I’d recommend synchronizing your local models folder with S3 at the end of the training session and using the model from S3 as a build artifact. You can use the below commands to do so with the AWS CLI in a script as part of your CI/CD (I have it set up as a step in my GitHub Actions, for example)
aws s3 sync ./models s3://rasa-artifacts/models --exclude .gitkeep
aws s3 sync ./logs s3://rasa-artifacts/logs --exclude .gitkeep # this is for testing logs
Although what @souvikg10 mentioned as a naming convention I think would also be a good idea, since you might have different types of models for different purposes. You may also want to consider naming the model something special during training with the --fixed-model-name CLI option during training time. A timestamp and the model id is a good place to start.