Upload SetFit section filter v0.2.0

1_Pooling/config.json

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

README.md

@@ -0,0 +1,213 @@
+---
+tags:
+- setfit
+- sentence-transformers
+- text-classification
+- generated_from_setfit_trainer
+widget:
+- text: Remote work is allowed provided the candidate has adequate home systems to
+    support the high internet data demands required for this position
+- text: · High School degree required, though we will consider candidates with equivalent
+    education or experience · Experience and verifiable competence in building systems
+    including HVAC, steam, gas, electrical, plumbing, repair work and/or equivalent
+    training are required
+- text: 'Beyond a light and engaging work environment, team members receive the following
+    benefits: Competitive salary PPO, HSA, and life insurance options 401k plan Open
+    vacation policy (discretionary time-off) DIY schedule for balancing personal and
+    professional responsibilities Equipment and tools for you to do your job  Tracker
+    is an equal opportunity employer'
+- text: Job descriptionA leading real estate firm in New Jersey is seeking an administrative
+    Marketing Coordinator with some experience in graphic design
+- text: QualificationsPortfolio of published articles (electronic and print)Excellent
+    writing and editing skills in EnglishEvidence of collaboration with clients and
+    within an office environmentHands-on experience with MailChimp, WordPress, SEO
+    tools, Microsoft Suite, and social mediaFamiliarity with web publicationsPhotography
+    skills preferred
+metrics:
+- accuracy
+pipeline_tag: text-classification
+library_name: setfit
+inference: true
+base_model: sentence-transformers/paraphrase-mpnet-base-v2
+---
+
+# SetFit with sentence-transformers/paraphrase-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/paraphrase-mpnet-base-v2](https://huggingface.co/sentence-transformers/paraphrase-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/paraphrase-mpnet-base-v2](https://huggingface.co/sentence-transformers/paraphrase-mpnet-base-v2)
+- **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:** 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                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                           |
+|:------|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| skip  | <ul><li>'Additional tasks may be assigned based on organizationalneeds and priorities.Culture:At the Kids’ Book Bank, we are a small but mighty team dedicated to getting more books to more children and fostering a love of reading'</li><li>'Founded in Sweden in 1907, today SKF is publicly traded on the Nasdaq Stockholm with annual sales in 2020 of approximately $10 billion'</li><li>'Compensation:$55,000-$75,000/year'</li></ul>                                                                                                                      |
+| keep  | <ul><li>'Requirements Must have at least 2 years Arizona or Colorado civil litigation experience, knowledge of both state and federal procedural rules, superior organizational skills, strong attention to detail and the ability to provide secretarial/administrative support to experienced trial attorneys'</li><li>'Experience with EMR systems Knowledge of Microsoft products (Word, Excel, Outlook)'</li><li>"Requirements:A bachelor's degree in exercise science, kinesiology, sports science, or a related field preferred but not required"</li></ul> |
+
+## 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("setfit_model_id")
+# Run inference
+preds = model("Remote work is allowed provided the candidate has adequate home systems to support the high internet data demands required for this position")
+```
+
+<!--
+### 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   | 1   | 24.1078 | 84  |
+
+| Label | Training Sample Count |
+|:------|:----------------------|
+| skip  | 52                    |
+| keep  | 50                    |
+
+### Training Hyperparameters
+- batch_size: (16, 16)
+- num_epochs: (4, 4)
+- max_steps: -1
+- sampling_strategy: oversampling
+- num_iterations: 20
+- body_learning_rate: (2e-05, 2e-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
+- l2_weight: 0.01
+- seed: 42
+- eval_max_steps: -1
+- load_best_model_at_end: True
+
+### Training Results
+| Epoch  | Step | Training Loss | Validation Loss |
+|:------:|:----:|:-------------:|:---------------:|
+| 0.0039 | 1    | 0.3866        | -               |
+| 0.1961 | 50   | 0.2075        | -               |
+| 0.3922 | 100  | 0.0179        | -               |
+| 0.5882 | 150  | 0.0005        | -               |
+| 0.7843 | 200  | 0.0003        | -               |
+| 0.9804 | 250  | 0.0002        | -               |
+| 1.0    | 255  | -             | 0.1885          |
+| 1.1765 | 300  | 0.0002        | -               |
+| 1.3725 | 350  | 0.0001        | -               |
+| 1.5686 | 400  | 0.0001        | -               |
+| 1.7647 | 450  | 0.0001        | -               |
+| 1.9608 | 500  | 0.0001        | -               |
+| 2.0    | 510  | -             | 0.1909          |
+| 2.1569 | 550  | 0.0001        | -               |
+| 2.3529 | 600  | 0.0001        | -               |
+| 2.5490 | 650  | 0.0001        | -               |
+| 2.7451 | 700  | 0.0001        | -               |
+| 2.9412 | 750  | 0.0001        | -               |
+| 3.0    | 765  | -             | 0.1904          |
+| 3.1373 | 800  | 0.0001        | -               |
+| 3.3333 | 850  | 0.0001        | -               |
+| 3.5294 | 900  | 0.0001        | -               |
+| 3.7255 | 950  | 0.0001        | -               |
+| 3.9216 | 1000 | 0.0001        | -               |
+| 4.0    | 1020 | -             | 0.1910          |
+
+### Framework Versions
+- Python: 3.12.3
+- SetFit: 1.1.3
+- Sentence Transformers: 5.2.0
+- Transformers: 4.57.3
+- PyTorch: 2.5.1+cu124
+- Datasets: 4.4.2
+- Tokenizers: 0.22.2
+
+## 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 +1,23 @@
+{
+  "architectures": [
+    "MPNetModel"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": 0,
+  "dtype": "float32",
+  "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,
+  "transformers_version": "4.57.3",
+  "vocab_size": 30527
+}

