checkpoint-778/README.md

metadata

language:
  - en
tags:
  - sentence-transformers
  - sentence-similarity
  - feature-extraction
  - generated_from_trainer
  - dataset_size:624583
  - loss:CachedGISTEmbedLoss
base_model: BAAI/bge-m3
widget:
  - source_sentence: >-
      Double Paralympic champion Kadeena Cox has been left out of the British
      Para-cycling performance squad.
    sentences:
      - >-
        Ten stamps will be on sale on 7 July, marking five decades since the
        band turned professional.

        The collection include the band's most famous album covers as well as
        live performance shots.

        Pink Floyd became known for its innovative album covers, which were made
        in collaboration with leading graphic designers and photographers.

        The album covers that have been made into stamps include The Piper At
        The Gates Of Dawn, Atom Heart Mother, The Dark Side Of The Moon, Wish
        You Were Here, Animals and The Endless River.

        A further four stamps show the band performing live on tour, including
        one photograph from a concert at London's UFO Club in 1966.

        Pink Floyd were among the first groups to make extensive use of light
        shows and projection of films for their live concerts, which increased
        in ambition over the decades.

        The band was formed in 1965 by Roger Waters, drummer Nick Mason and
        keyboardist Rick Wright, later joined by guitarist Syd Barrett.

        In 1968, guitarist David Gilmour joined the band shortly before
        Barrett's departure.

        The stamps are available to pre-order on the Post Office website and
        will be physically available in 8,000 post offices from 7 July 2016.
      - >-
        It said pre-tax profit for the year to the end of March was £593m,
        compared with £735m a year earlier.

        Operating profit at its wholesale gas division fell 94% to just £2.2m,
        from £36.6m a year earlier, as a result of the fall in gas prices.

        Costs relating to its coal-fired power stations rose to £287m in the
        year.

        In January, SSE cut its standard gas tariff for domestic customers by
        5.3%.

        But the UK's second largest energy company still lost about 300,000
        energy customers in the year, leaving it with 8.2 million households and
        businesses.

        SSE chief executive Alistair Phillips-Davies said the energy firm had
        coped well with "the impact of prevailing commodity prices and intense
        retail market competition".

        "At the same time, SSE has continued to demonstrate financial discipline
        and commitment to its long-term strategic framework. The fact that some
        of the mist is beginning to clear around the legislative, political and
        regulatory environment means there are grounds for some cautious
        optimism for the next couple of years," he added.

        "SSE continues to invest for the future and in the year ahead plans
        almost £1.75bn of investment into new energy infrastructure in the UK
        and Ireland and improvements in services for our customers,"

        In March, SSE closed its Ferrybridge coal-fired power station in
        Yorkshire.

        SSE also announced on Wednesday that it would be selling up to a third
        of its 50% stake in gas distribution business SGN to raise cash for
        shareholders or to reinvest.
      - >-
        The 26-year-old, who won gold medals in both cycling and athletics in
        Rio last year, is instead focusing on training for the World
        Para-Athletics Championships in London this summer.

        Cox had her UK Sport funding suspended in January while she took part in
        Channel 4 programme The Jump.

        GB's 26-strong squad includes Rio gold medallists Sarah Storey and Jody
        Cundy.

        Storey, 39, became Britain's most successful female Paralympian when she
        won her 14th gold medal at the Rio Games.

        Cundy, 38, and like Storey a former swimmer, has won seven Paralympic
        golds - four in cycling.

        They are joined in the 'podium squad' by fellow Paralympic medallists
        Megan Giglia, Karen Darke, Jon-Allan Butterworth, Louis Rolfe, Crystal
        Lane and David Stone.

        With no track events scheduled for 2017 or 2018, British Cycling is
        happy to allow Cox extended time away from the programme.

        It said in a statement: "Kadeena decided to take a break from cycling at
        the start of 2017 to pursue other opportunities afforded to her by her
        incredible achievements at the Paralympics, a decision we fully respect.

        "Her focus is currently on her training programme for the 2017 IPC
        Athletic World Championships in London and she has the full support of
        the Great Britain cycling team."

        Tuesday's squad announcement comes a fortnight after British Cycling
        announced changes to the Para-cycling pathway in the build-up to Tokyo
        2020.

        Riders on the Paralympic world-class programme are now split into two
        groups - podium and podium potential - while a foundation programme has
        also been established.

        Great Britain 2017 squad in full:

        Podium: James Ball, Steve Bate, Jon-Allan Butterworth, Jody Cundy, Karen
        Darke, Adam Duggleby, Lora Fachie, Neil Fachie, Megan Giglia, Jon
        Gildea, Corrine Hall, Crystal Lane, Craig Maclean, Pete Mitchell, Louis
        Rolfe, Matt Rotherham, Helen Scott, David Stone, Dame Sarah Storey,
        Sophie Thornhill.

