Add SetFit model

1_Pooling/config.json

@@ -0,0 +1,7 @@
+{
+  "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
+}

README.md

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+---
+library_name: setfit
+tags:
+- setfit
+- sentence-transformers
+- text-classification
+- generated_from_setfit_trainer
+metrics:
+- accuracy
+widget:
+- text: 'It was a jihad training camp.
+
+    '
+- text: 'Batten echoed that sentiment saying, “Tommy Robinson is a political prisoner."
+
+    '
+- text: 'Failing to answer, Ellison tried to move from person to person, allowing
+    his minions to try and provide cover for him, similar to that of Maxine Waters,
+    but there was no "member''s only" elevator to flee into.
+
+    '
+- text: 'More details about the horrid compound could be revealed Wednesday when the
+    five adults arrested from the site make their first court appearances.
+
+    '
+- text: 'Black Death Warning: The Plague Is Impossible To Eradicate
+
+    '
+pipeline_tag: text-classification
+inference: false
+base_model: sentence-transformers/paraphrase-mpnet-base-v2
+model-index:
+- name: SetFit with sentence-transformers/paraphrase-mpnet-base-v2
+  results:
+  - task:
+      type: text-classification
+      name: Text Classification
+    dataset:
+      name: Unknown
+      type: unknown
+      split: test
+    metrics:
+    - type: accuracy
+      value: 0.5849056603773585
+      name: Accuracy
+---
+
+# 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 OneVsRestClassifier 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 OneVsRestClassifier instance
+- **Maximum Sequence Length:** 512 tokens
+<!-- - **Number of Classes:** Unknown -->
+<!-- - **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)
+
+## Evaluation
+
+### Metrics
+| Label   | Accuracy |
+|:--------|:---------|
+| **all** | 0.5849   |
+
+## 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("anismahmahi/G2-multilabel-setfit-model")
+# Run inference
+preds = model("It was a jihad training camp.
+")
+```
+
+<!--
+### 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   | 26.6518 | 129 |
+
+### Training Hyperparameters
+- batch_size: (16, 16)
+- num_epochs: (2, 2)
+- max_steps: -1
+- sampling_strategy: oversampling
+- num_iterations: 10
+- 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 |
+|:-------:|:--------:|:-------------:|:---------------:|
+| 0.0006  | 1        | 0.3905        | -               |
+| 0.0275  | 50       | 0.2239        | -               |
+| 0.0550  | 100      | 0.2359        | -               |
+| 0.0826  | 150      | 0.2443        | -               |
+| 0.1101  | 200      | 0.2495        | -               |
+| 0.1376  | 250      | 0.2498        | -               |
+| 0.1651  | 300      | 0.116         | -               |
+| 0.1926  | 350      | 0.1672        | -               |
+| 0.2201  | 400      | 0.1281        | -               |
+| 0.2477  | 450      | 0.139         | -               |
+| 0.2752  | 500      | 0.0615        | -               |
+| 0.3027  | 550      | 0.0972        | -               |
+| 0.3302  | 600      | 0.0851        | -               |
+| 0.3577  | 650      | 0.1769        | -               |
+| 0.3853  | 700      | 0.1673        | -               |
+| 0.4128  | 750      | 0.0615        | -               |
+| 0.4403  | 800      | 0.1232        | -               |
+| 0.4678  | 850      | 0.0094        | -               |
+| 0.4953  | 900      | 0.0135        | -               |
+| 0.5228  | 950      | 0.0107        | -               |
+| 0.5504  | 1000     | 0.1137        | -               |
+| 0.5779  | 1050     | 0.0173        | -               |
+| 0.6054  | 1100     | 0.0573        | -               |
+| 0.6329  | 1150     | 0.0115        | -               |
+| 0.6604  | 1200     | 0.0374        | -               |
+| 0.6879  | 1250     | 0.0231        | -               |
+| 0.7155  | 1300     | 0.0392        | -               |
+| 0.7430  | 1350     | 0.0754        | -               |
+| 0.7705  | 1400     | 0.007         | -               |
