Add new SentenceTransformer model

1_Pooling/config.json

@@ -0,0 +1,10 @@
+{
+  "word_embedding_dimension": 768,
+  "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
+}

README.md

@@ -0,0 +1,636 @@
+---
+language:
+- en
+license: apache-2.0
+tags:
+- sentence-transformers
+- sentence-similarity
+- feature-extraction
+- generated_from_trainer
+- dataset_size:6433
+- loss:Infonce
+base_model: microsoft/mpnet-base
+widget:
+- source_sentence: What surprised the author about the appearance of sloths when looking
+    for animals to draw for the letter S
+  sentences:
+  - "Third National Bank may refer to:\n\nin the United States\n(by state)\nThird\
+    \ National Bank (Atlanta, Georgia), now The Metropolitan (Atlanta condominium\
+    \ building)\n Third National Bank (Glasgow, Kentucky), listed on the NRHP in Kentucky\n\
+    \ Third National Bank (Ohio), a predecessor of Fifth Third Bank\n Third National\
+    \ Bank (Syracuse, New York), listed on the NRHP in New York\n Third National Bank\
+    \ (Sandusky, Ohio), listed on the NRHP in Ohio\n Third National Bank in Nashville,\
+    \ now incorporated within SunTrust Bank"
+  - 'S is for Sloth
+
+    I never really paid much attention to sloths until I began searching for animals
+    to draw for the letter S. Looking at some photos, I was shocked to see just how
+    much they look like Muppets in real life! They''re hilarious!'
+  - 'History
+
+    The Annual Review of Animal Biosciences was first published in 2013, with Harris
+    A. Lewin and R. Michael Roberts as the founding co-editors. Though it was initially
+    published in print, as of 2021 it is only published electronically. Scope and
+    indexing
+
+    The Annual Review of Animal Biosciences defines its scope as covering significant
+    developments relevant to biotechnology, genomics, genetics, veterinary medicine,
+    animal breeding, and conservation biology. The intended audience for the journal
+    is scientists and veterinarians involved with wild and domestic animals. It is
+    abstracted and indexed in Scopus, Science Citation Index Expanded, MEDLINE, and
+    Embase, among others.'
+- source_sentence: What distinguished the roles of different prisoners, such as the
+    functionaries and the Sonderkommando, in the Auschwitz camps
+  sentences:
+  - "Michael Matthews is a South African writer, producer and director. In 2017, he\
+    \ directed Five Fingers for Marseilles, a film that won best film category at\
+    \ 14th Africa Movie Academy Awards. Early life\nMatthews was born in Durban. He\
+    \ studied filmmaking at the CityVarsity Cape Town campus. Career \nMatthews is\
+    \ the director of Five Fingers for Marseilles, a film dubbed as South African\
+    \ first western film."
+  - Warsame and Ahmed M. Hassan, who was elected to the Clarkston, Georgia City Council
+    on the same day, are the first Somali Americans to be elected to municipal offices
+    in the United States and were the highest elected Somali Americans in the country
+    at the time. Warsame's election set civic precedence in the Somali American community
+    of Minneapolis, in which his campaign energized and mobilized this sub-community's
+    powerful voting bloc.
+  - 'Designated as Aussenlager (external camp), Nebenlager (extension camp), Arbeitslager
+    (labor camp), or Aussenkommando (external work detail), camps were built at Blechhammer,
+    Jawiszowice, Jaworzno, Lagisze, Mysłowice, Trzebinia, and as far afield as the
+    Protectorate of Bohemia and Moravia in Czechoslovakia. Industries with satellite
+    camps included coal mines, foundries and other metal works, and chemical plants.
+    Prisoners were also made to work in forestry and farming. For example, Wirtschaftshof
+    Budy, in the Polish village of Budy near Brzeszcze, was a farming subcamp where
+    prisoners worked 12-hour days in the fields, tending animals, and making compost
+    by mixing human ashes from the crematoria with sod and manure. Incidents of sabotage
+    to decrease production took place in several subcamps, including Charlottengrube,
+    Gleiwitz II, and Rajsko. Living conditions in some of the camps were so poor that
+    they were regarded as punishment subcamps. Life in the camps
+
+
+    SS garrison
+
+
+    Rudolf Höss, born in Baden-Baden in 1900, was named the first commandant of Auschwitz
+    when Heinrich Himmler ordered on 27 April 1940 that the camp be established. Living
+    with his wife and children in a two-story stucco house near the commandant''s
+    and administration building, he served as commandant until 11 November 1943, with
+    Josef Kramer as his deputy. Succeeded as commandant by Arthur Liebehenschel, Höss
+    joined the SS Business and Administration Head Office in Oranienburg as director
+    of Amt DI, a post that made him deputy of the camps inspectorate. Richard Baer
+    became commandant of Auschwitz I on 11 May 1944 and Fritz Hartjenstein of Auschwitz