        Podium Potential: Will Bjergfelt, Craig McCann, Mel Nicholls, Simon
        Price, Liz Saul, David Smith.
  - source_sentence: A clean kitchen with the windows white and open.
    sentences:
      - 'Spacious white kitchen with brown cabinetry, sink and appliances. '
      - People are in the house.
      - Cramped black kitchen with white cabinetry, sink and appliances.
  - source_sentence: what is the full form of ms dos
    sentences:
      - >-
        89th Academy Awards Moonlight won three awards including Best Picture
        and La La Land won the most awards of the ceremony with six after
        receiving a record-tying 14 nominations. In an event unprecedented in
        the history of the Oscars, La La Land was incorrectly announced as the
        Best Picture. After a few minutes the error was corrected and Moonlight
        was declared the winner.[8][9] Moonlight became the first film with an
        all-black cast and the first LGBT-themed film to win Best
        Picture.[10][11] Hacksaw Ridge and Manchester by the Sea won two awards
        each. Winners with one award include Arrival, Fantastic Beasts and Where
        to Find Them, Fences, The Jungle Book, O.J.: Made in America, Piper, The
        Salesman, Sing, Suicide Squad, The White Helmets, and Zootopia.
      - >-
        MS-DOS MS-DOS (/ˌɛmˌɛsˈdɒs/ em-ess-DOSS; acronym for Microsoft Disk
        Operating System) is an operating system for x86-based personal
        computers mostly developed by Microsoft. Collectively, MS-DOS, its
        rebranding as IBM PC DOS, and some operating systems attempting to be
        compatible with MS-DOS, are sometimes referred to as "DOS" (which is
        also the generic acronym for disk operating system). MS-DOS was the main
        operating system for IBM PC compatible personal computers during the
        1980s and the early 1990s, when it was gradually superseded by operating
        systems offering a graphical user interface (GUI), in various
        generations of the graphical Microsoft Windows operating system.
      - >-
        Vincent and the Doctor "Vincent and the Doctor" is the tenth episode in
        the fifth series of British science fiction television series Doctor
        Who, first broadcast on BBC One on 5 June 2010. It was written by
        Richard Curtis and directed by Jonny Campbell and featured an uncredited
        guest appearance from actor Bill Nighy.
  - source_sentence: who does the voice for yoda in the starwars films
    sentences:
      - >-
        List of backward compatible games for Xbox One During Microsoft's E3
        2015 press conference on June 15, 2015, Microsoft announced plans to
        introduce Xbox 360 backward compatibility on the Xbox One at no
        additional cost.[10] Supported Xbox 360 games will run within an
        emulator and have access to certain Xbox One features, such as recording
        and broadcasting gameplay.[11] Games do not run directly from discs. A
        relicensed form of the game is downloaded automatically when a supported
        game is inserted, instead of having to make extensive modifications to
        the game in-order to port the original title. This means, that the only
        reason every single Xbox 360 title is not available, is a judicial
        issue, not an engineering one. All Xbox 360 games could run
        out-of-the-box on Xbox One, as they require no modifications or porting
        to run, other than a valid license. While digitally-purchased games will
        automatically appear for download in the user's library once
        available.[10] As with Xbox One titles,[12] if the game is installed
        using physical media, the disc is still required for validation
        purposes.[10][11]
      - >-
        Frank Oz Frank Oz (born Frank Richard Oznowicz[2] on May 25, 1944) is an
        English-born American puppeteer, filmmaker and actor. His career began
        as a puppeteer, where he performed the Muppet characters of Miss Piggy,
        Fozzie Bear, Animal, and Sam Eagle in The Muppet Show, and Cookie
        Monster, Bert, and Grover in Sesame Street.[4] He is also known for
        being the puppeteer and voice of Yoda in the Star Wars films.
      - >-
        Battle of Barnet The Battle of Barnet was a decisive engagement in the
        Wars of the Roses, a dynastic conflict of 15th-century England. The
        military action, along with the subsequent Battle of Tewkesbury, secured
        the throne for Edward IV. On 14 April 1471 near Barnet, then a small
        Hertfordshire town north of London, Edward led the House of York in a
        fight against the House of Lancaster, which backed Henry VI for the
        throne. Leading the Lancastrian army was Richard Neville, 16th Earl of
        Warwick, who played a crucial role in the fate of each king. Historians
        regard the battle as one of the most important clashes in the Wars of
        the Roses, since it brought about a decisive turn in the fortunes of the
        two houses. Edward's victory was followed by 14 years of Yorkist rule
        over England.
  - source_sentence: >-
      In mathematical astronomy , his fame is due to the introduction of the
      astronomical globe , and his early contributions to understanding the
      movement of the planets .
    sentences:
      - >-
        In 1994 , Rodrigo Leão left the band to start a solo career , replaced
        by Carlos Maria Trindade ( keyboard synthesizer ) .
      - >-
        His fame is due in mathematical astronomy to the introduction of the
        astronomical globe and to his early contributions to the understanding
        of the movement of the planets .
      - >-
        The Keita dynasty ruled Mali from the 12th to the early 17th century ,
        pre-imperial and imperial .
datasets:
  - bobox/enhanced_NLI-50K
  - sentence-transformers/natural-questions
  - tals/vitaminc
  - bobox/xSum-processed
  - google-research-datasets/paws
pipeline_tag: sentence-similarity
library_name: sentence-transformers
metrics:
  - pearson_cosine
  - spearman_cosine
  - cosine_accuracy
  - cosine_accuracy_threshold
  - cosine_f1
  - cosine_f1_threshold
  - cosine_precision
  - cosine_recall
  - cosine_ap
  - cosine_mcc
model-index:
  - name: SentenceTransformer based on BAAI/bge-m3
    results:
      - task:
          type: semantic-similarity
          name: Semantic Similarity
        dataset:
          name: sts test
          type: sts-test
        metrics:
          - type: pearson_cosine
            value: 0.9043945442719601
            name: Pearson Cosine
          - type: spearman_cosine
            value: 0.9181132986050412
            name: Spearman Cosine
      - task:
          type: binary-classification
          name: Binary Classification
        dataset:
          name: allNLI dev
          type: allNLI-dev
        metrics:
          - type: cosine_accuracy
            value: 0.78125
            name: Cosine Accuracy
          - type: cosine_accuracy_threshold
            value: 0.6732373237609863
            name: Cosine Accuracy Threshold
          - type: cosine_f1
            value: 0.72
            name: Cosine F1
          - type: cosine_f1_threshold
            value: 0.6590439081192017
            name: Cosine F1 Threshold
          - type: cosine_precision
            value: 0.631578947368421
            name: Cosine Precision
          - type: cosine_recall
            value: 0.8372093023255814
            name: Cosine Recall
          - type: cosine_ap
            value: 0.66692875458475
            name: Cosine Ap
          - type: cosine_mcc
            value: 0.5608411256005545
            name: Cosine Mcc
      - task:
          type: binary-classification
          name: Binary Classification
        dataset:
          name: Qnli dev
          type: Qnli-dev
        metrics:
          - type: cosine_accuracy
            value: 0.703125
            name: Cosine Accuracy
          - type: cosine_accuracy_threshold
            value: 0.7312531471252441
            name: Cosine Accuracy Threshold
          - type: cosine_f1
            value: 0.7183098591549295
            name: Cosine F1
          - type: cosine_f1_threshold
            value: 0.548336386680603
            name: Cosine F1 Threshold
          - type: cosine_precision
            value: 0.6144578313253012
            name: Cosine Precision
          - type: cosine_recall
            value: 0.864406779661017
            name: Cosine Recall
          - type: cosine_ap
            value: 0.7243762296174704
            name: Cosine Ap
          - type: cosine_mcc
            value: 0.4182713391161482
            name: Cosine Mcc

SentenceTransformer based on BAAI/bge-m3

This is a sentence-transformers model finetuned from BAAI/bge-m3 on the NLI, natural-questions, vitaminc, xsum, paws and global_dataset datasets. It maps sentences & paragraphs to a 1024-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: BAAI/bge-m3
• Maximum Sequence Length: 8192 tokens
• Output Dimensionality: 1024 dimensions
• Similarity Function: Cosine Similarity
• Training Datasets:
  • NLI
  • natural-questions
  • vitaminc
  • xsum
  • paws
  • global_dataset
• Language: en

Model Sources

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

Full Model Architecture

SentenceTransformer(
  (0): Transformer({'max_seq_length': 8192, 'do_lower_case': False}) with Transformer model: XLMRobertaModel 
  (1): AdvancedWeightedPooling(
    (mha): MultiheadAttention(
      (out_proj): NonDynamicallyQuantizableLinear(in_features=1024, out_features=1024, bias=True)
    )
    (MLP): Sequential(
      (0): SwiGLUBlock(
        (in_proj_swish): Linear(in_features=1024, out_features=2048, bias=True)
        (in_proj_gate): Linear(in_features=1024, out_features=2048, bias=True)
      )
      (1): Dropout(p=0.05, inplace=False)
      (2): Linear(in_features=2048, out_features=1024, bias=True)
    )
    (layernorm): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)
  )
)

Usage

Direct Usage (Sentence Transformers)

First install the Sentence Transformers library:

pip install -U sentence-transformers

Then you can load this model and run inference.

from sentence_transformers import SentenceTransformer

# Download from the 🤗 Hub
model = SentenceTransformer("bobox/XLMRoBERTaM3-CustomPoolin-v1.02-1024dMLP-s1-checkpoints-tmp")
# Run inference
sentences = [
    'In mathematical astronomy , his fame is due to the introduction of the astronomical globe , and his early contributions to understanding the movement of the planets .',
    'His fame is due in mathematical astronomy to the introduction of the astronomical globe and to his early contributions to the understanding of the movement of the planets .',
    'In 1994 , Rodrigo Leão left the band to start a solo career , replaced by Carlos Maria Trindade ( keyboard synthesizer ) .',
]
embeddings = model.encode(sentences)
print(embeddings.shape)
# [3, 1024]

# Get the similarity scores for the embeddings
similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [3, 3]

Evaluation

Metrics

Semantic Similarity

• Dataset: sts-test
• Evaluated with EmbeddingSimilarityEvaluator

Metric	Value
pearson_cosine	0.9044
spearman_cosine	0.9181

Binary Classification

• Datasets: allNLI-dev and Qnli-dev
• Evaluated with BinaryClassificationEvaluator

Metric	allNLI-dev	Qnli-dev
cosine_accuracy	0.7812	0.7031
cosine_accuracy_threshold	0.6732	0.7313
cosine_f1	0.72	0.7183
cosine_f1_threshold	0.659	0.5483
cosine_precision	0.6316	0.6145
cosine_recall	0.8372	0.8644
cosine_ap	0.6669	0.7244
cosine_mcc	0.5608	0.4183

Training Details

Training Datasets

NLI

NLI

• Dataset: NLI at d43e6fe
• Size: 750 training samples
• Columns: anchor, entailment, and negative
• Approximate statistics based on the first 750 samples:

  	anchor	entailment	negative
  type	string	string	string
  details	min: 5 tokens mean: 24.9 tokens max: 176 tokens	min: 5 tokens mean: 16.4 tokens max: 54 tokens	min: 6 tokens mean: 16.53 tokens max: 49 tokens

• Samples:

  anchor	entailment	negative
  09:00 On Thursday, AT&T said they have teamed with Juniper Networks to develop a mobile security platform for both businesses and consumers.	AT&T and Juniper to develop mobile security platform	AT&T and Juniper disassemble mobile security platform
  two police motorcycles driving down the road in front of a cop car	Two motorcycle cops and a police car on a street.	No motorcycle cops and a police car on a street.
  I've told you about their size.	I have told you about their size.	I have not told you about their size.

