Add SetFit model

1_Pooling/config.json

@@ -0,0 +1,10 @@
+{
+  "word_embedding_dimension": 768,
+  "pooling_mode_cls_token": false,
+  "pooling_mode_mean_tokens": true,
+  "pooling_mode_max_tokens": false,
+  "pooling_mode_mean_sqrt_len_tokens": false,
+  "pooling_mode_weightedmean_tokens": false,
+  "pooling_mode_lasttoken": false,
+  "include_prompt": true
+}

README.md

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+---
+language: en
+license: apache-2.0
+library_name: setfit
+tags:
+- setfit
+- sentence-transformers
+- text-classification
+- generated_from_setfit_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+widget:
+- text: not so jolly dolly so, last weekend my wife and i watched the oppen part of
+    the "barbenheimer" 2023 box-office two-headed monster and this week it was barbie's
+    turn. from the little i'd incidentally read in advance about the day-glo billion
+    dollar blockbuster, i was expecting some kind of retro-cool, existentialist, post-modernist
+    satire on the battle of the sexes, consumerism and childhood buffed up with a
+    little diversity along the way, but somehow with all these ducks lined up in a
+    row, i felt the film missed the mark.it starts brightly with eye-candy sets in
+    fifty shades of pink as we're introduced to margot robbie's barbie in her barbie-world
+    of alternative barbies, see through doll's houses and their various incomplete
+    consumer goods, for example our girl has her daily dry-shower and drinks non-existent
+    tea. everything appears to be perfect in her / their perfect world, unless you're
+    the boyfriend ken, here also in a variety of forms, all doomed to exist only in
+    barbie's slipstream and so experience recurring frustration at getting precisely
+    nowhere, all the time, with the object of his / their, i hesitate to call it,
+    desire.then things start to go wrong for robbie's "stereotypical" barbie. she
+    thinks of death and starts to malfunction and after a visit to kate mckinnon's
+    weird barbie, a concept i have to say i didn't get at all, she determines to go
+    to the real world to connect with the disillusioned mattel employee, played by
+    america ferrera, whose negativity, channelled through her disinterested daughter
+    ariana greenblatt, is upsetting the living doll's equilibrium. ryan gosling's
+    wheedling ken is also along for the ride and stows away in her penelope pitstop-mobile
+    and together they head for l. a., where ferrera lives, the headquarters of the
+    manufacturer mattel.for me, the film went downhill fast from there with ken's
+    head getting messed-up with perceptions of patriarchy while barbie has a meltdown
+    over her identity-crisis. there are unfunny, over-played scenes where barbie experiences
+    humiliation at the hands of greenblatt and her school chums, traipses down to
+    mattel hq to confront the all-male board of directors headed by a mis-cast will
+    ferrell as the company ceo, before returning to barbie-world with ferrera and
+    greenblatt in tow to take down ken's new-model kendom where outdated male-superiority
+    is literally back in the saddle.i have to admit, i got very bored, very soon with
+    this empty, supposedly satirical high-concept, fantasy-comedy. a world box-office
+    of 1.5 billion dollars and eight oscar nominations actually makes me wonder if
+    i've not switched places too with barbie-world as i'm afraid nothing about the
+    movie, including the soundtrack and unsuccessful attempts at either comedy or
+    pathos (especially when they wheel in rhea perlman as the doll's now-enlightened
+    creator) all missing me by miles.when at one point, all her namesakes shout "go
+    barbie!', i must admit i was with them 100% but for completely different reasons.
+- text: way better than expected i was amongst the people who thought they saw a majority
+    of this film based on all of the filming stills posted on the bird app in 2022.
+    i still wanted to see it. something about their perfect neon rollerblading outfits.
+    i saw one preview and wasn't sure what the plot was going to be, i didn't care,
+    i still wanted to see it. i wasn't expecting it to be amazing, but amazing it
+    was. well done!! margot really knocked it out of the dollhouse. ryan i'll never
+    look at the same way way again. this 1980s barbie superman is very pleased. it
+    won't be long until the opening dance scene is all over the clock app. i haven't
+    felt so compelled to learn choreography since michael jackson's thriller. also,
