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+---
+tags:
+- sentence-transformers
+- sentence-similarity
+- feature-extraction
+- dense
+- generated_from_trainer
+- dataset_size:11180
+- loss:CosineSimilarityLoss
+widget:
+- source_sentence: Of course she would, otherwise she stands no chance of becoming
+    prez. The only thing above Le Pen's xenophobia is their thrive for power.
+  sentences:
+  - Mormon Church declares same-sex couples apostates and excludes children of those
+    couples from blessings and baptism.
+  - Feminists have legitimate gripes with the way the world is structured and their
+    ideas are quite sane. The feminists of the world are not deluded or wacky and
+    it's a bad idea to call them that. Open your mind to new ideas and drop the patriarchal
+    thinking.
+  - Hi, Professor Lichtman. Thanks for doing this AMA. What would you say to people
+    who argue about the economy keys being affected by people not feeling, in terms
+    of their lived experiences, that the economy has been good (due to the cost of
+    living exceeding, in many cases, their income) and this potentially costing Harris
+    the election? They seem to believe that this should be costing her the ST and
+    LT economy keys.
+- source_sentence: Sondra Locke stinks in this film, but then she was an awful 'actress'
+    anyway. Unfortunately, she drags everyone else (including then =real life boyfriend
+    Clint Eastwood down the drain with her. But what was Clint Eastwood thinking when
+    he agreed to star in this one? One read of the script should have told him that
+    this one was going to be a real snorer. It's an exceptionally weak story, basically
+    no story or plot at all. Add in bored, poor acting, even from the normally good
+    Eastwood. There's absolutely no action except a couple arguments and as far as
+    I was concerned, this film ranks up at the top of the heap of natural sleep enhancers.
+    Wow! Could a film BE any more boring? I think watching paint dry or the grass
+    grow might be more fun. A real stinker. Don't bother with this one.
+  sentences:
+  - 'SPOILERS: The original Road House is one of those movies that I know is clichéd
+    and unoriginal, yet it''s done so well, I''m embarrassed to admit I really like
+    it. Turns out many of my friends, whose movie opinions I respect, think the same
+    way. So when they attempt to make a sequel to it and it''s as if it was written
+    by some high school kids who were given the rights to do a sequel, it''s just
+    bad; really, really bad.Oddly, Johnathon Schaech is listed as one of the writers
+    and I can only hope his WGA membership is revoked. The writing was just bad and
+    all the writers of this film should retire for complete lack of originality and
+    some of the worst dialog in this millennium. Schaech already appearing to be the
+    king of the straight-to-DVD sequel (8mm 2, Poison Ivy 2) and now after seeing
+    this and 8mm 2, I''m thinking his acting ability is non-existent. He was awful,
+    just awful.And it''s not the terrible fighting scenes that make this movie terrible,
+    but take it from me, they''re bad. Every fight scene is a slowly delivered punch
+    (yet still making the "wiff" sound in the air) that is then blocked by the opponent,
+    who returns a punch that sends the first guy to the ground. This is repeated throughout
+    the film, worse than any bad 1970s cop show. Or the fact that many of the people
+    involved in the fights seem to have a mouth full of cherry kool-aid for some reason.
+    And we''re supposed to believe Will Patton is a fighting machine; his fight scenes
+    look so amazingly fake I was honestly embarrassed watching. It''s the complete
+    lapses of logic in this ridiculous movie that make it terrible. For instance:
+    Johnathon Schaech''s character is in town for a day and already tells some girl
+    he barely knows who he has no idea what side she''s on, "I''m with the Feds, but
+    don''t tell anyone." The female villain, who fights the good girl in one fight
+    scene with acrobatics that rival any super hero, yet is easily held down by the
+    Will Patton, "old guy," in another scene by simply holding both her hands while
+    he utters some ridiculous line ("stab me once, shame on you, stab me twice, ain''t
+    gonna happen" whew, that''s bad) and then head-butts her. Jake Busey''s villain
+    shoots at the feds while caught in the middle of a drug deal, yet no DEA agents
+    or anyone simply go to his place and pick him up after, in fact, he''s simply
+    let go because "this is the sheriff''s territory." Busey wants the bar because
+    it''s "in a great location" for drug deals, yet his own house appears to be just
+    as good apparently offering all the perks the bar is supposed to have. Johnathon
+    Schaech''s character is supposed to be the son of Patrick Swayze''s character
+    in the original, yet Swayze''s character''s last name is Dalton and Schaech''s
+    isn''t (nor is the supposed brother of Swayze''s character). And Johnathon Schaech
+    looks about 50 in this movie. I looked it up, he''s 17 years younger than Swayze,
+    but he looks awful.But my favorite absolutely stupid scene in this movie was the
+    most stock fight scene ending in movies: the villain is knocked through a window
+    on a second floor and as they pan down I''m thinking "please don''t tell me he''s
+    impaled on something..." and sure enough, my worst fears were realized.Actually,
+    I could go on for another half hour about the things I hated about this movie.