• Loss: CachedGISTEmbedLoss with these parameters:

  {'guide': SentenceTransformer(
    (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: BertModel 
    (1): Pooling({'word_embedding_dimension': 384, 'pooling_mode_cls_token': True, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True})
    (2): Normalize()
  ), 'temperature': 0.02}
  

natural-questions

natural-questions

• Dataset: natural-questions at f9e894e
• Size: 750 training samples
• Columns: sentence1 and sentence2
• Approximate statistics based on the first 750 samples:

  	sentence1	sentence2
  type	string	string
  details	min: 10 tokens mean: 13.32 tokens max: 25 tokens	min: 17 tokens mean: 148.26 tokens max: 651 tokens

• Samples:

  sentence1	sentence2
  who is winner in bigg boss season 5 kannada	Bigg Boss Kannada 5 Bigg Boss Kannada 5 (BBK5) was the fifth season of the Kannada television series Bigg Boss Kannada, that premiered on 15 October 2017.[1] Sudeep reprised his role as the host of the show.[2] The finale of the season took place 28 January 2018, and rapper Chandan Shetty was declared the winner of the show and the prize money of ₹50 lakh. Sales representative Diwaker was voted the runner-up.[3]
  what side of the street do they drive on in sweden	Left- and right-hand traffic Sweden was LHT from about 1734 to 1967,[17] despite having land borders with RHT countries, and approximately 90 percent of cars being left-hand drive (LHD) vehicles.[18] A referendum was held in 1955, with an overwhelming majority voting against a change to RHT. Nevertheless, some years later the government ordered a conversion, which took place at 5 am on Sunday, 3 September 1967. The accident rate dropped sharply after the change,[19] but soon rose back to near its original level.[20] The day was known as Dagen H ("H-Day"), the 'H' being for Högertrafik or right traffic. When Iceland switched the following year, it was known as H-dagurinn, again meaning "H-Day".[21]
  what is the difference between mandelbrot and biscotti	Mandelbrot (cookie) Its precise origin is unknown, as is its historic relationship with biscotti, a similar Italian cookie. While mandelbrot and biscotti both have a crunchy exterior, mandelbrot is slightly softer than biscotti due to its higher oil and/or butter content.

• Loss: CachedGISTEmbedLoss with these parameters:

  {'guide': SentenceTransformer(
    (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: BertModel 
    (1): Pooling({'word_embedding_dimension': 384, 'pooling_mode_cls_token': True, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True})
    (2): Normalize()
  ), 'temperature': 0.02}
  

vitaminc

vitaminc

• Dataset: vitaminc at be6febb
• Size: 370,653 training samples
• Columns: claim and evidence
• Approximate statistics based on the first 1000 samples:

  	claim	evidence
  type	string	string
  details	min: 9 tokens mean: 20.44 tokens max: 73 tokens	min: 9 tokens mean: 44.61 tokens max: 191 tokens

• Samples:

  claim	evidence
  The Script is a pop band .	The Script are an Irish pop band formed in 2007 in Dublin , Ireland .
  Scott Skiles scored fewer than 55 points in home games .	He set several records during high school , including most points in a home game ( 53 ) and most points in an away game ( 56 ) .
  The Black Cauldron was released before July 25 , 1985 .	The film was distributed theatrically through Buena Vista Distribution on July 24 , 1985 .

• Loss: CachedGISTEmbedLoss with these parameters:

  {'guide': SentenceTransformer(
    (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: BertModel 
    (1): Pooling({'word_embedding_dimension': 384, 'pooling_mode_cls_token': True, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True})
    (2): Normalize()
  ), 'temperature': 0.02}
  

xsum

xsum

• Dataset: xsum at 044020f
• Size: 131,779 training samples
• Columns: summary and document
• Approximate statistics based on the first 1000 samples:

  	summary	document
  type	string	string
  details	min: 11 tokens mean: 30.72 tokens max: 62 tokens	min: 63 tokens mean: 311.14 tokens max: 550 tokens

• Samples:

  summary	document
  The amount of time spent needing daily care in late life has doubled in England over the past two decades, a study suggests.	The Newcastle University study found men spent 2.4 years on average needing regular care and women three years. This includes everything from help with washing and dressing each day to round-the-clock care. Researchers said it suggested there needed to be a sharp increase in the number of care home places to cope. It comes as ministers consider a new way to fund the system. The government has promised major reform amid reports that councils are struggling to provide enough support to cope with the ageing population. The latest research, published in the Lancet, looked at not just the growth in the numbers of older people but also how many of those years were spent needing daily care. Between 1991 and 2011, life expectancy increased by more than four years for both men and women to 82.6 and 85.6 respectively. But the number of those years spent with substantial care needs rose much more rapidly, from 1.1 to 2.4 for men and 1.6 to three for women. Looking ahead to 2025, it means there wi...
  A man has admitted sexually assaulting two women in the same street two months apart.	Craig Perkins had initially denied being involved in the attacks in Bournemouth's Boundary Road in September and December of last year. But on Wednesday at Bournemouth Crown Court he pleaded guilty to two counts of sexual assault. The 29-year-old, of Victoria Park Road, Bournemouth, has been remanded in custody and will be sentenced on 5 May. Police said the victims were both in their 20s - the first was assaulted on Tuesday 13 September and the second attack happened on Thursday 24 November. Perkins was arrested on 14 December. Det Ch Insp Sarah Derbyshire, of Dorset Police's major crime investigation team, said: "Stranger sex attacks such as these are very rare in Dorset and we are committed toward investigating them thoroughly and bringing the offender to justice. "The victims in this case have been updated about Perkins' guilty pleas and I would like to pay tribute to them for having the confidence to report these offences to Dorset Police and the assistance they have given to the ...
  Durham produced a below-par batting display as they lost by seven wickets to Worcestershire in the One-Day Cup.	A 22 overs-a-side game was all that was possible after a long rain delay, but the home side were bowled out for 90. Mark Stoneman top-scored with 29 and the only other batsman to reach double figures was Paul Collingwood (17). Chris Rushworth took 3-19 as the visitors began their reply, but Alexei Kervezee (37) and Brett D'Oliveira (20) saw them to 91-3 with 17 balls in hand. Their unbroken partnership was worth 60 after Kervezee collected the winning single from the bowling of Usman Arshad. Durham reached 35-1 at the start of their innings after play got under way at 15:30 BST, but then lost four wickets for 11 runs. D'Oliveira, Ed Barnard, Joe Leach and Chris Russell took two wickets each as they were finally dismissed at the start of the 22nd over. Durham's total was their seventh-lowest in non-Twenty20 limited-overs matches games. Rushworth exploited the conditions superbly at the start of Worcestershire's innings, but once he was out of the attack, Kervezee and D'Oliveira were abl...

• Loss: CachedGISTEmbedLoss with these parameters:

  {'guide': SentenceTransformer(
    (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: BertModel 
    (1): Pooling({'word_embedding_dimension': 384, 'pooling_mode_cls_token': True, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True})
    (2): Normalize()
  ), 'temperature': 0.02}
  

paws

paws

• Dataset: paws at 161ece9
• Size: 49,401 training samples
• Columns: sentence1 and sentence2
• Approximate statistics based on the first 1000 samples:

  	sentence1	sentence2
  type	string	string
  details	min: 12 tokens mean: 30.94 tokens max: 56 tokens	min: 11 tokens mean: 30.97 tokens max: 55 tokens

• Samples:

  sentence1	sentence2
  Charley Frazier ( born August 12 , 1939 in Houston , Texas ) is a former American Football Wide Receiver from the NFL and the American Football League .	Charley Frazier ( born August 12 , 1939 in Houston , Texas ) is a former American football receiver in the American Football League and the NFL .
  Indonesian dumplings were influenced and brought by Chinese immigrants to Indonesia .	Indonesian dumplings were influenced and brought to Indonesia by Chinese immigrants .
  The SSSI has an area of 190.3 hectares , while the SAC has 168.3 hectares .	The SSSI has an area of 190.3 hectares while the SAC covers 168.3 hectares .