+    II from 22 November 1943, followed by Josef Kramer from 15 May 1944 until the
+    camp''s liquidation in January 1945. Heinrich Schwarz was commandant of Auschwitz
+    III from the point at which it became an autonomous camp in November 1943 until
+    its liquidation. Höss returned to Auschwitz between 8 May and 29 July 1944 as
+    the local SS garrison commander (Standortältester) to oversee the arrival of Hungary''s
+    Jews, which made him the superior officer of all the commandants of the Auschwitz
+    camps. According to Aleksander Lasik, about 6,335 people (6,161 of them men) worked
+    for the SS at Auschwitz over the course of the camp''s existence; 4.2 percent
+    were officers, 26.1 percent non-commissioned officers, and 69.7 percent rank and
+    file. In March 1941, there were 700 SS guards; in June 1942, 2,000; and in August
+    1944, 3,342. At its peak in January 1945, 4,480 SS men and 71 SS women worked
+    in Auschwitz; the higher number is probably attributable to the logistics of evacuating
+    the camp. Female guards were known as SS supervisors (SS-Aufseherinnen). Most
+    of the staff were from Germany or Austria, but as the war progressed, increasing
+    numbers of Volksdeutsche from other countries, including Czechoslovakia, Poland,
+    Yugoslavia, and the Baltic states, joined the SS at Auschwitz. Not all were ethnically
+    German. Guards were also recruited from Hungary, Romania, and Slovakia. Camp guards,
+    around three quarters of the SS personnel, were members of the SS-Totenkopfverbände
+    (death''s head units). Other SS staff worked in the medical or political departments,
+    or in the economic administration, which was responsible for clothing and other
+    supplies, including the property of dead prisoners. The SS viewed Auschwitz as
+    a comfortable posting; being there meant they had avoided the front and had access
+    to the victims'' property. Functionaries and Sonderkommando
+
+
+    Certain prisoners, at first non-Jewish Germans but later Jews and non-Jewish Poles,
+    were assigned positions of authority as Funktionshäftlinge (functionaries), which
+    gave them access to better housing and food. The Lagerprominenz (camp elite) included
+    Blockschreiber (barracks clerk), Kapo (overseer), Stubendienst (barracks orderly),
+    and Kommandierte (trusties). Wielding tremendous power over other prisoners, the
+    functionaries developed a reputation as sadists. Very few were prosecuted after
+    the war, because of the difficulty of determining which atrocities had been performed
+    by order of the SS. Although the SS oversaw the murders at each gas chamber, the
+    forced labor portion of the work was done by prisoners known from 1942 as the
+    Sonderkommando (special squad). These were mostly Jews but they included groups
+    such as Soviet POWs. In 1940–1941 when there was one gas chamber, there were 20
+    such prisoners, in late 1943 there were 400, and by 1944 during the Holocaust
+    in Hungary the number had risen to 874. The Sonderkommando removed goods and corpses
+    from the incoming trains, guided victims to the dressing rooms and gas chambers,
+    removed their bodies afterwards, and took their jewelry, hair, dental work, and
+    any precious metals from their teeth, all of which was sent to Germany. Once the
+    bodies were stripped of anything valuable, the Sonderkommando burned them in the
+    crematoria. Because they were witnesses to the mass murder, the Sonderkommando
+    lived separately from the other prisoners, although this rule was not applied
+    to the non-Jews among them. Their quality of life was further improved by their
+    access to the property of new arrivals, which they traded within the camp, including
+    with the SS. Nevertheless, their life expectancy was short; they were regularly
+    murdered and replaced. About 100 survived to the camp''s liquidation. They were
+    forced on a death march and by train to the camp at Mauthausen, where three days
+    later they were asked to step forward during roll call. No one did, and because
+    the SS did not have their records, several of them survived. Tattoos and triangles
+
+
+    Uniquely at Auschwitz, prisoners were tattooed with a serial number, on their
+    left breast for Soviet prisoners of war and on the left arm for civilians. Categories
+    of prisoner were distinguishable by triangular pieces of cloth (German: Winkel)
+    sewn onto on their jackets below their prisoner number. Political prisoners (Schutzhäftlinge
+    or Sch), mostly Poles, had a red triangle, while criminals (Berufsverbrecher or
+    BV) were mostly German and wore green. Asocial prisoners (Asoziale or Aso), which
+    included vagrants, prostitutes and the Roma, wore black. Purple was for Jehovah''s
+    Witnesses (Internationale Bibelforscher-Vereinigung or IBV)''s and pink for gay
