Teacher Forcing Explained
Teacher forcing allows models to train with accurate data, enhancing parallelization during training. However, a mismatch occurs at test time, leading to potential compounding errors if the model predicts incorrectly. The dual objectives of translating accurately while maintaining grammatical correctness can create conflicting outcomes, resulting in translations that may be information-rich yet grammatically flawed.In this clip
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Machine Learning Street Talk (MLST)
#039 - Lena Voita - NLP
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