• Loss: CachedGISTEmbedLoss with these parameters:

  {'guide': SentenceTransformer(
    (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: BertModel 
    (1): Pooling({'word_embedding_dimension': 384, 'pooling_mode_cls_token': True, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True})
    (2): Normalize()
  ), 'temperature': 0.02}
  

global_dataset

global_dataset

• Dataset: global_dataset
• Size: 71,250 training samples
• Columns: sentence1 and sentence2
• Approximate statistics based on the first 1000 samples:

  	sentence1	sentence2
  type	string	string
  details	min: 7 tokens mean: 24.45 tokens max: 115 tokens	min: 6 tokens mean: 106.19 tokens max: 564 tokens

• Samples:

  sentence1	sentence2
  Taobao is a Chinese online shopping site similar to eBay , Amazon and Rakuten , which is operated by Alibaba Group in Hangzhou , Zhejiang .	Taobao is a Chinese online shopping website similar to eBay , Amazon and Rakuten , which is operated in Hangzhou , Zhejiang by Alibaba Group .
  Because of the lack of wood , boats were bundled with made papyrus reeds .	Because of the lack of wood , boats with papyrus reeds were bundled .
  New Zealand leg-spinner Ish Sodhi hopes his stint playing in Nottinghamshire's T20 campaign this summer will lead to a longer stay in England.	The 24-year-old has played 41 international matches in all formats. He has been particularly effective in T20, with 21 wickets at 14.47 and a strike-rate of a wicket every 13 balls. "In the last year or so I have definitely been a lot more successful in the T20 stuff than in the other stuff," he told BBC Radio Nottingham. "But in the last six months I have been finding my way in the four-stuff and one-dayers. "In the future I would love to come over and play all the forms. At this stage the T20 is the main focus. It is still a wee, wee way away but I will continue to look to hone my T20 skills and try to be in tip-top condition when I come over." Sodhi says playing in England is a "great opportunity" with the 2019 World Cup in mind. "It's great to play at these grounds where I will potentially play a World Cup, which I am targeting," he said. "It will be great to get used to conditions. The opportunity came up and I will try to grab it with both hands." Sodhi will be the second of two ...

• Loss: CachedGISTEmbedLoss with these parameters:

  {'guide': SentenceTransformer(
    (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: BertModel 
    (1): Pooling({'word_embedding_dimension': 384, 'pooling_mode_cls_token': True, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True})
    (2): Normalize()
  ), 'temperature': 0.02}
  

Evaluation Datasets

NLI

NLI

• Dataset: NLI at d43e6fe
• Size: 85 evaluation samples
• Columns: anchor, entailment, and negative
• Approximate statistics based on the first 85 samples:

  	anchor	entailment	negative
  type	string	string	string
  details	min: 9 tokens mean: 17.02 tokens max: 36 tokens	min: 6 tokens mean: 12.96 tokens max: 25 tokens	min: 6 tokens mean: 13.53 tokens max: 26 tokens

• Samples:

  anchor	entailment	negative
  The girls walk down the street.	Girls walk down the street.	Girls do not walk down the street.
  Two computers sitting on top of a desk.	A laptop computer and a desktop computer on a white desk	A laptop computer and a desktop computer on a black desk
  A bathroom with a toilette with it's seat down.	A bathroom with a sink and a toilet	A bathroom without a sink or a toilet

• Loss: CachedGISTEmbedLoss with these parameters:

  {'guide': SentenceTransformer(
    (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: BertModel 
    (1): Pooling({'word_embedding_dimension': 384, 'pooling_mode_cls_token': True, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True})
    (2): Normalize()
  ), 'temperature': 0.02}
  

natural-questions

natural-questions

• Dataset: natural-questions at f9e894e
• Size: 113 evaluation samples
• Columns: sentence1 and sentence2
• Approximate statistics based on the first 113 samples:

  	sentence1	sentence2
  type	string	string
  details	min: 10 tokens mean: 13.57 tokens max: 23 tokens	min: 34 tokens mean: 176.3 tokens max: 2497 tokens

• Samples:

  sentence1	sentence2
  kiss him not me where does the anime end in the manga	Kiss Him, Not Me Kiss Him, Not Me, known in Japan as Watashi ga Motete Dōsunda (Japanese: 私がモテてどうすんだ, Hepburn: lit. What's the Point of Me Getting Popular?), is a Japanese romantic comedy shōjo manga series written and illustrated by Junko.[2] It is published by Kodansha since 2013 on Bessatsu Friend magazine.[3] Twelve volumes compiling the chapters have been released so far.[2] It is published online in English by Crunchyroll and the volumes will be published by Kodansha USA.[3] An audio drama adaptation of the first chapter was released on January 13, 2015.[4] An anime adaptation by Brain's Base aired in Japan between October and December 2016.[5][6] The manga won Best Shōjo Manga at the 40th Kodansha Manga Awards.
  who sings i just want to use your love	Your Love (The Outfield song) "Your Love" is a song by the English rock band the Outfield, taken from their debut album Play Deep (1985). The song was penned by the band's guitarist John Spinks.
  how many episodes of westworld are in season 1	Westworld (season 1) The first season of the American science fiction western television series Westworld (subtitled The Maze) premiered on HBO on October 2, 2016, and concluded on December 4, 2016. It consisted of ten episodes, each running approximately 60 minutes in length and was broadcast on Sundays in the United States. The complete first season was released on home media on November 7, 2017.

• Loss: CachedGISTEmbedLoss with these parameters:

  {'guide': SentenceTransformer(
    (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: BertModel 
    (1): Pooling({'word_embedding_dimension': 384, 'pooling_mode_cls_token': True, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True})
    (2): Normalize()
  ), 'temperature': 0.02}
  

vitaminc

vitaminc

• Dataset: vitaminc at be6febb
• Size: 63,054 evaluation samples
• Columns: claim and evidence
• Approximate statistics based on the first 1000 samples:

  	claim	evidence
  type	string	string
  details	min: 10 tokens mean: 22.35 tokens max: 48 tokens	min: 11 tokens mean: 37.94 tokens max: 75 tokens

• Samples:

  claim	evidence
  More than 273 people have died from the 2019-20 coronavirus outside mainland China .	More than 3,200 people have died : almost 3,000 in mainland China and around 275 in other countries .
  More than 146,500 people have been infected with coronavirus globally , during the 2019�20 pandemic .	more than 147,000 cases have been confirmed worldwide .
  Over 278,000 coronavirus cases had been confirmed around the world by March 21 , 2020 .	As of 21 March , more than 278,000 cases of COVID-19 have been reported in over 186 countries and territories , resulting in more than 11,500 deaths and 92,000 recoveries. virus seems to mostly spread between people via respiratory droplets .

