Sentence-Similarity-Model

Name: Sentence-Similarity-Model
Author: AventIQ-AI

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AventIQ-AI

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Quick Summary

This project fine-tunes a Sentence-BERT model (`paraphrase-MiniLM-L6-v2`) on the STS Benchmark English dataset (`stsbmultimt`) to perform semantic similarity scoring between two text inputs.

Code Examples

📦 Dependenciespython

pip install -q transformers datasets sentence-transformers evaluate --upgrade

📦 Dependenciespython

pip install -q transformers datasets sentence-transformers evaluate --upgrade

📦 Dependenciespython

pip install -q transformers datasets sentence-transformers evaluate --upgrade

📦 Dependenciespython

pip install -q transformers datasets sentence-transformers evaluate --upgrade

📦 Dependenciespython

pip install -q transformers datasets sentence-transformers evaluate --upgrade

📦 Dependenciespython

pip install -q transformers datasets sentence-transformers evaluate --upgrade

📦 Dependenciespython

pip install -q transformers datasets sentence-transformers evaluate --upgrade

📦 Dependenciespython

pip install -q transformers datasets sentence-transformers evaluate --upgrade

📦 Dependenciespython

pip install -q transformers datasets sentence-transformers evaluate --upgrade

📦 Dependenciespython

pip install -q transformers datasets sentence-transformers evaluate --upgrade

📦 Dependenciespython

pip install -q transformers datasets sentence-transformers evaluate --upgrade

📦 Dependenciespython

pip install -q transformers datasets sentence-transformers evaluate --upgrade

📦 Dependenciespython

pip install -q transformers datasets sentence-transformers evaluate --upgrade

📦 Dependenciespython

pip install -q transformers datasets sentence-transformers evaluate --upgrade

📦 Dependenciespython

pip install -q transformers datasets sentence-transformers evaluate --upgrade

📦 Dependenciespython

pip install -q transformers datasets sentence-transformers evaluate --upgrade

📦 Dependenciespython

pip install -q transformers datasets sentence-transformers evaluate --upgrade

📦 Dependenciespython

pip install -q transformers datasets sentence-transformers evaluate --upgrade

📦 Dependenciespython

pip install -q transformers datasets sentence-transformers evaluate --upgrade

📦 Dependenciespython

pip install -q transformers datasets sentence-transformers evaluate --upgrade

📦 Dependenciespython

pip install -q transformers datasets sentence-transformers evaluate --upgrade

📦 Dependenciespython

pip install -q transformers datasets sentence-transformers evaluate --upgrade

📦 Dependenciespython

pip install -q transformers datasets sentence-transformers evaluate --upgrade

📦 Dependenciespython

pip install -q transformers datasets sentence-transformers evaluate --upgrade

📦 Dependenciespython

pip install -q transformers datasets sentence-transformers evaluate --upgrade

📦 Dependenciespython

pip install -q transformers datasets sentence-transformers evaluate --upgrade

📦 Dependenciespython

pip install -q transformers datasets sentence-transformers evaluate --upgrade

📦 Dependenciespython

pip install -q transformers datasets sentence-transformers evaluate --upgrade

📦 Dependenciespython

pip install -q transformers datasets sentence-transformers evaluate --upgrade

📦 Dependenciespython

pip install -q transformers datasets sentence-transformers evaluate --upgrade

📦 Dependenciespython

pip install -q transformers datasets sentence-transformers evaluate --upgrade

📦 Dependenciespython

pip install -q transformers datasets sentence-transformers evaluate --upgrade

📦 Dependenciespython

pip install -q transformers datasets sentence-transformers evaluate --upgrade

📊 Datasetpython

from datasets import load_dataset

dataset = load_dataset("stsb_multi_mt", name="en", split="train")
dataset = dataset.shuffle(seed=42).select(range(10000))  # Sample subset for faster training

📊 Datasetpython

from datasets import load_dataset

dataset = load_dataset("stsb_multi_mt", name="en", split="train")
dataset = dataset.shuffle(seed=42).select(range(10000))  # Sample subset for faster training

📊 Datasetpython

from datasets import load_dataset

dataset = load_dataset("stsb_multi_mt", name="en", split="train")
dataset = dataset.shuffle(seed=42).select(range(10000))  # Sample subset for faster training

📊 Datasetpython

from datasets import load_dataset

dataset = load_dataset("stsb_multi_mt", name="en", split="train")
dataset = dataset.shuffle(seed=42).select(range(10000))  # Sample subset for faster training

📊 Datasetpython

from datasets import load_dataset

dataset = load_dataset("stsb_multi_mt", name="en", split="train")
dataset = dataset.shuffle(seed=42).select(range(10000))  # Sample subset for faster training

📊 Datasetpython

from datasets import load_dataset

dataset = load_dataset("stsb_multi_mt", name="en", split="train")
dataset = dataset.shuffle(seed=42).select(range(10000))  # Sample subset for faster training

📊 Datasetpython

from datasets import load_dataset

dataset = load_dataset("stsb_multi_mt", name="en", split="train")
dataset = dataset.shuffle(seed=42).select(range(10000))  # Sample subset for faster training

📊 Datasetpython

from datasets import load_dataset

dataset = load_dataset("stsb_multi_mt", name="en", split="train")
dataset = dataset.shuffle(seed=42).select(range(10000))  # Sample subset for faster training

