File size: 12,893 Bytes
44c3049 e848f79 359f204 e848f79 44c3049 e848f79 44c3049 e848f79 44c3049 e848f79 44c3049 7203cd0 e848f79 44c3049 e848f79 359f204 e848f79 7203cd0 e848f79 40db897 e848f79 40db897 e848f79 40db897 e848f79 40db897 e848f79 359f204 40db897 e848f79 359f204 e848f79 359f204 e848f79 ad01649 e848f79 7203cd0 e848f79 ad01649 e848f79 40db897 e848f79 40db897 e848f79 40db897 e848f79 40db897 e848f79 40db897 e848f79 40db897 e848f79 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 |
---
tags:
- setfit
- sentence-transformers
- text-classification
- generated_from_setfit_trainer
widget:
- text: I need some icon suggestions for this layout
- text: Tighten the letter spacing
- text: Group the logo and title together
- text: Create a photo of a mountain landscape
- text: Mirror the logo vertically
metrics:
- accuracy
pipeline_tag: text-classification
library_name: setfit
inference: true
base_model: nomic-ai/nomic-embed-text-v1.5
model-index:
- name: SetFit with nomic-ai/nomic-embed-text-v1.5
results:
- task:
type: text-classification
name: Text Classification
dataset:
name: Unknown
type: unknown
split: test
metrics:
- type: accuracy
value: 0.2895622895622896
name: Accuracy
---
# SetFit with nomic-ai/nomic-embed-text-v1.5
This is a [SetFit](https://github.com/huggingface/setfit) model that can be used for Text Classification. This SetFit model uses [nomic-ai/nomic-embed-text-v1.5](https://huggingface.co/nomic-ai/nomic-embed-text-v1.5) 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:** [nomic-ai/nomic-embed-text-v1.5](https://huggingface.co/nomic-ai/nomic-embed-text-v1.5)
- **Classification head:** a [LogisticRegression](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html) instance
- **Maximum Sequence Length:** 8192 tokens
- **Number of Classes:** 63 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>'Add a corporate presentation background'</li></ul> |
| 1 | <ul><li>'I need some icon suggestions for this layout'</li></ul> |
| 2 | <ul><li>"Add a heading that says 'Welcome'"</li></ul> |
| 3 | <ul><li>'Distribute the shapes across the page'</li></ul> |
| 4 | <ul><li>'Add a zoom animation to the logo'</li></ul> |
| 5 | <ul><li>'Make everything fade in gradually'</li></ul> |
| 6 | <ul><li>'Remove the unwanted text overlay'</li></ul> |
| 7 | <ul><li>'Remove the background shape'</li></ul> |
| 8 | <ul><li>'What shape options do you have?'</li></ul> |
| 9 | <ul><li>'Distribute the buttons around the center image'</li></ul> |
| 10 | <ul><li>'Duplicate the page structure'</li></ul> |
| 11 | <ul><li>'Duplicate the icon and move it'</li></ul> |
| 12 | <ul><li>'Copy the content to the final page'</li></ul> |
| 13 | <ul><li>'Fix the letter spacing'</li></ul> |
| 14 | <ul><li>'Mirror the logo vertically'</li></ul> |
| 15 | <ul><li>'Create a photo of a mountain landscape'</li></ul> |
| 16 | <ul><li>'Create a card for a birthday party'</li></ul> |
| 17 | <ul><li>'Group the logo and title together'</li></ul> |
| 18 | <ul><li>'Move the image to the center'</li></ul> |
| 19 | <ul><li>'Apply a vintage filter to the photo'</li></ul> |
| 20 | <ul><li>'Find me texture patterns'</li></ul> |
| 21 | <ul><li>'Restore the previous color'</li></ul> |
| 22 | <ul><li>'Remove the background from the illustration'</li></ul> |
| 23 | <ul><li>'Delete the old sign'</li></ul> |
| 24 | <ul><li>'Replace the old logo with a new one'</li></ul> |
| 25 | <ul><li>'Replace the tagline'</li></ul> |
| 26 | <ul><li>'Reset the image adjustments'</li></ul> |
| 27 | <ul><li>'Scale the text up'</li></ul> |
| 28 | <ul><li>'Resize to LinkedIn post dimensions'</li></ul> |
| 29 | <ul><li>'Turn the logo 270 degrees'</li></ul> |