+    girls rule. sorry, ken. 12 out of 24 found this helpful. was this review helpful?
+    sign in to vote. permalink
+- text: 'anyone remember the film "life size"? from a far, i can see why people would
+    absolutely hate this movie. just the concept of "barbie: the movie" is enough
+    to make people feel like the art of cinema has been compromised by corporate america.
+    but, as a whole, this movie was very well received. it made over a billion dollars
+    at the box-office and was nominated for 8 oscars including "best picture", so
+    clearly it some people really liked it.there is a lot to enjoy in this film. the
+    movie does a good job with poking fun at the barbie brand without it feeling too
+    much like a spoof. this is a comedy, so the fact that the film is really funny
+    is kind of an important element. understandably comedy is a subjective thing,
+    so all i can say is for me, i laughed out loud several times through the movie.
+    the movie is clever in how it treats its "worldbuilding" and nicely avoids any
+    firm answers about how this world works. because, yeah, if you think about that
+    sort of stuff in the film there is a lot that doesn''t add up.it is nice that
+    they don''t spend too much time in "the real world" and focus on the creative
+    fun of "barbie world". the movie is more visually unique and can do more gags
+    when that is the case.when the movie is focusing on being a bizarre comedy, that
+    is when some of the best and most memorable things happen. when it tries to have
+    a more serious message, that is where it loses some momentum. don''t misunderstand
+    me, the movie needs some serious stuff in order to make the comedy work. and the
+    stuff with ugly betty and her daughter is good emotional stuff. but towards the
+    end, they realize that barbie needs to have a character arc and feel like they
+    tack one on last second. there are some very funny jokes towards the end, but
+    it does become a little repetitive and the message feels heavy handed by the 5th
+    time it''s brought up. side note: i wanted a cameo from the voice actress of barbie,
+    kelly sheridan, but she wasn''t there.i will emphasize this because hollywood
+    will learn all the wrong lessons from this movie''s success. we do not want a
+    "polly pocket" movie or an "uno" movie. what made this film a success, beyond
+    its brand or its marketing campaign, is that it was uniquely greta gerwig''s vision.
+    the movie wasn''t concerned with mass audience appeal, it would tell jokes that
+    they thought were funny and hoped others would enjoy as well. if you want to duplicate
+    barbie''s success, give creative people control to make some out there stuff.wrapped
+    in plastic, it''s fantastic.'
+- text: great expectations this film exceeded all of my expectations a n d i was looking
+    forward to seeing it. i wonder about any parents who might bring their children
+    to see it expecting something quite different from what this film is. one hour
+    fifty four minutes of fun from beginning to end. satire, sarcasm , humor at every
+    turn. production values and acting off the charts good. i can't believe mattel
+    let them make the movie with complete artistic freedom. think of nicole kidman
+    in the amc promo before a movie starts and says, " somehow heartbreak feels good
+    in a place like this ". well somehow watching a silly spoof like this movie feels
+    great all the way through and even afterwards. i loved it and i am not surprised
+    at the huge box office , this movie rocks. 4 out of 11 found this helpful. was
+    this review helpful? sign in to vote. permalink
+- text: decent i like what they did with this movie and the characters with its combining
+    the barbie world and the real world. barbie starts getting "vibes" and has to
+    go into the real world to find the girl who played with her to set things right
+    and winds up in the mattel headquarters. something resembling chaos ensues. ken
+    joins her and winds up causing further damage. i like what they do in various
+    stages of the story and with the characters. it was overall a very pleasant surprise
+    snd a good movie with a good cast. margot robbie, ryan gosling, america ferrera,
+    and will ferrell were all good in their roles. if you are a movie and/or a barbie
+    fan, you will love this movie.*** out of **** 2 out of 7 found this helpful. was
+    this review helpful? sign in to vote. permalink
