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# Model Card for mlpf-cms-2024_05_16_attn_model21M
This model reconstructs particles in a detector, based on the tracks and calorimeter clusters recorded by the detector.
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
- **Developed by:** Joosep Pata, Eric Wulff, Farouk Mokhtar, Mengke Zhang, David Southwick, Maria Girone, David Southwick, Javier Duarte
- **Model type:** transformer with 2x6 layers, 32 heads, head dim 16
- **License:** Apache License
### Model Sources
<!-- Provide the basic links for the model. -->
- **Repository:** https://github.com/jpata/particleflow/releases/tag/v1.8.0
## Uses
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
### Direct Use
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
This model may be used to study the physics and computational performance on ML-based reconstruction in simulation in the CMS collaboration.
### 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 our use outside the CMS collaboration.
## 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.
It's only meant for internal CMS use.
## Training Details
Approximately 2 weeks on 1x A100 80GB.
```
https://www.comet.com/jpata/particleflow-pt/9ceb52e8f9f54d7eb4ef06c9ff85bef2?compareXAxis=step&experiment-tab=panels&showOutliers=true&smoothing=0&xAxis=epoch
https://www.comet.com/jpata/particleflow-pt/35bb92e72a3846ff98fb563b0769be13?compareXAxis=step&experiment-tab=panels&showOutliers=true&smoothing=0&xAxis=epoch0
```
### Training Data
CMS ttbar, QCD, Ztautau with pileup, v1.7.1, 400k events each.
```
134G /eos/user/j/jpata/mlpf/tensorflow_datasets/cms/cms_pf_qcd/1.7.1
135G /eos/user/j/jpata/mlpf/tensorflow_datasets/cms/cms_pf_ttbar/1.7.1
130G /eos/user/j/jpata/mlpf/tensorflow_datasets/cms/cms_pf_ztt/1.7.1
```
### Training Procedure
```
#!/bin/bash
#SBATCH --partition gpu
#SBATCH --gres gpu:a100:1
#SBATCH --mem-per-gpu 80G
IMG=/home/software/singularity/pytorch.simg:2024-04-30
cd ~/particleflow
git checkout 8bd199fb064bb40558466d906d46498218848e5c
singularity exec --nv \
--env PYTHONPATH=hep_tfds \
--env KERAS_BACKEND=torch \
$IMG python3.10 mlpf/pyg_pipeline.py --dataset cms --gpus 1 \
--data-dir /path/to/tensorflow_datasets --config parameters/pytorch/pyg-cms.yaml \
--train --conv-type attention --num-epochs 100 --gpu-batch-multiplier 40 --num-workers 4 --prefetch-factor 50 --checkpoint-freq 1 --comet
```
## Evaluation
```
WEIGHTS=pyg-cms_20240430_094836_751206/checkpoints/checkpoint-25-17.631161.pth
singularity exec -B /scratch/persistent --nv \
--env PYTHONPATH=hep_tfds \
--env KERAS_BACKEND=torch \
$IMG python3.10 mlpf/pyg_pipeline.py --dataset cms --gpus 1 \
--data-dir /path/to/joosep/tensorflow_datasets --config parameters/pytorch/pyg-cms.yaml \
--test --make-plots --conv-type attention --gpu-batch-multiplier 10 --num-workers 8 --prefetch-factor 10 --load $WEIGHTS --test-datasets cms_pf_ttbar --ntest 50000
```
## Model Card Contact
Joosep Pata, [email protected]
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