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---
license: mit
---
This classification model is based on [sberbank-ai/ruRoberta-large](https://huggingface.co/sberbank-ai/ruRoberta-large).
The model should be used to produce relevance and specificity of the last message in the context of a dialog.
It is pretrained on corpus of dialog data from social networks and finetuned on [tinkoff-ai/context_similarity](https://huggingface.co/tinkoff-ai/context_similarity).
The performance of the model on validation split [tinkoff-ai/context_similarity](https://huggingface.co/tinkoff-ai/context_similarity) (with the best thresholds for validation samples):
<table>
<thead>
<tr>
<td colspan="2">relevance</td>
<td colspan="2">specificity</td>
</tr>
</thead>
<tbody>
<tr>
<td>f0.5</td>
<td>roc-auc</td>
<td>f0.5</td>
<td>roc-auc</td>
</tr>
<tr>
<td>0.86</td>
<td>0.83</td>
<td>0.85</td>
<td>0.86</td>
</tr>
</tbody>
</table>
The model can be loaded as follows:
```python
# pip install transformers
from transformers import AutoTokenizer, AutoModel
tokenizer = AutoTokenizer.from_pretrained("tinkoff-ai/context_similarity")
model = AutoModel.from_pretrained("tinkoff-ai/context_similarity")
# model.cuda()
``` |