+    men, who were mostly German. An estimated 5,000–15,000 gay men prosecuted under
+    German Penal Code Section 175 (proscribing sexual acts between men) were detained
+    in concentration camps, of whom an unknown number were sent to Auschwitz. Jews
+    wore a yellow badge, the shape of the Star of David, overlaid by a second triangle
+    if they also belonged to a second category. The nationality of the inmate was
+    indicated by a letter stitched onto the cloth. A racial hierarchy existed, with
+    German prisoners at the top. Next were non-Jewish prisoners from other countries.
+    Jewish prisoners were at the bottom. Transports
+
+
+    Deportees were brought to Auschwitz crammed in wretched conditions into goods
+    or cattle wagons, arriving near a railway station or at one of several dedicated
+    trackside ramps, including one next to Auschwitz I. The Altejudenrampe (old Jewish
+    ramp), part of the Oświęcim freight railway station, was used from 1942 to 1944
+    for Jewish transports. Located between Auschwitz I and Auschwitz II, arriving
+    at this ramp meant a 2.5 km journey to Auschwitz II and the gas chambers. Most
+    deportees were forced to walk, accompanied by SS men and a car with a Red Cross
+    symbol that carried the Zyklon B, as well as an SS doctor in case officers were
+    poisoned by mistake. Inmates arriving at night, or who were too weak to walk,
+    were taken by truck. Work on a new railway line and ramp (right) between sectors
+    BI and BII in Auschwitz II, was completed in May 1944 for the arrival of Hungarian
+    Jews between May and early July 1944. The rails led directly to the area around
+    the gas chambers. Life for the inmates
+
+    The day began at 4:30 am for the men (an hour later in winter), and earlier for
+    the women, when the block supervis'
+- source_sentence: Do restaurants like Chick-fil-A have signs indicating restrictions
+    against LGBTQ+ individuals
+  sentences:
+  - 'Restaurants have signs like "no smoking," "no guns," "no shoes, no service,"
+    but never have I seen a restaurant, especially Chick-fil-A, say "no gays or lesbians."
+    Get on the ball
+
+    In the newspaper this past week, "St. Charles seeks input on mall," how many more
+    studies are they going to do'
+  - His excavations lead to him being convinced that this site was more than likely
+    a pre-ceramic age and decided to discover it further. Later Voorhies worked to
+    understand and evaluate the Chantuto sites and the people who inhabited this area.
+  - Gross domestic product (GDP) is the market value of all final goods and services
+    from a nation in a given year.
+- source_sentence: How can Vaseline be used to help with chapped lips
+  sentences:
+  - '4. Soothe Chapped Lips
+
+    So, you probably already knew Vaseline made a great lip balm, but it can also
+    be used as a base in many lip scrubs, which will really come in handy during the
+    winter months. 5.'
+  - Retrieved March 30, 2005 from . Healthcare Information and Management Systems
+    Society (HIMSS) (2005, February).
+  - The Government of Zimbabwe strongly believes in the independence of the judiciary
+    and respects the principles of the separation of powers as set out in the Constitution
+    of Zimbabwe. The Government of Zimbabwe, therefore, recognises the importance
+    of the judiciary as a dependable interpreter of the law where various opinions
+    may arise.
+- source_sentence: What challenges do university researchers face when trying to turn
+    their discoveries into commercial products
+  sentences:
+  - 'A major shakeup has taken place at the top of the Boston Celtics. Danny Ainge
+    has stepped down as president of basketball operations, and head coach Brad Stevens
+    has stepped into the role. Stevens will now lead the search for a new coach. The
+    team made the announcement early Wednesday, one day after the Celtics were eliminated
+    by the Brooklyn Nets in the first round of the Eastern Conference playoffs. “Helping
+    guide this organization has been the thrill of a lifetime, and having worked side-by-side
+    with him since he’s been here, I know we couldn’t be in better hands than with
+    Brad guiding the team going forward,” Ainge said in a statement. “I’m grateful
+    to ownership, all of my Celtics colleagues, and the best fans in basketball for
+    being part of the journey.”
+
+    Ainge, 62, is a franchise legend.'
+  - 'Alfred William Lawson (March 24, 1869 – November 29, 1954) was an English born
+    professional baseball player, aviator and utopian philosopher. He was a baseball
+    player, manager, and league promoter from 1887 through 1916 and went on to play
+    a pioneering role in the U.S. aircraft industry. He published two early aviation
+    trade journals. He is frequently cited as the inventor of the airliner and was
+    awarded several of the first air mail contracts, which he ultimately could not
