How do I debug inconsistent output when using Hugging Face s model eval mode

Question

Can you tell me How do I debug inconsistent output when using Hugging Face’s model.eval() mode?

Answer 1

To debug inconsistent outputs, you have to ensure reproducibility by setting random seeds, disabling dropout, and using evaluation mode properly.

Here is the code reference showing how:

In the above code, we are using the following approaches:

• Set Random Seed: Ensures consistent behavior across runs by fixing randomness in Torch, NumPy, and Python.
• Evaluation Mode: Disables stochastic behaviors like dropout during model evaluation.
• Disable Gradients: Use torch.no_grad() to prevent gradient computation, which is unnecessary during evaluation.

Hence, by referring to the above, you can debug inconsistent output when using Hugging Face s model eval mode