+    Suffice to say, let''s put an end to these ridiculous straight-to-DVD sequels
+    to theatrical movies, at least the ones with Johnathon Schaech.'
+  - 'Who do neoliberals scapegoat? The uneducated I guess? But we certainly don''t
+    advocate for their destruction or dissolution or deportation, unless you think
+    wanting to improve education standards and accessibility is violent?
+
+
+    I have yet to see anyone unironically idolize Macron like the right does Trump
+    and the left does Bernie.'
+  - 'Republicans created their own safe space in arcon (flaired users only) since
+    their facts are fake and they are too much of snowflakes to take the criticism
+    of being fact checked, just like how Trump gets mad when fact checked.
+
+
+    Republicans don''t post here because they are cowards.'
+- source_sentence: U.S. Forces Kill 50 Sadr Militia in Baghdad Suburb (Reuters) Reuters
+    - U.S. forces killed more than 50 Shi'ite\militiamen Wednesday in a significant
+    advance into a Baghdad\suburb that is a powerbase for radical cleric Moqtada al-Sadr,\the
+    military said.
+  sentences:
+  - "'You haven't had it as bad as I had it,' is exactly why Millennials are the first\
+    \ generation ever to be worse off than their parents.\n \n If we're on the same\
+    \ team, let's act like it.\n\nFucking thank you!\n\nI literally didn't mention\
+    \ Boomers or say a damn thing negative about them.  I shared my experience as\
+    \ a Millenial in a thread for an article specifically about my generation.  And\
+    \ of fucking course a Boomer came in to tell me I don't know what real struggle\
+    \ is.  Like... okay, what the hell is your point Karen?"
+  - '"Dutch Schultz", AKA Arthur Fleggenheimer, was a real person and his rather nasty
+    life is fairly well documented. This movie which purports to depict his life should
+    have used a fictional character, because the overdramatized events are too strong
+    a departure from the facts and the chronology. Not only that, it ignores some
+    interesting details which other versions have included such as the public relations
+    fiasco in upstate N.Y. and his religious conversion. It is true that he was executed
+    by Luciano, Lansky, et. al. but that''s as far as it goes. The exploding plate
+    scene which represents Luciano carrying out the execution of Bo Weinberg in his
+    own home, assisted by his own mother is rediculous. Also, there is the scene in
+    which Dutch approaches his own mother to pay protection to Legs Diamond. It just
+    doesn''t work. The character of Mrs. Fleggenheimer doesn''t work either. This
+    movie does not need a doting Jewish mother for comic relief. The lame representation
+    of Legs Diamond was humorous enough. I''m sure the man is turning in his grave.
+    And, by the way, Dutch did in fact personally kill people, but, he was not Rambo
+    or 007. The scene in which he wipes out the brewery is absurd. I don''t know.
+    Maybe it was supposed to be a comedy and I just didn''t get it.'
+  - Can we stop with the whole "leader/s of the free world"? What does that even mean?
+    As far as I know we're all from distinct sovereign countries for now. Like I don't
+    hate Macron or Merkel and they are good options so far, but this crap with "leaders
+    of the free world" is just obnoxious.
+- source_sentence: Reasoned arguments and suggestions which make allowance for the
+    full difficulties of the state of war that exists may help, and will always be
+    listened to with respect and sympathy.
+  sentences:
+  - 'Because they''re primarily just racists. If they truly believed in their stated
+    ideology they would want Macron to win. If you''re an America First nationalist
+    who thinks globalism is terrible then you should want globalists in charge of
+    every other country.
+
+
+    Edit: To be fair it''s possible that they''re not racist but merely too stupid
+    to think through the basic logic of their own ideology.  It''s one or the other.'
+  - This is the last episode of the Goldenboy OVA series. Kentaro finds himself working
+    in an animation studio, which is rather interesting if you don't know anything
+    about the way anime studios were run. Besides episode 3, this was probably the
+    least risqué, but it had a nice girl interest, as well as a surprise reunion from
+    others in the previous episodes. My only complaint about this episode is it seemed
+    a little too short, but at the same time this may have only been because it was
+    the only original script for the show that wasn't based on one of the manga chapters.
