---
license: mit
language:
- ru
metrics:
- f1
- roc_auc
- precision
- recall
pipeline_tag: text-classification
tags:
- sentiment-analysis
- multi-class-classification
- sentiment analysis
- rubert
- sentiment
- bert
- tiny
- russian
- multiclass
- classification
datasets:
- sismetanin/rureviews
- RuSentiment
- LinisCrowd2015
- LinisCrowd2016
- KaggleRussianNews
---

The task is a __multi-class classification__ with the following labels:

```yaml
0: neutral
1: positive
2: negative
```

Label to Russian label:

```yaml
neutral: нейтральный
positive: позитивный
negative: негативный
```

## Usage

```python
from transformers import pipeline
model = pipeline(model="seara/rubert-tiny2-russian-sentiment")
model("Привет, ты мне нравишься!")
# [{'label': 'positive', 'score': 0.9398769736289978}]
```