---
language:
- ru
license: apache-2.0
datasets:
- 0x7194633/fialka-v3-data
pipeline_tag: text-generation
model-index:
- name: fialka-13B-v3
  results:
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: AI2 Reasoning Challenge (25-Shot)
      type: ai2_arc
      config: ARC-Challenge
      split: test
      args:
        num_few_shot: 25
    metrics:
    - type: acc_norm
      value: 30.97
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=0x7194633/fialka-13B-v3
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: HellaSwag (10-Shot)
      type: hellaswag
      split: validation
      args:
        num_few_shot: 10
    metrics:
    - type: acc_norm
      value: 48.83
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=0x7194633/fialka-13B-v3
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: MMLU (5-Shot)
      type: cais/mmlu
      config: all
      split: test
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 26.36
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=0x7194633/fialka-13B-v3
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: TruthfulQA (0-shot)
      type: truthful_qa
      config: multiple_choice
      split: validation
      args:
        num_few_shot: 0
    metrics:
    - type: mc2
      value: 40.58
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=0x7194633/fialka-13B-v3
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: Winogrande (5-shot)
      type: winogrande
      config: winogrande_xl
      split: validation
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 59.43
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=0x7194633/fialka-13B-v3
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: GSM8k (5-shot)
      type: gsm8k
      config: main
      split: test
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 1.29
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=0x7194633/fialka-13B-v3
      name: Open LLM Leaderboard
---
# Fialka v3.0 13B

![Violet](https://i.imgur.com/EDwW6t6.png)
## Description
Fialka language models are trained to follow instructions and maintain communication in Russian.
## Usage
The model has a query format as in zephyr.
```
<|user|>
Что такое мем?</s>
<|assistant|>
Мем (англ. meme) — это единица культурной информации, которая распространяется в социальных сетях и других онлайн-платформах с помощью цифровых технологий или через физический контакт. Мемы могут быть связаны между собой тематически или иметь общие черты, такие как использование определенных слов или фраз для создания определенного настроения или выражения эмоций. Они также могут содержать информацию о культуре, истории или науке, которую можно использовать для обучения новым вещам или расширения кругозора.
```
Check out the [space](https://huggingface.co/spaces/0x7194633/fialka) to use the model in UI without downloading.
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_0x7194633__fialka-13B-v3)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |34.58|
|AI2 Reasoning Challenge (25-Shot)|30.97|
|HellaSwag (10-Shot)              |48.83|
|MMLU (5-Shot)                    |26.36|
|TruthfulQA (0-shot)              |40.58|
|Winogrande (5-shot)              |59.43|
|GSM8k (5-shot)                   | 1.29|