MaksimTw/gemma-7b-it-tw-txt2sql
MaksimTw/gemma-7b-it-tw-txt2sql is an 8.5 billion parameter instruction-tuned causal language model, fine-tuned from Google's Gemma-7b-it. This model is specifically optimized for text-to-SQL generation tasks, leveraging its base architecture for enhanced performance in converting natural language queries into SQL commands. It is designed for applications requiring precise and efficient database interaction through natural language.
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Overview
MaksimTw/gemma-7b-it-tw-txt2sql is an 8.5 billion parameter language model, fine-tuned from the google/gemma-7b-it base model. This specialized version is trained on a generator dataset, focusing its capabilities on a particular domain.
Key Capabilities
- Text-to-SQL Generation: The model's primary specialization is converting natural language instructions into SQL queries, making it suitable for database interaction applications.
- Instruction Following: Inherits instruction-tuned capabilities from its base
gemma-7b-itmodel, allowing it to understand and execute specific commands.
Training Details
The model was trained with a learning rate of 0.0002 over 2 epochs, using an Adam optimizer. A constant learning rate scheduler with a warmup ratio of 0.03 was applied. The training involved a batch size of 3, with a total effective batch size of 6 due to gradient accumulation steps.
Intended Use Cases
This model is best suited for scenarios where natural language input needs to be translated into structured SQL queries, such as:
- Database query interfaces.
- Business intelligence tools.
- Automated data reporting systems.