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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+---
+library_name: setfit
+tags:
+- setfit
+- sentence-transformers
+- text-classification
+- generated_from_setfit_trainer
+metrics:
+- accuracy
+widget:
+- text: 'Neteja a deshores : Avui a les 7:30 del matí i s''ha presentat un senyor
+    amb una furgoneta de LLEIDA MÉS NETA al carrer dels Agustins i amb una mànega
+    a pressió i el seu compressor s''ha disposat a netejar el mobiliari urbà fins
+    a les 07:45. Cada cop que apretava la mànega es disparava el compresor fent així
+    molt soroll i finalment despertant a la canalla que ja tenen els dies comçlicats
+    com per a que se''ls allarguin més encara A les 7:30 està prohibit fer soroll.
+    Tinc varies fotos que ho demostren.'
+- text: 'Barana del canal : A l’alçada del canal del c/. Enginyer Antoni Llobet esta
+    instal.lada una barana que presenta un espai per la zona inferior que pot generar
+    un accident,doncs es una zona molt transitada per nens i si cauen per allí perfectament
+    es poden colar per sota i caure al canal. Sol.licito que hi fiquin algun tipo
+    de protecció.'
+- text: 'Escola de música d''adults : Hola. Voldria suggerir que féssiu algun descompte
+    a l''Escola de música d''adults per les persones amb discapacitat. Gràcies.'
+- text: 'Expedient DU13-380 Negociat de Disciplina Ue : Benvolguts Srs, Avui ens hem
+    personat a l''edifici Pal.las per contactar amb el Negociat de Disciplina Urbanística
+    i donar una resposta personal al requeriment. Estem en contacte amb un arquitecte
+    qui presentarà en breu els documents requerits. La persona d''Urbanisme que ens
+    ha atès aquest matí ens ha suggerit que presentéssim telemàticament l''escrit
+    que volíem avui mateix aportar al Negociat, i que adjuntem. Rebin una salutació,
+    Elisa Rosanes i Joan Valls'
+- text: 'Bonificació escola bressol : Bones, vaig fer la tramitació per família monoparental
+    per l''escola bressol la mitjana pero no s''he m''ha aplicat, ja que posa que
+    la cuantitar a pagar son 90 euros mensuals. He tornat a fer la solicitud per si
+    hi hagut algun problema. També voldria saber si ja esta aplicat el servei de menjador.
+    Gràcies.'
+pipeline_tag: text-classification
+inference: true
+base_model: ibaucells/RoBERTa-ca-CaWikiTC
+---
+
+# SetFit with ibaucells/RoBERTa-ca-CaWikiTC
+
+This is a [SetFit](https://github.com/huggingface/setfit) model that can be used for Text Classification. This SetFit model uses [ibaucells/RoBERTa-ca-CaWikiTC](https://huggingface.co/ibaucells/RoBERTa-ca-CaWikiTC) 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:** [ibaucells/RoBERTa-ca-CaWikiTC](https://huggingface.co/ibaucells/RoBERTa-ca-CaWikiTC)
+- **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:** 17 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                                                                                                                                                                       |
+|:------|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| 0     | <ul><li>'Aquest article tracta sobre Aigües'</li><li>'Aquest article tracta sobre Aigües'</li><li>'Aquest article tracta sobre Aigües'</li></ul>                               |
+| 1     | <ul><li>'Aquest article tracta sobre Comerç i mercats'</li><li>'Aquest article tracta sobre Comerç i mercats'</li><li>'Aquest article tracta sobre Comerç i mercats'</li></ul> |
+| 2     | <ul><li>'Aquest article tracta sobre Cultura'</li><li>'Aquest article tracta sobre Cultura'</li><li>'Aquest article tracta sobre Cultura'</li></ul>                            |
+| 3     | <ul><li>'Aquest article tracta sobre Economia'</li><li>'Aquest article tracta sobre Economia'</li><li>'Aquest article tracta sobre Economia'</li></ul>                         |
+| 4     | <ul><li>'Aquest article tracta sobre Educació'</li><li>'Aquest article tracta sobre Educació'</li><li>'Aquest article tracta sobre Educació'</li></ul>                         |
+| 5     | <ul><li>'Aquest article tracta sobre Enllumenat'</li><li>'Aquest article tracta sobre Enllumenat'</li><li>'Aquest article tracta sobre Enllumenat'</li></ul>                   |
+| 6     | <ul><li>'Aquest article tracta sobre Esports'</li><li>'Aquest article tracta sobre Esports'</li><li>'Aquest article tracta sobre Esports'</li></ul>                            |
+| 7     | <ul><li>'Aquest article tracta sobre Habitatge'</li><li>'Aquest article tracta sobre Habitatge'</li><li>'Aquest article tracta sobre Habitatge'</li></ul>                      |
+| 8     | <ul><li>'Aquest article tracta sobre Horta'</li><li>'Aquest article tracta sobre Horta'</li><li>'Aquest article tracta sobre Horta'</li></ul>                                  |
+| 9     | <ul><li>'Aquest article tracta sobre Medi ambient'</li><li>'Aquest article tracta sobre Medi ambient'</li><li>'Aquest article tracta sobre Medi ambient'</li></ul>             |
+| 10    | <ul><li>'Aquest article tracta sobre Mobilitat'</li><li>'Aquest article tracta sobre Mobilitat'</li><li>'Aquest article tracta sobre Mobilitat'</li></ul>                      |
+| 11    | <ul><li>'Aquest article tracta sobre Neteja'</li><li>'Aquest article tracta sobre Neteja'</li><li>'Aquest article tracta sobre Neteja'</li></ul>                               |
+| 12    | <ul><li>'Aquest article tracta sobre Salut'</li><li>'Aquest article tracta sobre Salut'</li><li>'Aquest article tracta sobre Salut'</li></ul>                                  |
+| 13    | <ul><li>'Aquest article tracta sobre Seguretat'</li><li>'Aquest article tracta sobre Seguretat'</li><li>'Aquest article tracta sobre Seguretat'</li></ul>                      |
+| 14    | <ul><li>'Aquest article tracta sobre Serveis socials'</li><li>'Aquest article tracta sobre Serveis socials'</li><li>'Aquest article tracta sobre Serveis socials'</li></ul>    |
+| 15    | <ul><li>'Aquest article tracta sobre Tramitacions'</li><li>'Aquest article tracta sobre Tramitacions'</li><li>'Aquest article tracta sobre Tramitacions'</li></ul>             |
+| 16    | <ul><li>'Aquest article tracta sobre Urbanisme'</li><li>'Aquest article tracta sobre Urbanisme'</li><li>'Aquest article tracta sobre Urbanisme'</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("adriansanz/test8")
+# Run inference
+preds = model("Escola de música d'adults : Hola. Voldria suggerir que féssiu algun descompte a l'Escola de música d'adults per les persones amb discapacitat. Gràcies.")
+```
+
+<!--
+### 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   | 5   | 5.2353 | 7   |
+
+| Label | Training Sample Count |
+|:------|:----------------------|
+| 0     | 8                     |
+| 1     | 8                     |
+| 2     | 8                     |
+| 3     | 8                     |
+| 4     | 8                     |
+| 5     | 8                     |
+| 6     | 8                     |
+| 7     | 8                     |
+| 8     | 8                     |
+| 9     | 8                     |
+| 10    | 8                     |
+| 11    | 8                     |
+| 12    | 8                     |
+| 13    | 8                     |
+| 14    | 8                     |
+| 15    | 8                     |
+| 16    | 8                     |
+
+### Training Hyperparameters
+- batch_size: (64, 64)
+- num_epochs: (60, 60)
+- 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 |
+|:------:|:----:|:-------------:|:---------------:|
+| 0.0037 | 1    | 0.4079        | -               |
+| 0.1838 | 50   | 0.3625        | -               |
+| 0.3676 | 100  | 0.3197        | -               |
+| 0.5515 | 150  | 0.22          | -               |
+| 0.7353 | 200  | 0.2259        | -               |
+| 0.9191 | 250  | 0.1748        | -               |
+
+### Framework Versions
+- Python: 3.10.12
+- SetFit: 1.0.3
+- Sentence Transformers: 2.6.1
+- Transformers: 4.38.2
+- PyTorch: 2.2.1+cu121
+- 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

