You can deploy this model and start earning money today!

fmeireles/
genderBR

Name: genderBR
Availability: InStock

torch

genderbr

tabular-classification

gpl-2.0

Views

No views yet

genderBR: Gender Prediction from Brazilian First Names

A character-level neural network that predicts the probability of a Brazilian first name being female.

Model

2-layer bidirectional GRU with attention pooling.

Parameter	Value
Embedding dim	64
Hidden dim	192
GRU layers	2 (bidirectional)
Pooling	Learned attention
Dropout	0.1 (embedding), 0.2 (inter-layer), 0.4 (output)
Parameters	~600K

Training

Data: 142K unique names from IBGE Census (2010 & 2022)
Target: Probability of a name being female (continuous, 0–1)
Loss: BCE with logits
Optimizer: Adam (lr=1e-3, weight_decay=1e-4)
Split: 80/10/10 train/validation/test
Early stopping: patience=5 on validation loss
Framework: R torch + luz

Performance (held-out test set)

Metric	Value
BCE loss	0.110
Accuracy (threshold 0.5)	96.5%

Usage

# install.packages("genderBR")
library(genderBR)

download_gender_model()  # one-time download

get_gender_nn("Maria")
#> "Female"

get_gender_nn(c("Lusjane", "Joao"), prob = TRUE)
#> 0.95  0.02

Files

genderbr_weights.pt — model state dict (R torch format) genderbr_vocab.rds — vocabulary and hyperparameters

fmeireles/genderBR