+    fulfill. He founded the Lawson Aircraft Company in Green Bay, Wisconsin, to build
+    military training aircraft and later the Lawson Airplane Company in South Milwaukee,
+    Wisconsin, to build airliners. The crash of his ambitious Lawson L-4 "Midnight
+    Liner"  during its trial flight takeoff on May 8, 1921, ended his best chance
+    for commercial aviation success. In 1904, he wrote a utopian novel, Born Again,
+    in which he developed the philosophy which later became Lawsonomy. Baseball career
+    (1888–1907)
+
+
+    He made one start for the Boston Beaneaters and two for the Pittsburgh Alleghenys
+    during the 1890 season. His minor league playing career lasted through 1895. He
+    later managed in the minors from 1905 to 1907. Union Professional League
+
+    In 1908, he started a new professional baseball league known as the Union Professional
+    League. The league took the field in April but folded one month later owing to
+    financial difficulties. Aviation career (1908–1928)
+
+    An early advocate or rather evangelist of aviation, in October 1908 Lawson started
+    the magazine Fly to stimulate public interest and educate readers in the fundamentals
+    of the new science of aviation. It sold for 10 cents a copy from newsstands across
+    the country. In 1910, moving to New York City, he renamed the magazine Aircraft
+    and published it until 1914. The magazine chronicled the technical developments
+    of the early aviation pioneers. Lawson was the first advocate for commercial air
+    travel, coining the term "airline." He also advocated for a strong American flying
+    force, lobbying Congress in 1913 to expand its appropriations for Army aircraft.
+    In early 1913, he learned to fly the Sloan-Deperdussin and the Moisant-Bleriot
+    monoplanes, becoming an accomplished pilot. Later that year he bought a Thomas
+    flying boat and became the first air commuter regularly flying from his country
+    house in Seidler''s Beach, New Jersey, to the foot of 75th Street in New York
+    City (about 35 miles). In 1917, utilizing the knowledge gained from ten years
+    of advocating aviation, he built his first airplane, the Lawson Military Tractor
+    1 (MT-1) trainer, and founded the Lawson Aircraft Corporation. The company''s
+    plant was sited at Green Bay, Wisconsin. There he secured a contract and built
+    the Lawson MT-2. He also designed the steel fuselage Lawson Armored Battler, which
+    never got beyond the drafting board, given doubts within the Army aviation community
+    and the signing of the armistice. After the war, in 1919 Lawson started a project
+    to build America''s first airline. He secured financial backing, and in five months
+    he had built and demonstrated in flight his biplane airliner, the 18-passenger
+    Lawson L-2. He demonstrated its capabilities in a 2000-mile multi-city tour from
+    Milwaukee to Chicago-Toledo-Cleveland-Buffalo-Syracuse-New york City-Washington,
+    D.C.-Collinsville-Dayton-Chicago and back to Milwaukee, creating a buzz of positive
+    press. The publicity allowed him to secure an additional $1 million to build the
+    26-passenger Midnight Liner. The aircraft crashed on takeoff on its maiden flight.
+    In late 1920, he secured government contracts for three airmail routes and to
+    deliver ten war planes, but owing to the fall 1920 recession, he could not secure
+    the necessary $100,000 in cash reserves called for in the contracts and had to
+    decline them.'
+  - 'Universities are vital to the process of innovation and advancement: they educate
+    students who bring new ways of thinking to old problems, and they make new discoveries
+    that no one else would make because no one else has the opportunity to delve so
+    deeply. In creating this type of refuge, we also create a comfort zone. Because
+    governmental support for science and technology is designed to support long-term,
+    high-risk work regardless of immediate return, ROI is not a factor in getting
+    government funding. University researchers become successful at pitching research
+    ideas without serious reference to commercial outcome. Peer review – which is
+    critical for the success of science – further reinforces this tendency. University
+    researchers are rewarded for thinking in this very specific way, and this creates
+    the comfort zone. As it dawns on a researcher that they may need to work with
+    a company or an entrepreneur to see their discoveries become products or services
+    that can benefit society, they may find themselves a victim of their own past
+    success. Many researchers reflexively approach companies as if they are yet another
+    type of funding agency, but since companies are not in the grant-making business,
+    a partnership fails to materialize. This basic failure to communicate means valuable
