README.md

---
language:
- uz
license: apache-2.0
size_categories:
- 100K<n<1M
task_categories:
- question-answering
- translation
pretty_name: Open Assistant Conversations Dataset Release 2 in Uzbek
dataset_info:
  features:
  - name: message_id
    dtype: string
  - name: parent_id
    dtype: string
  - name: user_id
    dtype: string
  - name: created_date
    dtype: string
  - name: text
    dtype: string
  - name: role
    dtype: string
  - name: lang
    dtype: string
  - name: review_count
    dtype: int64
  - name: review_result
    dtype: bool
  - name: deleted
    dtype: bool
  - name: rank
    dtype: float64
  - name: synthetic
    dtype: bool
  - name: model_name
    dtype: 'null'
  - name: detoxify
    struct:
    - name: identity_attack
      dtype: float64
    - name: insult
      dtype: float64
    - name: obscene
      dtype: float64
    - name: severe_toxicity
      dtype: float64
    - name: sexual_explicit
      dtype: float64
    - name: threat
      dtype: float64
    - name: toxicity
      dtype: float64
  - name: message_tree_id
    dtype: string
  - name: tree_state
    dtype: string
  - name: emojis
    struct:
    - name: count
      sequence: int64
    - name: name
      sequence: string
  - name: labels
    struct:
    - name: count
      sequence: int64
    - name: name
      sequence: string
    - name: value
      sequence: float64
  splits:
  - name: validation
    num_bytes: 5261768
    num_examples: 5123
  - name: train
    num_bytes: 128642107
    num_examples: 125181
  download_size: 43601021
  dataset_size: 133903875
configs:
- config_name: default
  data_files:
  - split: validation
    path: data/validation-*
  - split: train
    path: data/train-*
tags:
- human-feedback
---

# Open Assistant Conversations Dataset Release 2 (OASST2) in Uzbek language

This dataset is an Uzbek translated version of [OASST2](https://huggingface.co/datasets/OpenAssistant/oasst2) dataset.

Llama3 chat template + thread formatted dataset based on this translation is also available for model fine-tuning [here](https://huggingface.co/datasets/MLDataScientist/oasst2_uzbek_threads). 

The Uzbek translation was completed in 45 hours using a single T4 GPU and [nllb-200-3.3B](https://huggingface.co/facebook/nllb-200-3.3B) model.

Based on nllb metrics, you might want to only filter out records that were not originally in English or Russian since English-Uzbek and Russian-Uzbek have acceptable metrics and translation quality is noticeable better for those pairs based on my short reviews.

I am sharing the entire Uzbek translated dataset for future research.

The following repo and command was used to do the Uzbek translation.

Repo: https://github.com/UnderstandLingBV/LLaMa2lang

Command used:

```!python3 translate.py nllb --model_size 3.3B uzn_Latn output_uzbek --quant8  --base_dataset OpenAssistant/oasst2 --max_length 512 --checkpoint_n 400 --batch_size 40```

I will fine-tune LLAMA3 8B Uzbek chat model and release in HF soon.