+| 0.7980  | 1450     | 0.0138        | -               |
+| 0.8255  | 1500     | 0.0569        | -               |
+| 0.8531  | 1550     | 0.0971        | -               |
+| 0.8806  | 1600     | 0.1052        | -               |
+| 0.9081  | 1650     | 0.0084        | -               |
+| 0.9356  | 1700     | 0.0859        | -               |
+| 0.9631  | 1750     | 0.0081        | -               |
+| 0.9906  | 1800     | 0.0362        | -               |
+| 1.0     | 1817     | -             | 0.2354          |
+| 1.0182  | 1850     | 0.0429        | -               |
+| 1.0457  | 1900     | 0.056         | -               |
+| 1.0732  | 1950     | 0.0098        | -               |
+| 1.1007  | 2000     | 0.002         | -               |
+| 1.1282  | 2050     | 0.0892        | -               |
+| 1.1558  | 2100     | 0.0557        | -               |
+| 1.1833  | 2150     | 0.001         | -               |
+| 1.2108  | 2200     | 0.0125        | -               |
+| 1.2383  | 2250     | 0.0152        | -               |
+| 1.2658  | 2300     | 0.0202        | -               |
+| 1.2933  | 2350     | 0.0593        | -               |
+| 1.3209  | 2400     | 0.007         | -               |
+| 1.3484  | 2450     | 0.014         | -               |
+| 1.3759  | 2500     | 0.003         | -               |
+| 1.4034  | 2550     | 0.0012        | -               |
+| 1.4309  | 2600     | 0.0139        | -               |
+| 1.4584  | 2650     | 0.0149        | -               |
+| 1.4860  | 2700     | 0.002         | -               |
+| 1.5135  | 2750     | 0.009         | -               |
+| 1.5410  | 2800     | 0.0066        | -               |
+| 1.5685  | 2850     | 0.0173        | -               |
+| 1.5960  | 2900     | 0.0052        | -               |
+| 1.6236  | 2950     | 0.0039        | -               |
+| 1.6511  | 3000     | 0.0042        | -               |
+| 1.6786  | 3050     | 0.0339        | -               |
+| 1.7061  | 3100     | 0.001         | -               |
+| 1.7336  | 3150     | 0.0005        | -               |
+| 1.7611  | 3200     | 0.0049        | -               |
+| 1.7887  | 3250     | 0.01          | -               |
+| 1.8162  | 3300     | 0.0815        | -               |
+| 1.8437  | 3350     | 0.0227        | -               |
+| 1.8712  | 3400     | 0.005         | -               |
+| 1.8987  | 3450     | 0.0053        | -               |
+| 1.9263  | 3500     | 0.0152        | -               |
+| 1.9538  | 3550     | 0.0155        | -               |
+| 1.9813  | 3600     | 0.0182        | -               |
+| **2.0** | **3634** | **-**         | **0.2266**      |
+
+* The bold row denotes the saved checkpoint.
+### Framework Versions
+- Python: 3.10.12
+- SetFit: 1.0.1
+- Sentence Transformers: 2.2.2
+- Transformers: 4.35.2
+- PyTorch: 2.1.0+cu121
+- Datasets: 2.16.1
+- Tokenizers: 0.15.0
+
+## 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": "checkpoints/step_3634/",
+  "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": "4.35.2",
+  "vocab_size": 30527
+}

config_sentence_transformers.json

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+{
+  "__version__": {
+    "sentence_transformers": "2.0.0",
+    "transformers": "4.7.0",
+    "pytorch": "1.9.0+cu102"
+  }
+}

config_setfit.json

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+{
+  "normalize_embeddings": false,
+  "labels": null
+}

model.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:80373903682af993db094960f50d8bcb3de978e341c7f759a8137ccc4d6c1651
+size 437967672

model_head.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:b649a30dc0040d068305581bb5fc7140dc387d55f179bf9cdc824f0e1f1166ee
+size 39876

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"
+  }
+]

sentence_bert_config.json

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+{
+  "max_seq_length": 512,
+  "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
+    },
+    "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]"
+}