base_model: mistralai/Mistral-7B-Instruct-v0.3
datasets:
- generator
library_name: peft
license: apache-2.0
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: Mistral-7B-Text2SQL
results: []
Mistral-7B-Text2SQL
This model is a fine-tuned version of mistralai/Mistral-7B-Instruct-v0.3 on the generator dataset. It achieves the following results on the evaluation set:
- Loss: 0.4643
Model description
This repository contains a fine-tuned version of the Mistral 7B model, tailored specifically for text-to-SQL tasks. The model is designed to convert natural language queries into structured SQL queries, enabling seamless interaction with databases through conversational language.
Intended uses & limitations
The Mistral-7B-Text2SQL model is intended for applications that require converting natural language queries into SQL commands. Suitable use cases include:
Conversational Agents: Allowing users to retrieve information from databases through natural language interaction. Data Analytics: Enabling non-technical users to query databases without needing to know SQL syntax. Business Intelligence: Supporting decision-making processes by simplifying data access.
Training and evaluation data
The model was fine-tuned using the generator dataset, which consists of a variety of natural language queries paired with corresponding SQL commands. The dataset is designed to cover a wide range of query types, allowing the model to generalize better across different types of SQL queries.
Dataset Characteristics Diversity: The dataset includes examples from various domains, ensuring that the model learns to handle a broad spectrum of queries. Size: (Include the size of the dataset, e.g., the number of examples if available.) Annotations: Each example includes natural language input along with the expected SQL output, facilitating supervised learning.
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.8346 | 0.4 | 10 | 0.7031 |
| 0.5882 | 0.8 | 20 | 0.5273 |
| 0.487 | 1.2 | 30 | 0.4850 |
| 0.4423 | 1.6 | 40 | 0.4675 |
| 0.4235 | 2.0 | 50 | 0.4564 |
| 0.3464 | 2.4 | 60 | 0.4690 |
| 0.3411 | 2.8 | 70 | 0.4643 |
Framework versions
- PEFT 0.13.2
- Transformers 4.45.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.1