diff --git "a/README.md" "b/README.md" new file mode 100644--- /dev/null +++ "b/README.md" @@ -0,0 +1,835 @@ +--- +language: +- en +tags: +- sentence-transformers +- sentence-similarity +- feature-extraction +- dense +- generated_from_trainer +- dataset_size:4469886 +- loss:AnglELoss +- loss:CoSENTLoss +- loss:CachedMultipleNegativesRankingLoss +base_model: jhu-clsp/ettin-encoder-32m +widget: +- source_sentence: are finn and princess bubblegum dating? + sentences: + - In "Wizard Battle," Finn gets a kiss from Princess Bubblegum again (her last to + date) after winning the Wizard Battle. ... In "In Your Footsteps," Jake says that + Princess Bubblegum was his ex-girlfriend, but Finn replies "we never went steady." + - Jack Dylan Grazer Is Dating Finn Wolfhard According To Wikipedia. It was for a + total of 14 minutes before the troll edit was taken down by an eagle-eyed fan. + - Personal life. In January 2014, she dated Nollywood actor Jim Iyke. On 21 March + 2014, Jim Iyke proposed to Buari. She is a mother of twin girls but Jim Iyke is + not the father. + - At one point, Sonic and Amy start dating but their relationship doesn't last long + (in fact it's shorter than most of Sonic's relationships) and it turns back into + the one-sided relationship it used to be. + - Finneas is the older sibling. Billie is 17 and Finneas is turning 22-years-old + in just a few days. He was born on July 20, 1997. Finneas has described his family + as close-knit before, so we can probably assume that Billie and him are pretty + tight. + - “Hello, Bonnibel” This is the earliest episode on the list and it's the first + time we see Marceline and Bubblegum share the screen. It's couples night in the + Land of Ooo and Finn is trying to ask Princess Bubblegum out on a date. Naturally, + he and Jake turn to their vampire friend Marceline for advice. +- source_sentence: The joint management of the memorial by the United States Navy + and the National Park Service was founded on 9 September 1980 . + sentences: + - 'For example , in JavaScript the factorial function can be defined via such recursion + as anonymous :' + - The expansion of China Airlines political presence has long been limited by the + international status of Taiwan . + - The joint administration of the memorial by the National Park Service and the + United States Navy was established on September 9 , 1980 . +- source_sentence: A man is playing the piano. + sentences: + - A woman is playing a guitar on streets. + - A man puts pieces of meat into a plastic bag. + - A woman is playing the violin. +- source_sentence: A person peels shrimp. + sentences: + - The lady peeled the shrimp. + - Two women are sitting close to each other and talking. + - A woman is dancing in the street. +- source_sentence: can you grow italian cypress in pots + sentences: + - Pots and Soil. Container size depends on the size of an Italian cypress at planting. + A good rule of thumb is to use a container that is 2 inches larger in diameter + than the nursery pot in which the tree grows. As the tree increases in size, repot + it in a larger container until the tree reaches the size you desire. + - BCIP-NBT Solution is a 5-bromo, 4-chloro, 3-indolylphosphate (BCIP)/Nitro-Blue + Tetrazolium (NBT) substrate, used for the localization of alkaline phosphatase + (AP) labeled probes on western, northern, southern and dot blots. + - Dwarf varieties do great as ornamentals in small pots. Larger trees are an interesting + alternative to the traditional Christmas tree. The lemon cypress does best in + a location that gets at least five hours of full sun per day. If you are going + to keep them indoors, keep the cypress near the window for maximum light. +datasets: +- google-research-datasets/paws +- nyu-mll/glue +- mwong/fever-evidence-related +- tasksource/sts-companion +- tasksource/zero-shot-label-nli +- tomaarsen/natural-questions-hard-negatives +- tomaarsen/gooaq-hard-negatives +- bclavie/msmarco-500k-triplets +- sentence-transformers/msmarco-co-condenser-margin-mse-sym-mnrl-mean-v1 +- sentence-transformers/gooaq +- sentence-transformers/natural-questions +- sentence-transformers/quora-duplicates +pipeline_tag: sentence-similarity +library_name: sentence-transformers +--- + +# SentenceTransformer based on jhu-clsp/ettin-encoder-32m + +This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [jhu-clsp/ettin-encoder-32m](https://huggingface.co/jhu-clsp/ettin-encoder-32m) on 14 datasets. It maps sentences & paragraphs to a 384-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:** [jhu-clsp/ettin-encoder-32m](https://huggingface.co/jhu-clsp/ettin-encoder-32m) +- **Maximum Sequence Length:** 512 tokens +- **Output Dimensionality:** 384 dimensions +- **Similarity Function:** Cosine Similarity +- **Training Datasets:** + - [paws/labeled_final](https://huggingface.co/datasets/paws) + - [glue/mrpc](https://huggingface.co/datasets/glue) + - [fever-evidence-related](https://huggingface.co/datasets/mwong/fever-evidence-related) + - [glue/stsb](https://huggingface.co/datasets/glue) + - sick/relatedness + - [sts-companion](https://huggingface.co/datasets/tasksource/sts-companion) + - [zero-shot-label-nli](https://huggingface.co/datasets/tasksource/zero-shot-label-nli) + - [tomaarsen/natural-questions-hard-negatives](https://huggingface.co/datasets/tomaarsen/natural-questions-hard-negatives) + - [tomaarsen/gooaq-hard-negatives](https://huggingface.co/datasets/tomaarsen/gooaq-hard-negatives) + - [bclavie/msmarco-500k-triplets](https://huggingface.co/datasets/bclavie/msmarco-500k-triplets) + - [sentence-transformers/msmarco-co-condenser-margin-mse-sym-mnrl-mean-v1](https://huggingface.co/datasets/sentence-transformers/msmarco-co-condenser-margin-mse-sym-mnrl-mean-v1) + - [sentence-transformers/gooaq](https://huggingface.co/datasets/sentence-transformers/gooaq) + - [sentence-transformers/natural-questions](https://huggingface.co/datasets/sentence-transformers/natural-questions) + - [sentence-transformers/quora-duplicates](https://huggingface.co/datasets/sentence-transformers/quora-duplicates) +- **Language:** en + + +### Model Sources + +- **Documentation:** [Sentence Transformers Documentation](https://sbert.net) +- **Repository:** [Sentence Transformers on GitHub](https://github.com/huggingface/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': 512, 'do_lower_case': False, 'architecture': 'ModernBertModel'}) + (1): Pooling({'word_embedding_dimension': 384, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': True, '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("tasksource/ettin-32m-embed") +# Run inference +queries = [ + "can you grow italian cypress