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--- |
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license: mit |
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language: |
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- ru |
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metrics: |
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- f1 |
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- roc_auc |
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- precision |
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- recall |
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pipeline_tag: text-classification |
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tags: |
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- sentiment-analysis |
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- multi-class-classification |
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- sentiment analysis |
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- rubert |
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- sentiment |
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- bert |
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- tiny |
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- russian |
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- multiclass |
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- classification |
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datasets: |
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- sismetanin/rureviews |
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- RuSentiment |
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- LinisCrowd2015 |
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- LinisCrowd2016 |
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- KaggleRussianNews |
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--- |
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The task is a __multi-class classification__ with the following labels: |
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```yaml |
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0: neutral |
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1: positive |
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2: negative |
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``` |
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Label to Russian label: |
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```yaml |
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neutral: нейтральный |
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positive: позитивный |
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negative: негативный |
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``` |
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## Usage |
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```python |
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from transformers import pipeline |
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model = pipeline(model="seara/rubert-tiny2-russian-sentiment") |
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model("Привет, ты мне нравишься!") |
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# [{'label': 'positive', 'score': 0.9398769736289978}] |
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``` |
