README.md

---
library_name: transformers
license: apache-2.0
datasets:
- RussianNLP/rucola
language:
- ru
base_model:
- deepvk/RuModernBERT-small
pipeline_tag: text-classification
metrics:
- accuracy
- matthews_correlation
model-index:
  - name: d0rj/RuModernBERT-small-rucola
    results:
      - task:
          type: text-classification
        dataset:
          name: RussianNLP/rucola
          type: RussianNLP/rucola
        metrics:
          - name: Acc
            type: accuracy
            value: 0.70
          - name: MCC
            type: matthews_correlation
            value: 0.25
        source:
          name: RuCoLA benchmark
          url: https://rucola-benchmark.com/leaderboard?
---

# d0rj/RuModernBERT-small-rucola

## Usage

Labels: "1" refers to "acceptable", while "0" corresponds to "unacceptable".

### Simple

```python
from transformers import pipeline


pipe = pipeline('text-classification', model='d0rj/RuModernBERT-small-rucola')
pipe(["Мне предоставилась возможность все видеть, сам оставаясь незамеченным.", "Весной в лесу очень хорошо"])
>>> [{'label': 'LABEL_0', 'score': 0.5270525217056274},
>>> {'label': 'LABEL_1', 'score': 0.923351526260376}]
```

### Using weights

```python
import torch
from transformers import AutoModelForSequenceClassification, AutoTokenizer


model = AutoModelForSequenceClassification.from_pretrained("d0rj/RuModernBERT-small-rucola")
tokenizer = AutoTokenizer.from_pretrained("d0rj/RuModernBERT-small-rucola")


@torch.inference_mode()
def predict(text: str | list[str], model = model, tokenizer = tokenizer) -> list[int]:
    inputs = tokenizer(text, return_tensors='pt', padding=True, truncation=True).to(model.device)
    outputs = model(**inputs)
    probs = torch.nn.functional.softmax(outputs.logits, dim=-1)
    return probs.cpu().argmax(dim=-1).numpy().tolist()


predict(["Мне предоставилась возможность все видеть, сам оставаясь незамеченным.", "Весной в лесу очень хорошо"])
>>> [0, 1]
```

## Metrics

| name | accuracy | MCC | model size, params |
| ---- | -------- | --- | ------------------ |
| [d0rj/RuModernBERT-small-rucola](https://huggingface.co/d0rj/RuModernBERT-small-rucola) | 0.7 | 0.25 | 34.5M |
| [RussianNLP/ruRoBERTa-large-rucola](https://huggingface.co/RussianNLP/ruRoBERTa-large-rucola) | 0.82 | 0.56 | 355M |

## Training

See [raw Weights & Biases logs](https://wandb.ai/d0rj/rucola_small) or [simple report](https://wandb.ai/d0rj/rucola_small/reports/RuModernBERT-small-rucola--VmlldzoxMTcyNDgzNg).