### Introduction:
This model belongs to text-classification. You can determine the emotion behind a sentence.
### Label Explaination:
LABEL_1: Positive (have positive emotion)

LABEL_0: Negative (have negative emotion)
### Usage:
```python
>>> from transformers import pipeline
>>> ec = pipeline('sentiment-analysis', model='Osiris/emotion_classifer')
>>> ec("Hello, I'm a good model.")
```

### Accuracy:
We reach 81.81% for validation dataset, and % for test dataset.