| 30 | <ul><li>'Scatter the particles around the text'</li></ul> |
| 31 | <ul><li>'Select the footer content'</li></ul> |
| 32 | <ul><li>'Change to a light gray background'</li></ul> |
| 33 | <ul><li>'Change the blend mode to color burn'</li></ul> |
| 34 | <ul><li>'Blur the logo slightly'</li></ul> |
| 35 | <ul><li>'Add a double border to the image'</li></ul> |
| 36 | <ul><li>'Make the photo more illuminated'</li></ul> |
| 37 | <ul><li>'Send the logo to the back'</li></ul> |
| 38 | <ul><li>'Increase the image contrast'</li></ul> |
| 39 | <ul><li>'Crop to a polygon'</li></ul> |
| 40 | <ul><li>'Add a gradient shadow'</li></ul> |
| 41 | <ul><li>'Change the background color to green'</li></ul> |
| 42 | <ul><li>'Increase the menu font size'</li></ul> |
| 43 | <ul><li>'Make the text bold and strikethrough'</li></ul> |
| 44 | <ul><li>'Use a decorative font for the logo'</li></ul> |
| 45 | <ul><li>'Brighten the light areas'</li></ul> |
| 46 | <ul><li>'Set the picture as full background'</li></ul> |
| 47 | <ul><li>'Tighten the letter spacing'</li></ul> |
| 48 | <ul><li>'Add more line height'</li></ul> |
| 49 | <ul><li>'Reduce the opacity of the overlay'</li></ul> |
| 50 | <ul><li>'Reduce the paragraph spacing'</li></ul> |
| 51 | <ul><li>'Make the colors more vibrant'</li></ul> |
| 52 | <ul><li>'Make the shadows deeper'</li></ul> |
| 53 | <ul><li>'Increase the image sharpness'</li></ul> |
| 54 | <ul><li>'Left align the subtitle'</li></ul> |
| 55 | <ul><li>'Create a text container'</li></ul> |
| 56 | <ul><li>'Create text in a spiral pattern'</li></ul> |
| 57 | <ul><li>'Convert to bullet point format'</li></ul> |
| 58 | <ul><li>'Add a colored shadow to the text'</li></ul> |
| 59 | <ul><li>'Increase the warm color cast'</li></ul> |
| 60 | <ul><li>'I want to upload a new image'</li></ul> |
| 61 | <ul><li>'Revert the opacity change'</li></ul> |
| 62 | <ul><li>'Break apart the grouped elements'</li></ul> |
## Evaluation
### Metrics
| Label | Accuracy |
|:--------|:---------|
| **all** | 0.2896 |
## 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("Tighten the letter spacing")
```
<!--
### 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 | 3 | 5.2857 | 8 |
| Label | Training Sample Count |
|:------|:----------------------|
| 0 | 1 |
| 1 | 1 |
| 2 | 1 |
| 3 | 1 |
| 4 | 1 |
| 5 | 1 |
| 6 | 1 |
| 7 | 1 |
| 8 | 1 |
| 9 | 1 |
| 10 | 1 |
| 11 | 1 |
| 12 | 1 |
| 13 | 1 |
| 14 | 1 |
| 15 | 1 |
| 16 | 1 |
| 17 | 1 |
| 18 | 1 |
| 19 | 1 |
| 20 | 1 |
| 21 | 1 |
| 22 | 1 |
| 23 | 1 |
| 24 | 1 |
| 25 | 1 |
| 26 | 1 |
| 27 | 1 |
| 28 | 1 |
| 29 | 1 |
| 30 | 1 |
| 31 | 1 |
| 32 | 1 |
| 33 | 1 |
| 34 | 1 |
| 35 | 1 |
| 36 | 1 |
| 37 | 1 |
| 38 | 1 |
| 39 | 1 |
| 40 | 1 |
| 41 | 1 |
| 42 | 1 |
| 43 | 1 |
| 44 | 1 |
| 45 | 1 |
| 46 | 1 |
| 47 | 1 |
| 48 | 1 |
| 49 | 1 |
| 50 | 1 |
| 51 | 1 |
| 52 | 1 |
| 53 | 1 |
| 54 | 1 |
| 55 | 1 |
| 56 | 1 |
| 57 | 1 |
| 58 | 1 |
| 59 | 1 |
| 60 | 1 |
| 61 | 1 |
| 62 | 1 |
### Training Hyperparameters
- batch_size: (32, 32)
- num_epochs: (2, 2)
- 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
- l2_weight: 0.1
- seed: 42
- eval_max_steps: -1
- load_best_model_at_end: False
### Training Results
| Epoch | Step | Training Loss | Validation Loss |
|:------:|:----:|:-------------:|:---------------:|
| 0.0081 | 1 | 0.1179 | - |
| 0.4065 | 50 | 0.0211 | - |
| 0.8130 | 100 | 0.002 | - |
| 1.2195 | 150 | 0.0011 | - |
| 1.6260 | 200 | 0.0011 | - |
### Framework Versions
- Python: 3.12.11
- SetFit: 1.1.3
- Sentence Transformers: 5.1.0
- Transformers: 4.54.1
- PyTorch: 2.7.1
- Datasets: 4.0.0
- Tokenizers: 0.21.4
## 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.*
--> |