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tags:
- setfit
- sentence-transformers
- text-classification
- generated_from_setfit_trainer
widget:
- text: The environment around the school is not clean.
- text: Early marriage of girls
- text: The community faces a challenge with the government school in their village
not providing proper education.
- text: Children did not want to enroll in school and hence they did not go to school.
- text: About children's academic progress
metrics:
- accuracy
pipeline_tag: text-classification
library_name: setfit
inference: true
base_model: sentence-transformers/all-MiniLM-L6-v2
---
# SetFit with sentence-transformers/all-MiniLM-L6-v2
This is a [SetFit](https://github.com/huggingface/setfit) model that can be used for Text Classification. This SetFit model uses [sentence-transformers/all-MiniLM-L6-v2](https://huggingface.co/sentence-transformers/all-MiniLM-L6-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/all-MiniLM-L6-v2](https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2)
- **Classification head:** a [LogisticRegression](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html) instance
- **Maximum Sequence Length:** 256 tokens
- **Number of Classes:** 11 classes
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### 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 |
|:-----------------------------------------------|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| Other Factors | <ul><li>'Due to lack of education of the parents of the children, they are unable to send their children to school.'</li><li>"In some families, girls' education is not prioritized. Due to social stereotypes, household pressures, and a lack of awareness, girls' school attendance and enrollment are relatively low. As a result, girls are being deprived of education at the elementary level, which is a serious concern for their future."</li><li>'Due to development, the surrounding environment is not good and there is no awareness about education.'</li></ul> |
| Early Marriage | <ul><li>'Child marriage is another challenge facing this community.'</li><li>'Girls end up marrying their own people, which stops their education and limits their future prospects.'</li><li>'Child marriage'</li></ul> |
| Unknown/Unclear | <ul><li>'Children are enrolled in school but do not attend school regularly.'</li><li>'The importance of education in life and the progress of children in their country and their own lives if they are educated were discussed.'</li><li>'Being sick disrupts education'</li></ul> |
| Distance and Accessibility Issues | <ul><li>'Children are unable to attend school because the school is located on the edge of the forest.'</li><li>'The school is far away from the village.'</li><li>'The school is located in a secluded area, making it difficult for children to reach there.'</li></ul> |
| Teacher Capacity and Quality Issues | <ul><li>'There is no study in school'</li><li>'The rural woman said that there are English teachers in the schools, but the children do not know English.'</li><li>'In school, teachers make the child do cleaning work and since the school is very far away, the date of birth is not available.'</li></ul> |
| Poverty and Economic Barriers | <ul><li>'Children work in the fields with their parents.'</li><li>'Child Labor'</li><li>'Instead of going to school, children are being sent to graze goats.'</li></ul> |
| Safety Concerns | <ul><li>'Girls are unable to attend school regularly due to harassment on the way.'</li><li>'The head master discriminates against girls from lower caste by saying that these people are from lower caste, he gives them some favour in food and drinks and there is a lot of beating.'</li><li>'Parents, distressed by the harsh treatment meted out to girls, are afraid to send their children to school.'</li></ul> |
| Legal Document linked Barriers | <ul><li>'Children are not getting enrolled in school due to lack of Aadhaar card.'</li><li>'Some girls in her village go to school, some have left after enrolling, some do not go to school due to lack of Aadhar card.'</li><li>'Admission in school is not possible due to lack of Aadhar card'</li></ul> |
| Parental Attitudes and Socio-Cultural Barriers | <ul><li>'Lack of coordination between girls and parents'</li><li>'Girls take wrong steps and this is also the reason why higher education is wasted.'</li><li>'Children do not go to school because of household chores.'</li></ul> |
| Substance Abuse and Addiction | <ul><li>'Parents challenged that their children do not go to school and are always busy playing games and using mobile phones.'</li><li>"Children's studies are being disrupted due to misuse of mobile phones."</li><li>'Fathers who drink alcohol often neglect their children.'</li></ul> |
| School Infrastructure and Facility Issues | <ul><li>'In Shiksha Chaupal, the parents were told that there is only a school up to class 5 in our village.'</li><li>'Lack of proper infrastructure for education.'</li><li>'When we go to Anganwadi, the Didi does not make us take care of food and cleanliness.'</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("Early marriage of girls")
```
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## Training Details
### Training Set Metrics
| Training set | Min | Median | Max |
|:-------------|:----|:--------|:----|
| Word count | 1 | 15.3202 | 158 |
| Label | Training Sample Count |
|:-----------------------------------------------|:----------------------|
| Distance and Accessibility Issues | 500 |
| Early Marriage | 500 |
| Legal Document linked Barriers | 500 |
| Other Factors | 500 |
| Parental Attitudes and Socio-Cultural Barriers | 500 |
| Poverty and Economic Barriers | 500 |
| Safety Concerns | 500 |
| School Infrastructure and Facility Issues | 500 |
| Substance Abuse and Addiction | 500 |
| Teacher Capacity and Quality Issues | 500 |
| Unknown/Unclear | 500 |
### Training Hyperparameters
- batch_size: (16, 16)
- num_epochs: (1, 1)
- max_steps: -1
- sampling_strategy: oversampling
- num_iterations: 1
- 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: 0.01
- seed: 42
- eval_max_steps: -1
- load_best_model_at_end: False
### Training Results
| Epoch | Step | Training Loss | Validation Loss |
|:------:|:----:|:-------------:|:---------------:|
| 0.0015 | 1 | 0.2641 | - |
| 0.0727 | 50 | 0.2312 | - |
| 0.1453 | 100 | 0.2069 | - |
| 0.2180 | 150 | 0.1816 | - |
| 0.2907 | 200 | 0.155 | - |
| 0.3634 | 250 | 0.1408 | - |
| 0.4360 | 300 | 0.1306 | - |
| 0.5087 | 350 | 0.1371 | - |
| 0.5814 | 400 | 0.1301 | - |
| 0.6541 | 450 | 0.1239 | - |
| 0.7267 | 500 | 0.1236 | - |
| 0.7994 | 550 | 0.1213 | - |
| 0.8721 | 600 | 0.122 | - |
| 0.9448 | 650 | 0.1298 | - |
### Framework Versions
- Python: 3.12.3
- SetFit: 1.1.3
- Sentence Transformers: 5.6.0
- Transformers: 4.57.6
- PyTorch: 2.13.0+cpu
- Datasets: 2.16.1
- 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}
}
```
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