---
library_name: transformers
tags: []
---

# Model Card for Model ID

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## Model Details

### Model Description

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This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.

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### Model Sources [optional]

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## Uses

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### 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

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#### 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



## Model Examination [optional]

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## Environmental Impact

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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).

- **Hardware Type:** [More Information Needed]
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## Technical Specifications [optional]

### Model Architecture and Objective

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## Citation [optional]

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## Glossary [optional]

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## Model Card Authors [optional]

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## Model Card Contact

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## Benchmark Results

Evaluated on **100-example custom GEC test** (pure model inference, no pre/post pipeline).

| Category | Score |
|----------|-------|
| Орфография (емле) | 0/30 (0%) |
| Грамматика | 0/20 (0%) |
| Пунктуация | 0/15 (0%) |
| Смешанный | 0/20 (0%) |
| Identity preservation | 1/15 (7%) |
| **Total** | **1/100 (1%)** |


## Leaderboard (100-example custom benchmark)

| Модель | Total | Емле/30 | Грамм/20 | Пункт/15 | Смеш/20 | Ident/15 |
|--------|-------|---------|----------|----------|---------|---------|
| **[sozkz-core-llama-600m-kk-gec-v1](https://huggingface.co/stukenov/sozkz-core-llama-600m-kk-gec-v1)** | **47%** | 15 | 12 | 3 | 2 | 15/15 |
| [sozkz-fix-qwen-500m-kk-gec-v3](https://huggingface.co/stukenov/sozkz-fix-qwen-500m-kk-gec-v3) | 38% | 0 | 16 | 9 | 0 | 13/15 |
| [sozkz-core-llama-300m-kk-gec-v4](https://huggingface.co/stukenov/sozkz-core-llama-300m-kk-gec-v4) | 37% | 9 | 6 | 4 | 3 | 15/15 |
| [sozkz-fix-qwen-500m-kk-gec-v1](https://huggingface.co/stukenov/sozkz-fix-qwen-500m-kk-gec-v1) | 35% | 0 | 12 | 8 | 0 | 15/15 |
| [sozkz-fix-qwen-500m-kk-gec-v2](https://huggingface.co/stukenov/sozkz-fix-qwen-500m-kk-gec-v2) | 30% | 0 | 11 | 7 | 0 | 12/15 |
| [sozkz-core-llama-1b-kk-gec-v1](https://huggingface.co/stukenov/sozkz-core-llama-1b-kk-gec-v1) | 16% | 2 | 6 | 1 | 0 | 7/15 |
| [sozkz-fix-qwen-500m-kk-gec-v4](https://huggingface.co/stukenov/sozkz-fix-qwen-500m-kk-gec-v4) | 5% | 0 | 1 | 4 | 0 | 0/15 |
| [sozkz-fix-mt5b-kk-gec-run13-v1](https://huggingface.co/stukenov/sozkz-fix-mt5b-kk-gec-run13-v1) | 5% | 0 | 2 | 0 | 0 | 3/15 |
| [sozkz-nllb-1b-kk-gec-v1](https://huggingface.co/stukenov/sozkz-nllb-1b-kk-gec-v1) | 1% | 0 | 1 | 0 | 0 | 0/15 |
| [sozkz-nllb-1b-kk-pretrain-v1](https://huggingface.co/stukenov/sozkz-nllb-1b-kk-pretrain-v1) | 1% | 0 | 1 | 0 | 0 | 0/15 |
| [sozkz-core-llama-300m-kk-gec-v3](https://huggingface.co/stukenov/sozkz-core-llama-300m-kk-gec-v3) | 1% | 0 | 1 | 0 | 0 | 0/15 |
| sozkz-core-llama-300m-kk-gec-v1/v2a/v2b | 0–1% | 0 | 0 | 0 | 0 | 0–1 |
| sozkz-fix-mt5-50m-kk-gec-v1 | 0% | 0 | 0 | 0 | 0 | 0/15 |