> ## Documentation Index > Fetch the complete documentation index at: https://docs.finetunedb.com/llms.txt > Use this file to discover all available pages before exploring further. # Training on Logs > In FinetuneDB, you can search and filter past LLM requests to inspect responses and build a training dataset. ## Identify Logs Logs are systematically tracked for future fine-tuning, capturing feedback, tags, and anomalies. Use the Log Viewer to identify relevant logs. Apply filters such as model and custom tags to locate the data needed for fine-tuning. Hero Light Hero Dark ## Add Logs to Dataset Select the filtered logs and import them into a dataset. Save the dataset to use it for fine-tuning your models. Hero Light Hero Dark ## Train on Logs By leveraging production data, you can speed up the creation of fine-tuning datasets. This approach also facilitates switching between models, such as moving from a proprietary model (like GPT-4) to an open-source model.