Semantic Textual Similarity On Sts16
Metrics
Spearman Correlation
Results
Performance results of various models on this benchmark
Comparison Table
| Model Name | Spearman Correlation |
|---|---|
| scaling-sentence-embeddings-with-large | 0.8627 |
| diffcse-difference-based-contrastive-learning | 0.8212 |
| trans-encoder-unsupervised-sentence-pair | 0.8305 |
| trans-encoder-unsupervised-sentence-pair | 0.8503 |
| trans-encoder-unsupervised-sentence-pair | 0.8481 |
| on-the-sentence-embeddings-from-pre-trained | 0.7763 |
| trans-encoder-unsupervised-sentence-pair | 0.8377 |
| scaling-sentence-embeddings-with-large | 0.8590 |
| angle-optimized-text-embeddings | 0.8700 |
| deep-continuous-prompt-for-contrastive-1 | 0.8496 |
| an-unsupervised-sentence-embedding-method | 0.7016 |
| angle-optimized-text-embeddings | 0.8691 |
| fast-effective-and-self-supervised | 0.78 |
| diffcse-difference-based-contrastive-learning | 0.8054 |
| scaling-sentence-embeddings-with-large | 0.8591 |
| generating-datasets-with-pretrained-language | 0.7718 |
| simcse-simple-contrastive-learning-of | 0.8393 |
| angle-optimized-text-embeddings | 0.8700 |
| sentence-bert-sentence-embeddings-using | 0.7682 |
| fast-effective-and-self-supervised | 0.743 |