+    but it ended well, leaving us with the nice feeling that Kentaro is permanently
+    25, studying on. Definitely watch the rest of the series all the way through,
+    you can buy the whole series for like $17, you can watch it all the way through
+    in about 2 1/2 hours, or watch your favorite episode if you have 20 minutes free
+    time (which i do if i have a lunch break at school.) good series, check it out.
+  - 'DON''T STOP NOW: DEMAND AN END TO CHEMICAL CASTRATION of CHILDREN! Under Scrutiny,
+    Texas Judge Caves Under Pressure, Grants Father ''A Say'' In Son''s Transitioning
+    - But Only with a Gag Order. STAND YOUR GROUND AND KEEP FIGHTING!.'
+- source_sentence: Nationalism is a silly cock crowing on his own dunghill.
+  sentences:
+  - "There absolutely was voter fraud. There's voter fraud in every election. However,\
+    \ they are generally isolated incidents and I don't think there has been any credible\
+    \ evidence presented that indicates any wide-scale systemic voter fraud happened\
+    \ in 2020. \n\nI would like a federal commission started that investigates and\
+    \ looks for systemic voter and election fraud. Especially one that would be empowered\
+    \ to look into cases of disenfranchisement and voter suppression as well. Everyone\
+    \ that is legally allowed to vote should be able to easily and securely register\
+    \ and cast their vote."
+  - 'The 1970''s saw a rise and fall of what we have come to know as "Blacksploitation"
+    Films. The term is a reference to kind of broad catch-all, rather than a true
+    Genre of Film. In short, any comedy, drama, adventure, western or urban cops &
+    robbers shoot-em-up, that are so constructed and so cast as to appeal to the large
+    Urban Black population of the Mid 20th Century. That indeed could embrace the
+    widest type of films, as long as the had a slant toward the inner-city black population.It
+    appears that the idea of producing these films of particularly keen interest to
+    Black Americans had its genesis with the Eastertime Release of 100 RIFLES (Marvin
+    Schwartz Prod./20th Century-Fox, 1969). In it, former Syracuse University All-American
+    Footballer and Several Times All-Pro Fullback for the Cleveland Browns, Jim Brown,
+    had a Co-Starring Billing. Having appeared in a number of films already, as for
+    example, RIO CONCHOS (1964),THE DIRTY DOZEN (1967), (ICE STTION ZEBRA (1968)*
+    and others, it was beginning to make more sense to the Studios'' "Suits" that
+    Jim was a hot property.Now this 100 RIFLES brings record numbers of Black patrons
+    to the Big Cities'' central business districts on Easter Sunday to view Mr. Brown.
+    Why not start to film more of these adventure epics and other types of film with
+    more Black Players and Stars? Why not, indeed.** So we saw a succession of Cops
+    & Robbers, Bad-ass Private Detective Films, Comedies, all going the route. Along
+    the way, we eventually got to some more family oriented, wider appealing films.
+    The movie goers were treated to SOUNDER (1972), THE TAKE (1974), CONRACK (1974)and,
+    ultimately, CLAUDINE (1974).In CLAUDINE, we find no stigma nor easy classification
+    as being "Blackploitation", as the story is universal, and could easily have been
+    done as a story about people of any descent, any where, and not just in the 1970''s
+    USA.That the story was done of a SINGLE mother, Claudine (Dianne Carroll), struggling
+    to keep a family together after "....two marriages and two almost marriages.",
+    is a far cry from a shoot-em-up Harlem Style. The problems that plague the everyday
+    citizens of our nation are confronted and examined under the ol'' sociological
+    microscope.But we also consider Claudine''s psychological and physical needs as
+    a female. For "Woman Needs Man and Man Must Have His MATE",***and we do concede
+    this point. (That''s S-E-X that we''re talking about, Schultz!) Claudine meets
+    up with a very masculine, broad shouldered, athletic type in Private Scavanger
+    Garbage Man, Ruppert B. Marshall (James Earl Jones) and they go on a date.The
+    Great Welfare State intervenes with the Couple as Claudine''s Welfare Case Worker,
+    Miss Tayback (Elisa Loti), comes snooping around to see just who is this unattached
+    Male, who is suddenly paying so much attention to Claudine''s family.After a humiliating
+    experience with the Welfare Bureau''s auditing and "deducting" binge, which would
+    be the norm for the family, the two decide to get married with or without the
+    blessing of Big Brother.Meanwhile, Claudine''s elder son has gotten involved with
+    some big talking but little doing Black Activist group. But, with Ruppert''s help,
+    he and they all come through it A.O.K.It ends on a Happy, Upbeat and Hopeful note.