+pipeline_tag: text-classification
+inference: true
+model-index:
+- name: SetFit
+  results:
+  - task:
+      type: text-classification
+      name: Text Classification
+    dataset:
+      name: data/raw/barbie.jsonl
+      type: unknown
+      split: test
+    metrics:
+    - type: accuracy
+      value: 0.8811688311688312
+      name: Accuracy
+    - type: precision
+      value: 0.9952114924181963
+      name: Precision
+    - type: recall
+      value: 0.8757022471910112
+      name: Recall
+    - type: f1
+      value: 0.9316398954053045
+      name: F1
+---
+
+# SetFit
+
+This is a [SetFit](https://github.com/huggingface/setfit) model that can be used for Text Classification. A [LogisticRegression](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html) instance is used for classification.
+
+The model has been trained using an efficient few-shot learning technique that involves:
+
+1. Fine-tuning a [Sentence Transformer](https://www.sbert.net) with contrastive learning.
+2. Training a classification head with features from the fine-tuned Sentence Transformer.
+
+## Model Details
+
+### Model Description
+- **Model Type:** SetFit
+<!-- - **Sentence Transformer:** [Unknown](https://huggingface.co/unknown) -->
+- **Classification head:** a [LogisticRegression](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html) instance
+- **Maximum Sequence Length:** 512 tokens
+- **Number of Classes:** 2 classes
+<!-- - **Training Dataset:** [Unknown](https://huggingface.co/datasets/unknown) -->
+- **Language:** en
+- **License:** apache-2.0
+
+### Model Sources
+
+- **Repository:** [SetFit on GitHub](https://github.com/huggingface/setfit)
+- **Paper:** [Efficient Few-Shot Learning Without Prompts](https://arxiv.org/abs/2209.11055)
+- **Blogpost:** [SetFit: Efficient Few-Shot Learning Without Prompts](https://huggingface.co/blog/setfit)
+
+### Model Labels
+| Label    | Examples                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                        |
+|:---------|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| negative | <ul><li>"definitely not for kids i've just taken 2 nieces, 9 and 14, to see barbie. they both hated it... really, really hated it!! and, me: i'm just stunned. i've no idea what i've just seen.if barbie is meant to be a dark satire, it's alright. if it's meant to be a kids movie, it's unconscionably bad. and, i'm totally confused which type of movie it's supposed to be. what the literal heck is going on!!if you're looking for a twenty first century dark cultural satire, you're at least in your twenties, you've an open mind, this is your movie... maybe. if you're looking for a movie to take your kids to, before getting ice cream, this is absolutely not the movie you're looking for. my advice: give barbie a miss and go straight for the ice cream. you will be so much happier. i wish i had. 15 out of 30 found this helpful. was this review helpful? sign in to vote. permalink"</li><li>"the most political movie i've ever seen. i loved the effort with the sets and the fun outfits. i also really enjoyed the ads threw out movie.i was really enjoying this movie but then it started getting really political, i was kind of fine with it but then they started making politics the whole story line and so it was really no longer a fun movie. after the movie finished i just ended up leaving miserable and like i waisted money... how is a family meant to enjoy this?? i can't see any 13 year old understanding anything they talk about.also they want to talk about how being a human is hard and that were not perfect but then they hire someone to play a teen girl who has perfect hair and skin. a bit of a confusing message? 180 out of 276 found this helpful. was this review helpful? sign in to vote. permalink"</li><li>"mediocre at best i had high expectations as a result of the media press, however these we're crushed from the start.first of all, i did expect it to feel a little generic and cheesy although all i could feel throughout the movie is that it was rushed and cheap. the storyline was dry and over-political.i'd have liked to see more lgbtq+ representation and breaking stereotypes, as it felt like just a generic film. even the barbies were considered stereotypes!comedy throughout was limited and wasn't engaging at all - sometimes trying too hard to emphasise feminism and going too far in the opposite direction to the world is heading in (i'm not encouraging patriarchy).however, i did find the music quite good (especially the billie eilish song) and did redeem the movie a little bit.in summary, the movie was mediocre at best and there's not much to discuss. it felt like a cheap version of movies like spirited and the greatest showman with no real emotion."</li></ul>                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                            |
