ShauryaNova/autotrain-ShauryaNova

Model Trained Using AutoTrain

• Problem type: Sentence Transformers

Validation Metrics

loss: 6.586054801940918

validation_pearson_cosine: 0.15590647163663807

validation_spearman_cosine: 0.28867513459481287

validation_pearson_manhattan: 0.20874094632850035

validation_spearman_manhattan: 0.28867513459481287

validation_pearson_euclidean: 0.21989747670451043

validation_spearman_euclidean: 0.28867513459481287

validation_pearson_dot: 0.15590640231031966

validation_spearman_dot: 0.28867513459481287

validation_pearson_max: 0.21989747670451043

validation_spearman_max: 0.28867513459481287

runtime: 0.1469

samples_per_second: 34.037

steps_per_second: 6.807

: 3.0

Usage

Direct Usage (Sentence Transformers)

First install the Sentence Transformers library:

pip install -U sentence-transformers

Then you can load this model and run inference.

from sentence_transformers import SentenceTransformer

# Download from the Hugging Face Hub
model = SentenceTransformer("sentence_transformers_model_id")
# Run inference
sentences = [
    'search_query: autotrain',
    'search_query: auto train',
    'search_query: i love autotrain',
]
embeddings = model.encode(sentences)
print(embeddings.shape)

# Get the similarity scores for the embeddings
similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)