This is a part of the MTEB test.
# !pip install tensorflow_text
import tensorflow_hub as hub
from tensorflow_text import SentencepieceTokenizer
import tensorflow as tf
embedder=hub.load("https://tfhub.dev/google/universal-sentence-encoder-multilingual-large/3")
class USE():
def encode(self, sentences, batch_size=32, **kwargs):
embeddings = []
for i in range(0, len(sentences), batch_size):
batch_sentences = sentences[i:i+batch_size]
batch_embeddings = embedder(batch_sentences)
embeddings.extend(batch_embeddings)
return embeddings
model = USE()
- Downloads last month
- 0
Unable to determine this model's library. Check the
docs
.
Evaluation results
- accuracy on MTEB AmazonCounterfactualClassification (en)test set self-reported70.806
- ap on MTEB AmazonCounterfactualClassification (en)test set self-reported32.820
- f1 on MTEB AmazonCounterfactualClassification (en)test set self-reported64.532
- accuracy on MTEB AmazonPolarityClassificationtest set self-reported67.045
- ap on MTEB AmazonPolarityClassificationtest set self-reported61.734
- f1 on MTEB AmazonPolarityClassificationtest set self-reported66.662
- accuracy on MTEB AmazonReviewsClassification (en)test set self-reported35.850
- f1 on MTEB AmazonReviewsClassification (en)test set self-reported35.332
- v_measure on MTEB ArxivClusteringP2Ptest set self-reported34.745
- v_measure on MTEB ArxivClusteringS2Stest set self-reported22.621
- cos_sim_pearson on MTEB BIOSSEStest set self-reported80.309
- cos_sim_spearman on MTEB BIOSSEStest set self-reported79.137
- euclidean_pearson on MTEB BIOSSEStest set self-reported78.924
- euclidean_spearman on MTEB BIOSSEStest set self-reported79.137
- manhattan_pearson on MTEB BIOSSEStest set self-reported79.054
- manhattan_spearman on MTEB BIOSSEStest set self-reported79.152
- accuracy on MTEB Banking77Classificationtest set self-reported74.669
- f1 on MTEB Banking77Classificationtest set self-reported73.794
- v_measure on MTEB BiorxivClusteringP2Ptest set self-reported28.751
- v_measure on MTEB BiorxivClusteringS2Stest set self-reported20.143
- accuracy on MTEB EmotionClassificationtest set self-reported42.305
- f1 on MTEB EmotionClassificationtest set self-reported38.547