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---
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] |