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---
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