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--- |
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library_name: setfit |
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metrics: |
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- accuracy |
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pipeline_tag: text-classification |
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tags: |
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- setfit |
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- sentence-transformers |
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- text-classification |
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- generated_from_setfit_trainer |
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widget: |
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- text: "Copy env-production to .env (setting up)\nHi, very sorry to ask, dont know\ |
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\ if here would be ok... but where can I get the env-production file to be copied\ |
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\ to .env? because here https://github.com/frappe/frappe_docker/wiki/Easiest-Install\ |
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\ says so but cant be found...```\r\n\r\nThanks,\r\n\r\n$ **cp env-production\ |
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\ .env**\r\n$ sed -i -e \"s/FRAPPE_VERSION=edge/FRAPPE_VERSION=v12.9.4/g\" .env\r\ |
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\n$ sed -i -e \"s/ERPNEXT_VERSION=edge/ERPNEXT_VERSION=v12.6.2/g\" .env\r\n$ sed\ |
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\ -i -e \"s/email@example.com/hello@myweb.com/g\" .env\r\n$ sed -i -e \"s/erp.example.com/erp.myweb.com/g\"\ |
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\ .env\r\n$ sed -i -e \"s/ADMIN_PASSWORD=admin/ADMIN_PASSWORD=supersecret/g\"\ |
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\ .env\r\n$ sed -i -e \"s/MYSQL_ROOT_PASSWORD=admin/MYSQL_ROOT_PASSWORD=longsecretpassword/g\"\ |
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\ .env\r\n```" |
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- text: "[BUG] Unwanted \"supported\" or \"unknown\" message\n## User Story\r\nI see\ |
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\ string \"supported\" on \"start\" command.\r\n\r\n## Basic info\r\n\r\n* **Distro:**\ |
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\ Ubuntu 20.04.3 LTS\r\n* **Game:** Any\r\n* **Command:** start\r\n* **LinuxGSM\ |
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\ version:** v21.5.0\r\n\r\n## Further Information\r\n\r\nProbably it is debug\ |
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\ message from deps check. \"supported\" is replaced by \"unknown\" on unsupported\ |
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\ distro.\r\nThis LGSM is upgraded from previous version.\r\n```\r\naaa@hostname:~$\ |
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\ ./arma3server start\r\nsupported\r\nsupported\r\nsupported\r\n[ OK ] Starting\ |
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\ arma3server: server name\r\n```\r\n\r\n## To Reproduce\r\n\r\nSteps to reproduce\ |
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\ the behaviour:\r\n1. Use start command\r\n\r\n## Expected behaviour\r\nSee only\ |
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\ \"[ OK ] Starting arma3server: server name\" message," |
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- text: 'Docs are still using `DBT_PROJECT_DIR` |
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This was switched to `ARTEFACTS_ DBT_PROJECT_DIR` last release.' |
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- text: 'Document CNI upgrade strategies |
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Document supported CNIs + supported CNI upgrade strategies.' |
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- text: 'Read the Docs |
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Implement read the docs for documentation' |
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inference: true |
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--- |
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# SetFit |
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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. |
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The model has been trained using an efficient few-shot learning technique that involves: |
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1. Fine-tuning a [Sentence Transformer](https://www.sbert.net) with contrastive learning. |
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2. Training a classification head with features from the fine-tuned Sentence Transformer. |
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## Model Details |
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### Model Description |
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- **Model Type:** SetFit |
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<!-- - **Sentence Transformer:** [Unknown](https://huggingface.co/unknown) --> |
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- **Classification head:** a [LogisticRegression](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html) instance |
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- **Maximum Sequence Length:** 384 tokens |
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- **Number of Classes:** 2 classes |
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<!-- - **Training Dataset:** [Unknown](https://huggingface.co/datasets/unknown) --> |
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<!-- - **Language:** Unknown --> |
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<!-- - **License:** Unknown --> |
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### Model Sources |
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- **Repository:** [SetFit on GitHub](https://github.com/huggingface/setfit) |
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- **Paper:** [Efficient Few-Shot Learning Without Prompts](https://arxiv.org/abs/2209.11055) |
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- **Blogpost:** [SetFit: Efficient Few-Shot Learning Without Prompts](https://huggingface.co/blog/setfit) |
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### Model Labels |
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| Label | Examples | |
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|:--------|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| |
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| 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> | |
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| 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> | |
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## Uses |
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### Direct Use for Inference |
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First install the SetFit library: |
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```bash |
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pip install setfit |
