seq2seq nlp project

[Aways]

i subscribed Google Colab Pro+ to train a neural network (seq2seq) for nlp project but after almost an hour when I started the training the runtime has changed to connecting---- and at the bottom the message "Waiting to finish the current execution" has appeared and now the model has been training for more than 6 hours and more than that time is left to accomplish the training also I cannot see the resource that I used in the runtime. so my question is what is the solution for this kind of problem and will I lost all the variables that worked on so far in this session particularly the variable that stores the training history?

[McMaco]

Hello @Aways ,

Welcome to Google Cloud Community!

There are several potential reasons for the issue you're encountering with your Google Colab Pro+ runtime:

1. Resource Constraints:

• GPU Availability: If your project requires a GPU for training, ensure that you have selected a runtime with a GPU accelerator. Google Colab Pro+ offers GPU-accelerated runtimes, but availability can vary.
• Memory and Storage: If your dataset or model is large, you might be running out of memory or storage on the runtime. Consider reducing the dataset size, using a smaller model, or requesting a runtime with more resources.

2. Network Connectivity Issues:

• Intermittent Connection: If your internet connection is unstable, it can cause the runtime to disconnect and restart, leading to delays and potential loss of progress. Try improving your network connection or using a more stable network.

3. Code Errors:

• Infinite Loops: Check your code for any infinite loops or other logical errors that might be causing the runtime to hang.
• Memory Leaks: Ensure that your code doesn't have any memory leaks that could be consuming resources over time.

4. Model Complexity:

• Training Time: Training a large or complex neural network can take a significant amount of time, even on powerful hardware. If your model is particularly complex, it might require more resources or time to train.

Solutions:

• Check Runtime Resources: Verify that you have selected a runtime with sufficient GPU, memory, and storage for your project.
• Improve Network Connectivity: Ensure a stable internet connection.
• Debug Code: Carefully review your code for any errors or inefficiencies.
• Consider Model Simplification: If your model is too complex, explore ways to simplify it or reduce its size.
• Save Progress: Regularly save checkpoints or intermediate results to avoid losing progress in case of unexpected interruptions.

Regarding your variables:

• Variable Persistence: By default, variables in a Colab session are not persistent. If you need to save variables for later use, you can use methods like saving them to a file or using a cloud storage service.
• Checkpoints: If you're training a model, consider saving checkpoints periodically to resume training from the last saved point in case of interruptions.

By addressing these potential causes and following the suggested solutions, you should be able to resolve the issue and successfully train your neural network on Google Colab Pro+.

I hope the above information is helpful.

[Aways]

Thanks, McMaco.

fortunately, my session reconnected to the runtime and finished the training although it took a long time (16 hours). but again my session crashed at the inference phase and it automatically restarted although I tried to test the saved model multiple times I wasn't able to because of the constant session crash. so please any solution.

Thanks