+    commercial opportunities are often not recognized, or when they are, the resulting
+    partnership does not go well.'
+pipeline_tag: sentence-similarity
+library_name: sentence-transformers
+---
+
+# MPNet base trained on AllNLI triplets
+
+This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [microsoft/mpnet-base](https://huggingface.co/microsoft/mpnet-base). It maps sentences & paragraphs to a 768-dimensional dense vector space and can be used for semantic textual similarity, semantic search, paraphrase mining, text classification, clustering, and more.
+
+## Model Details
+
+### Model Description
+- **Model Type:** Sentence Transformer
+- **Base model:** [microsoft/mpnet-base](https://huggingface.co/microsoft/mpnet-base) <!-- at revision 6996ce1e91bd2a9c7d7f61daec37463394f73f09 -->
+- **Maximum Sequence Length:** 512 tokens
+- **Output Dimensionality:** 768 dimensions
+- **Similarity Function:** Cosine Similarity
+<!-- - **Training Dataset:** Unknown -->
+- **Language:** en
+- **License:** apache-2.0
+
+### Model Sources
+
+- **Documentation:** [Sentence Transformers Documentation](https://sbert.net)
+- **Repository:** [Sentence Transformers on GitHub](https://github.com/UKPLab/sentence-transformers)
+- **Hugging Face:** [Sentence Transformers on Hugging Face](https://huggingface.co/models?library=sentence-transformers)
+
+### Full Model Architecture
+
+```
+SentenceTransformer(
+  (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: MPNetModel 
+  (1): Pooling({'word_embedding_dimension': 768, '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})
+)
+```
+
+## 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("Jrinky/mpnet-base-all-nli-triplet")
+# Run inference
+sentences = [
+    'What challenges do university researchers face when trying to turn their discoveries into commercial products',
+    'Universities are vital to the process of innovation and advancement: they educate students who bring new ways of thinking to old problems, and they make new discoveries that no one else would make because no one else has the opportunity to delve so deeply. In creating this type of refuge, we also create a comfort zone. Because governmental support for science and technology is designed to support long-term, high-risk work regardless of immediate return, ROI is not a factor in getting government funding. University researchers become successful at pitching research ideas without serious reference to commercial outcome. Peer review – which is critical for the success of science – further reinforces this tendency. University researchers are rewarded for thinking in this very specific way, and this creates the comfort zone. As it dawns on a researcher that they may need to work with a company or an entrepreneur to see their discoveries become products or services that can benefit society, they may find themselves a victim of their own past success. Many researchers reflexively approach companies as if they are yet another type of funding agency, but since companies are not in the grant-making business, a partnership fails to materialize. This basic failure to communicate means valuable commercial opportunities are often not recognized, or when they are, the resulting partnership does not go well.',
+    'A major shakeup has taken place at the top of the Boston Celtics. Danny Ainge has stepped down as president of basketball operations, and head coach Brad Stevens has stepped into the role. Stevens will now lead the search for a new coach. The team made the announcement early Wednesday, one day after the Celtics were eliminated by the Brooklyn Nets in the first round of the Eastern Conference playoffs. “Helping guide this organization has been the thrill of a lifetime, and having worked side-by-side with him since he’s been here, I know we couldn’t be in better hands than with Brad guiding the team going forward,” Ainge said in a statement. “I’m grateful to ownership, all of my Celtics colleagues, and the best fans in basketball for being part of the journey.”\nAinge, 62, is a franchise legend.',
+]
+embeddings = model.encode(sentences)
+print(embeddings.shape)
+# [3, 768]
+
+# Get the similarity scores for the embeddings
+similarities = model.similarity(embeddings, embeddings)
+print(similarities.shape)
+# [3, 3]
+```
+
+<!--
+### Direct Usage (Transformers)
+
+<details><summary>Click to see the direct usage in Transformers</summary>
+
+</details>
+-->
+
+<!--
+### Downstream Usage (Sentence Transformers)
+
+You can finetune this model on your own dataset.
+
+<details><summary>Click to expand</summary>
+
+</details>
+-->
+
+<!--
+### Out-of-Scope Use
+
+*List how the model may foreseeably be misused and address what users ought not to do with the model.*
+-->
+
+<!--
+## Bias, Risks and Limitations
+
+*What are the known or foreseeable issues stemming from this model? You could also flag here known failure cases or weaknesses of the model.*
+-->
+
+<!--
+### Recommendations
