-Embedding-2_R", "prompt": "Which test was devised to determine whether robots can think?", "output": [["Which test was devised to determine whether robots can think?", "Turing test\n\nThe Turing test, originally called the imitation game by Alan Turing in 1950, is a test of a machine's ability to exhibit intelligent behaviour equivalent to, or indistinguishable from, that of a human. Turing proposed that a human evaluator would judge natural language conversations between a human and a machine designed to generate human-like responses. The evaluator would be aware that one of the two partners in conversation was a machine, and all participants would be separated from one another. The conversation would be limited to a text-only channel, such as a computer keyboard and screen, so the result would not depend on the machine's ability to render words as speech. If the evaluator could not reliably tell the machine from the human, the machine would be said to have passed the test. The test results would not depend on the machine's ability to give correct answers to questions, only on how closely its answers resembled those a human would give. Since the Turing test is a test of indistinguishability in performance capacity, the verbal version generalizes naturally to all of human performance capacity, verbal as well as nonverbal (robotic)."]], "corpus": "wikipedia"}