---
language: en
tags:
- vad
- emotion
- bert
license: mit
model-index:
- name: vad-bert
  results: []
datasets:
- reallycarlaost/emobank
base_model:
- google-bert/bert-base-uncased
---

# vad-bert

A BERT-based model fine-tuned to predict **Valence, Arousal, and Dominance (VAD)** values from text.

## Intended use

This model is intended for regression tasks on emotional dimensions. It outputs 3 float values corresponding to:

- Valence (pleasant vs unpleasant)
- Arousal (calm vs excited)
- Dominance (controlled vs in control)

## Example

```python
from transformers import AutoTokenizer, AutoModelForSequenceClassification

tokenizer = AutoTokenizer.from_pretrained("RobroKools/vad-bert")
model = AutoModelForSequenceClassification.from_pretrained("RobroKools/vad-bert")

inputs = tokenizer("I'm feeling great!", return_tensors="pt")
outputs = model(**inputs)

vad = outputs.logits.detach().squeeze().tolist()
print(vad)  # [valence, arousal, dominance]