+
+*What are recommendations with respect to the foreseeable issues? For example, filtering explicit content.*
+-->
+
+## Training Details
+
+### Training Dataset
+
+#### Unnamed Dataset
+
+* Size: 6,433 training samples
+* Columns: <code>anchor</code> and <code>positive</code>
+* Approximate statistics based on the first 1000 samples:
+  |         | anchor                                                                            | positive                                                                            |
+  |:--------|:----------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|
+  | type    | string                                                                            | string                                                                              |
+  | details | <ul><li>min: 6 tokens</li><li>mean: 16.21 tokens</li><li>max: 42 tokens</li></ul> | <ul><li>min: 5 tokens</li><li>mean: 140.69 tokens</li><li>max: 512 tokens</li></ul> |
+* Samples:
+  | anchor                                                                                                                          | positive                                                                                                                                                                                                                                                                                                    |
+  |:--------------------------------------------------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+  | <code>What type of event is being described by Pierre LeBrun in relation to the NHL</code>                                      | <code>ESPN’s Pierre LeBrun said, “It's not just about one NHL game anymore. It's a week-long event.</code>                                                                                                                                                                                                  |
+  | <code>Who designed the property's landscape and when was the building listed on the National Register of Historic Places</code> | <code>The property's landscape continues a circular theme, with flower beds, fencing, and parking arranged in concentric patterns around the structure. It was designed by the Washington, DC firm of Deigert & Yerkes. The building was listed on the National Register of Historic Places in 2017.</code> |
+  | <code>Is 'ladens' a valid word to use in Scrabble and other word games</code>                                                   | <code>Scrabble?! LADENSIs ladens valid for Scrabble? Words With Friends? Lexulous? WordFeud? Other games</code>                                                                                                                                                                                             |
+* Loss: <code>selfloss.Infonce</code> with these parameters:
+  ```json
+  {
+      "scale": 20.0,
+      "similarity_fct": "cos_sim"
+  }
+  ```
+
+### Evaluation Dataset
+
+#### Unnamed Dataset
+
+* Size: 804 evaluation samples
+* Columns: <code>anchor</code> and <code>positive</code>
+* Approximate statistics based on the first 804 samples:
+  |         | anchor                                                                            | positive                                                                            |
+  |:--------|:----------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|
+  | type    | string                                                                            | string                                                                              |
+  | details | <ul><li>min: 7 tokens</li><li>mean: 16.44 tokens</li><li>max: 38 tokens</li></ul> | <ul><li>min: 8 tokens</li><li>mean: 149.21 tokens</li><li>max: 512 tokens</li></ul> |
+* Samples:
+  | anchor                                                                         | positive                                                                                                                                                                                                                                                                                                                                                                                                                                                       |
+  |:-------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+  | <code>What types of special events can the salon services be booked for</code> | <code>Our fabulous salon services are available at your special event! Whether it's a wedding, photo shoot, prom, or just a fun girls' night in- we do it all.</code>                                                                                                                                                                                                                                                                                          |
