SetFit with sentence-transformers/paraphrase-mpnet-base-v2
This is a SetFit model that can be used for Text Classification. This SetFit model uses sentence-transformers/paraphrase-mpnet-base-v2 as the Sentence Transformer embedding model. A LogisticRegression instance is used for classification.
The model has been trained using an efficient few-shot learning technique that involves:
- Fine-tuning a Sentence Transformer with contrastive learning.
- Training a classification head with features from the fine-tuned Sentence Transformer.
Model Details
Model Description
Model Sources
Model Labels
| Label |
Examples |
| 1 |
- "Hi Jonathan, I hope this message finds you well. I hear things are going well with the Beta project. That said, Terry mentioned that there were some issues with the reports. From what I understand, they would like them to be more concise and straight to the point, as well as more business focused. I recommend you reach out to Terry so you both could review in detail one of the reports he submits. This should help you help you align to their expectations. Additionally, i'd be happy to review the reports before you send them off to Terry and provide my feedback. I know this project is important to you, so please let me know how this meeting goes and how else I can help. Regards, William"
- "Jonathan, I hope you are well - I am very excited that you are part of this development team and really appreciate all the support you give to us; while doing this some comments have arise that can be opportunity areas to improve your work and get this program ahead.1. The communication between team members is not clear and improvements can be done to this: by this I mean to connect more with other team members before submitting your reports.2. One of the reasons you were chosen is because of your enthusiastic attitude and knowledge, but too much information sometimes can harm the delivery reports that needs to be concise and business oriented. 3.Please forward me your latest report so we can discuss it furthermore when I come back and see what can be improve and we can work from there.4. Please don't be discourage, these are opportunity areas that we can engage and as always keep up the good work. Have a great week. Thanks"
- 'Hi Jonathan, Good to hear you are enjoying the work. I would like to discuss with you feedback on your assignment and the reports you are producing. It is very important to understand the stakeholders who will be reading your report. You may have gathered a lot of good information BUT do not put them all on your reports. The report should state facts and not your opinions. Create reports for the purpose and for the audience. I would also suggest that you reach out to Terry to understand what information is needed on the reports you produce.Having said that, the additional insights you gathered are very important too. Please add them to our knowledge repository and share with the team. It will be a great sharing and learning experience. You are very valuable in your knowledge and I think that it would benefit you and the organization tremendously when you are to channelize your insights and present the facts well. I would encourage you to enroll for the business writing training course. Please choose a date from the learning calendar and let me know. Regards, William'
|
| 0 |
- 'Jonathan, First I want to thank you for your help with the Beta project. However, it has been brought to my attention that perhaps ABC-5 didn't do enough to prepare you for the extra work and I would like to discuss some issues. The nature of these reports requires them to be technical in nature. Your insights are very valuable and much appreciated but as the old line goes "please give me just the facts". Given the critical nature of the information you are providing I can't stress the importance of concise yet detail factual reports. I would like to review your reports as a training exercise to help you better meet the team requirements. Given that there are some major reports coming up in the immediate future, I would like you to review some training options and then present a report for review. Again your insights are appreciated but we need to make sure we are presenting the end-use with only the information they need to make a sound business decision. I also understand you would like to grow into a leadership position so I would like to discuss how successfully implementing these changes would be beneficial in demonstrating an ability to grow and take on new challenges. '
- "Hi Jonathan, How are You doing with the Beta project? It seams You are very exited about the project.There are two topics that I want to point out that I expct to be Your focus on this project.I review the latest report and saw that in addition to a tchnical information that we have agreed to be included in that, there is a lots of commentaries from Your side. It is greeate that You see the opportunities and perspectives on the findings but I ask You to focus on collecting and passing on the technical information according to the agreed template. We can focus on Your ideas separately once the Beta gets to that stage.The second thing I'd like you to focus is the organizing the details in the reports. Please work together with Terry on that. As the deadlines for presenting the reports to CEO are quite challenging, they have lost of hints and tricks how to make the report informative and easy to read. I've have used his experience and competence myself. It is very important that we submit the report on time. Please add me as well to the reciepient list once You send the infotmation to Terry. Good luck!"