in pots", +] +documents = [ + 'Pots and Soil. Container size depends on the size of an Italian cypress at planting. A good rule of thumb is to use a container that is 2 inches larger in diameter than the nursery pot in which the tree grows. As the tree increases in size, repot it in a larger container until the tree reaches the size you desire.', + 'Dwarf varieties do great as ornamentals in small pots. Larger trees are an interesting alternative to the traditional Christmas tree. The lemon cypress does best in a location that gets at least five hours of full sun per day. If you are going to keep them indoors, keep the cypress near the window for maximum light.', + 'BCIP-NBT Solution is a 5-bromo, 4-chloro, 3-indolylphosphate (BCIP)/Nitro-Blue Tetrazolium (NBT) substrate, used for the localization of alkaline phosphatase (AP) labeled probes on western, northern, southern and dot blots.', +] +query_embeddings = model.encode_query(queries) +document_embeddings = model.encode_document(documents) +print(query_embeddings.shape, document_embeddings.shape) +# [1, 384] [3, 384] + +# Get the similarity scores for the embeddings +similarities = model.similarity(query_embeddings, document_embeddings) +print(similarities) +# tensor([[0.7291, 0.4247, 0.1270]]) +``` + + + + + + + + + + + +## Training Details + +### Training Datasets +
paws/labeled_final + +#### paws/labeled_final + +* Dataset: [paws/labeled_final](https://huggingface.co/datasets/paws) at [161ece9](https://huggingface.co/datasets/paws/tree/161ece9501cf0a11f3e48bd356eaa82de46d6a09) +* Size: 49,401 training samples +* Columns: sentence1, sentence2, and label +* Approximate statistics based on the first 1000 samples: + | | sentence1 | sentence2 | label | + |:--------|:-----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:------------------------------------------------| + | type | string | string | int | + | details | | | | +* Samples: + | sentence1 | sentence2 | label | + |:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------| + | In Paris , in October 1560 , he secretly met the English ambassador , Nicolas Throckmorton , asking him for a passport to return to England through Scotland . | In October 1560 , he secretly met with the English ambassador , Nicolas Throckmorton , in Paris , and asked him for a passport to return to Scotland through England . | 0 | + | The NBA season of 1975 -- 76 was the 30th season of the National Basketball Association . | The 1975 -- 76 season of the National Basketball Association was the 30th season of the NBA . | 1 | + | There are also specific discussions , public profile debates and project discussions . | There are also public discussions , profile specific discussions , and project discussions . | 0 | +* Loss: [AnglELoss](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#angleloss) with these parameters: + ```json + { + "scale": 20.0, + "similarity_fct": "pairwise_angle_sim" + } + ``` +
+
glue/mrpc + +#### glue/mrpc + +* Dataset: [glue/mrpc](https://huggingface.co/datasets/glue) at [bcdcba7](https://huggingface.co/datasets/glue/tree/bcdcba79d07bc864c1c254ccfcedcce55bcc9a8c) +* Size: 3,668 training samples +* Columns: sentence1, sentence2, and label +* Approximate statistics based on the first 1000 samples: + | | sentence1 | sentence2 | label | + |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:------------------------------------------------| + | type | string | string | int | + | details | | | | +* Samples: + | sentence1 | sentence2 | label | + |:-----------------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------------------|:---------------| + | Amrozi accused his brother , whom he called " the witness " , of deliberately distorting his evidence . | Referring to him as only " the witness " , Amrozi accused his brother of deliberately distorting his evidence . | 1 | + | Yucaipa owned Dominick 's before selling the chain to Safeway in 1998 for $ 2.5 billion . | Yucaipa bought Dominick 's in 1995 for $ 693 million and sold it to Safeway for $ 1.8 billion in 1998 . | 0 | + | They had published an advertisement on the Internet on June 10 , offering the cargo for sale , he added . | On June 10 , the ship 's owners had published an advertisement on the Internet , offering the explosives for sale . | 1 | +* Loss: [AnglELoss](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#angleloss) with these parameters: + ```json + { + "scale": 20.0, + "similarity_fct": "pairwise_angle_sim" + } + ``` +
+
fever-evidence-related + +#### fever-evidence-related + +* Dataset: [fever-evidence-related](https://huggingface.co/datasets/mwong/fever-evidence-related) at [14aba00](https://huggingface.co/datasets/mwong/fever-evidence-related/tree/14aba009b5fcd97b1a9ee6f3e3b0da0e308cf7cb) +* Size: 403,218 training samples +* Columns: sentence1, sentence2, and label +* Approximate statistics based on the first 1000 samples: + | | sentence1 | sentence2 | label | + |:--------|:----------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:------------------------------------------------| + | type | string | string | int | + | details | | | | +* Samples: + | sentence1 | sentence2 | label | + |:-----------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------| + | Nikolaj Coster-Waldau worked with the Fox Broadcasting Company. | Nikolaj Coster-Waldau -LRB- -LSB- neɡolaɪ kʰʌsdɐ ˈʋaldɑʊ -RSB- ; born 27 July 1970 -RRB- is a Danish actor , producer and screenwriter .. He graduated from Danish National School of Theatre in Copenhagen in 1993 .. Danish National School of Theatre. Danish National School of Theatre and Contemporary Dance. Copenhagen. Copenhagen. Coster-Waldau 's breakthrough performance in Denmark was his role in the film Nightwatch -LRB- 1994 -RRB- .. Nightwatch. Nightwatch ( 1994 film ). Since then he has appeared in numerous films in his native Scandinavia and Europe in general , including Headhunters -LRB- 2011 -RRB- and A Thousand Times Good Night -LRB- 2013 -RRB- .. Headhunters. Headhunters ( film ). A Thousand Times Good Night. A Thousand Times Good Night. In the United States , his debut film role was in the war film Black Hawk Down -LRB- 2001 -RRB- , playing Medal of Honor recipient Gary Gordon .. Black Hawk Down. Black Hawk Down ( film ). Gary Gordon. Gary Gordon. He then played Detective Jo... | 0 | + | Nikolaj Coster-Waldau worked with the Fox Broadcasting Company. | Majboor -LRB- Hindi : मजबर , English : Compulsed -RRB- is a 1974 Indian Hindi crime-thriller film directed by Ravi Tandon .. Ravi Tandon. Ravi Tandon. Hindi. Hindi. crime. crime film. thriller film. thriller film. Music is by Laxmikant Pyarelal and lyrics by Anand Bakshi .. Laxmikant