+    We know that it may not be exactly "...Happily Ever After!", but rather the''ll
+    make it all together! If there is a single criticism that we must state it is
+    that sometimes in a movie like this, a misconception is spread to a large portion
+    of Urban Blacks. And that is, the apparent implied myth that all Whites are wealthy,
+    having none of their kind ever in need of a helping hand, out of work or suffering
+    any disabilities.Well, folks, it just ain''t true! NOTE: * At one point, Jim Brown''s
+    career was a real hit as a rugged actioner. He was even being tauted as "...The
+    Black John Wayne." NOTE: ** The idea of producing films with All-Black Casts,
+    filmed for All-Black consumption was not a new idea. In the 1920''s, ''30''s and
+    ''40''s, we saw productions from people like Noble Johnson, Spencer Williams,
+    Jr. and Rex Ingram.NOTE: *** That''s "As Time Goes By", you know, Schultz, it''s
+    from CASABLANCA (Warner Brothers, 1942).'
+  - Thinks gun confiscation is . . .
+pipeline_tag: sentence-similarity
+library_name: sentence-transformers
+metrics:
+- pearson_cosine
+- spearman_cosine
+model-index:
+- name: SentenceTransformer
+  results:
+  - task:
+      type: semantic-similarity
+      name: Semantic Similarity
+    dataset:
+      name: similarity
+      type: similarity
+    metrics:
+    - type: pearson_cosine
+      value: 0.41059188174486916
+      name: Pearson Cosine
+    - type: spearman_cosine
+      value: 0.4260753939913245
+      name: Spearman Cosine
+---
+
+# SentenceTransformer
+
+This is a [sentence-transformers](https://www.SBERT.net) model trained. 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:** [Unknown](https://huggingface.co/unknown) -->
+- **Maximum Sequence Length:** 512 tokens
+- **Output Dimensionality:** 1024 dimensions
+- **Similarity Function:** Cosine Similarity
+<!-- - **Training Dataset:** Unknown -->
+<!-- - **Language:** Unknown -->
+<!-- - **License:** Unknown -->
+
+### 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, 'architecture': 'BertModel'})
+  (1): Pooling({'word_embedding_dimension': 1024, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': True, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True})
+  (2): Normalize()
+)
+```
+
+## Usage
+
+### Direct Usage (Sentence Transformers)
+
+First install the Sentence Transformers library:
+
+```bash
+pip install -U sentence-transformers
+```
+
+Then you can load this model and run inference.
+```python
+from sentence_transformers import SentenceTransformer
+
+# Download from the 🤗 Hub
+model = SentenceTransformer("sentence_transformers_model_id")
+# Run inference
+sentences = [
+    'Nationalism is a silly cock crowing on his own dunghill.',
+    'The 1970\'s saw a rise and fall of what we have come to know as "Blacksploitation" Films. The term is a reference to kind of broad catch-all, rather than a true Genre of Film. In short, any comedy, drama, adventure, western or urban cops & robbers shoot-em-up, that are so constructed and so cast as to appeal to the large Urban Black population of the Mid 20th Century. That indeed could embrace the widest type of films, as long as the had a slant toward the inner-city black population.It appears that the idea of producing these films of particularly keen interest to Black Americans had its genesis with the Eastertime Release of 100 RIFLES (Marvin Schwartz Prod./20th Century-Fox, 1969). In it, former Syracuse University All-American Footballer and Several Times All-Pro Fullback for the Cleveland Browns, Jim Brown, had a Co-Starring Billing. Having appeared in a number of films already, as for example, RIO CONCHOS (1964),THE DIRTY DOZEN (1967), (ICE STTION ZEBRA (1968)* and others, it was beginning to make more sense to the Studios\' "Suits" that Jim was a hot property.Now this 100 RIFLES brings record numbers of Black patrons to the Big Cities\' central business districts on Easter Sunday to view Mr. Brown. Why not start to film more of these adventure epics and other types of film with more Black Players and Stars? Why not, indeed.