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Is the encoder style arch better for representing classification tasks at a given compute budget than a causal LM? Is this because the final represention in be

Is the encoder style arch better for representing classification tasks at a given compute budget than a causal LM? Is this because the final represention in bert style models more globally focused, rather than being optimized for next token prediction?

jerrygenser 2y ago
They are 100% better for classification at a given compute budget. They can account for information before and after e.g. a token for token classification and use that information to classify.