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+{
+  "_name_or_path": "ibaucells/RoBERTa-ca-CaWikiTC",
+  "architectures": [
+    "RobertaModel"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": 0,
+  "classifier_dropout": null,
+  "eos_token_id": 2,
+  "finetuning_task": "mnli",
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "entailment",
+    "1": "neutral",
+    "2": "contradiction"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "contradiction": 2,
+    "entailment": 0,
+    "neutral": 1
+  },
+  "layer_norm_eps": 1e-05,
+  "max_position_embeddings": 514,
+  "model_type": "roberta",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 1,
+  "position_embedding_type": "absolute",
+  "problem_type": "single_label_classification",
+  "torch_dtype": "float32",
+  "transformers_version": "4.38.2",
+  "type_vocab_size": 1,
+  "use_cache": true,
+  "vocab_size": 50262
+}

config_sentence_transformers.json

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+{
+  "__version__": {
+    "sentence_transformers": "2.6.1",
+    "transformers": "4.38.2",
+    "pytorch": "2.2.1+cu121"
+  },
+  "prompts": {},
+  "default_prompt_name": null
+}

config_setfit.json

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

model.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:f11b8907b5d6616602c988a2c81e9564fc04d5796808a2308545fa5422d5a659
+size 498595688

model_head.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:95a2349eb3f96eb70d9185b2f02af4ffabe28566b0bbeda0ad56312e9e6879cb
+size 324

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": true,
+    "rstrip": false,
+    "single_word": false
+  },
+  "cls_token": {
+    "content": "<s>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eos_token": {
+    "content": "</s>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  },
+  "mask_token": {
+    "content": "<mask>",
+    "lstrip": true,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "<pad>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  },
+  "sep_token": {
+    "content": "</s>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  },
+  "unk_token": {
+    "content": "<unk>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer_config.json

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+{
+  "add_prefix_space": true,
+  "added_tokens_decoder": {
+    "0": {
+      "content": "<s>",
+      "lstrip": false,
+      "normalized": true,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "1": {
+      "content": "<pad>",
+      "lstrip": false,
+      "normalized": true,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "2": {
+      "content": "</s>",
+      "lstrip": false,
+      "normalized": true,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "3": {
+      "content": "<unk>",
+      "lstrip": false,
+      "normalized": true,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "4": {
+      "content": "<mask>",
+      "lstrip": true,
+      "normalized": true,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "bos_token": "<s>",
+  "clean_up_tokenization_spaces": true,
+  "cls_token": "<s>",
+  "eos_token": "</s>",
+  "errors": "replace",
+  "mask_token": "<mask>",
+  "max_len": 512,
+  "max_length": 512,
+  "model_max_length": 512,
+  "pad_to_multiple_of": null,
+  "pad_token": "<pad>",
+  "pad_token_type_id": 0,
+  "padding_side": "right",
+  "sep_token": "</s>",
+  "stride": 0,
+  "tokenizer_class": "RobertaTokenizer",
+  "trim_offsets": true,
+  "truncation_side": "right",
+  "truncation_strategy": "longest_first",
+  "unk_token": "<unk>"
+}