Pyarelal. Laxmikant Pyarelal. Anand Bakshi. Anand Bakshi. The film was written by Salim-Javed .. Salim-Javed. Salim-Javed. The movie stars Amitabh Bachchan , Parveen Babi , Pran , Madan Puri , Rehman and Farida Jalal .. Amitabh Bachchan. Amitabh Bachchan. Parveen Babi. Parveen Babi. Pran. Pran ( actor ). Farida Jalal. Farida Jalal. Madan Puri. Madan Puri. Rehman. Rehman ( actor ). It is a remake of an American film titled Zig Zag -LRB- 1970 film -RRB- starring George Kennedy The film was later remade in Telugu by director K. Raghavendra Rao as Raja -LRB- 1976 -RRB- starring Shobhan Babu and Jayasudha .. George Kennedy. George Kennedy. Telugu. Telugu language. K. Raghavendra Rao. K. Raghavendra Rao. Raja.... | 1 | + | Nikolaj Coster-Waldau worked with the Fox Broadcasting Company. | The small snakehead ' -LRB- Channa asiatica -RRB- is a species of snakehead .. Channa. Channa. snakehead. Channidae. It is one of four species of the genus Channa '' native to China .. Channa. Channa. China. China. It also can be found in Taiwan and southern Japan , to which it migrated -LRB- or was introduced -RRB- .. Taiwan. Taiwan. Japan. Japan. It is a medium-sized snakehead which is a nestbuilder -LRB- as opposed to the Indian mouthbrooder dwarf snakeheads -RRB- .. snakehead. Channidae. mouthbrooder. mouthbrooder | 1 | +* Loss: [AnglELoss](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#angleloss) with these parameters: + ```json + { + "scale": 20.0, + "similarity_fct": "pairwise_angle_sim" + } + ``` +
+
glue/stsb + +#### glue/stsb + +* Dataset: [glue/stsb](https://huggingface.co/datasets/glue) at [bcdcba7](https://huggingface.co/datasets/glue/tree/bcdcba79d07bc864c1c254ccfcedcce55bcc9a8c) +* Size: 5,749 training samples +* Columns: sentence1, sentence2, and label +* Approximate statistics based on the first 1000 samples: + | | sentence1 | sentence2 | label | + |:--------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:---------------------------------------------------------------| + | type | string | string | float | + | details | | | | +* Samples: + | sentence1 | sentence2 | label | + |:-----------------------------------------------------------|:----------------------------------------------------------------------|:-------------------------------| + | A plane is taking off. | An air plane is taking off. | 5.0 | + | A man is playing a large flute. | A man is playing a flute. | 3.799999952316284 | + | A man is spreading shreded cheese on a pizza. | A man is spreading shredded cheese on an uncooked pizza. | 3.799999952316284 | +* Loss: [CoSENTLoss](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#cosentloss) with these parameters: + ```json + { + "scale": 20.0, + "similarity_fct": "pairwise_cos_sim" + } + ``` +
+
sick/relatedness + +#### sick/relatedness + +* Dataset: sick/relatedness +* Size: 4,439 training samples +* Columns: sentence1, sentence2, and label +* Approximate statistics based on the first 1000 samples: + | | sentence1 | sentence2 | label | + |:--------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:---------------------------------------------------------------| + | type | string | string | float | + | details | | | | +* Samples: + | sentence1 | sentence2 | label | + |:--------------------------------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------------------|:-------------------------------| + | A group of kids is playing in a yard and an old man is standing in the background | A group of boys in a yard is playing and a man is standing in the background | 4.5 | + | A group of children is playing in the house and there is no man standing in the background | A group of kids is playing in a yard and an old man is standing in the background | 3.200000047683716 | + | The young boys are playing outdoors and the man is smiling nearby | The kids are playing outdoors near a man with a smile | 4.699999809265137 | +* Loss: [CoSENTLoss](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#cosentloss) with these parameters: + ```json + { + "scale": 20.0, + "similarity_fct": "pairwise_cos_sim" + } + ``` +
+
sts-companion + +#### sts-companion + +* Dataset: [sts-companion](https://huggingface.co/datasets/tasksource/sts-companion) at [fd8beff](https://huggingface.co/datasets/tasksource/sts-companion/tree/fd8beffb788df5f6673bc688e6dcbe3690a3acc6) +* Size: 4,760 training samples +* Columns: label, sentence1, and sentence2 +* Approximate statistics based on the first 1000 samples: + | | label | sentence1 | sentence2 | + |:--------|:---------------------------------------------------------------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| + | type | float | string | string | + | details | | | | +* Samples: + | label | sentence1 | sentence2 | + |:-----------------|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------| + | 1.6 | this lus in this frame refer to biological entities labeled by the fe organism. an organism is described as something that can be alive, or have naturally occuring biological processes and functions, however the concept of life is often used metaphorically for non-organic entities which resemble or act as if they have organic life. | living things collectively; | + | 3.8 | Washington's Economic Boom, Financed by You Real life "Hunger Games" | Washington?s Economic Boom, Financed by You | + | 4.4 | Knowledge of foreign languages is accepted as a necessary precursor to mobility. | It is accepted that knowledge of foreign languages is a necessary precondition to mobility. | +* Loss: [CoSENTLoss](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#cosentloss) with these parameters: + ```json + { + "scale": 20.0, + "similarity_fct": "pairwise_cos_sim" + } + ``` +
+
zero-shot-label-nli + +#### zero-shot-label-nli + +* Dataset: [zero-shot-label-nli](https://huggingface.co/datasets/tasksource/zero-shot-label-nli) at [ee693db](https://huggingface.co/datasets/tasksource/zero-shot-label-nli/tree/ee693dba923b5d5484aa9232b7357c5e45dd39b8) +* Size: 800,000 training samples +* Columns: label, sentence1, and sentence2 +* Approximate statistics based on the first 1000 samples: + | | label | sentence1 | sentence2 | + |:--------|:------------------------------------------------|:-----------------------------------------------------------------------------------|:---------------------------------------------------------------------------------| + | type | int | string | string | + | details | | | | +* Samples: + | label | sentence1 | sentence2 | + |:---------------|:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:--------------------------------------------| + | 0 | How can you build website like Facebook?
