A dialogue model is trained by processing entire multi-turn conversations as single, concatenated sequences of text. To make this process efficient, the training loss is calculated based only on the model's ability to predict certain parts of the sequence, while the log-probabilities of other parts are ignored. Given the following two-turn conversation, which parts of the sequence would be used to calculate the training loss?
- Turn 1 (User): 'What is the weather like'
- Turn 1 (Model): 'In which city?'
- Turn 2 (User): 'In London'
- Turn 2 (Model): 'It is currently raining.'
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Ch.4 Alignment - Foundations of Large Language Models
Foundations of Large Language Models
Foundations of Large Language Models Course
Computing Sciences
Application in Bloom's Taxonomy
Cognitive Psychology
Psychology
Social Science
Empirical Science
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A dialogue model is trained by processing entire multi-turn conversations as single, concatenated sequences of text. To make this process efficient, the training loss is calculated based only on the model's ability to predict certain parts of the sequence, while the log-probabilities of other parts are ignored. Given the following two-turn conversation, which parts of the sequence would be used to calculate the training loss?
- Turn 1 (User): 'What is the weather like'
- Turn 1 (Model): 'In which city?'
- Turn 2 (User): 'In London'
- Turn 2 (Model): 'It is currently raining.'
Debugging a Dialogue Model Training Loop
Evaluating Dialogue Model Training Strategies
Dataset-Level Objective for Multi-Round Conversational Models