You can create experiments manually in Picsellia in the Experiments tab. It's a basic usage that allows you to initialize an experiment instance with a few parameters :
- Name
- Description
- Base architecture
- Hyperparameters (will be stored in a data asset)
- Datasets
Let's dive into the concept of base architecture and dataset !
Base architecture
If you click on one of the buttons, a modal will open and a list of available base architecture will appear.
And then if you select a base model, you will see it appear like this.
What is the point ?
As ML/AI training is an iterative process, you may or may not want to use previous checkpoints, trained models, and configuration files of a previous version of your experiments.
This is done automatically when selecting a base experiment or model 😌
Dataset
If you are doing a computer vision experiment, you might have some data in your Datalake and have created some Datasets;
Please note that the name requested is only an alias that will help you manage your train, test, and validation datasets :)
To attach a dataset to your experiment so you can download the images or annotations in your code, you can select one here (alternatively you can always pull your datasets by using the Dataset class of the Python SDK).
You can now observe the experiments you created in the experiment list of your project, it will look like this.