+| positive | <ul><li>"fabulously done so, i didn't have that much of a high expectation going in to see this because i really wasn't sure what is was going to be. i grew up playing barbie's and have watched the animated films many times with my kids.the movie from start to finish is so thoughtfully executed. it's for everyone, but mainly young girls need to see this. it's a great reminder of how special we are as women and how special all of us are individually as a person and the life we get to experience.another fantastic element is adding a very 90s feel to the film. you will laugh like you used to laugh when fun comedies would come out in theatre's years ago. i haven't seen just a good comedy with heart in years.i brought my 7yr old and we dressed up for it too. i wanted her to see me comfortable in my own skin and her as well and the film touches on that. it's suited for any age, regardless of the rating.i don't give high ratings like this to films usually, as i find small things usually that i wish had been addressed more... but not in barbie. what a fun movie and a great time you'll have watching this in theatre (or at home) knowing it's your childhood come to life."</li><li>"sure, life in plastic is fantastic but only in barbieland the barbie movie was unexpected. it was a colorful and clever ride in the cinema. i was not expecting all the deep emotions that the film gave. life is not all about perfection, which a lot of people wants to constantly achieve these days, imperfections is what identifies us and that's okay.i'm a visual kind of cinema goer and i have the say that dance sequence (dance the night) and the scene where barbie and ken where traveling to the real world were amazing. kudos to the creative team behind it, i absolutely adore the set.greta gerwig and her team delivered a visual spectacle with a heart. 10 out of 28 found this helpful. was this review helpful? sign in to vote. permalink"</li><li>"funny with social commentary barbie (margot robbie) lives in barbieland. ken (ryan gosling) is always desperate for her attention. all the ken and barbie dolls live in a happy matriarchy unaware of the real world. out of the blue, barbie starts pondering death and her existence. weird barbie (kate mckinnon) tells her that she has opened a portal to the real world and must fix whatever is her real world problem before she can return to her perfect self. she and stowaway ken find the real world completely different than their expectations. mattel ceo (will ferrell) insists on putting her back in the box. mattel secretary gloria (america ferrera) had caused the problem by drawing new forms of barbie.first, i love the premise and i love the 2001 opening. the start is a lot funnier than i expected. margot robbie is great and ryan gosling is hilarious. it's a great start in barbieland. the first moments in la is a little too much. quite frankly, barbie and ken would not stand out at venice beach. the male leering is good enough. they don't need to do the stereotype abusive guys. the real world should be realistic. barbie and ken would be better fishes out of the water in a recognizable regular world. the more average the real world is, the better it is for the characters to showcase their outrageousness.mattel is fun and i like the ridiculous silliness. will ferrell is a good way to show their outrageous quality. the movie has a lot of social commentary and that aspect does threaten to overwhelm it. the last act has some wonky moments as the movie tries to wrap its arms around the heavier social discussions. i would like to keep that more contained and concentrate on the mother daughter relationships. it's gloria and sasha, but it's also ruth and barbara. that's a perfect way to end the movie. i do like the montage idea, but i didn't realize what it was doing initially. it would have been fine to do that for the closing credits. all in all, this is a funny engaging movie and it's able to deal with some of the tougher social material."</li></ul> |
+
+## Evaluation
+
+### Metrics
+| Label   | Accuracy | Precision | Recall | F1     |
+|:--------|:---------|:----------|:-------|:-------|
+| **all** | 0.8812   | 0.9952    | 0.8757 | 0.9316 |
