Understanding Teacher Forcing in Seq2Seq Models

Teacher forcing is a training technique for seq2seq models where the correct token from the dataset is fed as input at each decoder step, rather than using the model's own previous prediction. Without it, a single early misprediction cascades into compounding errors, making training slow and unstable. With teacher forcing, the model always sees the right context, leading to faster convergence and more stable training.