How do you make a site like Facebook? | This example is not_duplicate. | + | 0 | Warren Buffet was born on August 30 , 1932 .
Warren Edward Buffett -LRB- -LSB- ˈbʌfᵻt -RSB- born August 30 , 1930 -RRB- is an American business magnate , investor , and philanthropist . | This example is SUPPORTS. | + | 0 | raise : Raise a siege. :
raise : The President raised several million dollars for his college. : | This example is True. | +* Loss: [AnglELoss](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#angleloss) with these parameters: + ```json + { + "scale": 20.0, + "similarity_fct": "pairwise_angle_sim" + } + ``` +
+
tomaarsen/natural-questions-hard-negatives + +#### tomaarsen/natural-questions-hard-negatives + +* Dataset: [tomaarsen/natural-questions-hard-negatives](https://huggingface.co/datasets/tomaarsen/natural-questions-hard-negatives) at [52dfa09](https://huggingface.co/datasets/tomaarsen/natural-questions-hard-negatives/tree/52dfa09a3d5d3f90e7e115c407ccebe30fe79764) +* Size: 96,658 training samples +* Columns: query, answer, negative_1, negative_2, negative_3, negative_4, and negative_5 +* Approximate statistics based on the first 1000 samples: + | | query | answer | negative_1 | negative_2 | negative_3 | negative_4 | negative_5 | + |:--------|:-----------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| + | type | string | string | string | string | string | string | string | + | details | | | | | | | | +* Samples: + | query | answer | negative_1 | negative_2 | negative_3 | negative_4 | negative_5 | + |:----------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| + | when did richmond last play in a preliminary final | Richmond Football Club Richmond began 2017 with 5 straight wins, a feat it had not achieved since 1995. A series of close losses hampered the Tigers throughout the middle of the season, including a 5-point loss to the Western Bulldogs, 2-point loss to Fremantle, and a 3-point loss to the Giants. Richmond ended the season strongly with convincing victories over Fremantle and St Kilda in the final two rounds, elevating the club to 3rd on the ladder. Richmond's first final of the season against the Cats at the MCG attracted a record qualifying final crowd of 95,028; the Tigers won by 51 points. Having advanced to the first preliminary finals for the first time since 2001, Richmond defeated Greater Western Sydney by 36 points in front of a crowd of 94,258 to progress to the Grand Final against Adelaide, their first Grand Final appearance since 1982. The attendance was 100,021, the largest crowd to a grand final since 1986. The Crows led at quarter time and led by as many as 13, but the Tig... | Brisbane Bears However, the club was still struggling off-field. One of the Bears' biggest problems was its lack of support (both on and off the field) in Melbourne, the location of most of its away matches. In mid-1996, the struggling Fitzroy Football Club collapsed due to financial pressures and was seeking to merge its assets with another club. When a merger with North Melbourne in forming the North Fitzroy Kangaroos failed to win the support of the other AFL clubs, a deal for a merger was done between Fitzroy and the Bears. The new team was known as the Brisbane Lions, based at the Gabba, with Northey as the coach of the merged club. As such, the history of the Brisbane Bears as an individual entity ended after the 1996 season, with ten seasons of competition and the third-place finish in 1996 as its best performance. The Bears last match as a separate entity was a preliminary final on Saturday 21 September 1996 at the Melbourne Cricket Ground (where the Bears played their first VF... | Virginia Tech–West Virginia football rivalry Virginia Tech held the trophy in six of the nine years in which it was contested, but West Virginia leads the all-time series 28–23–1. The last game was played on September 3, 2017 at FedEx Field in Landover, MD; Virginia Tech won 31–24. | Martin Truex Jr. To start off the Round of 12, Truex scored his 6th win of the season at Charlotte after leading 91 out of 334 laps to secure a spot for the Round of 8. Just two weeks later, he scored another win at Kansas despite having a restart violation early in the race. | Adelaide Football Club Star midfielder for many years Patrick Dangerfield left the club at the end of the 2015 season (a season in which he won the club's best and fairest) and Don Pyke, a former premiership player and assistant coach with West Coast who had also been an assistant coach at Adelaide from 2005 to 2006, was appointed Adelaide's senior coach for at least three years.[9] Adelaide was widely tipped to slide out of the finals in 2016[27][28][29] but the Crows proved to be one of the successes of the season, comfortably qualifying for a home elimination final and defeating North Melbourne by 62 points, before being eliminated the next week by eventual beaten grand finalists, Sydney in the semi-finals. The club had a dominant 2017 season, winning their opening six games and never falling below second place for the entire season. Adelaide claimed their second McClelland Trophy as minor premiers.[30] The Adelaide Crows entered the 2017 finals series as favourites for the premiers... | Battle of Appomattox Court House The Battle of Appomattox Court House (Virginia, U.S.), fought on the morning of April 9, 1865, was one of the last battles of the American Civil War (1861–1865). It was the final engagement of Confederate States Army General-in-Chief, Robert E. Lee, and his Army of Northern Virginia before it surrendered to the Union Army of the Potomac under the Commanding General of the United States, Ulysses S. Grant. Lee, having abandoned the Confederate capital of Richmond, Virginia, after the nine and one-half month Siege of Petersburg and Richmond, retreated west, hoping to join his army with the remaining Confederate forces in North Carolina, the Army of Tennessee under Gen. Joseph E. Johnston. Union infantry and cavalry forces under Gen. Philip Sheridan pursued and cut off the Confederates' retreat at the central Virginia village of Appomattox Court House. Lee launched a last-ditch attack to break through the Union forces to his front, assuming the Union forc... | + | who sang what in the world's come over you | Jack Scott (singer) At the beginning of 1960, Scott again changed record labels, this time to Top Rank Records.[1] He then recorded four Billboard Hot 100 hits – "What in the World's Come Over You" (#5), "Burning Bridges" (#3) b/w "Oh Little One" (#34), and "It Only Happened Yesterday" (#38).[1] "What in the World's Come Over You" was Scott's second gold disc winner.[6] Scott continued to record and perform during the 1960s and 1970s.[1] His song "You're Just Gettin' Better" reached the country charts in 1974.