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README.md
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### Evaluation
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* Dataset: triplet
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* Size: 7,267 evaluation samples
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* Columns: <code>anchor</code>, <code>positive</code>, <code>negative_1</code>, <code>negative_2</code>, and <code>negative_3</code>
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* Approximate statistics based on the first 1000 samples:
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| | anchor | positive | negative_1 | negative_2 | negative_3 |
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|:--------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|
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| type | string | string | string | string | string |
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| details | <ul><li>min: 6 tokens</li><li>mean: 13.62 tokens</li><li>max: 46 tokens</li></ul> | <ul><li>min: 6 tokens</li><li>mean: 13.58 tokens</li><li>max: 39 tokens</li></ul> | <ul><li>min: 6 tokens</li><li>mean: 18.32 tokens</li><li>max: 107 tokens</li></ul> | <ul><li>min: 6 tokens</li><li>mean: 18.1 tokens</li><li>max: 174 tokens</li></ul> | <ul><li>min: 6 tokens</li><li>mean: 18.26 tokens</li><li>max: 172 tokens</li></ul> |
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* Samples:
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| anchor | positive | negative_1 | negative_2 | negative_3 |
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|:------------------------------------------------------------------------------------|:---------------------------------------------------------------|:------------------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|
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| <code>How do I make friends in office?</code> | <code>How can I make friends in office?</code> | <code>How do I lose friends in office?</code> | <code>How do I lose enemies in office?</code> | <code>I already have plenty of friends at work.</code> |
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| <code>Is it good to do MBA after Engineering?</code> | <code>Is it necessary to do MBA after Engineering?</code> | <code>Is learning to code essential for a successful marketing career?</code> | <code>Not necessarily; an MBA isn't *always* the best next step after engineering – practical experience or specialized master's degrees can be more valuable depending on career goals.</code> | <code>Is it bad to do MBA after Engineering?</code> |
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| <code>How I should fix my computer while it is showing no boot device found?</code> | <code>How do I fix the "Boot device not found" problem?</code> | <code>My computer is booting normally and does not have any issues with the boot device.</code> | <code>I should not fix my computer while it is showing no boot device found.</code> | <code>When will I break my phone while it is showing full boot device found?</code> |
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* Loss: [<code>MatryoshkaLoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#matryoshkaloss) with these parameters:
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```json
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{
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"loss": "CachedMultipleNegativesRankingLoss",
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"matryoshka_dims": [
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768,
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512,
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256,
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128,
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64
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],
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"matryoshka_weights": [
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1,
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1,
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1,
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1,
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1
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],
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"n_dims_per_step": -1
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}
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```
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### Training Hyperparameters
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#### Non-Default Hyperparameters
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}
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```
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### Evaluation
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### Training Hyperparameters
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#### Non-Default Hyperparameters
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