# Troubleshooting[¶](https://knowledge.dataiku.com/latest/courses/advanced-analytics/image-classification-code/wrap-up.html#troubleshooting "Permalink to this headline")

**Cannot reproduce the stetps.** To reproduce the steps, you’ll need Dataiku version 11.0 or above.

**Poor results.** When the amount of training data is low, the model can fail to converge, leading to varying model accuracy.

**Training is slow.** The training/scoring of Keras models can be run on either a CPU, or one or more GPUs. Training on GPUs is usually much faster, especially when images are involved. When running on a CPU, try a class rebalance sampling method, setting the number of records to 2000 or less in the **Train / Test Set** step of the **Design**.

**Code environment errors.** **Code environment errors.** Ensure the runtime environment setting in the model design is set to your deep learning code environment.

# Wrap Up[¶](https://knowledge.dataiku.com/latest/courses/advanced-analytics/image-classification-code/wrap-up.html#wrap-up "Permalink to this headline")

* See a completed version of this project on the Dataiku gallery.

* See the Dataiku DSS reference documentation on deep learning.
