This modelcard aims to be a base template for new models. It has been generated using
this raw template.
The OmniJet- \(\alpha\) model was published in
here was used as the base model for identifying hadronically decaying taus, reconstructing their kinematics and predicting their decay mode.
The base model, initially trained on
JetClass dataset, was now fine-tuned on
Fu \(\tau\)ure dataset.
The models included here are for 3 separate tasks:
This will add up to 9 different models.
The intended use of the models is to study the feasibility of foundation models for the purposes of reconstructing and identifying hadronically decaying tau leptons.
This model is not intended for physics measurements on real data. The trainings have been done on CLIC detector simulations.
The model has only been trained on simulation data and has not been validated against real data. Although the base model has been published in a peer-reviewed journal, the fine-tuned model has not been.
Use the code below to get started with the model.
1# Clone the repository
2git clone git@github.com:HEP-KBFI/ml-tau-en-reg.git --recursive
3cd ml-tau-en-reg
4
5
6# Get the models
7git clone https://huggingface.co/LauritsT/TauRecoID models
The data used to fine-tune the base model can be found here:
Fu \(\tau\)ure dataset
Training on 1M jets on AMD MI250x for 100 epochs takes ~8h.
Testing data can also be found in the same
Zenodo entry as the rest of the data.
Software to train and analyze the model
