Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud. With Finetuner, one can easily enhance the performance of pre-trained models and make them production-ready without expensive hardware.
jina-aiThis release covers Finetuner version 0.7.6, including dependencies finetuner-api 0.5.6 and finetuner-core 0.13.4.
This release contains 2 refactorings and 1 bug fix.
⚙ Refactoring
Do not display PIL warning messages.
Beforehand, when fine-tuning with a vision backbone, the PIL package would generate numerous warning messages that contaminated Finetuner's logs. However, this issue has been resolved, and PIL warnings are filtered out.
Display small loss values with higher precision.
Previously, the progress bar would display a loss value of 0 when it was too small. To address this issue, we now use a higher precision when the loss value is too small.
🐞 Bug Fixes
The DocArray version is set to a value lower than 0.3.0.
Previously, Finetuner automatically installed the latest version of DocArray. However, Docarray v2 has now been released and is a breaking change that is incompatible with the current version of Finetuner. Finetuner only supports DocArray up to version 0.3.0. Please upgrade your Finetuner to the latest version to resolve this issue.
We will release a version of Finetuner compatible with DocArray v2 in the immediate future.
🤟 Contributors
We would like to thank all contributors to this release:
- Wang Bo (@bwanglzu)
- Michael Günther (@guenthermi)
- Scott Martens (@scott-martens)
