motivbot-multilingual-mdeberta-v1

MotivBot Multilingual Mental Health Classifier — mDeBERTa (Best Fold)

This model uses mDeBERTa‑v3‑base as backbone, with CLS+mean pooling and structured features (Age, Gender, PHQ‑9, RSES).
It was trained on a 5‑fold ensemble; this is the best single fold (Fold 4) with a validation ternary macro‑F1 of 0.6538.

Load the model

import torch
import json
from transformers import AutoTokenizer
from modeling import MentalHealthClassifierV6

device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')

with open("model_config.json") as f:
    config = json.load(f)
with open("preprocess_stats.json") as f:
    stats = json.load(f)

model = MentalHealthClassifierV6(model_name=config["model_name"])
model.load_state_dict(torch.load("pytorch_model.bin", map_location=device))
model.to(device).eval()
tokenizer = AutoTokenizer.from_pretrained(".")

# Normalise structured features using stats:
age_norm = (age - stats['num_mean']['Age']) / stats['num_std']['Age']
# ... similarly for PHQ9, RSES, Gender