All the 5 fits failed. It is very likely that your model is misconfigured. You can try to debug the ...

It sounds like you are encountering issues with training your machine learning model. Here are some steps you can take to debug the issue:

1. Check the input data: Make sure that the input data you are using for training is in the correct format and does not contain any missing or corrupted values. You can try visualizing the data to identify any patterns or outliers that may be causing issues.

2. Check the model architecture: Ensure that the architecture of your model is appropriate for the task at hand. You can consult research papers or online resources for guidance on selecting the right architecture.

3. Check the hyperparameters: Experiment with different hyperparameters such as learning rate, batch size, and number of epochs. It may take some trial and error to find the optimal set of hyperparameters for your model.

4. Check the loss function: Make sure that the loss function you are using is appropriate for the task at hand. You can experiment with different loss functions to see if it improves the performance of your model.

5. Check the hardware resources: Ensure that your machine has enough resources (such as memory and processing power) to train the model. You may need to consider using a cloud computing service or upgrading your hardware if you are running into resource constraints.

By following these steps, you should be able to identify and resolve any issues with your machine learning model.