- 'Good Afternoon Jonathan, I hope you are well and the travelling is not too exhausting. I wanted to touch base with you to see how you are enjoying working with the Beta project team? I have been advised that you are a great contributor and are identifying some great improvements, so well done. I understand you are completing a lot of reports and imagine this is quite time consuming which added to your traveling must be quite overwhelming. I have reviewed some of your reports and whilst they provide all the technical information that is required, they are quite lengthy and i think it would be beneficial for you to have some training on report structures. This would mean you could spend less time on the reports by providing only the main facts needed and perhaps take on more responsibility. When the reports are reviewed by higher management they need to be able to clearly and quickly identify any issues. Attending some training would also be great to add to your career profile for the future. In the meantime perhaps you could review your reports before submitting to ensure they are clear and consise with only the technical information needed,Let me know your thoughts. Many thanks again and well done for all your hard work. Kind regards William'
|
Uses
Direct Use for Inference
First install the SetFit library:
pip install setfit
Then you can load this model and run inference.
from setfit import SetFitModel
model = SetFitModel.from_pretrained("gmenchetti/paraphrase-mpnet-base-v2-empathy")
preds = model("Hello Jonathan, I hope you day is going well. The purpose of this msg is to improve your communication regarding your work on the Beta Project. You are important which is why we need to make sure that your thoughts and Ideas are clearly communicated with helpful factual info. I want to get your thoughts on how you best communicate and your thoughts on how to communicate more concisely. Please come up with 2-3 suggestions as will I and lets set up a time within the next 48 hours that you and I can build a plan that will help ensure your great work is being understood for the success of Beta. I am confident that we will develop a plan that continues allow your work to help the program. Please meg me what time works best for you when you end your travel. Best, William")
Training Details
Training Set Metrics
| Training set |
Min |
Median |
Max |
| Word count |
95 |
213.2333 |
377 |
| Label |
Training Sample Count |
| 0 |
13 |
| 1 |
17 |
Training Hyperparameters
- batch_size: (4, 4)
- num_epochs: (3, 3)
- max_steps: -1
- sampling_strategy: oversampling
- num_iterations: 20
- body_learning_rate: (2e-05, 2e-05)
- head_learning_rate: 2e-05
- loss: CosineSimilarityLoss
- distance_metric: cosine_distance
- margin: 0.25
- end_to_end: False
- use_amp: False
- warmup_proportion: 0.1
- seed: 42
- eval_max_steps: -1
- load_best_model_at_end: False
Training Results
| Epoch |
Step |
Training Loss |
Validation Loss |
| 0.0033 |
1 |
0.3705 |
- |
| 0.1667 |
50 |
0.2017 |
- |
| 0.3333 |
100 |
0.0503 |
- |
| 0.5 |
150 |
0.0006 |
- |
| 0.6667 |
200 |
0.0005 |
- |
| 0.8333 |
250 |
0.0001 |
- |
| 1.0 |
300 |
0.0002 |
- |
| 1.1667 |
350 |
0.0002 |
- |
| 1.3333 |
400 |
0.0001 |
- |
| 1.5 |
450 |
0.0001 |
- |
| 1.6667 |
500 |
0.0 |
- |
| 1.8333 |
550 |
0.0 |
- |
| 2.0 |
600 |
0.0001 |
- |
| 2.1667 |
650 |
0.0001 |
- |
| 2.3333 |
700 |
0.0 |
- |
| 2.5 |
750 |
0.0 |
- |
| 2.6667 |
800 |
0.0001 |
- |
| 2.8333 |
850 |
0.0 |
- |
| 3.0 |
900 |
0.0 |
- |
Framework Versions
- Python: 3.10.13
- SetFit: 1.0.3
- Sentence Transformers: 2.6.1
- Transformers: 4.39.3
- PyTorch: 2.0.0.post200
- Datasets: 2.16.1
- Tokenizers: 0.15.2
Citation
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}
}