** So we saw a succession of Cops & Robbers, Bad-ass Private Detective Films, Comedies, all going the route. Along the way, we eventually got to some more family oriented, wider appealing films. The movie goers were treated to SOUNDER (1972), THE TAKE (1974), CONRACK (1974)and, ultimately, CLAUDINE (1974).In CLAUDINE, we find no stigma nor easy classification as being "Blackploitation", as the story is universal, and could easily have been done as a story about people of any descent, any where, and not just in the 1970\'s USA.That the story was done of a SINGLE mother, Claudine (Dianne Carroll), struggling to keep a family together after "....two marriages and two almost marriages.", is a far cry from a shoot-em-up Harlem Style. The problems that plague the everyday citizens of our nation are confronted and examined under the ol\' sociological microscope.But we also consider Claudine\'s psychological and physical needs as a female. For "Woman Needs Man and Man Must Have His MATE",***and we do concede this point. (That\'s S-E-X that we\'re talking about, Schultz!) Claudine meets up with a very masculine, broad shouldered, athletic type in Private Scavanger Garbage Man, Ruppert B. Marshall (James Earl Jones) and they go on a date.The Great Welfare State intervenes with the Couple as Claudine\'s Welfare Case Worker, Miss Tayback (Elisa Loti), comes snooping around to see just who is this unattached Male, who is suddenly paying so much attention to Claudine\'s family.After a humiliating experience with the Welfare Bureau\'s auditing and "deducting" binge, which would be the norm for the family, the two decide to get married with or without the blessing of Big Brother.Meanwhile, Claudine\'s elder son has gotten involved with some big talking but little doing Black Activist group. But, with Ruppert\'s help, he and they all come through it A.O.K.It ends on a Happy, Upbeat and Hopeful note. We know that it may not be exactly "...Happily Ever After!", but rather the\'ll make it all together! If there is a single criticism that we must state it is that sometimes in a movie like this, a misconception is spread to a large portion of Urban Blacks. And that is, the apparent implied myth that all Whites are wealthy, having none of their kind ever in need of a helping hand, out of work or suffering any disabilities.Well, folks, it just ain\'t true! NOTE: * At one point, Jim Brown\'s career was a real hit as a rugged actioner. He was even being tauted as "...The Black John Wayne." NOTE: ** The idea of producing films with All-Black Casts, filmed for All-Black consumption was not a new idea. In the 1920\'s, \'30\'s and \'40\'s, we saw productions from people like Noble Johnson, Spencer Williams, Jr. and Rex Ingram.NOTE: *** That\'s "As Time Goes By", you know, Schultz, it\'s from CASABLANCA (Warner Brothers, 1942).',
+    "There absolutely was voter fraud. There's voter fraud in every election. However, they are generally isolated incidents and I don't think there has been any credible evidence presented that indicates any wide-scale systemic voter fraud happened in 2020. \n\nI would like a federal commission started that investigates and looks for systemic voter and election fraud. Especially one that would be empowered to look into cases of disenfranchisement and voter suppression as well. Everyone that is legally allowed to vote should be able to easily and securely register and cast their vote.",
+]
+embeddings = model.encode(sentences)
+print(embeddings.shape)
+# [3, 1024]
+
+# Get the similarity scores for the embeddings
+similarities = model.similarity(embeddings, embeddings)
+print(similarities)
+# tensor([[1.0000, 0.1908, 0.3587],
+#         [0.1908, 1.0000, 0.3531],
+#         [0.3587, 0.3531, 1.0000]])
+```
+
+<!--
+### 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.*
+-->
+
+## Evaluation
+
+### Metrics
+
+#### Semantic Similarity
+
+* Dataset: `similarity`
+* Evaluated with [<code>EmbeddingSimilarityEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.EmbeddingSimilarityEvaluator)
+
+| Metric              | Value      |
+|:--------------------|:-----------|
+| pearson_cosine      | 0.4106     |
+| **spearman_cosine** | **0.4261** |
+
+<!--
+## 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: 11,180 training samples
+* Columns: <code>sentence_0</code>, <code>sentence_1</code>, and <code>label</code>
+* Approximate statistics based on the first 1000 samples:
+  |         | sentence_0                                                                          | sentence_1                                                                          | label                                                          |
+  |:--------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:---------------------------------------------------------------|
+  | type    | string                                                                              | string                                                                              | float                                                          |
+  | details | <ul><li>min: 4 tokens</li><li>mean: 104.44 tokens</li><li>max: 512 tokens</li></ul> | <ul><li>min: 5 tokens</li><li>mean: 109.27 tokens</li><li>max: 512 tokens</li></ul> | <ul><li>min: 0.0</li><li>mean: 0.52</li><li>max: 1.0</li></ul> |
+* Samples:
+  | sentence_0                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                             | sentence_1                                                                                                                                                                             | label                           |