+  | <code>What material is the Hudson Baby plush hooded robe made of</code>        | <code>Dimensions (Overall): 10 inches (L), 10 inches (H) x 1 inches (W)<br>Weight: 1 pounds<br>Textile Material: 100% Polyester<br>• Animal face plush hooded bath robe. • Made with 100% plush coral fleece fabric<br>• Soft and gentle on baby's skin<br>• Optimal for everyday use<br>• Affordable, high quality bath robe<br>Hudson Baby plush hooded robe is made of super soft, cozy plush material to dry and warm baby after bath or pool time.</code> |
+  | <code>Where is this uncommon species thought to occur</code>                   | <code>It is also thought to occur in New Zealand. It is an uncommon species, growing in "heathy woodland [in] semi shade".</code>                                                                                                                                                                                                                                                                                                                              |
+* Loss: <code>selfloss.Infonce</code> with these parameters:
+  ```json
+  {
+      "scale": 20.0,
+      "similarity_fct": "cos_sim"
+  }
+  ```
+
+### Training Hyperparameters
+#### Non-Default Hyperparameters
+
+- `eval_strategy`: steps
+- `per_device_train_batch_size`: 32
+- `per_device_eval_batch_size`: 32
+- `learning_rate`: 2e-05
+- `num_train_epochs`: 6
+- `warmup_ratio`: 0.1
+- `fp16`: True
+- `batch_sampler`: no_duplicates
+
+#### All Hyperparameters
+<details><summary>Click to expand</summary>
+
+- `overwrite_output_dir`: False
+- `do_predict`: False
+- `eval_strategy`: steps
+- `prediction_loss_only`: True
+- `per_device_train_batch_size`: 32
+- `per_device_eval_batch_size`: 32
+- `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`: 2e-05
+- `weight_decay`: 0.0
+- `adam_beta1`: 0.9
+- `adam_beta2`: 0.999
+- `adam_epsilon`: 1e-08
+- `max_grad_norm`: 1.0
+- `num_train_epochs`: 6
+- `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
+- `gradient_checkpointing`: False
+- `gradient_checkpointing_kwargs`: None
+- `include_inputs_for_metrics`: False
+- `include_for_metrics`: []
+- `eval_do_concat_batches`: True
+- `fp16_backend`: auto
+- `push_to_hub_model_id`: None
+- `push_to_hub_organization`: None
+- `mp_parameters`: 
+- `auto_find_batch_size`: False
+- `full_determinism`: False
+- `torchdynamo`: None
+- `ray_scope`: last
+- `ddp_timeout`: 1800
+- `torch_compile`: False
+- `torch_compile_backend`: None
+- `torch_compile_mode`: None
+- `dispatch_batches`: None
+- `split_batches`: None
+- `include_tokens_per_second`: False
+- `include_num_input_tokens_seen`: False
+- `neftune_noise_alpha`: None
+- `optim_target_modules`: None
+- `batch_eval_metrics`: False
+- `eval_on_start`: False
+- `use_liger_kernel`: False
+- `eval_use_gather_object`: False
+- `average_tokens_across_devices`: False
+- `prompts`: None
+- `batch_sampler`: no_duplicates
+- `multi_dataset_batch_sampler`: proportional
+
+</details>
+
+### Training Logs
+| Epoch  | Step | Training Loss | Validation Loss |
+|:------:|:----:|:-------------:|:---------------:|
+| 0.9901 | 100  | 1.4311        | 0.2171          |
+| 1.9802 | 200  | 0.237         | 0.1718          |
+| 2.9703 | 300  | 0.1466        | 0.1561          |
+| 3.9604 | 400  | 0.1084        | 0.1541          |
+| 4.9505 | 500  | 0.0879        | 0.1528          |
+| 5.9406 | 600  | 0.0794        | 0.1514          |
+
+
+### Framework Versions
+- Python: 3.10.12
+- Sentence Transformers: 3.4.0
+- Transformers: 4.48.1
+- PyTorch: 2.5.1+cu124
+- Accelerate: 1.3.0
+- Datasets: 3.2.0
+- Tokenizers: 0.21.0
+
+## Citation
+
+### BibTeX
+
+#### Sentence Transformers
+```bibtex
+@inproceedings{reimers-2019-sentence-bert,
+    title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks",
+    author = "Reimers, Nils and Gurevych, Iryna",
+    booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing",
+    month = "11",
+    year = "2019",
+    publisher = "Association for Computational Linguistics",
+    url = "https://arxiv.org/abs/1908.10084",
+}
+```
+
+#### Infonce
+```bibtex
+@misc{henderson2017efficient,
+    title={Efficient Natural Language Response Suggestion for Smart Reply},
+    author={Matthew Henderson and Rami Al-Rfou and Brian Strope and Yun-hsuan Sung and Laszlo Lukacs and Ruiqi Guo and Sanjiv Kumar and Balint Miklos and Ray Kurzweil},
+    year={2017},
+    eprint={1705.00652},
+    archivePrefix={arXiv},
+    primaryClass={cs.CL}
+}
+```
+
+<!--
+## Glossary
+
+*Clearly define terms in order to be accessible across audiences.*
+-->
+
+<!--
+## Model Card Authors
+
+*Lists the people who create the model card, providing recognition and accountability for the detailed work that goes into its construction.*
+-->
+
+<!--
+## Model Card Contact
+
+*Provides a way for people who have updates to the Model Card, suggestions, or questions, to contact the Model Card authors.*
+-->