• Loss: CachedGISTEmbedLoss with these parameters:

  {'guide': SentenceTransformer(
    (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: BertModel 
    (1): Pooling({'word_embedding_dimension': 384, 'pooling_mode_cls_token': True, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True})
    (2): Normalize()
  ), 'temperature': 0.02}
  

xsum

xsum

• Dataset: xsum at 044020f
• Size: 131,779 evaluation samples
• Columns: summary and document
• Approximate statistics based on the first 1000 samples:

  	summary	document
  type	string	string
  details	min: 17 tokens mean: 30.71 tokens max: 43 tokens	min: 70 tokens mean: 305.77 tokens max: 543 tokens

• Samples:

  summary	document
  A new species of moss has been found growing on 10 maple trees in a Carmarthenshire car park, but experts are in two minds about its origins.	Welsh Bristle-moss was discovered near Dryslwyn Castle, close to Llandeilo, by the Countryside Council for Wales. It said it might have evolved from a genetically similar moss. But it could be an undiscovered species that was imported from the Continent on maples used to landscape the car park in the 1990s. There are about 900 species of moss in Britain and 587 of those are found in Wales. The Welsh Bristle-moss was discovered during a survey which is recording mosses growing on trees in south Wales. Experts said the moss had a unique combination of distinctive traits. It differed from related mosses because of its round-tipped leaf tips and flat leaf edges. Countryside Council for Wales (CCW) moss ecologist Sam Bosanquet, who made the new find, said: "Welsh Bristle-moss highlights the need to be ever vigilant and open-minded, even when looking at plants in mundane places like car parks. "This is a high-point in our regular work of recording mosses which grow on trees in south Wales. "...
  A former Soviet army officer has been convicted by a US jury of planning and leading a Taliban attack on American forces in Afghanistan in 2009.	The jury found Irek Hamidullin guilty on 15 counts, including supporting terrorists and conspiracy to use a weapon of mass destruction. The 55-year-old is the first military prisoner from Afghanistan to be tried in a US federal court. Some of the charges carry a mandatory life sentence. About 30 insurgents died in the attack, with Hamidullin the only survivor, while no American or Afghan soldiers were killed. Hamidullin, who did not testify during the trial, is expected to be sentenced on 6 November. Lawyers say it is unusual for someone captured on the battlefield in Afghanistan to be transferred to the United States for trial in a federal court. Hamidullin's defence lawyers had tried unsuccessfully to have the charges dismissed, saying their client was a prisoner of war and ineligible for trial in civilian court. Prosecutors argued federal law protected US soldiers no matter where they were. The jury in Richmond. Virginia, reached its verdict after five days of testimony and eight ho...
  UK troops could be deployed to train moderate Syrian rebels in the fight against Islamic State militants (IS), the defence secretary has said.	Michael Fallon told BBC News that UK troops could be sent to a country neighbouring Syria, possibly Jordan. He insisted however that UK forces would not engage in direct combat. The US is leading efforts to train a Syrian opposition to fight IS, also known as ISIS, which has captured large parts of of the country. The country's National Security Adviser Susan Rice said a deal had been reached with Turkey to allow the US to train Syrian rebels on its soil, although this has been denied by Turkish officials. Mr Fallon discussed the possibility of launching training operations, while visiting the Royal Fleet Auxiliary Ship, Argus, in Falmouth. A specialist team of 12 soldiers from the Yorkshire Regiment is already training Kurdish fighters in Iraq to use UK-supplied heavy machine guns. And the UK is to fund bomb disposal training for the Kurdish Peshmerga forces to counter the threat of Improvised Explosive Devices (IEDs), Foreign Secretary Philip Hammond announced on Monday. The Prime Mi...

• Loss: CachedGISTEmbedLoss with these parameters:

  {'guide': SentenceTransformer(
    (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: BertModel 
    (1): Pooling({'word_embedding_dimension': 384, 'pooling_mode_cls_token': True, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True})
    (2): Normalize()
  ), 'temperature': 0.02}
  

paws

paws

• Dataset: paws at 161ece9
• Size: 8,000 evaluation samples
• Columns: sentence1 and sentence2
• Approximate statistics based on the first 1000 samples:

  	sentence1	sentence2
  type	string	string
  details	min: 11 tokens mean: 31.67 tokens max: 56 tokens	min: 10 tokens mean: 31.33 tokens max: 54 tokens

• Samples:

  sentence1	sentence2
  He also wrote a large number of vocal arrangements and orchestral accompaniments to varieties .	He also wrote a large number of vocal arrangements and orchestral accompaniments for varieties .
  In 1994 , Rodrigo Leão left the band to start a solo career , being replaced by Carlos Maria Trindade ( keyboard synthesizer ) .	In 1994 , Rodrigo Leão left the band to start a solo career , replaced by Carlos Maria Trindade ( keyboard synthesizer ) .
  Until 1951 , he was active as a socialist in post-war legislation when he decided to focus on local politics .	He was active as a socialist in the post-war legislature until 1951 , when he decided to focus on local politics .

• Loss: CachedGISTEmbedLoss with these parameters:

  {'guide': SentenceTransformer(
    (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: BertModel 
    (1): Pooling({'word_embedding_dimension': 384, 'pooling_mode_cls_token': True, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True})
    (2): Normalize()
  ), 'temperature': 0.02}
  

global_dataset

global_dataset

• Dataset: global_dataset
• Size: 256 evaluation samples
• Columns: sentence1 and sentence2
• Approximate statistics based on the first 256 samples:

  	sentence1	sentence2
  type	string	string
  details	min: 10 tokens mean: 23.68 tokens max: 51 tokens	min: 6 tokens mean: 112.38 tokens max: 511 tokens

• Samples:

  sentence1	sentence2
  All babies born from Tuesday across the UK will have an anti-hepatitis B injection added to the other routine vaccinations they are given in their early life.	The jab protects against viral infections that cause cirrhosis and liver cancer. Babies are already vaccinated against diphtheria, tetanus, whooping cough, Hib and polio. Public Health England said the new vaccine had been "shown to be safe". Babies are currently given vaccinations when they are eight, 12 and 16 weeks old and the new injection will be given at the same time as the others. Previously, the hepatitis B vaccine was available on the NHS as a separate jab and was only administered to infants considered at risk, such as those born to infected mothers. While hepatitis B rates in the UK are generally very low, in some inner city areas up to 1% of antenatal women are infected. The infection has no symptoms so many of these women will be unaware they are ill, while their babies are considered at high risk. Mary Ramsay, head of immunisation at Public Health England, said: "The Hexavalent vaccine has been extensively tested and shown to be safe and is widely used internationally wi...
  A black man in a long sleeves white collared shirt and a tie is walking to work in a big city.	The man is wearing work attire and is walking to his job.
  ACVM is based in Glasgow and has offices in Edinburgh , Aberdeen , Newcastle , Manchester and Milton Keynes .	ACVM is based in Glasgow and has subsidiaries in Edinburgh , Aberdeen , Newcastle , Manchester and Milton Keynes .

• Loss: CachedGISTEmbedLoss with these parameters:

  {'guide': SentenceTransformer(
    (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: BertModel 
    (1): Pooling({'word_embedding_dimension': 384, 'pooling_mode_cls_token': True, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True})
    (2): Normalize()
  ), 'temperature': 0.02}
  

Training Hyperparameters

Non-Default Hyperparameters

• eval_strategy: steps
• per_device_train_batch_size: 192
• per_device_eval_batch_size: 256
• learning_rate: 0.0001
• weight_decay: 0.001
• lr_scheduler_type: cosine_with_min_lr
• lr_scheduler_kwargs: {'num_cycles': 0.5, 'min_lr': 3.3333333333333335e-05}
• warmup_ratio: 0.15
• save_safetensors: False
• fp16: True
• remove_unused_columns: False
• push_to_hub: True
• hub_model_id: bobox/XLMRoBERTaM3-CustomPoolin-v1.02-1024dMLP-s1-checkpoints-tmp
• hub_strategy: all_checkpoints
• hub_private_repo: False
• batch_sampler: no_duplicates

