---
library_name: setfit
metrics:
- accuracy
pipeline_tag: text-classification
tags:
- setfit
- sentence-transformers
- text-classification
- generated_from_setfit_trainer
widget:
- text: "Copy env-production to .env (setting up)\nHi, very sorry to ask, dont know\
\ if here would be ok... but where can I get the env-production file to be copied\
\ to .env? because here https://github.com/frappe/frappe_docker/wiki/Easiest-Install\
\ says so but cant be found...```\r\n\r\nThanks,\r\n\r\n$ **cp env-production\
\ .env**\r\n$ sed -i -e \"s/FRAPPE_VERSION=edge/FRAPPE_VERSION=v12.9.4/g\" .env\r\
\n$ sed -i -e \"s/ERPNEXT_VERSION=edge/ERPNEXT_VERSION=v12.6.2/g\" .env\r\n$ sed\
\ -i -e \"s/email@example.com/hello@myweb.com/g\" .env\r\n$ sed -i -e \"s/erp.example.com/erp.myweb.com/g\"\
\ .env\r\n$ sed -i -e \"s/ADMIN_PASSWORD=admin/ADMIN_PASSWORD=supersecret/g\"\
\ .env\r\n$ sed -i -e \"s/MYSQL_ROOT_PASSWORD=admin/MYSQL_ROOT_PASSWORD=longsecretpassword/g\"\
\ .env\r\n```"
- text: "[BUG] Unwanted \"supported\" or \"unknown\" message\n## User Story\r\nI see\
\ string \"supported\" on \"start\" command.\r\n\r\n## Basic info\r\n\r\n* **Distro:**\
\ Ubuntu 20.04.3 LTS\r\n* **Game:** Any\r\n* **Command:** start\r\n* **LinuxGSM\
\ version:** v21.5.0\r\n\r\n## Further Information\r\n\r\nProbably it is debug\
\ message from deps check. \"supported\" is replaced by \"unknown\" on unsupported\
\ distro.\r\nThis LGSM is upgraded from previous version.\r\n```\r\naaa@hostname:~$\
\ ./arma3server start\r\nsupported\r\nsupported\r\nsupported\r\n[ OK ] Starting\
\ arma3server: server name\r\n```\r\n\r\n## To Reproduce\r\n\r\nSteps to reproduce\
\ the behaviour:\r\n1. Use start command\r\n\r\n## Expected behaviour\r\nSee only\
\ \"[ OK ] Starting arma3server: server name\" message,"
- text: 'Docs are still using `DBT_PROJECT_DIR`
This was switched to `ARTEFACTS_ DBT_PROJECT_DIR` last release.'
- text: 'Document CNI upgrade strategies
Document supported CNIs + supported CNI upgrade strategies.'
- text: 'Read the Docs
Implement read the docs for documentation'
inference: true
---
# SetFit
This is a [SetFit](https://github.com/huggingface/setfit) model that can be used for Text Classification. 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
- **Classification head:** a [LogisticRegression](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html) instance
- **Maximum Sequence Length:** 384 tokens
- **Number of Classes:** 2 classes
### 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 |
|:--------|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| bug | - 'lookatme requirements should specify click<9\n`lookatme` specifies a requirements of `click>=7,<8` but in fact seems to work fine with click 8+. Many tools (including poetry, and soon pip) will refuse to install lookatme in a venv with modern Python packages because those packages require click 8+.\r\n\r\nThis is easily fixed by updating requirements.\r\n\r\nSteps to reproduce the behavior:\r\n\r\n```\r\npoetry shell\r\npoetry add black\r\npoetry add lookatme\r\n```\r\n\r\n**Expected behavior**\r\nlookatme can be installed with black.\r\n\r\n**Actual behavior**\r\npoetry refuses to install lookatme because of the unnecessary requirement.\r\n\r\n**Additional context**\r\nPR inbound.'
