brands_emotion_textual_v1

Turkish Social Media Emotion Classifier (BERTurk fine-tuned)

A fine-tuned version of dbmdz/bert-base-turkish-128k-uncased for 7-class emotion classification of Turkish (and mixed Turkish/English) social media text.

Labels

The model predicts one of 7 basic emotion categories (Ekman's basic emotions + neutrality):

Training Data

The model was fine-tuned on a semi-supervised training set of Turkish/English social media messages (brand posts and user comments), weakly labeled via emoji co-occurrence with emotion lexicons (Turkish Emotion Lexicon and NRC Emotion Lexicon). The training corpus is heavily imbalanced toward happiness, reflecting the natural distribution of emoji-labeled social media content:

Training Procedure

Fine-tuned for 5 epochs with a 15% held-out validation split.

Evaluation Results

Evaluated on a held-out 15% test split (n=15,569):

Model performance is strongest on the majority happy class and the (small-support) disgust and neutral classes, and weaker on surprise and fear, largely reflecting class imbalance in the weakly-labeled training data.

Intended Use

This model classifies the dominant emotion in Turkish-language social media text, including brand posts and user replies/comments. It may generalize to other Turkish social media sentiment/emotion tasks depending on domain similarity.

Limitations: Training labels were derived automatically from emoji co-occurrence rather than human annotation, so label noise is present. Performance on minority classes (fear, surprise) is comparatively weaker.

How to Use

from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline

model_name = "<your-username>/<model-repo-name>"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForSequenceClassification.from_pretrained(model_name)

classifier = pipeline("text-classification", model=model, tokenizer=tokenizer)
classifier("Bugün harika bir gün geçirdim, çok mutluyum 😊")

Base Model

This model was fine-tuned from dbmdz/bert-base-turkish-128k-uncased (BERTurk), a Turkish BERT model trained by MDZ Digital Library team at the Bavarian State Library.