📊 Datasetpython

from datasets import load_dataset

dataset = load_dataset("stsb_multi_mt", name="en", split="train")
dataset = dataset.shuffle(seed=42).select(range(10000))  # Sample subset for faster training

📊 Datasetpython

from datasets import load_dataset

dataset = load_dataset("stsb_multi_mt", name="en", split="train")
dataset = dataset.shuffle(seed=42).select(range(10000))  # Sample subset for faster training

📊 Datasetpython

from datasets import load_dataset

dataset = load_dataset("stsb_multi_mt", name="en", split="train")
dataset = dataset.shuffle(seed=42).select(range(10000))  # Sample subset for faster training

📊 Datasetpython

from datasets import load_dataset

dataset = load_dataset("stsb_multi_mt", name="en", split="train")
dataset = dataset.shuffle(seed=42).select(range(10000))  # Sample subset for faster training

📊 Datasetpython

from datasets import load_dataset

dataset = load_dataset("stsb_multi_mt", name="en", split="train")
dataset = dataset.shuffle(seed=42).select(range(10000))  # Sample subset for faster training

📊 Datasetpython

from datasets import load_dataset

dataset = load_dataset("stsb_multi_mt", name="en", split="train")
dataset = dataset.shuffle(seed=42).select(range(10000))  # Sample subset for faster training

📊 Datasetpython

from datasets import load_dataset

dataset = load_dataset("stsb_multi_mt", name="en", split="train")
dataset = dataset.shuffle(seed=42).select(range(10000))  # Sample subset for faster training

📊 Datasetpython

from datasets import load_dataset

dataset = load_dataset("stsb_multi_mt", name="en", split="train")
dataset = dataset.shuffle(seed=42).select(range(10000))  # Sample subset for faster training

📊 Datasetpython

from datasets import load_dataset

dataset = load_dataset("stsb_multi_mt", name="en", split="train")
dataset = dataset.shuffle(seed=42).select(range(10000))  # Sample subset for faster training

📊 Datasetpython

from datasets import load_dataset

dataset = load_dataset("stsb_multi_mt", name="en", split="train")
dataset = dataset.shuffle(seed=42).select(range(10000))  # Sample subset for faster training

📊 Datasetpython

from datasets import load_dataset

dataset = load_dataset("stsb_multi_mt", name="en", split="train")
dataset = dataset.shuffle(seed=42).select(range(10000))  # Sample subset for faster training

📊 Datasetpython

from datasets import load_dataset

dataset = load_dataset("stsb_multi_mt", name="en", split="train")
dataset = dataset.shuffle(seed=42).select(range(10000))  # Sample subset for faster training

📊 Datasetpython

from datasets import load_dataset

dataset = load_dataset("stsb_multi_mt", name="en", split="train")
dataset = dataset.shuffle(seed=42).select(range(10000))  # Sample subset for faster training

📊 Datasetpython

from datasets import load_dataset

dataset = load_dataset("stsb_multi_mt", name="en", split="train")
dataset = dataset.shuffle(seed=42).select(range(10000))  # Sample subset for faster training

📊 Datasetpython

from datasets import load_dataset

dataset = load_dataset("stsb_multi_mt", name="en", split="train")
dataset = dataset.shuffle(seed=42).select(range(10000))  # Sample subset for faster training

📊 Datasetpython

from datasets import load_dataset

dataset = load_dataset("stsb_multi_mt", name="en", split="train")
dataset = dataset.shuffle(seed=42).select(range(10000))  # Sample subset for faster training

📊 Datasetpython

from datasets import load_dataset

dataset = load_dataset("stsb_multi_mt", name="en", split="train")
dataset = dataset.shuffle(seed=42).select(range(10000))  # Sample subset for faster training

📊 Datasetpython

from datasets import load_dataset

dataset = load_dataset("stsb_multi_mt", name="en", split="train")
dataset = dataset.shuffle(seed=42).select(range(10000))  # Sample subset for faster training

📊 Datasetpython

from datasets import load_dataset

dataset = load_dataset("stsb_multi_mt", name="en", split="train")
dataset = dataset.shuffle(seed=42).select(range(10000))  # Sample subset for faster training

📊 Datasetpython

from datasets import load_dataset

dataset = load_dataset("stsb_multi_mt", name="en", split="train")
dataset = dataset.shuffle(seed=42).select(range(10000))  # Sample subset for faster training

📊 Datasetpython

from datasets import load_dataset

dataset = load_dataset("stsb_multi_mt", name="en", split="train")
dataset = dataset.shuffle(seed=42).select(range(10000))  # Sample subset for faster training

📊 Datasetpython

from datasets import load_dataset

dataset = load_dataset("stsb_multi_mt", name="en", split="train")
dataset = dataset.shuffle(seed=42).select(range(10000))  # Sample subset for faster training

📊 Datasetpython

from datasets import load_dataset

dataset = load_dataset("stsb_multi_mt", name="en", split="train")
dataset = dataset.shuffle(seed=42).select(range(10000))  # Sample subset for faster training

📊 Datasetpython

from datasets import load_dataset

dataset = load_dataset("stsb_multi_mt", name="en", split="train")
dataset = dataset.shuffle(seed=42).select(range(10000))  # Sample subset for faster training

📊 Datasetpython

from datasets import load_dataset

dataset = load_dataset("stsb_multi_mt", name="en", split="train")
dataset = dataset.shuffle(seed=42).select(range(10000))  # Sample subset for faster training

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