Create README.md

README.md

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+---
+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
+- russian
+- multiclass
+- classification
+---
+
+Модель [RuBERT](https://huggingface.co/DeepPavlov/rubert-base-cased) которая был fine-tuned на задачу __sentiment classification__ для коротких __Russian__ текстов.
+Задача представляет собой __multi-class classification__ со следующими метками:
+
+```yaml
+0: neutral
+1: positive
+2: negative
+```
+
+## Usage
+
+```python
+from transformers import pipeline
+model = pipeline(model="r1char9/rubert-base-cased-russian-sentiment")
+model("Привет, ты мне нравишься!")
+# [{'label': 'positive', 'score': 0.9818321466445923}]
+```
+
+## Dataset
+
+Модель была натренирована на данных:
+
+- Kaggle Russian News Dataset
+- Linis Crowd 2015
+- Linis Crowd 2016
+- RuReviews
+- RuSentiment
+
+```yaml
+tokenizer.max_length: 256
+batch_size: 32
+optimizer: adam
+lr: 0.00001
+weight_decay: 0
+epochs: 2
+```
+
+Train/validation/test splits are 80%/10%/10%.
+
+## Eval results (on test split)
+
+|         |neutral|positive|negative|macro avg|weighted avg|
+|---------|-------|--------|--------|---------|------------|
+|precision|0.72   |0.85    |0.75    |0.77     |0.77        |
+|recall   |0.75   |0.84    |0.72    |0.77     |0.77        |
+|f1-score |0.73   |0.84    |0.73    |0.77     |0.77        |
+|auc-roc  |0.86   |0.96    |0.92    |0.91     |0.91        |
+|support  |5196   |3831    |3599    |12626    |12626       |