Validation set accuracy: 0.092

A validation set accuracy of 0.092 indicates that the model is performing poorly on the validation set. This means that the model is not able to generalize well to new data, which is a key requirement for any machine learning model.

There could be several reasons for this poor performance, such as overfitting to the training data, underfitting due to a lack of model complexity, or issues with the data itself. It's important to carefully analyze the model's performance and make modifications to improve its accuracy on the validation set. This could involve adjusting the model architecture, tuning hyperparameters, or collecting more or better quality data.