[1] In May 1977, Scott recorded a Peel session for BBC Radio 1 disc jockey, John Peel. | Lover, You Should've Come Over "Lover, You Should've Come Over" is the seventh track on Jeff Buckley's album Grace. Inspired by the ending of the relationship between Buckley and Rebecca Moore,[1] it concerns the despondency of a young man growing older, finding that his actions represent a perspective he feels that he should have outgrown. Biographer and critic David Browne describes the lyrics as "confused and confusing" and the music as "a languid beauty."[1] | It's Christmas (All Over The World) "It's Christmas (All Over The World)" is a song recorded by Scottish singer Sheena Easton. It was released in November 1985 as the theme song from the soundtrack of Santa Claus: The Movie. The song was written by Bill House and John Hobbs. | The End of the World (Skeeter Davis song) "The End of the World" is a country pop song written by Arthur Kent and Sylvia Dee, for American singer Skeeter Davis. It had success in the 1960s and spawned many covers. | Israel Kamakawiwoʻole His voice became famous outside Hawaii when his album Facing Future was released in 1993. His medley of "Somewhere Over the Rainbow/What a Wonderful World" was released on his albums Ka ʻAnoʻi and Facing Future. It was subsequently featured in several films, television programs, and television commercials. | Make the World Go Away "Make the World Go Away'" is a country-popular music song composed by Hank Cochran. It has become a Top 40 popular success three times: for Timi Yuro (during 1963), for Eddy Arnold (1965), and for the brother-sister duo Donny and Marie Osmond (1975). The original version of the song was recorded by Ray Price during 1963. It has remained a country crooner standard ever since. | + | who produces the most wool in the world | Wool Global wool production is about 2 million tonnes per year, of which 60% goes into apparel. Wool comprises ca 3% of the global textile market, but its value is higher owing to dying and other modifications of the material.[1] Australia is a leading producer of wool which is mostly from Merino sheep but has been eclipsed by China in terms of total weight.[30] New Zealand (2016) is the third-largest producer of wool, and the largest producer of crossbred wool. Breeds such as Lincoln, Romney, Drysdale, and Elliotdale produce coarser fibers, and wool from these sheep is usually used for making carpets. | Baa, Baa, Black Sheep As with many nursery rhymes, attempts have been made to find origins and meanings for the rhyme, most which have no corroborating evidence.[1] Katherine Elwes Thomas in The Real Personages of Mother Goose (1930) suggested that the rhyme referred to resentment at the heavy taxation on wool.[5] This has particularly been taken to refer to the medieval English "Great" or "Old Custom" wool tax of 1275, which survived until the fifteenth century.[1] More recently the rhyme has been connected to the slave trade, particularly in the southern United States.[6] This explanation was advanced during debates over political correctness and the use and reform of nursery rhymes in the 1980s, but has no supporting historical evidence.[7] Rather than being negative, the wool of black sheep may have been prized as it could be made into dark cloth without dyeing.[6] | Raymond Group Raymond Group is an Indian branded fabric and fashion retailer, incorporated in 1925. It produces suiting fabric, with a capacity of producing 31 million meters of wool and wool-blended fabrics. Gautam Singhania is the chairman and managing director of the Raymond group.[3] | Silk in the Indian subcontinent Silk in the Indian subcontinent is a luxury good. In India, about 97% of the raw mulberry silk is produced in the five Indian states of Karnataka, Andhra Pradesh, Tamil Nadu, West Bengal and Jammu and Kashmir.[1] Mysore and North Bangalore, the upcoming site of a US$20 million "Silk City", contribute to a majority of silk production.[2] Another emerging silk producer is Tamil Nadu where mulberry cultivation is concentrated in Salem, Erode and Dharmapuri districts. Hyderabad, Andhra Pradesh and Gobichettipalayam, Tamil Nadu were the first locations to have automated silk reeling units.[3] yoyo quantity::: | F. W. Woolworth Company The two Woolworth brothers pioneered and developed merchandising, direct purchasing, sales, and customer service practices commonly used today. Despite its growing to be one of the largest retail chains in the world through most of the 20th century, increased competition led to its decline beginning in the 1980s, while its sporting goods division grew. The chain went out of business in July 1997, when the company decided to focus primarily on sporting goods and renamed itself Venator Group. By 2001, the company focused exclusively on the sporting goods market, changing its name to the present Foot Locker, Inc., changing its ticker symbol from its familiar Z in 2003 to its present ticker (NYSE: FL). | Silk Silk's absorbency makes it comfortable to wear in warm weather and while active. Its low conductivity keeps warm air close to the skin during cold weather. It is often used for clothing such as shirts, ties, blouses, formal dresses, high fashion clothes, lining, lingerie, pajamas, robes, dress suits, sun dresses and Eastern folk costumes. For practical use, silk is excellent as clothing that protects from many biting insects that would ordinarily pierce clothing, such as mosquitoes and horseflies. | +* Loss: [CachedMultipleNegativesRankingLoss](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#cachedmultiplenegativesrankingloss) with these parameters: + ```json + { + "scale": 20.0, + "similarity_fct": "cos_sim", + "mini_batch_size": 32, + "gather_across_devices": false + } + ``` +
+
tomaarsen/gooaq-hard-negatives + +#### tomaarsen/gooaq-hard-negatives + +* Dataset: [tomaarsen/gooaq-hard-negatives](https://huggingface.co/datasets/tomaarsen/gooaq-hard-negatives) at [87594a1](https://huggingface.co/datasets/tomaarsen/gooaq-hard-negatives/tree/87594a1e6c58e88b5843afa9da3a97ffd75d01c2) +* Size: 800,000 training samples +* Columns: question, answer, negative_1, negative_2, negative_3, negative_4, and negative_5 +* Approximate statistics based on the first 1000 samples: + | | question | answer | negative_1 | negative_2 | negative_3 | negative_4 | negative_5 | + |:--------|:----------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| + | type | string | string | string | string | string | string | string | + | details | | | | | | | | +* Samples: + | question | answer | negative_1 | negative_2 | negative_3 | negative_4 | negative_5 | + |:---------------------------------------------------|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| + | is toprol xl the same as metoprolol? | Metoprolol succinate is also known by the brand name Toprol XL. It is the extended-release form of metoprolol. Metoprolol succinate is approved to treat high blood pressure, chronic chest pain, and congestive heart failure. | Secondly, metoprolol and