All Hyperparameters

Click to expand

• overwrite_output_dir: False
• do_predict: False
• eval_strategy: steps
• prediction_loss_only: True
• per_device_train_batch_size: 192
• per_device_eval_batch_size: 256
• 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: 0.0001
• weight_decay: 0.001
• adam_beta1: 0.9
• adam_beta2: 0.999
• adam_epsilon: 1e-08
• max_grad_norm: 1.0
• num_train_epochs: 3
• max_steps: -1
• lr_scheduler_type: cosine_with_min_lr
• lr_scheduler_kwargs: {'num_cycles': 0.5, 'min_lr': 3.3333333333333335e-05}
• warmup_ratio: 0.15
• warmup_steps: 0
• log_level: passive
• log_level_replica: warning
• log_on_each_node: True
• logging_nan_inf_filter: True
• save_safetensors: False
• 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: False
• label_names: None
• load_best_model_at_end: False
• ignore_data_skip: False
• fsdp: []
• fsdp_min_num_params: 0
• fsdp_config: {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}
• tp_size: 0
• fsdp_transformer_layer_cls_to_wrap: None
• accelerator_config: {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None}
• deepspeed: None
• label_smoothing_factor: 0.0
• optim: adamw_torch
• optim_args: None
• adafactor: False
• group_by_length: False
• length_column_name: length
• ddp_find_unused_parameters: None
• ddp_bucket_cap_mb: None
• ddp_broadcast_buffers: False
• dataloader_pin_memory: True
• dataloader_persistent_workers: False
• skip_memory_metrics: True
• use_legacy_prediction_loop: False
• push_to_hub: True
• resume_from_checkpoint: None
• hub_model_id: bobox/XLMRoBERTaM3-CustomPoolin-v1.02-1024dMLP-s1-checkpoints-tmp
• hub_strategy: all_checkpoints
• hub_private_repo: False
• 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
• 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