+
+## Uses
+
+### Direct Use for Inference
+
+First install the SetFit library:
+
+```bash
+pip install setfit
+```
+
+Then you can load this model and run inference.
+
+```python
+from setfit import SetFitModel
+
+# Download from the 🤗 Hub
+model = SetFitModel.from_pretrained("carlesoctav/SentimentClassifierBarbieDune-8shot")
+# Run inference
+preds = model("decent i like what they did with this movie and the characters with its combining the barbie world and the real world. barbie starts getting \"vibes\" and has to go into the real world to find the girl who played with her to set things right and winds up in the mattel headquarters. something resembling chaos ensues. ken joins her and winds up causing further damage. i like what they do in various stages of the story and with the characters. it was overall a very pleasant surprise snd a good movie with a good cast. margot robbie, ryan gosling, america ferrera, and will ferrell were all good in their roles. if you are a movie and/or a barbie fan, you will love this movie.*** out of **** 2 out of 7 found this helpful. was this review helpful? sign in to vote. permalink")
+```
+
+<!--
+### Downstream Use
+
+*List how someone could finetune this model on their own dataset.*
+-->
+
+<!--
+### Out-of-Scope Use
+
+*List how the model may foreseeably be misused and address what users ought not to do with the model.*
+-->
+
+<!--
+## Bias, Risks and Limitations
+
+*What are the known or foreseeable issues stemming from this model? You could also flag here known failure cases or weaknesses of the model.*
+-->
+
+<!--
+### Recommendations
+
+*What are recommendations with respect to the foreseeable issues? For example, filtering explicit content.*
+-->
+
+## Training Details
+
+### Training Set Metrics
+| Training set | Min | Median   | Max  |
+|:-------------|:----|:---------|:-----|
+| Word count   | 112 | 234.1953 | 1424 |
+
+| Label    | Training Sample Count |
+|:---------|:----------------------|
+| negative | 64                    |
+| positive | 64                    |
+
+### Training Hyperparameters
+- batch_size: (16, 16)
+- num_epochs: (1, 1)
+- max_steps: -1
+- sampling_strategy: oversampling
+- body_learning_rate: (2e-05, 1e-05)
+- head_learning_rate: 0.01
+- loss: CosineSimilarityLoss
+- distance_metric: cosine_distance
+- margin: 0.25
+- end_to_end: False
+- use_amp: False
+- warmup_proportion: 0.1
+- seed: 42
+- eval_max_steps: -1
+- load_best_model_at_end: True
+
+### Training Results
+| Epoch   | Step    | Training Loss | Validation Loss |
+|:-------:|:-------:|:-------------:|:---------------:|
+| 0.0019  | 1       | 0.3627        | -               |
+| 0.0962  | 50      | 0.0007        | -               |
+| 0.1923  | 100     | 0.1003        | -               |
+| 0.2885  | 150     | 0.0001        | -               |
+| 0.3846  | 200     | 0.0001        | -               |
+| 0.4808  | 250     | 0.0001        | -               |
+| 0.5769  | 300     | 0.0001        | -               |
+| 0.6731  | 350     | 0.0           | -               |
+| 0.7692  | 400     | 0.0001        | -               |
+| 0.8654  | 450     | 0.0           | -               |
+| 0.9615  | 500     | 0.0           | -               |
+| **1.0** | **520** | **-**         | **0.2312**      |
+
+* The bold row denotes the saved checkpoint.
+### Framework Versions
+- Python: 3.10.11
+- SetFit: 1.0.3
+- Sentence Transformers: 2.5.1
+- Transformers: 4.38.2
+- PyTorch: 2.0.1
+- Datasets: 2.18.0
+- Tokenizers: 0.15.2
+
+## Citation
+
+### BibTeX
+```bibtex
+@article{https://doi.org/10.48550/arxiv.2209.11055,
+    doi = {10.48550/ARXIV.2209.11055},
+    url = {https://arxiv.org/abs/2209.11055},
+    author = {Tunstall, Lewis and Reimers, Nils and Jo, Unso Eun Seo and Bates, Luke and Korat, Daniel and Wasserblat, Moshe and Pereg, Oren},
+    keywords = {Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer and information sciences},
+    title = {Efficient Few-Shot Learning Without Prompts},
+    publisher = {arXiv},
+    year = {2022},
+    copyright = {Creative Commons Attribution 4.0 International}
+}
+```
+
+<!--
+## Glossary
+
+*Clearly define terms in order to be accessible across audiences.*
+-->
+
+<!--
+## Model Card Authors
+
+*Lists the people who create the model card, providing recognition and accountability for the detailed work that goes into its construction.*
+-->
+
+<!--
+## Model Card Contact
+
+*Provides a way for people who have updates to the Model Card, suggestions, or questions, to contact the Model Card authors.*
+-->