metoprolol ER have different brand-name equivalents: Brand version of metoprolol: Lopressor. Brand version of metoprolol ER: Toprol XL. | Pill with imprint 1 is White, Round and has been identified as Metoprolol Tartrate 25 mg. | Interactions between your drugs No interactions were found between Allergy Relief and metoprolol. This does not necessarily mean no interactions exist. Always consult your healthcare provider. | Metoprolol is a type of medication called a beta blocker. It works by relaxing blood vessels and slowing heart rate, which improves blood flow and lowers blood pressure. Metoprolol can also improve the likelihood of survival after a heart attack. | Metoprolol starts to work after about 2 hours, but it can take up to 1 week to fully take effect. You may not feel any different when you take metoprolol, but this doesn't mean it's not working. It's important to keep taking your medicine. | + | are you experienced cd steve hoffman? | The Are You Experienced album was apparently mastered from the original stereo UK master tapes (according to Steve Hoffman - one of the very few who has heard both the master tapes and the CDs produced over the years). ... The CD booklets were a little sparse, but at least they stayed true to the album's original design. | I Saw the Light. Showcasing the unique talent and musical influence of country-western artist Hank Williams, this candid biography also sheds light on the legacy of drug abuse and tormented relationships that contributes to the singer's legend. | (Read our ranking of his top 10.) And while Howard dresses the part of director, any notion of him as a tortured auteur or dictatorial taskmasker — the clichés of the Hollywood director — are tossed aside. He's very nice. | He was a music star too. Where're you people born and brought up? We 're born and brought up here in Anambra State at Nkpor town, near Onitsha. | At the age of 87 he has now retired from his live shows and all the traveling involved. And although he still picks up his Martin Guitar and does a show now and then, his life is now devoted to writing his memoirs. | The owner of the mysterious voice behind all these videos is a man who's seen a lot, visiting a total of 56 intimate celebrity spaces over the course of five years. His name is Joe Sabia — that's him in the photo — and he's currently the VP of creative development at Condé Nast Entertainment. | + | how are babushka dolls made? | Matryoshka dolls are made of wood from lime, balsa, alder, aspen, and birch trees; lime is probably the most common wood type. ... After cutting, the trees are stripped of most of their bark, although a few inner rings of bark are left to bind the wood and keep it from splitting. | A quick scan of the auction and buy-it-now listings on eBay finds porcelain doll values ranging from around $5 and $10 to several thousand dollars or more but no dolls listed above $10,000. | Japanese dolls are called as ningyō in Japanese and literally translates to 'human form'. | Matyoo: All Fresno Girl dolls come just as real children are born. | As of September 2016, there are over 100 characters. The main toy line includes 13-inch Dolls, the mini-series, and a variety of mini play-sets and plush dolls as well as Lalaloopsy Littles, smaller siblings of the 13-inch dolls. A spin-off known as "Lala-Oopsies" came out in late 2012. | LOL dolls are little baby dolls that come wrapped inside a surprise toy ball. Each ball has layers that contain stickers, secret messages, mix and match accessories–and finally–a doll. ... The doll on the ball is almost never the doll inside. Dolls are released in series, so not every doll is available all the time. | +* Loss: [CachedMultipleNegativesRankingLoss](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#cachedmultiplenegativesrankingloss) with these parameters: + ```json + { + "scale": 20.0, + "similarity_fct": "cos_sim", + "mini_batch_size": 32, + "gather_across_devices": false + } + ``` +
+
bclavie/msmarco-500k-triplets + +#### bclavie/msmarco-500k-triplets + +* Dataset: [bclavie/msmarco-500k-triplets](https://huggingface.co/datasets/bclavie/msmarco-500k-triplets) at [cb1a85c](https://huggingface.co/datasets/bclavie/msmarco-500k-triplets/tree/cb1a85c1261fa7c65f4ea43f94e50f8b467c372f) +* Size: 500,000 training samples +* Columns: query, positive, and negative +* Approximate statistics based on the first 1000 samples: + | | query | positive | negative | + |:--------|:---------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| + | type | string | string | string | + | details | | | | +* Samples: + | query | positive | negative | + |:-----------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| + | the most important factor that influences k+ secretion is __________. | The regulation of K+ distribution between the intracellular and extracellular space is referred to as internal K+ balance. The most important factors regulating this movement under normal conditions are insulin and catecholamines (1). | They are both also important for secretion and flow of bile: 1 Cholecystokinin: The name of this hormone describes its effect on the biliary system-cholecysto = gallbladder and kinin = movement. 2 Secretin: This hormone is secreted in response to acid in the duodenum. | + | how much did the mackinac bridge cost to build | The cost to design the project was $3,500,000 (Steinman Company). The cost to construct the bridge was $70, 268,500. Two primary contractors were hired to build the bridge: American Bridge for superstructure - $44,532,900; and Merritt-Chapman and Scott of New York for the foundations - $25,735,600. | When your child needs a dental tooth bridge, you need to know the average cost so you can factor the price into your budget. Several factors affect the price of a bridge, which can run between $700 to $1,500 per tooth. If you have insurance or your child is covered by Medicaid, part of the cost may be covered. | + | when do concussion symptoms appear | Then you can get advice on what to do next. For milder symptoms, the doctor may recommend rest and ask you to watch your child closely for changes, such as a headache that gets worse. Symptoms of a concussion don't always show up right away, and can develop within 24 to 72 hours after an injury. | Concussion: A traumatic injury to soft tissue, usually the brain, as a result of a violent blow, shaking, or spinning. A brain concussion can cause immediate but temporary impairment of brain functions, such as thinking, vision, equilibrium, and consciousness. After a person has had a concussion, he or she is at increased risk for recurrence. Moreover, after a person has several concussions, less of a blow can cause injury, and the person can require more time to recover. | +* Loss: [CachedMultipleNegativesRankingLoss](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#cachedmultiplenegativesrankingloss) with these parameters: + ```json + { + "scale": 20.0, + "similarity_fct": "cos_sim", + "mini_batch_size": 32, + "gather_across_devices": false + } + ``` +
