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

@@ -0,0 +1,342 @@
+---
+library_name: setfit
+tags:
+- setfit
+- sentence-transformers
+- text-classification
+- generated_from_setfit_trainer
+metrics:
+- accuracy
+widget:
+- text: But the author is Bharath Ganesh.
+- text: The documents, which suggest all the adults were involved in the training,
+    say a person serving as a foster parent caring for one of the kids revealed the
+    details about the training.
+- text: Louis Farrakhan, the 84-year-old head of the Nation of Islam, has been back
+    in the headlines after a previously unreleased photo of him with President Barack
+    Obama was published in January and Mr. Farrakhan gave an anti-Semitic speech at
+    his organization’s annual convention last month.
+- text: The name of that CIA official whose torture activities the Post described
+    is Gina Haspel.
+- text: This is not just about Facebook or Twitter.
+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: 0.7125193199381762
+      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** | 0.7125   |
+
+## 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-with-noPropaganda-multilabel-setfit-model")
+# Run inference
+preds = model("But the author is Bharath Ganesh.")
+```
+
+<!--
+### 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   | 23.3972 | 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 |
+|:-------:|:--------:|:-------------:|:---------------:|
+| 0.0003  | 1        | 0.3874        | -               |
+| 0.0135  | 50       | 0.3734        | -               |
+| 0.0270  | 100      | 0.2741        | -               |
+| 0.0405  | 150      | 0.2802        | -               |
+| 0.0539  | 200      | 0.2355        | -               |
+| 0.0674  | 250      | 0.2616        | -               |
+| 0.0809  | 300      | 0.262         | -               |
+| 0.0944  | 350      | 0.2302        | -               |
+| 0.1079  | 400      | 0.1962        | -               |
+| 0.1214  | 450      | 0.1438        | -               |
+| 0.1348  | 500      | 0.2001        | -               |
+| 0.1483  | 550      | 0.2126        | -               |
+| 0.1618  | 600      | 0.1244        | -               |
+| 0.1753  | 650      | 0.1968        | -               |
+| 0.1888  | 700      | 0.1473        | -               |
+| 0.2023  | 750      | 0.2407        | -               |
+| 0.2157  | 800      | 0.1607        | -               |
+| 0.2292  | 850      | 0.1376        | -               |
+| 0.2427  | 900      | 0.145         | -               |
+| 0.2562  | 950      | 0.1439        | -               |
+| 0.2697  | 1000     | 0.0418        | -               |
+| 0.2832  | 1050     | 0.0822        | -               |
+| 0.2967  | 1100     | 0.1042        | -               |
+| 0.3101  | 1150     | 0.0381        | -               |
+| 0.3236  | 1200     | 0.17          | -               |
+| 0.3371  | 1250     | 0.0253        | -               |
+| 0.3506  | 1300     | 0.1009        | -               |
+| 0.3641  | 1350     | 0.1355        | -               |
+| 0.3776  | 1400     | 0.0314        | -               |
+| 0.3910  | 1450     | 0.2185        | -               |
+| 0.4045  | 1500     | 0.0774        | -               |
+| 0.4180  | 1550     | 0.0512        | -               |
+| 0.4315  | 1600     | 0.0814        | -               |
+| 0.4450  | 1650     | 0.0169        | -               |
+| 0.4585  | 1700     | 0.0591        | -               |
+| 0.4720  | 1750     | 0.1232        | -               |
+| 0.4854  | 1800     | 0.0941        | -               |
+| 0.4989  | 1850     | 0.1024        | -               |
+| 0.5124  | 1900     | 0.0031        | -               |
+| 0.5259  | 1950     | 0.037         | -               |
+| 0.5394  | 2000     | 0.1418        | -               |
+| 0.5529  | 2050     | 0.0685        | -               |
+| 0.5663  | 2100     | 0.0326        | -               |
+| 0.5798  | 2150     | 0.0143        | -               |
+| 0.5933  | 2200     | 0.064         | -               |
+| 0.6068  | 2250     | 0.0612        | -               |
+| 0.6203  | 2300     | 0.0689        | -               |
+| 0.6338  | 2350     | 0.1402        | -               |
+| 0.6472  | 2400     | 0.288         | -               |
+| 0.6607  | 2450     | 0.0075        | -               |
+| 0.6742  | 2500     | 0.0785        | -               |
+| 0.6877  | 2550     | 0.0339        | -               |
+| 0.7012  | 2600     | 0.0668        | -               |
+| 0.7147  | 2650     | 0.0319        | -               |
+| 0.7282  | 2700     | 0.0622        | -               |
+| 0.7416  | 2750     | 0.1169        | -               |
+| 0.7551  | 2800     | 0.0249        | -               |
+| 0.7686  | 2850     | 0.0218        | -               |
+| 0.7821  | 2900     | 0.0621        | -               |
+| 0.7956  | 2950     | 0.0698        | -               |
+| 0.8091  | 3000     | 0.0562        | -               |
+| 0.8225  | 3050     | 0.0412        | -               |
+| 0.8360  | 3100     | 0.0048        | -               |
+| 0.8495  | 3150     | 0.0085        | -               |
+| 0.8630  | 3200     | 0.0122        | -               |
+| 0.8765  | 3250     | 0.0387        | -               |
+| 0.8900  | 3300     | 0.0053        | -               |
+| 0.9035  | 3350     | 0.0032        | -               |
+| 0.9169  | 3400     | 0.0156        | -               |
+| 0.9304  | 3450     | 0.0013        | -               |
