An auto-regressive language model is being trained on the text sequence: 'The quick brown fox jumps'. At the training step where the model has processed the input 'The quick brown fox', what two quantities are compared by the cross-entropy loss function to calculate the error signal for updating the model's parameters?
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Ch.1 Pre-training - Foundations of Large Language Models
Foundations of Large Language Models
Foundations of Large Language Models Course
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Total Loss Calculation for a Token Sequence
An auto-regressive language model is being trained on the text sequence: 'The quick brown fox jumps'. At the training step where the model has processed the input 'The quick brown fox', what two quantities are compared by the cross-entropy loss function to calculate the error signal for updating the model's parameters?
Language Model Training Step Analysis
An auto-regressive language model is being trained on a large text corpus. At one training step, the model processes the input 'The cat sat on the' and must predict the next token. The actual next token in the training data is 'mat'. Which of the following predicted probability distributions for the next token would result in the lowest cross-entropy loss?