From ca9ae21116f4d242357507a147d24c5670a49a1d Mon Sep 17 00:00:00 2001 From: aniruthraj Date: Thu, 5 Dec 2024 15:29:08 +0530 Subject: [PATCH] Fixing broken link Found one broken link in this tutorial and I have replaced it with right one. --- .../semantic_similarity_with_tf_hub_universal_encoder.ipynb | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/site/en/hub/tutorials/semantic_similarity_with_tf_hub_universal_encoder.ipynb b/site/en/hub/tutorials/semantic_similarity_with_tf_hub_universal_encoder.ipynb index 47d99947ffb..9bde607b4a0 100644 --- a/site/en/hub/tutorials/semantic_similarity_with_tf_hub_universal_encoder.ipynb +++ b/site/en/hub/tutorials/semantic_similarity_with_tf_hub_universal_encoder.ipynb @@ -260,7 +260,7 @@ "source": [ "## Evaluation: STS (Semantic Textual Similarity) Benchmark\n", "\n", - "The [**STS Benchmark**](https://ixa2.si.ehu.es/stswiki/index.php/STSbenchmark) provides an intrinsic evaluation of the degree to which similarity scores computed using sentence embeddings align with human judgements. The benchmark requires systems to return similarity scores for a diverse selection of sentence pairs. [Pearson correlation](https://en.wikipedia.org/wiki/Pearson_correlation_coefficient) is then used to evaluate the quality of the machine similarity scores against human judgements." + "The [**STS Benchmark**](https://ixa2.si.ehu.eus/stswiki/stswiki/index.php/Special:Random.html) provides an intrinsic evaluation of the degree to which similarity scores computed using sentence embeddings align with human judgements. The benchmark requires systems to return similarity scores for a diverse selection of sentence pairs. [Pearson correlation](https://en.wikipedia.org/wiki/Pearson_correlation_coefficient) is then used to evaluate the quality of the machine similarity scores against human judgements." ] }, {