Model Fine Tuning Full Process Guide
Volcano Ark's model fine-tuning feature allows organizations to pre-train large models with aVertical Adaptation, which operates in four key steps:
- Creating Tasks: Navigate to [Model Fine-tuning] in the console → click [New Fine-tuning Task].
- Data preparation: Compliant business datasets need to be uploaded:
- Formatting requirements: TXT or CSV standardized formats
- Content specification: needs to match the input format of the target model (e.g. language model needs to be plain text)
- Data quality: cleaning of noisy data is recommended, sample size is recommended ≥1000 items
- Parameter Configuration::
- Base model selection (e.g., Bacchus 7B, MiniMax, etc.)
- Training parameter tuning: learning rate (default 1e-5), batch size (recommended 32/64)
- priming training: The system automatically allocates GPU resources in the cloud, and you can monitor the progress in [Task Management].
Note: A new version of the fine-tuned model will be generated, which can be downloaded locally or deployed directly to the inference service. For users who try it for the first time, it is recommended to use the platform's default parameters for test training first.
This answer comes from the articleVolcano Ark: Big Model Training and Cloud Computing Service, Sign Up for $150 Equivalent ArithmeticThe
May not be reproduced without permission:AI productivity tools " How do I perform model fine-tuning on Volcano Ark? What data needs to be prepared?