+
sentence-transformers/msmarco-co-condenser-margin-mse-sym-mnrl-mean-v1 + +#### sentence-transformers/msmarco-co-condenser-margin-mse-sym-mnrl-mean-v1 + +* Dataset: [sentence-transformers/msmarco-co-condenser-margin-mse-sym-mnrl-mean-v1](https://huggingface.co/datasets/sentence-transformers/msmarco-co-condenser-margin-mse-sym-mnrl-mean-v1) at [84ed2d3](https://huggingface.co/datasets/sentence-transformers/msmarco-co-condenser-margin-mse-sym-mnrl-mean-v1/tree/84ed2d35626f617d890bd493b4d6db69a741e0e2) +* Size: 800,000 training samples +* Columns: query, positive, and negative +* Approximate statistics based on the first 1000 samples: + | | query | positive | negative | + |:--------|:---------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| + | type | string | string | string | + | details | | | | +* Samples: + | query | positive | negative | + |:----------------------------------------|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| + | what are the liberal arts? | liberal arts. 1. the academic course of instruction at a college intended to provide general knowledge and comprising the arts, humanities, natural sciences, and social sciences, as opposed to professional or technical subjects. | Rather than preparing students for a specific career, liberal arts programs focus on cultural literacy and hone communication and analytical skills. They often cover various disciplines, ranging from the humanities to social sciences. 1 Program Levels in Liberal Arts: Associate degree, Bachelor's degree, Master's degree. | + | what are the liberal arts? | liberal arts. 1. the academic course of instruction at a college intended to provide general knowledge and comprising the arts, humanities, natural sciences, and social sciences, as opposed to professional or technical subjects. | Artes Liberales: The historical basis for the modern liberal arts, consisting of the trivium (grammar, logic, and rhetoric) and the quadrivium (arithmetic, geometry, astronomy, and music). General Education: That part of a liberal education curriculum that is shared by all students. | + | what are the liberal arts? | liberal arts. 1. the academic course of instruction at a college intended to provide general knowledge and comprising the arts, humanities, natural sciences, and social sciences, as opposed to professional or technical subjects. | Liberal Arts. Upon completion of the Liberal Arts degree, students will be able to express ideas in coherent, creative, and appropriate forms, orally and in writing. Students will be able to apply their reading abilities in order to interconnect an understanding of resources to academic, professional, and personal interests. | +* Loss: [CachedMultipleNegativesRankingLoss](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#cachedmultiplenegativesrankingloss) with these parameters: + ```json + { + "scale": 20.0, + "similarity_fct": "cos_sim", + "mini_batch_size": 32, + "gather_across_devices": false + } + ``` +
+
sentence-transformers/gooaq + +#### sentence-transformers/gooaq + +* Dataset: [sentence-transformers/gooaq](https://huggingface.co/datasets/sentence-transformers/gooaq) at [b089f72](https://huggingface.co/datasets/sentence-transformers/gooaq/tree/b089f728748a068b7bc5234e5bcf5b25e3c8279c) +* Size: 800,000 training samples +* Columns: question and answer +* Approximate statistics based on the first 1000 samples: + | | question | answer | + |:--------|:----------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| + | type | string | string | + | details | | | +* Samples: + | question | answer | + |:---------------------------------------------------|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| + | is toprol xl the same as metoprolol? | Metoprolol succinate is also known by the brand name Toprol XL. It is the extended-release form of metoprolol. Metoprolol succinate is approved to treat high blood pressure, chronic chest pain, and congestive heart failure. | + | are you experienced cd steve hoffman? | The Are You Experienced album was apparently mastered from the original stereo UK master tapes (according to Steve Hoffman - one of the very few who has heard both the master tapes and the CDs produced over the years). ... The CD booklets were a little sparse, but at least they stayed true to the album's original design. | + | how are babushka dolls made? | Matryoshka dolls are made of wood from lime, balsa, alder, aspen, and birch trees; lime is probably the most common wood type. ... After cutting, the trees are stripped of most of their bark, although a few inner rings of bark are left to bind the wood and keep it from splitting. | +* Loss: [CachedMultipleNegativesRankingLoss](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#cachedmultiplenegativesrankingloss) with these parameters: + ```json + { + "scale": 20.0, + "similarity_fct": "cos_sim", + "mini_batch_size": 32, + "gather_across_devices": false + } + ``` +
+
sentence-transformers/natural-questions + +#### sentence-transformers/natural-questions + +* Dataset: [sentence-transformers/natural-questions](https://huggingface.co/datasets/sentence-transformers/natural-questions) at [f9e894e](https://huggingface.co/datasets/sentence-transformers/natural-questions/tree/f9e894e1081e206e577b4eaa9ee6de2b06ae6f17) +* Size: 100,231 training samples +* Columns: query and answer +* Approximate statistics based on the first 1000 samples: + | | query | answer | + |:--------|:-----------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| + | type | string | string | + | details | | | +* Samples: + | query | answer | + |:----------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| + | when did richmond last play in a preliminary final | Richmond Football Club Richmond began 2017 with 5 straight wins, a feat it had not achieved since 1995. A series of close losses hampered the Tigers throughout the middle of the season, including a 5-point loss to the Western Bulldogs, 2-point loss to Fremantle, and a 3-point loss to the Giants. Richmond ended the season strongly with convincing victories over Fremantle and St Kilda in the final two rounds, elevating the club to 3rd on the ladder. Richmond's first final of the season against the Cats at the MCG attracted a record qualifying final crowd of 95,028; the Tigers won by 51 points. Having advanced to the first preliminary finals for the first time since 2001, Richmond defeated Greater Western Sydney by 36 points in front of a crowd of 94,258 to progress to the Grand Final against Adelaide, their first Grand Final appearance since 1982. The attendance was 100,021, the largest crowd to a grand final since 1986. The Crows led at quarter time and led by as many as 13, but the Tig... | + | who sang what in the world's come over you | Jack Scott (singer) At the beginning of 1960, Scott again changed record labels, this time to Top Rank Records.