---
library_name: transformers
datasets:
- pasukka/autoparts_filters
license: apache-2.0
language:
- ru
metrics:
- f1
- accuracy
base_model: ai-forever/ruRoberta-large
---

# Model Card for Model ID

<!-- Provide a quick summary of what the model is/does. -->


## Model Details

### Model Description

- **Language(s) (NLP):** Russian
- **License:** apache-2.0
- **Finetuned from model:** ai-forever/ruRoberta-large


## Usage

```python
from transformers import AutoTokenizer, AutoModelForSequenceClassification

model = AutoModelForSequenceClassification.from_pretrained("pasukka/auto-filters-term-classifier-v.0.2")
tokenizer = AutoTokenizer.from_pretrained('ai-forever/ruRoberta-large')

term = 'фильтр топливный'
outputs = model.forward(**tokenizer(term, return_tensors='pt').to(device='cuda'))
id = outputs.logits.argmax(dim=1)[0].item()

print(model.config.id2label[id])
```
Result:
```
фильтр
```


### Direct Use

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### Downstream Use [optional]

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### Out-of-Scope Use

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## Bias, Risks, and Limitations

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### Recommendations

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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.

## How to Get Started with the Model

Use the code below to get started with the model.

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## Training Details

### Training Data

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### Training Procedure

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#### Preprocessing [optional]

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#### Training Hyperparameters

- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->

#### Speeds, Sizes, Times [optional]

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## Evaluation

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### Testing Data, Factors & Metrics

#### Testing Data

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#### Factors

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#### Metrics

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### Results

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#### Summary