Update README.md

README.md

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----
-license: mit
----
+---
+license: mit
+language:
+- en
+tags:
+- tau
+- hep
+- fcc
+- clic
+- ee
+- reconstruction
+- identification
+- decay_mode
+- foundation_model
+- omnijet_alpha
+---
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+This modelcard aims to be a base template for new models. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/modelcard_template.md?plain=1).
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+- **Developed by:** Joschka Birk, Anna Hallin, Gregor Kasieczka
+- **Model type:** Transformer
+- **Language(s) (NLP):** Pytorch
+- **Finetuned from model:** https://doi.org/10.1088/2632-2153/ad66ad
+
+The OmniJet- \\(\alpha\\) model was published in [here](https://doi.org/10.1088/2632-2153/ad66ad) 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](https://doi.org/10.5281/zenodo.6619768), was now fine-tuned on [Fu \\(\tau\\)ure](https://doi.org/10.5281/zenodo.13881061) dataset.
+The models included here are for 3 separate tasks:
+
+- Tau-tagging (binary classification)
+- Tau kinematic reconstruction (regression)
+- Tau decay mode classification (multiclass-classification)
+
+And for 3 different ways of training:
+
+- From scratch
+- Fixed backbone (fine-tune only head)
+- Fine-tuning (fine-tune both head and backbone)
+
+This will add up to 9 different models.
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository (base model):** https://github.com/uhh-pd-ml/omnijet_alpha
+- **Repository (fine-tuned model):** https://github.com/HEP-KBFI/ml-tau-en-reg
+- **Paper:**  https://doi.org/10.1088/2632-2153/ad66ad
+
+## Uses
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+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.
+
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+This model is not intended for physics measurements on real data. The trainings have been done on CLIC detector simulations.
+
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+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.
+
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+```bash
+# Clone the repository
+git clone git@github.com:HEP-KBFI/ml-tau-en-reg.git --recursive
+cd ml-tau-en-reg
+
+
+# Get the models
+git clone https://huggingface.co/LauritsT/TauRecoID models
+```
+
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+The data used to fine-tune the base model can be found here: [Fu \\(\tau\\)ure](https://doi.org/10.5281/zenodo.13881061) dataset
+
+
+
+#### Training Hyperparameters
+
+- No hyperparameter tuning has been done. <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+Training on 1M jets on AMD MI250x for 100 epochs takes ~8h.
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+Testing data can also be found in the same [Zenodo entry](https://doi.org/10.5281/zenodo.13881061) as the rest of the data.
+
+
+#### Software
+
+[Software](https://github.com/HEP-KBFI/ml-tau-en-reg/) to train and analyze the model
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+[OmniJet- \\(\alpha\\)](https://doi.org/10.1088/2632-2153/ad66ad)
+## Model Card Authors [optional]
+
+Laurits Tani (laurits.tani@cern.ch)
+
+## Model Card Contact
+
+Laurits Tani (laurits.tani@cern.ch)