+  |:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:--------------------------------|
+  | <code>The concept that things could be possibly be worse therefore do not strive to improve things is a weak and cowardly mentality. <br>Nobody wants to hear your dumbass shit.<br><br>Edit: This dude dm'd me and had a total emotional meltdown, that's how bad my words hurt this man.</code>                                                                                                                                                                                                                                                                                                                                      | <code>Based Macron needs to snort something off of your girlfriends titis</code>                                                                                                       | <code>1.0</code>                |
+  | <code>Even #foxnews pundit Brit Hume is calling this tweet a lie and should be the reason he loses the next election or is impeached & found guilty by the majority Republican Senate ASAP! #MuellerReport. End of story!</code>                                                                                                                                                                                                                                                                                                                                                                                                       | <code>An election like this will hardly ever be more decisive, thats just how these things are. I agree its sad that even someone like Le Pen doesnt break the habit.</code>           | <code>0.7071067811865475</code> |
+  | <code>*review may contain spoilers*predictable, campy, bad special effects. it has a TV-movie feeling to it. the idea of the UN as being taken over by Satan is an interesting twist to the end of the world according to the bible. the premise is interesting, but its excution falls waaaay short. if you want to convert people to Christianity with a film like this, at least make it a quality one! i was seriously checking my watch while watching this piece of dreck. can't say much else about this film since i saw it over a year ago, and there isn't really much to say about this film other than.....skip it!</code> | <code>wonderful movie with good story great humour (some great one-liners) and a soundtrack to die for.i've seen it 3 times so far.the american audiences are going to love it.</code> | <code>0.3333333333333333</code> |
+* Loss: [<code>CosineSimilarityLoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#cosinesimilarityloss) with these parameters:
+  ```json
+  {
+      "loss_fct": "torch.nn.modules.loss.MSELoss"
+  }
+  ```
+
+### Training Hyperparameters
+#### Non-Default Hyperparameters
+
+- `eval_strategy`: steps
+- `per_device_train_batch_size`: 32
+- `per_device_eval_batch_size`: 32
+- `fp16`: True
+- `multi_dataset_batch_sampler`: round_robin
+
+#### 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`: 5e-05
+- `weight_decay`: 0.0
+- `adam_beta1`: 0.9
+- `adam_beta2`: 0.999
+- `adam_epsilon`: 1e-08
+- `max_grad_norm`: 1
+- `num_train_epochs`: 3
+- `max_steps`: -1
+- `lr_scheduler_type`: linear
+- `lr_scheduler_kwargs`: {}
+- `warmup_ratio`: 0.0
+- `warmup_steps`: 0
+- `log_level`: passive
+- `log_level_replica`: warning
+- `log_on_each_node`: True
+- `logging_nan_inf_filter`: True
+- `save_safetensors`: True
+- `save_on_each_node`: False
+- `save_only_model`: False
+- `restore_callback_states_from_checkpoint`: False
+- `no_cuda`: False
+- `use_cpu`: False
+- `use_mps_device`: False
+- `seed`: 42
+- `data_seed`: None
+- `jit_mode_eval`: False
+- `use_ipex`: False
+- `bf16`: False
+- `fp16`: True
+- `fp16_opt_level`: O1
+- `half_precision_backend`: auto
+- `bf16_full_eval`: False
+- `fp16_full_eval`: False
+- `tf32`: None
+- `local_rank`: 0
+- `ddp_backend`: None
+- `tpu_num_cores`: None
+- `tpu_metrics_debug`: False
+- `debug`: []
+- `dataloader_drop_last`: False
+- `dataloader_num_workers`: 0
+- `dataloader_prefetch_factor`: None
+- `past_index`: -1
+- `disable_tqdm`: False
+- `remove_unused_columns`: True
+- `label_names`: None
+- `load_best_model_at_end`: False
+- `ignore_data_skip`: False
+- `fsdp`: []
+- `fsdp_min_num_params`: 0
+- `fsdp_config`: {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}
+- `fsdp_transformer_layer_cls_to_wrap`: None
+- `accelerator_config`: {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None}
+- `deepspeed`: None
+- `label_smoothing_factor`: 0.0
+- `optim`: adamw_torch
+- `optim_args`: None