config_sentence_transformers.json

@@ -0,0 +1,14 @@
+{
+  "__version__": {
+    "sentence_transformers": "5.2.0",
+    "transformers": "4.57.3",
+    "pytorch": "2.5.1+cu124"
+  },
+  "model_type": "SentenceTransformer",
+  "prompts": {
+    "query": "",
+    "document": ""
+  },
+  "default_prompt_name": null,
+  "similarity_fn_name": "cosine"
+}

config_setfit.json

@@ -0,0 +1,6 @@
+{
+  "labels": [
+    "skip",
+    "keep"
+  ]
+}

model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f3b029ee591192357cfa319dd9c6351bbc9a888b7740912269e0909180805ace
+size 437967672

model_head.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0fd8f97bf296efb11454e74372526ac4e0720e0e0223767377627235dede8c35
+size 7019

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 +1,60 @@
+{
+  "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
+    },
+    "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_basic_tokenize": true,
+  "do_lower_case": true,
+  "eos_token": "</s>",
+  "extra_special_tokens": {},
+  "mask_token": "<mask>",
+  "model_max_length": 512,
+  "never_split": null,
+  "pad_token": "<pad>",
+  "sep_token": "</s>",
+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "MPNetTokenizer",
+  "unk_token": "[UNK]"
+}

training_metadata.json

@@ -0,0 +1,22 @@
+{
+  "version": "v0.2.0",
+  "base_model": "sentence-transformers/paraphrase-mpnet-base-v2",
+  "labels": [
+    "skip",
+    "keep"
+  ],
+  "training": {
+    "batch_size": 16,
+    "num_epochs": 4,
+    "num_iterations": 20,
+    "body_learning_rate": 2e-05,
+    "solver": "liblinear",
+    "max_iter": 100,
+    "random_seed": 42,
+    "data_dir": "data/training/section_filter"
+  },
+  "test_metrics": {
+    "accuracy": 0.8571428571428571,
+    "total": 14
+  }
+}

version.txt

@@ -0,0 +1 @@
+v0.2.0