uvegesistvan/proposal_2b_german_to_hungarian_PT_label_v2

Proposal 2B: German to Hungarian Emotion Labeling (v2)

Model Description

This model is designed for emotion classification in Hungarian texts. It was fine-tuned to recognize nine emotion categories and trained on a dataset with labeled examples.

Labels and Their Meanings

Evaluation Metrics

The model was evaluated using precision, recall, f1-score, and accuracy.

Classification Report

Overall Performance:

• —Accuracy: 72%
• —Macro Avg: Precision: 0.73, Recall: 0.72, F1-score: 0.73
• —Weighted Avg: Precision: 0.72, Recall: 0.72, F1-score: 0.72

How to Use

To use this model for text classification in Python:

from transformers import pipeline

classifier = pipeline("text-classification", model="uvegesistvan/proposal_2b_german_to_hungarian_PT_label_v2")

text = "Ich bin sehr glücklich, dass du hier bist!"  # German
result = classifier(text)
print(result)