---
datasets:
- breadlicker45/muti-label-gender-test2
base_model:
- ibm-granite/granite-embedding-278m-multilingual
pipeline_tag: text-classification
---

### Model Description

This is a model for classifying male, female, and non-binary genders from one paragraph.

## Training Details 

* batch-size: 32
* epoch: 1
* GPU used: An Nvidia P40 gpu

# Evaluation 
- F1 Score: 0.6816
- ROC AUC: 0.6976
- Accuracy: 0.4122