| | --- |
| | 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 |
| | <!-- - **Sentence Transformer:** [Unknown](https://huggingface.co/unknown) --> |
| | - **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 |
| | <!-- - **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 | |
| | |:--------|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| |
| | | bug | <ul><li>'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.'</li><li>'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<img src="https://www.dropbox.com/s/06o9rixg2r5ocvz/ppic155.jpeg?raw=1" alt="" style="zoom:33%;" />\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'</li><li>'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'</li></ul> | |
| | | non-bug | <ul><li>'Migrating Woo Comparison table to Sparks\n### Description:\r\nWe need to migrate the current comparison table to Sparks and remove it from Otter.'</li><li>'[bug] Hard code \'movie_id\' in neg_sampler.py\n<img width="914" alt="Screen Shot 2022-06-20 at 3 26 21 PM" src="https://user-images.githubusercontent.com/15731690/174547685-40628045-4d29-466c-a68a-ded28e1ced6d.png">\r\n\r\nUse item parameter instead of hard code \'movie_id\'.'</li><li>"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."</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("Read the Docs |
| | Implement read the docs for documentation") |
| | ``` |
| | |
| | <!-- |
| | ### 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 | 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} |
| | } |
| | ``` |
| | |
| | <!-- |
| | ## 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.* |
| | --> |