+- `adafactor`: False
+- `group_by_length`: False
+- `length_column_name`: length
+- `ddp_find_unused_parameters`: None
+- `ddp_bucket_cap_mb`: None
+- `ddp_broadcast_buffers`: False
+- `dataloader_pin_memory`: True
+- `dataloader_persistent_workers`: False
+- `skip_memory_metrics`: True
+- `use_legacy_prediction_loop`: False
+- `push_to_hub`: False
+- `resume_from_checkpoint`: None
+- `hub_model_id`: None
+- `hub_strategy`: every_save
+- `hub_private_repo`: None
+- `hub_always_push`: False
+- `hub_revision`: None
+- `gradient_checkpointing`: 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
+- `liger_kernel_config`: None
+- `eval_use_gather_object`: False
+- `average_tokens_across_devices`: False
+- `prompts`: None
+- `batch_sampler`: batch_sampler
+- `multi_dataset_batch_sampler`: round_robin
+- `router_mapping`: {}
+- `learning_rate_mapping`: {}
+
+</details>
+
+### Training Logs
+| Epoch  | Step | Training Loss | similarity_spearman_cosine |
+|:------:|:----:|:-------------:|:--------------------------:|
+| 0.0286 | 10   | -             | 0.1359                     |
+| 0.0571 | 20   | -             | 0.1424                     |
+| 0.0857 | 30   | -             | 0.1525                     |
+| 0.1143 | 40   | -             | 0.1651                     |
+| 0.1429 | 50   | -             | 0.1759                     |
+| 0.1714 | 60   | -             | 0.1846                     |
+| 0.2    | 70   | -             | 0.1947                     |
+| 0.2286 | 80   | -             | 0.2056                     |
+| 0.2571 | 90   | -             | 0.2144                     |
+| 0.2857 | 100  | -             | 0.2298                     |
+| 0.3143 | 110  | -             | 0.2409                     |
+| 0.3429 | 120  | -             | 0.2526                     |
+| 0.3714 | 130  | -             | 0.2511                     |
+| 0.4    | 140  | -             | 0.2661                     |
+| 0.4286 | 150  | -             | 0.2664                     |
+| 0.4571 | 160  | -             | 0.2572                     |
+| 0.4857 | 170  | -             | 0.2804                     |
+| 0.5143 | 180  | -             | 0.2885                     |
+| 0.5429 | 190  | -             | 0.2885                     |
+| 0.5714 | 200  | -             | 0.2933                     |
+| 0.6    | 210  | -             | 0.3037                     |
+| 0.6286 | 220  | -             | 0.3163                     |
+| 0.6571 | 230  | -             | 0.3197                     |
+| 0.6857 | 240  | -             | 0.3275                     |
+| 0.7143 | 250  | -             | 0.3238                     |
+| 0.7429 | 260  | -             | 0.3262                     |
+| 0.7714 | 270  | -             | 0.3295                     |
+| 0.8    | 280  | -             | 0.3129                     |
+| 0.8286 | 290  | -             | 0.3491                     |
+| 0.8571 | 300  | -             | 0.3354                     |
+| 0.8857 | 310  | -             | 0.3448                     |
+| 0.9143 | 320  | -             | 0.3581                     |
+| 0.9429 | 330  | -             | 0.3658                     |
+| 0.9714 | 340  | -             | 0.3386                     |
+| 1.0    | 350  | -             | 0.3503                     |
+| 1.0286 | 360  | -             | 0.3533                     |
+| 1.0571 | 370  | -             | 0.3604                     |
+| 1.0857 | 380  | -             | 0.3624                     |
+| 1.1143 | 390  | -             | 0.3549                     |
+| 1.1429 | 400  | -             | 0.3594                     |
+| 1.1714 | 410  | -             | 0.3747                     |
+| 1.2    | 420  | -             | 0.3465                     |
+| 1.2286 | 430  | -             | 0.3378                     |
+| 1.2571 | 440  | -             | 0.3809                     |
+| 1.2857 | 450  | -             | 0.3856                     |
+| 1.3143 | 460  | -             | 0.3522                     |
+| 1.3429 | 470  | -             | 0.3987                     |
+| 1.3714 | 480  | -             | 0.3847                     |
+| 1.4    | 490  | -             | 0.3688                     |
+| 1.4286 | 500  | 0.1157        | 0.3937                     |
+| 1.4571 | 510  | -             | 0.3857                     |
+| 1.4857 | 520  | -             | 0.4039                     |
+| 1.5143 | 530  | -             | 0.3913                     |
+| 1.5429 | 540  | -             | 0.3900                     |
+| 1.5714 | 550  | -             | 0.3497                     |
+| 1.6    | 560  | -             | 0.3613                     |
+| 1.6286 | 570  | -             | 0.4067                     |
+| 1.6571 | 580  | -             | 0.4016                     |
+| 1.6857 | 590  | -             | 0.3954                     |
