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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+---
+base_model: sentence-transformers/all-mpnet-base-v2
+library_name: setfit
+metrics:
+- accuracy
+pipeline_tag: text-classification
+tags:
+- setfit
+- sentence-transformers
+- text-classification
+- generated_from_setfit_trainer
+widget:
+- text: 'There is, of course, much to digest. I hope that these rubes and those who
+    incited them are locked up, along with the fake electors and their advisors, and
+    those who conspired to convince elections officials to violate the law, and finally,
+    those who have and continue to threaten true Americans just doing their constitution-based
+    jobs. One thing jumps out. Judge McFadden, who seems willing to demand that the
+    government prove its case beyond a reasonable doubt, also seems to be willing
+    to sentence convicted lawbreakers to serious time. That he acquitted the guy who
+    claimed the police let him gives me confidence that these are not sham trials.The
+    thing that I haven’t heard much about are the firings, trials, convictions, and
+    sentences of those LEOs who aided and abetted the traitors. That would include
+    the cops who let Mr. Martin enter the Capitol, and those on Trump’s secret service
+    detail who may have been aiding Trump’s efforts to foment a riot.
+
+    '
+- text: 'Both Vladimir Putin and Yevgeny Prigozhin are international war criminals.Both
+    also undermined US elections in favor of Trump.<a href="https://www.reuters.com/world/us/russias-prigozhin-admits-interfering-us-elections-2022-11-07"
+    target="_blank">https://www.reuters.com/world/us/russias-prigozhin-admits-interfering-us-elections-2022-11-07</a>/
+
+    '
+- text: 'Aaron 100 percent. citizens united was a huge win for Russian citizen Vlad
+    and Chinese citizen Xi.
+
+    '
+- text: 'George Corsetti “Russia did NOT interfere in the 2016 election.”Sorry George,
+    this is not true. Read the Russia report, it details more than a dozen felonies
+    committed by TFG and his family and Campaign personnel during the 2015/16 Campaign
+    along with evidence of Russian hackers and agents directly interfering in the
+    2016 election.
+
+    '
+- text: 'Ms.Renkl does a nice job here, yet only hints at the decimation to public
+    schools, libraries, governance, and healthcare by Bill Lee and the Red Legislators
+    .Tennessee has a $50 B per year budget, $25B 0f this comes from federal government.
+    It is a  wealthy state ranking in the top 16 economically and 3rd in fiscal stability
+    ( USNews).The stability comes from the egregious, wrongheaded use of federal monies
+    earmarked for public schools and healthcare,Governor controls all Federal  school
+    and healthcare dollars rather than decimating to citizens. The US tax payer is
+    subsidizing this state as the Governor and legislators deny ACA low cost insurance
+    to WORKING poor and the Governor used for unrelated purposes. . Federal public
+    school monies are used to subsidize private schools and Lee’s pet project:private
+    DeVos/Hillsdale religious charter schools. US tax payers should be made aware
+    of the mishandling of our tax dollars in support of the ultra conservative regime.
+
+    '
+inference: true
+model-index:
+- name: SetFit with sentence-transformers/all-mpnet-base-v2
+  results:
+  - task:
+      type: text-classification
+      name: Text Classification
+    dataset:
+      name: Unknown
+      type: unknown
+      split: test
+    metrics:
+    - type: accuracy
+      value: 0.8
+      name: Accuracy
+---
+
+# SetFit with sentence-transformers/all-mpnet-base-v2
+
+This is a [SetFit](https://github.com/huggingface/setfit) model that can be used for Text Classification. This SetFit model uses [sentence-transformers/all-mpnet-base-v2](https://huggingface.co/sentence-transformers/all-mpnet-base-v2) as the Sentence Transformer embedding model. 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 body:** [sentence-transformers/all-mpnet-base-v2](https://huggingface.co/sentence-transformers/all-mpnet-base-v2)
+- **Classification head:** a [LogisticRegression](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html) instance
+- **Maximum Sequence Length:** 384 tokens
+- **Number of Classes:** 2 classes
+<!-- - **Training Dataset:** [Unknown](https://huggingface.co/datasets/unknown) -->
+<!-- - **Language:** Unknown -->
+<!-- - **License:** Unknown -->
+
+### 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                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                  |
+|:------|:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| yes   | <ul><li>'Ken The FBI and DOJ should open an investigation into Russian interference in the 2022 election.\n'</li><li>"But you still haven't mentioned the crucial upcoming elections in Czechia, which cold alter the  balance in Eastern/Central Europe.\n"</li><li>'factsonly She won the 2022 election.  She beat at least one Dem primary opponent and beat her Republican opponent by a decent margin in the general election.\n'</li></ul>                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                          |
+| no    | <ul><li>"Sean Who needs a source when you have Trump's well documented relationship with Putin?\n"</li><li>'After a years-long crime spree by Donald Trump, his children,  and his accomplices, we\'re still waiting for indictments.  Why?  Why is this so hard?  The man who said, "Russia, if you\'re listening..." has openly and loudly ignored the law, the constitution, precedent, tradition, common decency and common sense for years, and yet we\'re still waiting for some part of his manifold misdeeds to land him in the docket.  Again, why?  Why?!  There is so much evidence against him, it is impossible to see why he hasn\'t been arrested and charged for sedition, insurrection, money laundering, violating the Espionage Act, the Presidential Records Act,  payoffs to hide his adulterous affairs, and other crimes up to and including attempting to mastermind a coup.  There is no Witch Hunt.  There\'s a just an inexplicably as-yet unindicted multiple felon who continues to grift dollars out of his hoodwinked followers.I am beginning to wonder if the DOJ has forgotten what upholding the law means, or if it is just the person who runs the DOJ.Donald Trump is not the only person to have questions that need to be answered: so does Merrick Garland -- and foremost amongst them is, \'What\'s the hold up?\'\n'</li><li>"Most writers just imitate what they've read. They repeat formulas and replicate familiar sentence structures. Most TV could be written by ChatGPT. So it seems like ChatGPT writes pretty much like 90 percent of writers in a creative writing class. And 90 percent of readers don't want writing that pushes creative limits—look at the success of Colleen Hoover. I'd don't see why something like ChatGPT couldn't write her books. I don't mean that to be insulting—I do doubt an AI book would touch hearts as hers apparently do because it would lack her ineffable humanity. But even if an AI novel became a popular success, it wouldn't mean that AI had bested Nabokov or Woolf or DFW or … well, it's a very large list, and I'm not even claiming these as anything more than the first three whose names came to mind.(And in answer to Elon, sure, if I had to choose, I guess I'd rather live under the rule of Marcus Aurelius than Caligula's. But in fact I wouldn't get a vote on that, and I'd rather not live under an emperor at all.)\n"</li></ul> |
+
+## Evaluation
+
+### Metrics
+| Label   | Accuracy |
+|:--------|:---------|
+| **all** | 0.8      |
+
+## 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("davidadamczyk/setfit-model-2")
+# Run inference
+preds = model("Aaron 100 percent. citizens united was a huge win for Russian citizen Vlad and Chinese citizen Xi.
+")
+```
+
+<!--
+### 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   | 6   | 80.325 | 276 |
+
+| Label | Training Sample Count |
+|:------|:----------------------|
+| no    | 18                    |
+| yes   | 22                    |
+
+### Training Hyperparameters
+- batch_size: (16, 16)
+- num_epochs: (1, 1)
+- max_steps: -1
+- sampling_strategy: oversampling
+- num_iterations: 120
+- body_learning_rate: (2e-05, 2e-05)
+- head_learning_rate: 2e-05
+- loss: CosineSimilarityLoss
+- distance_metric: cosine_distance
+- margin: 0.25
+- end_to_end: False
+- use_amp: False
+- warmup_proportion: 0.1
+- l2_weight: 0.01
+- seed: 42
+- eval_max_steps: -1
+- load_best_model_at_end: False
+
+### Training Results
+| Epoch  | Step | Training Loss | Validation Loss |
+|:------:|:----:|:-------------:|:---------------:|
+| 0.0017 | 1    | 0.4496        | -               |
+| 0.0833 | 50   | 0.1797        | -               |
+| 0.1667 | 100  | 0.0034        | -               |
+| 0.25   | 150  | 0.0003        | -               |
+| 0.3333 | 200  | 0.0002        | -               |
+| 0.4167 | 250  | 0.0002        | -               |
+| 0.5    | 300  | 0.0001        | -               |
+| 0.5833 | 350  | 0.0001        | -               |
+| 0.6667 | 400  | 0.0001        | -               |
+| 0.75   | 450  | 0.0001        | -               |
+| 0.8333 | 500  | 0.0001        | -               |
+| 0.9167 | 550  | 0.0001        | -               |
+| 1.0    | 600  | 0.0001        | -               |
+
+### Framework Versions
+- Python: 3.10.13
+- SetFit: 1.1.0
+- Sentence Transformers: 3.0.1
+- Transformers: 4.45.2
+- PyTorch: 2.4.0+cu124
+- Datasets: 2.21.0
+- Tokenizers: 0.20.0
+
+## 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

