Sentence Similarity
sentence-transformers
Safetensors
Persian
Arabic
multilingual
xlm-roberta
feature-extraction
persian
arabic
qa
information-retrieval
hadith
islmic
text-embeddings-inference
Instructions to use hamtaai/e5-large-hadith-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use hamtaai/e5-large-hadith-v2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("hamtaai/e5-large-hadith-v2") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
| epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accuracy@10,cosine-Precision@1,cosine-Recall@1,cosine-Precision@3,cosine-Recall@3,cosine-Precision@5,cosine-Recall@5,cosine-Precision@10,cosine-Recall@10,cosine-MRR@10,cosine-NDCG@10,cosine-MAP@100 | |
| 1.0,848,0.4823309687249136,0.710037844656695,0.7818771605039401,0.8530775405888039,0.4823309687249136,0.4823309687249136,0.2366792815522316,0.710037844656695,0.15637543210078803,0.7818771605039401,0.0853077540588804,0.8530775405888039,0.6104707385884038,0.669529997808553,0.6158768696778474 | |
| 2.0,1696,0.5440128442471207,0.7857599239830273,0.8538147741607824,0.9159389898261767,0.5440128442471207,0.5440128442471207,0.2619199746610091,0.7857599239830273,0.1707629548321565,0.8538147741607824,0.09159389898261769,0.9159389898261767,0.6770503739867464,0.7355305129821589,0.6808359513417348 | |
| 3.0,2544,0.5773685676370844,0.8208850079457396,0.8878585822179262,0.9423811006078081,0.5773685676370844,0.5773685676370844,0.2736283359819132,0.8208850079457396,0.17757171644358527,0.8878585822179262,0.09423811006078082,0.9423811006078081,0.7104179490239936,0.7674212357621277,0.7133230262644287 | |
| 4.0,3392,0.6013368502105212,0.8451481839479676,0.908304526614132,0.9565523681580629,0.6013368502105212,0.6013368502105212,0.2817160613159892,0.8451481839479676,0.18166090532282642,0.908304526614132,0.0956552368158063,0.9565523681580629,0.7331144061681039,0.7881963670893256,0.7354466956609658 | |
| 5.0,4240,0.6158521600943659,0.8605809400547191,0.920690050623372,0.9647438522911581,0.6158521600943659,0.6158521600943659,0.28686031335157297,0.8605809400547191,0.18413801012467443,0.920690050623372,0.09647438522911582,0.9647438522911581,0.7469129741926596,0.8007440911740579,0.7488402597891997 | |