Perplexity

Creator
Creator
Seonglae ChoSeonglae Cho
Created
Created
2023 Mar 28 11:55
Editor
Edited
Edited
2025 May 30 17:43
Refs

PPL

Important metric for language modeling is validation perplexity, which is a representative of upstream quality. However, since it does not guarantee the performance of the downstream task, it should be checked separately. In other words, a low PPL value means high probability on data, but it does not necessarily mean a good language model.
Perplexity is defined as the exponentiated average negative log-likelihood of a sequence. If we have a tokenized sequence .
Calculating Perplexity for predetermined input text is more common. When measuring the context length limit to determine how much tolerance a model has for context length, it is assessed during generation.

Property

  • When perplexity is high, the model tends to have flat attention scores rather than focusing on specific tokens, while with low perplexity, it shows sharp attention patterns focused on relevant tokens
Perplexity Notion
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Perplexity of fixed-length models
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Perplexity of fixed-length models
03-05 펄플렉서티(Perplexity, PPL)
두 개의 모델 A, B가 있을 때 이 모델의 성능은 어떻게 비교할 수 있을까요? 두 개의 모델을 오타 교정, 기계 번역 등의 평가에 투입해볼 수 있겠습니다. 그리고 두 모델이 해…
03-05 펄플렉서티(Perplexity, PPL)
 
 
 

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