- 'Quarto error when trying to render a simple .qmd file\n### System details\r\n\r\nVersion 2022.11.0-daily+87 (2022.11.0-daily+87)\r\nsysname\r\n"Darwin"\r\nrelease\r\n"21.5.0"\r\nversion\r\n"Darwin Kernel Version 21.5.0: Tue Apr 26 21:08:37 PDT 2022; root:xnu8020.121.3~4/RELEASE_ARM64_T6000" \r\n\r\n\r\n### Steps to reproduce the problem\r\nthis is an example `qmd file`\r\n```\r\n---\r\ntitle: "An Introduction to data science"\r\nformat: revealjs\r\n---\r\n\r\n\r\n\r\n---\r\n# How is the project is constructed\r\n\r\n1. Intro\r\n\r\n2. Literature review\r\n\r\n3. Hypothesis\r\n\r\n4. Methods: which tools did you use and how you used them (more on this in a bit)\r\n\r\n5. Main results\r\n\r\n6. Conclusions\r\n\r\n
\r\n\r\n---\r\n# Intro\r\n\r\nPresent the research topic and research hypothesis\r\n\r\n---\r\n# Literature review\r\n\r\nat least 5-6 papers you will summarize relating to your project\r\n\r\n\r\n```\r\n\r\n### Describe the problem in detail\r\n\r\nwhen rendering I get errors, here is the error from the example file above\r\n```\r\nERROR: YAMLError: end of the stream or a document separator is expected at line 10, column 12:\r\n 4. Methods: which tools did you use and ho ... \r\n ^\r\n```\r\n\r\n\r\n### Describe the behavior you expected\r\n\r\nexpected for the file to render correctly \r\n\r\n- [ X] I have read the guide for [submitting good bug reports](https://github.com/rstudio/rstudio/wiki/Writing-Good-Bug-Reports).\r\n- [ X] I have installed the latest version of RStudio, and confirmed that the issue still persists.\r\n- [ X] If I am reporting an RStudio crash, I have included a [diagnostics report](https://support.rstudio.com/hc/en-us/articles/200321257-Running-a-Diagnostics-Report).\r\n- [ X] I have done my best to include a minimal, self-contained set of instructions for consistently reproducing the issue.\r\n' - 'Nested buttons do not handle enabled properly\nWith 2 nested buttons, if the outside one has the prop `enabled={false}` then then inside one does not receive touch events.\r\n\r\nTested on iOS, not sure about Android.\r\n\r\nSnack: https://snack.expo.io/H15lpZuFQ'
|
| non-bug | - 'Migrating Woo Comparison table to Sparks\n### Description:\r\nWe need to migrate the current comparison table to Sparks and remove it from Otter.'
- '[bug] Hard code \'movie_id\' in neg_sampler.py\n
\r\n\r\nUse item parameter instead of hard code \'movie_id\'.' - "mk: omit transitive shared-library dependencies from linker command line\nRight now, binaries created directly within a build directory are linked slightly different compared to binaries created as depot archive. When created in the build directory, all shared-library dependencies including transitive shared-library dependencies of the target's used shared libraries end up at the linker command line. In contrast, when building a depot archive - where transitive shared libraries are not known because they are hidden behind the library's ABI - only the immediate dependencies appear at the linker command line. To improve the consistency, we should better link without transitive shared objects in both cases."
|
## 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("Read the Docs
Implement read the docs for documentation")
```
## Training Details
### Training Set Metrics
| Training set | Min | Median | Max |
|:-------------|:----|:---------|:------|
| Word count | 3 | 186.9402 | 10443 |
| Label | Training Sample Count |
|:--------|:----------------------|
| bug | 47 |
| non-bug | 137 |
### Training Hyperparameters
- batch_size: (16, 2)
- num_epochs: (1, 1)
- max_steps: -1
- sampling_strategy: oversampling
- num_iterations: 20
- 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 |
|:------:|:----:|:-------------:|:---------------:|
| 0.0022 | 1 | 0.6468 | - |
| 0.1087 | 50 | 0.2755 | - |
| 0.2174 | 100 | 0.0535 | - |
| 0.3261 | 150 | 0.0011 | - |
| 0.4348 | 200 | 0.0004 | - |
| 0.5435 | 250 | 0.0003 | - |
| 0.6522 | 300 | 0.0003 | - |
| 0.7609 | 350 | 0.0002 | - |
| 0.8696 | 400 | 0.0002 | - |
| 0.9783 | 450 | 0.0001 | - |
### Framework Versions
- Python: 3.11.6
- SetFit: 1.1.0
- Sentence Transformers: 3.0.1
- Transformers: 4.44.2
- PyTorch: 2.4.1+cu121
- Datasets: 2.21.0
- Tokenizers: 0.19.1
## 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}
}
```