Description
This model is a fine-tuned version of google-bert/bert-base-multilingual-cased using the Kundyzka/informatics_kaz dataset. Developed by Kundyz Maksutova, PhD Candidate, this model is specifically optimized for question-answering tasks in the Kazakh language, with a focus on computer science and informatics.
Key Features:
- Developer: Kundyz Maksutova, PhD Candidate
- Base Model:
google-bert/bert-base-multilingual-cased
- Dataset:
Kundyzka/informatics_kaz
- Language: Kazakh (
kk)
- Task: Question Answering (
pipeline_tag: question-answering)
- Library:
adapter-transformers
Performance:
This model demonstrates significant improvements after fine-tuning, as highlighted by the following metrics:
- Before Training:
- F1 Score: 24.586
- Exact Match (EM): 11.818
- After Training:
- F1 Score: 63.317
- Exact Match (EM): 43.162
These metrics were evaluated on the Kundyzka/informatics_kaz dataset, indicating a substantial enhancement in the model’s ability to handle domain-specific questions.
Intended Use:
This model is intended for question-answering applications in the Kazakh language. Potential use cases include:
- Educational Platforms: Assisting students with queries in informatics and computer science.
- Research Projects: Supporting research in Kazakh natural language processing.
- AI Applications: Enhancing intelligent systems, chatbots, or virtual assistants requiring Kazakh language support.
Limitations:
- Domain-Specific Training: The model is optimized for informatics and computer science topics, and performance may degrade on unrelated queries.
- Language Support: The model supports only the Kazakh language and does not handle multilingual tasks.
- Bias: Potential biases in the dataset may influence model outputs.
Tags:
computerscienceinformaticsquestion-answeringKazakhadapter-transformers
This model is a step forward in enabling high-quality question-answering systems for low-resource languages like Kazakh. For further details, customization, or fine-tuning, refer to the model repository.
