metadata
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