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minsuas
/
Misconceptions1

Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
Generated from Trainer
dataset_size:17405
loss:CachedMultipleNegativesRankingLoss
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use minsuas/Misconceptions1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use minsuas/Misconceptions1 with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("minsuas/Misconceptions1")
    
    sentences = [
        "Subject: Range and Interquartile Range from a List of Data\nConstruct: Calculate the range from a list of data\nQuestion: What is the range of the following numbers?\n\\[\n1,5,5,17,-6\n\\]\nIncorrect Answer: \\( 5 \\)",
        "To find the range adds the biggest and smallest number rather than subtract\nThe passage is clarifying a common misunderstanding about how to calculate the range of a set of numbers. The misconception here is that someone might think the range is found by adding the largest number to the smallest number in the dataset. However, this is incorrect. The correct method to find the range is to subtract the smallest number from the largest number in the dataset. This subtraction gives the difference, which represents how spread out the numbers are.",
        "Finds the mode rather than the range\nThe passage is indicating a common mistake made in solving math problems, particularly those involving statistics. The misconception lies in a confusion between two statistical concepts: the mode and the range.\n\n- **Mode**: This is the value that appears most frequently in a set of data. It helps to identify the most typical or common value.\n- **Range**: This is the difference between the highest and lowest values in a set of data. It gives an idea about the spread or dispersion of the values.\n\nThe misconception described here suggests that a student might calculate the mode when asked to find the range, or simply mix up these two concepts. The important distinction is that while the mode tells you about the frequency of the most common value, the range informs you about the span of the data.",
        "Believes a cubic expression should have three terms\nThe misconception described here is that someone might think a cubic expression, which is a polynomial of degree three, should consist of exactly three terms. This is a misunderstanding because a cubic expression can have any number of terms, but the highest power of the variable must be three. \n\nFor example, both \\( x^3 + 2x + 1 \\) and \\( 4x^3 - 3x^2 + x - 7 \\) are cubic expressions, even though they have different numbers of terms. The defining characteristic is that the highest power of the variable (x in these examples) is three. So, a cubic expression can have fewer or more than three terms, as long as the degree (the highest power) of the expression is three."
    ]
    embeddings = model.encode(sentences)
    
    similarities = model.similarity(embeddings, embeddings)
    print(similarities.shape)
    # [4, 4]
  • Notebooks
  • Google Colab
  • Kaggle
Misconceptions1
91.9 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 2 commits
minsuas's picture
minsuas
Add new SentenceTransformer model
5f505e9 verified over 1 year ago
  • 1_Pooling
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  • .gitattributes
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  • README.md
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  • config.json
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  • config_sentence_transformers.json
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  • model.safetensors
    90.9 MB
    xet
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  • modules.json
    349 Bytes
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  • sentence_bert_config.json
    53 Bytes
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  • special_tokens_map.json
    695 Bytes
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  • tokenizer.json
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  • tokenizer_config.json
    1.46 kB
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  • vocab.txt
    232 kB
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