sentence-transformers 3.1.1

v3.1.1 - Patch hard negative mining & remove `numpy<2` restriction

on Python PyPI

from sentence_transformers.util import mine_hard_negatives
from sentence_transformers import SentenceTransformer
from datasets import load_dataset

# Load a Sentence Transformer model
model = SentenceTransformer("mixedbread-ai/mxbai-embed-large-v1").bfloat16()

# Load a dataset to mine hard negatives from
dataset = load_dataset("sentence-transformers/natural-questions", split="train[:10000]")
print(dataset)
"""
Dataset({
    features: ['query', 'answer'],
    num_rows: 10000
})
"""

# Mine hard negatives
dataset = mine_hard_negatives(
    dataset=dataset,
    model=model,
    range_min=10,
    range_max=50,
    max_score=0.8,
    margin=0.1,
    num_negatives=5,
    sampling_strategy="random",
    batch_size=128,
    use_faiss=True,
)
'''
Batches: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 75/75 [00:21<00:00,  3.51it/s]
Batches: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 79/79 [00:03<00:00, 25.77it/s]
Querying FAISS index: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00,  3.98it/s]
Metric       Positive       Negative     Difference
Count          10,000         47,711
Mean           0.7600         0.5376         0.2299
Median         0.7673         0.5379         0.2274
Std            0.0658         0.0387         0.0629
Min            0.3858         0.3732         0.1044
25%            0.7219         0.5129         0.1833
50%            0.7673         0.5379         0.2274
75%            0.8058         0.5617         0.2724
Max            0.9341         0.7024         0.4780
Skipped 48770 potential negatives (9.56%) due to the margin of 0.1.
Could not find enough negatives for 2289 samples (4.58%). Consider adjusting the range_max, range_min, margin and max_score parameters if you'd like to find more valid negatives.
'''
print(dataset)
'''
Dataset({
    features: ['query', 'answer', 'negative'],
    num_rows: 47711
})
'''
print(dataset[0])
'''
{
    'query': 'where is the us navy base in japan located',
    'answer': 'United States Fleet Activities Yokosuka The United States Fleet Activities Yokosuka (横須賀海 軍施設, Yokosuka kaigunshisetsu) or Commander Fleet Activities Yokosuka (司令官艦隊活動横須賀, Shirei-kan kantai katsudō Yokosuka) is a United States Navy base in Yokosuka, Japan. Its mission is to maintain and operate base facilities for the logistic, recreational, administrative support and service of the U.S. Naval Forces Japan, Seventh Fleet and other operating forces assigned in the Western Pacific. CFAY is the largest strategically important U.S. naval installation in the western Pacific.[1] As of August 2013[update], it was commanded by Captain David Glenister.',
    'negative': "2011 Tōhoku earthquake and tsunami The earthquake took place at 14:46 JST (UTC 05:46) around 67\xa0km (42\xa0mi) from the nearest point on Japan's coastline, and initial estimates indicated the tsunami would have taken 10 to 30\xa0minutes to reach the areas first affected, and then areas farther north and south based on the geography of the coastline.[127][128] Just over an hour after the earthquake at 15:55 JST, a tsunami was observed flooding Sendai Airport, which is located near the coast of Miyagi Prefecture,[129][130] with waves sweeping away cars and planes and flooding various buildings as they traveled inland.[131][132] The impact of the tsunami in and around Sendai Airport was filmed by an NHK News helicopter, showing a number of vehicles on local roads trying to escape the approaching wave and being engulfed by it.[133] A 4-metre-high (13\xa0ft) tsunami hit Iwate Prefecture.[134] Wakabayashi Ward in Sendai was also particularly hard hit.[135] At least 101 designated tsunami evacuation sites were hit by the wave.[136]"
}
'''
dataset.push_to_hub("natural-questions-hard-negatives", "triplet")