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Update ettin.md #2968

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Expand Up @@ -104,7 +104,7 @@ For the first time, we can fairly compare encoder and decoder architectures trai

The results show clear patterns:

**Encoders dominate classification and retrieval**: On MNLI classification, even a 150M encoder (89.2) outperforms a 400M decoder (88.2). For retrieval tasks, the gap is smaller but still noticable - especially when decoders are not trained with MNTP.
**Encoders dominate classification and retrieval**: On MNLI classification, even a 150M encoder (89.2) outperforms a 400M decoder (88.2). For retrieval tasks, the gap is smaller but still noticeable - especially when decoders are not trained with MNTP.

**Decoders excel at generation**: On generative tasks, decoders maintain consistent advantages, with the performance gap actually widening at larger model sizes.

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