+| 0.9439  | 3500     | 0.001         | -               |
+| 0.9574  | 3550     | 0.0009        | -               |
+| 0.9709  | 3600     | 0.0025        | -               |
+| 0.9844  | 3650     | 0.0006        | -               |
+| 0.9978  | 3700     | 0.0832        | -               |
+| 1.0     | 3708     | -             | 0.2776          |
+| 1.0113  | 3750     | 0.0735        | -               |
+| 1.0248  | 3800     | 0.0053        | -               |
+| 1.0383  | 3850     | 0.0614        | -               |
+| 1.0518  | 3900     | 0.0005        | -               |
+| 1.0653  | 3950     | 0.0046        | -               |
+| 1.0787  | 4000     | 0.0024        | -               |
+| 1.0922  | 4050     | 0.0004        | -               |
+| 1.1057  | 4100     | 0.0016        | -               |
+| 1.1192  | 4150     | 0.0789        | -               |
+| 1.1327  | 4200     | 0.0016        | -               |
+| 1.1462  | 4250     | 0.0018        | -               |
+| 1.1597  | 4300     | 0.0005        | -               |
+| 1.1731  | 4350     | 0.0051        | -               |
+| 1.1866  | 4400     | 0.0139        | -               |
+| 1.2001  | 4450     | 0.0021        | -               |
+| 1.2136  | 4500     | 0.0064        | -               |
+| 1.2271  | 4550     | 0.0025        | -               |
+| 1.2406  | 4600     | 0.0054        | -               |
+| 1.2540  | 4650     | 0.0022        | -               |
+| 1.2675  | 4700     | 0.0734        | -               |
+| 1.2810  | 4750     | 0.026         | -               |
+| 1.2945  | 4800     | 0.0004        | -               |
+| 1.3080  | 4850     | 0.0574        | -               |
+| 1.3215  | 4900     | 0.0043        | -               |
+| 1.3350  | 4950     | 0.0975        | -               |
+| 1.3484  | 5000     | 0.0125        | -               |
+| 1.3619  | 5050     | 0.0045        | -               |
+| 1.3754  | 5100     | 0.0011        | -               |
+| 1.3889  | 5150     | 0.0061        | -               |
+| 1.4024  | 5200     | 0.0004        | -               |
+| 1.4159  | 5250     | 0.0278        | -               |
+| 1.4293  | 5300     | 0.005         | -               |
+| 1.4428  | 5350     | 0.0302        | -               |
+| 1.4563  | 5400     | 0.0341        | -               |
+| 1.4698  | 5450     | 0.0007        | -               |
+| 1.4833  | 5500     | 0.0128        | -               |
+| 1.4968  | 5550     | 0.0459        | -               |
+| 1.5102  | 5600     | 0.0128        | -               |
+| 1.5237  | 5650     | 0.0003        | -               |
+| 1.5372  | 5700     | 0.004         | -               |
+| 1.5507  | 5750     | 0.0005        | -               |
+| 1.5642  | 5800     | 0.0005        | -               |
+| 1.5777  | 5850     | 0.001         | -               |
+| 1.5912  | 5900     | 0.0069        | -               |
+| 1.6046  | 5950     | 0.0124        | -               |
+| 1.6181  | 6000     | 0.0026        | -               |
+| 1.6316  | 6050     | 0.0143        | -               |
+| 1.6451  | 6100     | 0.0005        | -               |
+| 1.6586  | 6150     | 0.0362        | -               |
+| 1.6721  | 6200     | 0.0002        | -               |
+| 1.6855  | 6250     | 0.0608        | -               |
+| 1.6990  | 6300     | 0.0006        | -               |
+| 1.7125  | 6350     | 0.0003        | -               |
+| 1.7260  | 6400     | 0.0041        | -               |
+| 1.7395  | 6450     | 0.0045        | -               |
+| 1.7530  | 6500     | 0.0005        | -               |
+| 1.7665  | 6550     | 0.0014        | -               |
+| 1.7799  | 6600     | 0.0004        | -               |
+| 1.7934  | 6650     | 0.0211        | -               |
+| 1.8069  | 6700     | 0.0002        | -               |
+| 1.8204  | 6750     | 0.0048        | -               |
+| 1.8339  | 6800     | 0.0368        | -               |
+| 1.8474  | 6850     | 0.0107        | -               |
+| 1.8608  | 6900     | 0.0045        | -               |
+| 1.8743  | 6950     | 0.0062        | -               |
+| 1.8878  | 7000     | 0.0003        | -               |
+| 1.9013  | 7050     | 0.0001        | -               |
+| 1.9148  | 7100     | 0.0096        | -               |
+| 1.9283  | 7150     | 0.0008        | -               |
+| 1.9417  | 7200     | 0.0184        | -               |
+| 1.9552  | 7250     | 0.0006        | -               |
+| 1.9687  | 7300     | 0.0291        | -               |
+| 1.9822  | 7350     | 0.0335        | -               |
+| 1.9957  | 7400     | 0.0149        | -               |
+| **2.0** | **7416** | **-**         | **0.2666**      |
+
+* 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

@@ -0,0 +1,24 @@
+{
+  "_name_or_path": "checkpoints/step_7416/",
+  "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

@@ -0,0 +1,7 @@
+{
+  "__version__": {
+    "sentence_transformers": "2.0.0",
+    "transformers": "4.7.0",
+    "pytorch": "1.9.0+cu102"
+  }
+}

config_setfit.json

@@ -0,0 +1,4 @@
+{
+  "normalize_embeddings": false,
+  "labels": null
+}

model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:3182c9d3035a96fa09f9b7eac3c21e1b42c73a08291b6c6ab3ebb22c06bb0b94
+size 437967672

model_head.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:11e968a9dcbf03193b2be1e6bff3ecd5651ca4144cd69533bedc1d5bb73cfe28
+size 46356

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": {
+      "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]"
+}