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``` |
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Then you can load this model and run inference. |
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```python |
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from setfit import SetFitModel |
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# Download from the 🤗 Hub |
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model = SetFitModel.from_pretrained("setfit_model_id") |
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# Run inference |
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preds = model("Read the Docs |
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Implement read the docs for documentation") |
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``` |
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<!-- |
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### Downstream Use |
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*List how someone could finetune this model on their own dataset.* |
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<!-- |
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### Out-of-Scope Use |
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*List how the model may foreseeably be misused and address what users ought not to do with the model.* |
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## Bias, Risks and Limitations |
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*What are the known or foreseeable issues stemming from this model? You could also flag here known failure cases or weaknesses of the model.* |
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### Recommendations |
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*What are recommendations with respect to the foreseeable issues? For example, filtering explicit content.* |
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## Training Details |
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### Training Set Metrics |
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| Training set | Min | Median | Max | |
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|:-------------|:----|:---------|:------| |
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| Word count | 3 | 186.9402 | 10443 | |
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| Label | Training Sample Count | |
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|:--------|:----------------------| |
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| bug | 47 | |
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| non-bug | 137 | |
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### Training Hyperparameters |
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- batch_size: (16, 2) |
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- num_epochs: (1, 1) |
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- max_steps: -1 |
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- sampling_strategy: oversampling |
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- num_iterations: 20 |
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- body_learning_rate: (2e-05, 1e-05) |
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- head_learning_rate: 0.01 |
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- loss: CosineSimilarityLoss |
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- distance_metric: cosine_distance |
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- margin: 0.25 |
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- end_to_end: False |
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- use_amp: False |
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- warmup_proportion: 0.1 |
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- l2_weight: 0.01 |
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- seed: 42 |
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- eval_max_steps: -1 |
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- load_best_model_at_end: False |
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### Training Results |
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| Epoch | Step | Training Loss | Validation Loss | |
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|:------:|:----:|:-------------:|:---------------:| |
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| 0.0022 | 1 | 0.6468 | - | |
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| 0.1087 | 50 | 0.2755 | - | |
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| 0.2174 | 100 | 0.0535 | - | |
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| 0.3261 | 150 | 0.0011 | - | |
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| 0.4348 | 200 | 0.0004 | - | |
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| 0.5435 | 250 | 0.0003 | - | |
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| 0.6522 | 300 | 0.0003 | - | |
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| 0.7609 | 350 | 0.0002 | - | |
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| 0.8696 | 400 | 0.0002 | - | |
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| 0.9783 | 450 | 0.0001 | - | |
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### Framework Versions |
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- Python: 3.11.6 |
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- SetFit: 1.1.0 |
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- Sentence Transformers: 3.0.1 |
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- Transformers: 4.44.2 |
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- PyTorch: 2.4.1+cu121 |
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- Datasets: 2.21.0 |
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- Tokenizers: 0.19.1 |
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## Citation |
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### BibTeX |
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```bibtex |
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@article{https://doi.org/10.48550/arxiv.2209.11055, |
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doi = {10.48550/ARXIV.2209.11055}, |
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url = {https://arxiv.org/abs/2209.11055}, |
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author = {Tunstall, Lewis and Reimers, Nils and Jo, Unso Eun Seo and Bates, Luke and Korat, Daniel and Wasserblat, Moshe and Pereg, Oren}, |
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keywords = {Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer and information sciences}, |
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title = {Efficient Few-Shot Learning Without Prompts}, |
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publisher = {arXiv}, |
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year = {2022}, |
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copyright = {Creative Commons Attribution 4.0 International} |
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} |
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``` |
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*Clearly define terms in order to be accessible across audiences.* |
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