The training loss drops steadily during fine-tuning.But the translated sentences are grammatically wrong.BLEU and other quality metrics do not improve.It feels like the model is optimizing the wrong thing.
Decode Trail Latest Questions
The model produces grammatically correct text.But it keeps repeating the same phrases.The output never moves forward.It feels stuck in a loop?
I fine-tuned a Transformer model without any memory issues.But when I call model.generate(), CUDA runs out of memory.This happens even for short prompts.Training worked fine, so this feels confusing.
The agent performs well in simulation.When deployed in the real world, it makes strange decisions.The physics is slightly different.Small changes lead to big failures.
I added thousands of new user interactions to my training dataset.Instead of improving, the recommendation quality dropped.Users are now getting irrelevant suggestions.It feels like more data made the model less accurate.
My model recognizes actions well in static camera videos.When the camera pans or shakes, predictions become unstable.The action is the same.Only the camera motion changes.
My speech-to-text model produces accurate transcripts when tested in a quiet office.However, when I try to use it in public places, accuracy drops sharply.Background noise causes words to be skipped or misheard.The model feels fragile outside controlled ...
My model uses both image and text inputs.It works well when both are provided.If one modality is missing, outputs become random or broken.Real-world data is often incomplete.
My model gives great accuracy on my laptop.When deployed on a server, predictions become inconsistent.The same input sometimes produces different outputs.Nothing crashes, but the behavior is unreliable.
I trained an LSTM for next-word prediction on text data.The training loss decreases normally.But when I generate text, it repeats the same token again and again.It feels like the model is ignoring the sentence.