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+{
+  "_name_or_path": "sentence-transformers/all-mpnet-base-v2",
+  "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": "4.45.2",
+  "vocab_size": 30527
+}

config_sentence_transformers.json

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+{
+  "__version__": {
+    "sentence_transformers": "3.0.1",
+    "transformers": "4.45.2",
+    "pytorch": "2.4.0+cu124"
+  },
+  "prompts": {},
+  "default_prompt_name": null,
+  "similarity_fn_name": null
+}

config_setfit.json

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+{
+  "normalize_embeddings": false,
+  "labels": [
+    "no",
+    "yes"
+  ]
+}

model.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:de392552d940712a1d5c4068d4e44795f067b60b78704736015c5a02b2edeb92
+size 437967672

model_head.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:bbe3b25b490465dd08ca78edccf63dd2b7b5b483b4ee07db886ed8fc64ed5a5f
+size 7023

modules.json

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

sentence_bert_config.json

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+{
+  "max_seq_length": 384,
+  "do_lower_case": false
+}

special_tokens_map.json

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+{
+  "bos_token": {
+    "content": "<s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "cls_token": {
+    "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

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+{
+  "added_tokens_decoder": {
+    "0": {
+      "content": "<s>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "1": {
+      "content": "<pad>",
+      "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
+    },
+    "3": {
+      "content": "<unk>",
+      "lstrip": false,
+      "normalized": true,
+      "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": false,
+  "cls_token": "<s>",
+  "do_lower_case": true,
+  "eos_token": "</s>",
+  "mask_token": "<mask>",
+  "max_length": 128,
+  "model_max_length": 384,
+  "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]"
+}