Make the T5 model tests use cosine similarity #895
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https://github.com/nod-ai/shark-ai/actions/runs/13164598080/job/36809434362?pr=895 stuck? I'm going to cancel it @sogartar |
There were several xfail tests with bad metric. Cosine similarity is a better metric for language embeddings. The comparison between bf16 and f32 exhibits a small fraction of outliers that have a higher per-token numerical error than the majority of tokens. To account for that the testing metric is expanded to test for inlier and outlier absolute tolerance.
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There were several xfail tests with bad metric. Cosine similarity is a better metric for language embeddings. The comparison between bf16 and f32 exhibits a small fraction of outliers that have a higher per-token numerical error than the majority of tokens. To account for that the testing metric is expanded to test for inlier and outlier absolute tolerance.
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There were several xfail tests with bad metric. Cosine similarity is a better metric for language embeddings.
The comparison between bf16 and f32 exhibits a small fraction of outliers that have a higher per-token numerical error than the majority of tokens. To account for that the testing metric is expanded to test for inlier and outlier absolute tolerance.