roberta-kaz-large
| Property | Value |
|---|---|
| Parameter Count | 355M |
| Model Type | RoBERTa |
| License | AFL-3.0 |
| Tensor Type | F32 |
| Language | Kazakh |
What is roberta-kaz-large?
roberta-kaz-large is a sophisticated language model specifically designed for the Kazakh language, built on the RoBERTa architecture and trained from scratch. This model represents a significant advancement in Kazakh language processing, featuring 355 million parameters and trained on a comprehensive multidomain dataset.
Implementation Details
The model was trained using state-of-the-art hardware consisting of two NVIDIA A100 GPUs, processing over 5.3 million examples across 10 epochs. The training procedure incorporated gradient accumulation for efficient batch processing and utilized a carefully designed learning rate schedule optimized over 208,100 steps.
- Implements RobertaForMaskedLM architecture
- Trained on kz-transformers/multidomain-kazakh-dataset
- Utilizes advanced tokenization through RobertaTokenizerFast
- Optimized for masked language modeling tasks
Core Capabilities
- Advanced masked language modeling for Kazakh text
- Broad domain coverage through diverse training data
- Efficient text processing with fast tokenization
- Seamless integration with Hugging Face Transformers library
- Support for inference endpoints
Frequently Asked Questions
Q: What makes this model unique?
This model stands out as a specialized large-scale language model for the Kazakh language, trained on a comprehensive dataset covering multiple domains. Its architecture and training approach make it particularly effective for masked language modeling tasks in Kazakh text processing.
Q: What are the recommended use cases?
The model is ideal for masked language modeling tasks in Kazakh text, including text completion, language understanding, and analysis. It's particularly suitable for applications requiring deep understanding of Kazakh language context and structure.