config.json

@@ -0,0 +1,24 @@
+{
+  "_name_or_path": "microsoft/mpnet-base",
+  "architectures": [
+    "MPNetModel"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": 0,
+  "eos_token_id": 2,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "layer_norm_eps": 1e-05,
+  "max_position_embeddings": 514,
+  "model_type": "mpnet",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 1,
+  "relative_attention_num_buckets": 32,
+  "torch_dtype": "float32",
+  "transformers_version": "4.48.1",
+  "vocab_size": 30527
+}

config_sentence_transformers.json

@@ -0,0 +1,10 @@
+{
+  "__version__": {
+    "sentence_transformers": "3.4.0",
+    "transformers": "4.48.1",
+    "pytorch": "2.5.1+cu124"
+  },
+  "prompts": {},
+  "default_prompt_name": null,
+  "similarity_fn_name": "cosine"
+}

model.safetensors

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+oid sha256:81fec4167b7d016f1b784e1238cc5a091f315a1a18fcbde26126971fa0466e36
+size 437967672

modules.json

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+[
+  {
+    "idx": 0,
+    "name": "0",
+    "path": "",
+    "type": "sentence_transformers.models.Transformer"
+  },
+  {
+    "idx": 1,
+    "name": "1",
+    "path": "1_Pooling",
+    "type": "sentence_transformers.models.Pooling"
+  }
+]

sentence_bert_config.json

@@ -0,0 +1,4 @@
+{
+  "max_seq_length": 512,
+  "do_lower_case": false
+}

special_tokens_map.json

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+{
+  "bos_token": {
+    "content": "<s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "cls_token": {
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+    "rstrip": false,
+    "single_word": false
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+    "single_word": false
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+  "mask_token": {
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+    "lstrip": true,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
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+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
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+    "single_word": false
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+    "content": "[UNK]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer_config.json

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+{
+  "added_tokens_decoder": {
+    "0": {
+      "content": "<s>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
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+      "special": true
+    }
+  },
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+  "clean_up_tokenization_spaces": false,
+  "cls_token": "<s>",
+  "do_lower_case": true,
+  "eos_token": "</s>",
+  "extra_special_tokens": {},
+  "mask_token": "<mask>",
+  "model_max_length": 512,
+  "pad_token": "<pad>",
+  "sep_token": "</s>",
+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "MPNetTokenizer",
+  "unk_token": "[UNK]"
+}