config.json

@@ -0,0 +1,24 @@
+{
+  "_name_or_path": "exp/Dune2Classifier64shot/step_520",
+  "architectures": [
+    "MPNetModel"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": 0,
+  "eos_token_id": 2,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "layer_norm_eps": 1e-05,
+  "max_position_embeddings": 514,
+  "model_type": "mpnet",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 1,
+  "relative_attention_num_buckets": 32,
+  "torch_dtype": "float32",
+  "transformers_version": "4.38.2",
+  "vocab_size": 30527
+}

config_sentence_transformers.json

@@ -0,0 +1,9 @@
+{
+  "__version__": {
+    "sentence_transformers": "2.0.0",
+    "transformers": "4.7.0",
+    "pytorch": "1.9.0+cu102"
+  },
+  "prompts": {},
+  "default_prompt_name": null
+}

config_setfit.json

@@ -0,0 +1,7 @@
+{
+  "normalize_embeddings": false,
+  "labels": [
+    "negative",
+    "positive"
+  ]
+}

model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ab2da127bc3afdc7345786f19cfa0b797c882977a7117012968c03179bc3ef7c
+size 437967672

model_head.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5c66f517ee30db960dece161133ad096dcab2caf2a1c58e8f6ca037aaa5470b5
+size 6997

modules.json

@@ -0,0 +1,14 @@
+[
+  {
+    "idx": 0,
+    "name": "0",
+    "path": "",
+    "type": "sentence_transformers.models.Transformer"
+  },
+  {
+    "idx": 1,
+    "name": "1",
+    "path": "1_Pooling",
+    "type": "sentence_transformers.models.Pooling"
+  }
+]

sentence_bert_config.json

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

special_tokens_map.json

@@ -0,0 +1,51 @@
+{
+  "bos_token": {
+    "content": "<s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "cls_token": {
+    "content": "<s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eos_token": {
+    "content": "</s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "mask_token": {
+    "content": "<mask>",
+    "lstrip": true,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "<pad>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "sep_token": {
+    "content": "</s>",
+    "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 +1,66 @@
+{
+  "added_tokens_decoder": {
+    "0": {
+      "content": "<s>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "1": {
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+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "2": {
+      "content": "</s>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "104": {
+      "content": "[UNK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "30526": {
+      "content": "<mask>",
+      "lstrip": true,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "bos_token": "<s>",
+  "clean_up_tokenization_spaces": true,
+  "cls_token": "<s>",
+  "do_basic_tokenize": true,
+  "do_lower_case": true,
+  "eos_token": "</s>",
+  "mask_token": "<mask>",
+  "max_length": 512,
+  "model_max_length": 512,
+  "never_split": null,
+  "pad_to_multiple_of": null,
+  "pad_token": "<pad>",
+  "pad_token_type_id": 0,
+  "padding_side": "right",
+  "sep_token": "</s>",
+  "stride": 0,
+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "MPNetTokenizer",
+  "truncation_side": "right",
+  "truncation_strategy": "longest_first",
+  "unk_token": "[UNK]"
+}