Training Logs

Click to expand

Epoch	Step	Training Loss	NLI loss	natural-questions loss	vitaminc loss	xsum loss	paws loss	global dataset loss	sts-test_spearman_cosine	allNLI-dev_cosine_ap	Qnli-dev_cosine_ap
0.0026	1	0.7912	-	-	-	-	-	-	-	-	-
0.0051	2	3.5781	-	-	-	-	-	-	-	-	-
0.0077	3	0.8711	-	-	-	-	-	-	-	-	-
0.0102	4	0.9923	-	-	-	-	-	-	-	-	-
0.0128	5	0.6723	-	-	-	-	-	-	-	-	-
0.0153	6	1.0542	-	-	-	-	-	-	-	-	-
0.0179	7	0.8721	-	-	-	-	-	-	-	-	-
0.0204	8	0.8121	-	-	-	-	-	-	-	-	-
0.0230	9	0.9226	-	-	-	-	-	-	-	-	-
0.0255	10	0.7534	-	-	-	-	-	-	-	-	-
0.0281	11	0.9769	-	-	-	-	-	-	-	-	-
0.0306	12	1.1295	-	-	-	-	-	-	-	-	-
0.0332	13	0.9773	-	-	-	-	-	-	-	-	-
0.0357	14	0.7239	-	-	-	-	-	-	-	-	-
0.0383	15	0.6364	-	-	-	-	-	-	-	-	-
0.0408	16	0.7573	-	-	-	-	-	-	-	-	-
0.0434	17	0.7629	-	-	-	-	-	-	-	-	-
0.0459	18	0.8665	-	-	-	-	-	-	-	-	-
0.0485	19	0.6049	-	-	-	-	-	-	-	-	-
0.0510	20	0.6587	-	-	-	-	-	-	-	-	-
0.0536	21	0.5717	-	-	-	-	-	-	-	-	-
0.0561	22	0.4781	-	-	-	-	-	-	-	-	-
0.0587	23	0.4699	-	-	-	-	-	-	-	-	-
0.0612	24	1.7145	-	-	-	-	-	-	-	-	-
0.0638	25	0.531	-	-	-	-	-	-	-	-	-
0.0663	26	0.5584	-	-	-	-	-	-	-	-	-
0.0689	27	0.398	-	-	-	-	-	-	-	-	-
0.0714	28	0.5015	-	-	-	-	-	-	-	-	-
0.0740	29	0.4741	-	-	-	-	-	-	-	-	-
0.0765	30	0.3762	-	-	-	-	-	-	-	-	-
0.0791	31	0.6952	-	-	-	-	-	-	-	-	-
0.0816	32	0.2723	-	-	-	-	-	-	-	-	-
0.0842	33	0.4301	-	-	-	-	-	-	-	-	-
0.0867	34	0.3839	-	-	-	-	-	-	-	-	-
0.0893	35	0.3154	-	-	-	-	-	-	-	-	-
0.0918	36	0.2796	-	-	-	-	-	-	-	-	-
0.0944	37	0.2964	-	-	-	-	-	-	-	-	-
0.0969	38	0.2232	-	-	-	-	-	-	-	-	-
0.0995	39	0.2661	-	-	-	-	-	-	-	-	-
0.1020	40	0.3133	-	-	-	-	-	-	-	-	-
0.1046	41	0.2047	-	-	-	-	-	-	-	-	-
0.1071	42	0.2206	-	-	-	-	-	-	-	-	-
0.1097	43	0.1694	-	-	-	-	-	-	-	-	-
0.1122	44	0.1864	-	-	-	-	-	-	-	-	-
0.1148	45	0.2126	-	-	-	-	-	-	-	-	-
0.1173	46	0.1589	-	-	-	-	-	-	-	-	-
0.1199	47	0.2539	-	-	-	-	-	-	-	-	-
0.1224	48	0.2403	-	-	-	-	-	-	-	-	-
0.125	49	0.1666	-	-	-	-	-	-	-	-	-
0.1276	50	0.1633	-	-	-	-	-	-	-	-	-
0.1301	51	0.2204	-	-	-	-	-	-	-	-	-
0.1327	52	0.0716	-	-	-	-	-	-	-	-	-
0.1352	53	0.1254	-	-	-	-	-	-	-	-	-
0.1378	54	0.3478	-	-	-	-	-	-	-	-	-
0.1403	55	0.2607	-	-	-	-	-	-	-	-	-
0.1429	56	0.2158	-	-	-	-	-	-	-	-	-
0.1454	57	0.2082	-	-	-	-	-	-	-	-	-
0.1480	58	0.2334	-	-	-	-	-	-	-	-	-
0.1505	59	0.2203	0.9447	0.2167	2.4175	0.1710	0.0204	0.2824	0.9129	0.6641	0.7343
0.1531	60	0.1368	-	-	-	-	-	-	-	-	-
0.1556	61	0.2153	-	-	-	-	-	-	-	-	-
0.1582	62	0.0711	-	-	-	-	-	-	-	-	-
0.1607	63	0.2255	-	-	-	-	-	-	-	-	-
0.1633	64	0.0982	-	-	-	-	-	-	-	-	-
0.1658	65	0.1388	-	-	-	-	-	-	-	-	-
0.1684	66	0.1797	-	-	-	-	-	-	-	-	-
0.1709	67	0.4173	-	-	-	-	-	-	-	-	-
0.1735	68	0.0102	-	-	-	-	-	-	-	-	-
0.1760	69	0.0634	-	-	-	-	-	-	-	-	-
0.1786	70	0.1956	-	-	-	-	-	-	-	-	-
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0.1862	73	0.1489	-	-	-	-	-	-	-	-	-
0.1888	74	0.1567	-	-	-	-	-	-	-	-	-
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0.1990	78	0.2364	-	-	-	-	-	-	-	-	-
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0.2092	82	0.1126	-	-	-	-	-	-	-	-	-
0.2117	83	0.1151	-	-	-	-	-	-	-	-	-
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0.2245	88	0.0836	-	-	-	-	-	-	-	-	-
0.2270	89	0.1276	-	-	-	-	-	-	-	-	-
0.2296	90	0.181	-	-	-	-	-	-	-	-	-
0.2321	91	0.1516	-	-	-	-	-	-	-	-	-
0.2347	92	0.1769	-	-	-	-	-	-	-	-	-
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0.2526	99	0.0807	-	-	-	-	-	-	-	-	-
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0.2653	104	0.1289	-	-	-	-	-	-	-	-	-
0.2679	105	0.7234	-	-	-	-	-	-	-	-	-
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0.2755	108	0.2446	-	-	-	-	-	-	-	-	-
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0.2806	110	0.0427	-	-	-	-	-	-	-	-	-
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0.2857	112	0.1524	-	-	-	-	-	-	-	-	-
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0.2959	116	0.1539	-	-	-	-	-	-	-	-	-
0.2985	117	0.1548	-	-	-	-	-	-	-	-	-
0.3010	118	0.1284	0.8682	0.1388	2.3304	0.1062	0.0200	0.2694	0.9151	0.6651	0.7364
0.3036	119	0.0939	-	-	-	-	-	-	-	-	-
0.3061	120	0.2675	-	-	-	-	-	-	-	-	-
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0.4490	176	0.0968	-	-	-	-	-	-	-	-	-
0.4515	177	0.0868	0.8198	0.0984	2.3936	0.0804	0.0204	0.2730	0.9166	0.6676	0.7384
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0.7526	295	0.0807	0.8120	0.0891	2.4979	0.0711	0.0203	0.2989	0.9157	0.6781	0.7280
0.7551	296	0.059	-	-	-	-	-	-	-	-	-
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1.5	588	0.0479	-	-	-	-	-	-	-	-	-
1.5026	589	0.0586	-	-	-	-	-	-	-	-	-
1.5051	590	0.047	0.8208	0.1414	2.3800	0.0879	0.0204	0.3144	0.9184	0.6576	0.7268
1.5077	591	0.071	-	-	-	-	-	-	-	-	-
1.5102	592	0.0954	-	-	-	-	-	-	-	-	-
1.5128	593	0.0224	-	-	-	-	-	-	-	-	-
1.5153	594	0.0772	-	-	-	-	-	-	-	-	-
1.5179	595	0.0385	-	-	-	-	-	-	-	-	-
1.5204	596	0.054	-	-	-	-	-	-	-	-	-
1.5230	597	0.0575	-	-	-	-	-	-	-	-	-
1.5255	598	0.0843	-	-	-	-	-	-	-	-	-
1.5281	599	0.0619	-	-	-	-	-	-	-	-	-
1.5306	600	0.1038	-	-	-	-	-	-	-	-	-
1.5332	601	0.0363	-	-	-	-	-	-	-	-	-
1.5357	602	0.0509	-	-	-	-	-	-	-	-	-
1.5383	603	0.1219	-	-	-	-	-	-	-	-	-
1.5408	604	0.0381	-	-	-	-	-	-	-	-	-
1.5434	605	0.0303	-	-	-	-	-	-	-	-	-
1.5459	606	0.04	-	-	-	-	-	-	-	-	-
1.5485	607	0.0718	-	-	-	-	-	-	-	-	-
1.5510	608	0.048	-	-	-	-	-	-	-	-	-
1.5536	609	0.0963	-	-	-	-	-	-	-	-	-
1.5561	610	0.0606	-	-	-	-	-	-	-	-	-
1.5587	611	0.0801	-	-	-	-	-	-	-	-	-
1.5612	612	0.1044	-	-	-	-	-	-	-	-	-
1.5638	613	0.0713	-	-	-	-	-	-	-	-	-
1.5663	614	0.0746	-	-	-	-	-	-	-	-	-
1.5689	615	0.1045	-	-	-	-	-	-	-	-	-
1.5714	616	0.0897	-	-	-	-	-	-	-	-	-
1.5740	617	0.0447	-	-	-	-	-	-	-	-	-
1.5765	618	0.0715	-	-	-	-	-	-	-	-	-
1.5791	619	0.0285	-	-	-	-	-	-	-	-	-
1.5816	620	0.0387	-	-	-	-	-	-	-	-	-
1.5842	621	0.1302	-	-	-	-	-	-	-	-	-
1.5867	622	0.0461	-	-	-	-	-	-	-	-	-
1.5893	623	0.0674	-	-	-	-	-	-	-	-	-
1.5918	624	0.0401	-	-	-	-	-	-	-	-	-
1.5944	625	0.0609	-	-	-	-	-	-	-	-	-
1.5969	626	0.0883	-	-	-	-	-	-	-	-	-
1.5995	627	0.1179	-	-	-	-	-	-	-	-	-
1.6020	628	0.068	-	-	-	-	-	-	-	-	-
1.6046	629	0.0375	-	-	-	-	-	-	-	-	-
1.6071	630	0.0626	-	-	-	-	-	-	-	-	-
1.6097	631	0.0419	-	-	-	-	-	-	-	-	-