+| 1.7143 | 600  | -             | 0.3947                     |
+| 1.7429 | 610  | -             | 0.3864                     |
+| 1.7714 | 620  | -             | 0.4194                     |
+| 1.8    | 630  | -             | 0.3985                     |
+| 1.8286 | 640  | -             | 0.4003                     |
+| 1.8571 | 650  | -             | 0.4061                     |
+| 1.8857 | 660  | -             | 0.4074                     |
+| 1.9143 | 670  | -             | 0.4004                     |
+| 1.9429 | 680  | -             | 0.4022                     |
+| 1.9714 | 690  | -             | 0.4056                     |
+| 2.0    | 700  | -             | 0.3991                     |
+| 2.0286 | 710  | -             | 0.3944                     |
+| 2.0571 | 720  | -             | 0.3952                     |
+| 2.0857 | 730  | -             | 0.4014                     |
+| 2.1143 | 740  | -             | 0.3846                     |
+| 2.1429 | 750  | -             | 0.3719                     |
+| 2.1714 | 760  | -             | 0.4073                     |
+| 2.2    | 770  | -             | 0.3828                     |
+| 2.2286 | 780  | -             | 0.3858                     |
+| 2.2571 | 790  | -             | 0.4114                     |
+| 2.2857 | 800  | -             | 0.3930                     |
+| 2.3143 | 810  | -             | 0.3845                     |
+| 2.3429 | 820  | -             | 0.4053                     |
+| 2.3714 | 830  | -             | 0.3582                     |
+| 2.4    | 840  | -             | 0.3848                     |
+| 2.4286 | 850  | -             | 0.4139                     |
+| 2.4571 | 860  | -             | 0.3609                     |
+| 2.4857 | 870  | -             | 0.4122                     |
+| 2.5143 | 880  | -             | 0.4101                     |
+| 2.5429 | 890  | -             | 0.4261                     |
+
+
+### Framework Versions
+- Python: 3.11.9
+- Sentence Transformers: 5.1.0
+- Transformers: 4.53.3
+- PyTorch: 2.5.1
+- Accelerate: 1.10.0
+- Datasets: 2.14.4
+- 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",
+}
+```
+
+<!--
+## 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 @@
+{
+  "architectures": [
+    "BertModel"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 1024,
+  "initializer_range": 0.02,
+  "intermediate_size": 4096,
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 16,
+  "num_hidden_layers": 24,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "torch_dtype": "float32",
+  "transformers_version": "4.53.3",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
+}

config_sentence_transformers.json

@@ -0,0 +1,14 @@
+{
+  "model_type": "SentenceTransformer",
+  "__version__": {
+    "sentence_transformers": "5.1.0",
+    "transformers": "4.53.3",
+    "pytorch": "2.5.1"
+  },
+  "prompts": {
+    "query": "",
+    "document": ""
+  },
+  "default_prompt_name": null,
+  "similarity_fn_name": "cosine"
+}

model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:faa9fd1420b2d60582e5e578fe49d3a281c0b0575ad2667ab4693179f64142a2
+size 1340612432

modules.json

@@ -0,0 +1,20 @@
+[
+  {
+    "idx": 0,
+    "name": "0",
+    "path": "",
+    "type": "sentence_transformers.models.Transformer"
+  },
+  {
+    "idx": 1,
+    "name": "1",
+    "path": "1_Pooling",
+    "type": "sentence_transformers.models.Pooling"
+  },
+  {
+    "idx": 2,
+    "name": "2",
+    "path": "2_Normalize",
+    "type": "sentence_transformers.models.Normalize"
+  }
+]

sentence_bert_config.json

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

special_tokens_map.json

@@ -0,0 +1,37 @@
+{
+  "cls_token": {
+    "content": "[CLS]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "mask_token": {
+    "content": "[MASK]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "[PAD]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "sep_token": {
+    "content": "[SEP]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "unk_token": {
+    "content": "[UNK]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer_config.json

@@ -0,0 +1,56 @@
+{
+  "added_tokens_decoder": {
+    "0": {
+      "content": "[PAD]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "100": {
+      "content": "[UNK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "101": {
+      "content": "[CLS]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "102": {
+      "content": "[SEP]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "103": {
+      "content": "[MASK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "clean_up_tokenization_spaces": true,
+  "cls_token": "[CLS]",
+  "do_lower_case": true,
+  "extra_special_tokens": {},
+  "mask_token": "[MASK]",
+  "model_max_length": 512,
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "BertTokenizer",
+  "unk_token": "[UNK]"
+}