[1] He then recorded four Billboard Hot 100 hits – "What in the World's Come Over You" (#5), "Burning Bridges" (#3) b/w "Oh Little One" (#34), and "It Only Happened Yesterday" (#38).[1] "What in the World's Come Over You" was Scott's second gold disc winner.[6] Scott continued to record and perform during the 1960s and 1970s.[1] His song "You're Just Gettin' Better" reached the country charts in 1974.[1] In May 1977, Scott recorded a Peel session for BBC Radio 1 disc jockey, John Peel. | + | who produces the most wool in the world | Wool Global wool production is about 2 million tonnes per year, of which 60% goes into apparel. Wool comprises ca 3% of the global textile market, but its value is higher owing to dying and other modifications of the material.[1] Australia is a leading producer of wool which is mostly from Merino sheep but has been eclipsed by China in terms of total weight.[30] New Zealand (2016) is the third-largest producer of wool, and the largest producer of crossbred wool. Breeds such as Lincoln, Romney, Drysdale, and Elliotdale produce coarser fibers, and wool from these sheep is usually used for making carpets. | +* Loss: [CachedMultipleNegativesRankingLoss](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#cachedmultiplenegativesrankingloss) with these parameters: + ```json + { + "scale": 20.0, + "similarity_fct": "cos_sim", + "mini_batch_size": 32, + "gather_across_devices": false + } + ``` +
+
sentence-transformers/quora-duplicates + +#### sentence-transformers/quora-duplicates + +* Dataset: [sentence-transformers/quora-duplicates](https://huggingface.co/datasets/sentence-transformers/quora-duplicates) at [451a485](https://huggingface.co/datasets/sentence-transformers/quora-duplicates/tree/451a4850bd141edb44ade1b5828c259abd762cdb) +* Size: 101,762 training samples +* Columns: anchor, positive, and negative +* Approximate statistics based on the first 1000 samples: + | | anchor | positive | negative | + |:--------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| + | type | string | string | string | + | details | | | | +* Samples: + | anchor | positive | negative | + |:--------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------------------------------------| + | Why in India do we not have one on one political debate as in USA? | Why cant we have a public debate between politicians in India like the one in US? | Can people on Quora stop India Pakistan debate? We are sick and tired seeing this everyday in bulk? | + | What is OnePlus One? | How is oneplus one? | Why is OnePlus One so good? | + | Does our mind control our emotions? | How do smart and successful people control their emotions? | How can I control my positive emotions for the people whom I love but they don't care about me? | +* Loss: [CachedMultipleNegativesRankingLoss](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#cachedmultiplenegativesrankingloss) with these parameters: + ```json + { + "scale": 20.0, + "similarity_fct": "cos_sim", + "mini_batch_size": 32, + "gather_across_devices": false + } + ``` +
+ +### Training Hyperparameters +#### Non-Default Hyperparameters + +- `per_device_train_batch_size`: 512 +- `weight_decay`: 1e-06 +- `num_train_epochs`: 2 +- `warmup_ratio`: 0.1 +- `fp16`: True +- `gradient_checkpointing`: True + +#### All Hyperparameters +
Click to expand + +- `overwrite_output_dir`: False +- `do_predict`: False +- `eval_strategy`: no +- `prediction_loss_only`: True +- `per_device_train_batch_size`: 512 +- `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`: 5e-05 +- `weight_decay`: 1e-06 +- `adam_beta1`: 0.9 +- `adam_beta2`: 0.999 +- `adam_epsilon`: 1e-08 +- `max_grad_norm`: 1.0 +- `num_train_epochs`: 2 +- `max_steps`: -1 +- `lr_scheduler_type`: linear +- `lr_scheduler_kwargs`: {} +- `warmup_ratio`: 0.1 +- `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`: True +- `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} +- `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 +- `hub_revision`: None +- `gradient_checkpointing`: True +- `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 +- `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 +- `liger_kernel_config`: None +- `eval_use_gather_object`: False +- `average_tokens_across_devices`: False +- `prompts`: None +- `batch_sampler`: batch_sampler +- `multi_dataset_batch_sampler`: proportional +- `router_mapping`: {} +- `learning_rate_mapping`: {} + +
+ +### Training Logs +| Epoch | Step | Training Loss | +|:------:|:-----:|:-------------:| +| 0.0572 | 500 | 5.9465 | +| 0.1145 | 1000 | 3.9914 | +| 0.1717 | 1500 | 3.5411 | +| 0.2289 | 2000 | 3.1609 | +| 0.2861 | 2500 | 2.9574 | +| 0.3434 | 3000 | 3.3644 | +| 0.4006 | 3500 | 3.2858 | +| 0.4578 | 4000 | 2.8112 | +| 0.5151 | 4500 | 2.8811 | +| 0.5723 | 5000 | 3.1508 | +| 0.6295 | 5500 | 3.0018 | +| 0.6867 | 6000 | 2.8756 | +| 0.7440 | 6500 | 3.3382 | +| 0.8012 | 7000 | 2.7634 | +| 0.8584 | 7500 | 3.1173 | +| 0.9156 | 8000 | 2.76 | +| 0.9729 | 8500 | 2.7867 | +| 1.0301 | 9000 | 2.9218 | +| 1.0873 | 9500 | 2.5824 | +| 1.1446 | 10000 | 2.6713 | +| 1.2018 | 10500 | 2.699 | +| 1.2590 | 11000 | 2.5318 | +| 1.3162 | 11500 | 2.7864 | +| 1.3735 | 12000 | 2.6938 | +| 1.4307 | 12500 | 2.3338 | +| 1.4879 | 13000 | 2.5586 | +| 1.5452 | 13500 | 2.2072 | +| 1.6024 | 14000 | 2.727 | +| 1.6596 | 14500 | 2.308 | +| 1.7168 | 15000 | 2.4809 | +| 1.7741 | 15500 | 2.5995 | +| 1.8313 | 16000 | 2.673 | +| 1.8885 | 16500 | 2.6192 | +| 1.9457 | 17000 | 2.8355 | + + +### Framework Versions +- Python: 3.12.10 +- Sentence Transformers: 5.1.2 +- Transformers: 4.53.2 +- PyTorch: 2.7.1+cu126 +- Accelerate: 1.7.0 +- Datasets: 3.6.0 +- Tokenizers: 0.21.1 + +## 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", +} +``` + +#### AnglELoss +```bibtex +@inproceedings{li-li-2024-aoe, + title = "{A}o{E}: Angle-optimized Embeddings for Semantic Textual Similarity", + author = "Li, Xianming and Li, Jing", + year = "2024", + publisher = "Association for Computational Linguistics", + url = "https://aclanthology.org/2024.acl-long.101/", + doi = "10.18653/v1/2024.acl-long.101" +} +``` + +#### CoSENTLoss +```bibtex +@article{10531646, + author={Huang, Xiang and Peng, Hao and Zou, Dongcheng and Liu, Zhiwei and Li, Jianxin and Liu, Kay and Wu, Jia and Su, Jianlin and Yu, Philip S.}, + journal={IEEE/ACM Transactions on Audio, Speech, and Language Processing}, + title={CoSENT: Consistent Sentence Embedding via Similarity Ranking}, + year={2024}, + doi={10.1109/TASLP.2024.3402087} +} +``` + +#### CachedMultipleNegativesRankingLoss +```bibtex +@misc{gao2021scaling, + title={Scaling Deep Contrastive Learning Batch Size under Memory Limited Setup}, + author={Luyu Gao and Yunyi Zhang and Jiawei Han and Jamie Callan}, + year={2021}, + eprint={2101.06983}, + archivePrefix={arXiv}, + primaryClass={cs.LG} +} +``` + + + + + + \ No newline at end of file