1.6122	632	0.0574	-	-	-	-	-	-	-	-	-
1.6148	633	0.0463	-	-	-	-	-	-	-	-	-
1.6173	634	0.0538	-	-	-	-	-	-	-	-	-
1.6199	635	0.1048	-	-	-	-	-	-	-	-	-
1.6224	636	0.0416	-	-	-	-	-	-	-	-	-
1.625	637	0.0183	-	-	-	-	-	-	-	-	-
1.6276	638	0.0314	-	-	-	-	-	-	-	-	-
1.6301	639	0.0215	-	-	-	-	-	-	-	-	-
1.6327	640	0.0097	-	-	-	-	-	-	-	-	-
1.6352	641	0.0294	-	-	-	-	-	-	-	-	-
1.6378	642	0.0497	-	-	-	-	-	-	-	-	-
1.6403	643	0.0709	-	-	-	-	-	-	-	-	-
1.6429	644	0.0311	-	-	-	-	-	-	-	-	-
1.6454	645	0.0536	-	-	-	-	-	-	-	-	-
1.6480	646	0.0485	-	-	-	-	-	-	-	-	-
1.6505	647	0.0653	-	-	-	-	-	-	-	-	-
1.6531	648	0.0309	-	-	-	-	-	-	-	-	-
1.6556	649	0.0409	0.8265	0.1232	2.4417	0.0819	0.0206	0.3362	0.9194	0.6599	0.7431
1.6582	650	0.0788	-	-	-	-	-	-	-	-	-
1.6607	651	0.0917	-	-	-	-	-	-	-	-	-
1.6633	652	0.035	-	-	-	-	-	-	-	-	-
1.6658	653	0.0411	-	-	-	-	-	-	-	-	-
1.6684	654	0.059	-	-	-	-	-	-	-	-	-
1.6709	655	0.035	-	-	-	-	-	-	-	-	-
1.6735	656	0.0791	-	-	-	-	-	-	-	-	-
1.6760	657	0.0235	-	-	-	-	-	-	-	-	-
1.6786	658	0.0869	-	-	-	-	-	-	-	-	-
1.6811	659	0.0886	-	-	-	-	-	-	-	-	-
1.6837	660	0.0461	-	-	-	-	-	-	-	-	-
1.6862	661	0.0761	-	-	-	-	-	-	-	-	-
1.6888	662	0.0488	-	-	-	-	-	-	-	-	-
1.6913	663	0.0531	-	-	-	-	-	-	-	-	-
1.6939	664	0.0801	-	-	-	-	-	-	-	-	-
1.6964	665	0.0326	-	-	-	-	-	-	-	-	-
1.6990	666	0.0147	-	-	-	-	-	-	-	-	-
1.7015	667	0.0252	-	-	-	-	-	-	-	-	-
1.7041	668	0.0776	-	-	-	-	-	-	-	-	-
1.7066	669	0.0213	-	-	-	-	-	-	-	-	-
1.7092	670	0.0213	-	-	-	-	-	-	-	-	-
1.7117	671	0.093	-	-	-	-	-	-	-	-	-
1.7143	672	0.0989	-	-	-	-	-	-	-	-	-
1.7168	673	0.0264	-	-	-	-	-	-	-	-	-
1.7194	674	0.059	-	-	-	-	-	-	-	-	-
1.7219	675	0.1042	-	-	-	-	-	-	-	-	-
1.7245	676	0.0509	-	-	-	-	-	-	-	-	-
1.7270	677	0.0224	-	-	-	-	-	-	-	-	-
1.7296	678	0.067	-	-	-	-	-	-	-	-	-
1.7321	679	0.3453	-	-	-	-	-	-	-	-	-
1.7347	680	0.1518	-	-	-	-	-	-	-	-	-
1.7372	681	0.0635	-	-	-	-	-	-	-	-	-
1.7398	682	0.0669	-	-	-	-	-	-	-	-	-
1.7423	683	0.0635	-	-	-	-	-	-	-	-	-
1.7449	684	0.1072	-	-	-	-	-	-	-	-	-
1.7474	685	0.008	-	-	-	-	-	-	-	-	-
1.75	686	0.0338	-	-	-	-	-	-	-	-	-
1.7526	687	0.0986	-	-	-	-	-	-	-	-	-
1.7551	688	0.0534	-	-	-	-	-	-	-	-	-
1.7577	689	0.0464	-	-	-	-	-	-	-	-	-
1.7602	690	0.0364	-	-	-	-	-	-	-	-	-
1.7628	691	0.0276	-	-	-	-	-	-	-	-	-
1.7653	692	0.0598	-	-	-	-	-	-	-	-	-
1.7679	693	0.0372	-	-	-	-	-	-	-	-	-
1.7704	694	0.0759	-	-	-	-	-	-	-	-	-
1.7730	695	0.0294	-	-	-	-	-	-	-	-	-
1.7755	696	0.0537	-	-	-	-	-	-	-	-	-
1.7781	697	0.0608	-	-	-	-	-	-	-	-	-
1.7806	698	0.1348	-	-	-	-	-	-	-	-	-
1.7832	699	0.0588	-	-	-	-	-	-	-	-	-
1.7857	700	0.0524	-	-	-	-	-	-	-	-	-
1.7883	701	0.0247	-	-	-	-	-	-	-	-	-
1.7908	702	0.0673	-	-	-	-	-	-	-	-	-
1.7934	703	0.0206	-	-	-	-	-	-	-	-	-
1.7959	704	0.109	-	-	-	-	-	-	-	-	-
1.7985	705	0.0592	-	-	-	-	-	-	-	-	-
1.8010	706	0.071	-	-	-	-	-	-	-	-	-
1.8036	707	0.0589	-	-	-	-	-	-	-	-	-
1.8061	708	0.0772	0.8253	0.1323	2.5016	0.1077	0.0208	0.3019	0.9176	0.6682	0.7276
1.8087	709	0.0416	-	-	-	-	-	-	-	-	-
1.8112	710	0.0622	-	-	-	-	-	-	-	-	-
1.8138	711	0.0237	-	-	-	-	-	-	-	-	-
1.8163	712	0.0598	-	-	-	-	-	-	-	-	-
1.8189	713	0.0259	-	-	-	-	-	-	-	-	-
1.8214	714	0.075	-	-	-	-	-	-	-	-	-
1.8240	715	0.0778	-	-	-	-	-	-	-	-	-
1.8265	716	0.0424	-	-	-	-	-	-	-	-	-
1.8291	717	0.0711	-	-	-	-	-	-	-	-	-
1.8316	718	0.0508	-	-	-	-	-	-	-	-	-
1.8342	719	0.0765	-	-	-	-	-	-	-	-	-
1.8367	720	0.0457	-	-	-	-	-	-	-	-	-
1.8393	721	0.1753	-	-	-	-	-	-	-	-	-
1.8418	722	0.0397	-	-	-	-	-	-	-	-	-
1.8444	723	0.0708	-	-	-	-	-	-	-	-	-
1.8469	724	0.035	-	-	-	-	-	-	-	-	-
1.8495	725	0.5028	-	-	-	-	-	-	-	-	-
1.8520	726	0.0604	-	-	-	-	-	-	-	-	-
1.8546	727	0.0838	-	-	-	-	-	-	-	-	-
1.8571	728	0.1376	-	-	-	-	-	-	-	-	-
1.8597	729	0.0947	-	-	-	-	-	-	-	-	-
1.8622	730	0.3682	-	-	-	-	-	-	-	-	-
1.8648	731	0.0916	-	-	-	-	-	-	-	-	-
1.8673	732	0.0413	-	-	-	-	-	-	-	-	-
1.8699	733	0.037	-	-	-	-	-	-	-	-	-
1.8724	734	0.0439	-	-	-	-	-	-	-	-	-
1.875	735	0.0511	-	-	-	-	-	-	-	-	-
1.8776	736	0.0639	-	-	-	-	-	-	-	-	-
1.8801	737	0.0189	-	-	-	-	-	-	-	-	-
1.8827	738	0.0726	-	-	-	-	-	-	-	-	-
1.8852	739	0.0966	-	-	-	-	-	-	-	-	-
1.8878	740	0.0848	-	-	-	-	-	-	-	-	-
1.8903	741	0.038	-	-	-	-	-	-	-	-	-
1.8929	742	0.0846	-	-	-	-	-	-	-	-	-
1.8954	743	0.0832	-	-	-	-	-	-	-	-	-
1.8980	744	0.033	-	-	-	-	-	-	-	-	-
1.9005	745	0.0761	-	-	-	-	-	-	-	-	-
1.9031	746	0.012	-	-	-	-	-	-	-	-	-
1.9056	747	0.0153	-	-	-	-	-	-	-	-	-
1.9082	748	0.0663	-	-	-	-	-	-	-	-	-
1.9107	749	0.0436	-	-	-	-	-	-	-	-	-
1.9133	750	0.0511	-	-	-	-	-	-	-	-	-
1.9158	751	0.0698	-	-	-	-	-	-	-	-	-
1.9184	752	0.0322	-	-	-	-	-	-	-	-	-
1.9209	753	0.0245	-	-	-	-	-	-	-	-	-
1.9235	754	0.0245	-	-	-	-	-	-	-	-	-
1.9260	755	0.027	-	-	-	-	-	-	-	-	-
1.9286	756	0.0507	-	-	-	-	-	-	-	-	-
1.9311	757	0.0587	-	-	-	-	-	-	-	-	-
1.9337	758	0.0697	-	-	-	-	-	-	-	-	-
1.9362	759	0.0789	-	-	-	-	-	-	-	-	-
1.9388	760	0.0577	-	-	-	-	-	-	-	-	-
1.9413	761	0.0919	-	-	-	-	-	-	-	-	-
1.9439	762	0.0737	-	-	-	-	-	-	-	-	-
1.9464	763	0.069	-	-	-	-	-	-	-	-	-
1.9490	764	0.1402	-	-	-	-	-	-	-	-	-
1.9515	765	0.0599	-	-	-	-	-	-	-	-	-
1.9541	766	0.042	-	-	-	-	-	-	-	-	-
1.9566	767	0.1276	0.8538	0.1168	2.5234	0.0960	0.0204	0.3155	0.9181	0.6669	0.7244
1.9592	768	0.0995	-	-	-	-	-	-	-	-	-
1.9617	769	0.0381	-	-	-	-	-	-	-	-	-
1.9643	770	0.1053	-	-	-	-	-	-	-	-	-
1.9668	771	0.0385	-	-	-	-	-	-	-	-	-
1.9694	772	0.0452	-	-	-	-	-	-	-	-	-
1.9719	773	0.0702	-	-	-	-	-	-	-	-	-
1.9745	774	0.0506	-	-	-	-	-	-	-	-	-
1.9770	775	0.0351	-	-	-	-	-	-	-	-	-
1.9796	776	0.2187	-	-	-	-	-	-	-	-	-
1.9821	777	0.0222	-	-	-	-	-	-	-	-	-
1.9847	778	0.0532	-	-	-	-	-	-	-	-	-

Framework Versions

• Python: 3.11.11
• Sentence Transformers: 3.4.1
• Transformers: 4.51.1
• PyTorch: 2.5.1+cu124
• Accelerate: 1.3.0
• Datasets: 3.5.0
• Tokenizers: 0.21.0

Citation

BibTeX

Sentence Transformers

@inproceedings{reimers-2019-sentence-bert,
    title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks",
    author = "Reimers, Nils and Gurevych, Iryna",
    booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing",
    month = "11",
    year = "2019",
    publisher = "Association for Computational Linguistics",
    url = "https://arxiv.org/abs/1908.10084",
}