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[
"Fine Tuning Similar Cars Search - Qdrant",
"Trainable Model"
] | /articles/cars-recognition/ | html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(20) | [
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] | p | We have just configured the training-related settings of a TrainableModel. | [
"articles",
"articles/cars-recognition"
] | 4,772 |
[
"Fine Tuning Similar Cars Search - Qdrant",
"Trainable Model"
] | /articles/cars-recognition/ | html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(20) | [
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[
"Fine Tuning Similar Cars Search - Qdrant",
"Trainable Model"
] | /articles/cars-recognition/ | html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(20) | [
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"articles",
"articles/cars-recognition"
] | 4,774 |
[
"Fine Tuning Similar Cars Search - Qdrant",
"Trainable Model"
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"articles",
"articles/cars-recognition"
] | 4,775 |
[
"Fine Tuning Similar Cars Search - Qdrant",
"Trainable Model"
] | /articles/cars-recognition/ | html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(20) | [
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] | p | As previously stated, a SimilarityModel is composed of one or more Encoders and an EncoderHead. | [
"articles",
"articles/cars-recognition"
] | 4,780 |
[
"Fine Tuning Similar Cars Search - Qdrant",
"Encoder"
] | /articles/cars-recognition/ | html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(21) | [
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"articles",
"articles/cars-recognition"
] | 4,781 |
[
"Fine Tuning Similar Cars Search - Qdrant",
"Encoder"
] | /articles/cars-recognition/ | html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(21) | [
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] | p | EncoderHead is still trainable and has enough parameters to adapt to the new task at hand. | [
"articles",
"articles/cars-recognition"
] | 4,782 |
[
"Fine Tuning Similar Cars Search - Qdrant",
"Encoder"
] | /articles/cars-recognition/ | html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(21) | [
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"articles",
"articles/cars-recognition"
] | 4,783 |
[
"Fine Tuning Similar Cars Search - Qdrant",
"Encoder"
] | /articles/cars-recognition/ | html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(21) | [
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] | p | to let you properly initialize the head layer. | [
"articles",
"articles/cars-recognition"
] | 4,786 |
[
"Fine Tuning Similar Cars Search - Qdrant",
"Encoder"
] | /articles/cars-recognition/ | html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(21) | [
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] | p | Let’s see how an Encoder is implemented in the following code borrowed from encoders.py: | [
"articles",
"articles/cars-recognition"
] | 4,787 |
[
"Fine Tuning Similar Cars Search - Qdrant",
"Encoder"
] | /articles/cars-recognition/ | html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(22) | [
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"articles",
"articles/cars-recognition"
] | 4,788 |
[
"Fine Tuning Similar Cars Search - Qdrant",
"Encoder"
] | /articles/cars-recognition/ | html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(22) | [
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"articles",
"articles/cars-recognition"
] | 4,789 |
[
"Fine Tuning Similar Cars Search - Qdrant",
"Encoder"
] | /articles/cars-recognition/ | html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(22) | [
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] | p | Depending on how you create your submodules, this method may be more complex; | [
"articles",
"articles/cars-recognition"
] | 4,790 |
[
"Fine Tuning Similar Cars Search - Qdrant",
"Encoder"
] | /articles/cars-recognition/ | html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(22) | [
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] | p | however, we simply pass the input through a pretrained ResNet152 backbone in this example: | [
"articles",
"articles/cars-recognition"
] | 4,791 |
[
"Fine Tuning Similar Cars Search - Qdrant",
"Encoder"
] | /articles/cars-recognition/ | html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(23) | [
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[
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[
"Fine Tuning Similar Cars Search - Qdrant",
"Encoder"
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"articles",
"articles/cars-recognition"
] | 4,794 |
[
"Fine Tuning Similar Cars Search - Qdrant",
"Encoder"
] | /articles/cars-recognition/ | html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(23) | [
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] | p | To be able to use these two methods, you need to implement save() and load() methods in your Encoder. | [
"articles",
"articles/cars-recognition"
] | 4,795 |
[
"Fine Tuning Similar Cars Search - Qdrant",
"Encoder"
] | /articles/cars-recognition/ | html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(23) | [
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] | p | Additionally, it is also important that you define your subclass of Encoder outside the __main__ namespace, | [
"articles",
"articles/cars-recognition"
] | 4,796 |
[
"Fine Tuning Similar Cars Search - Qdrant",
"Encoder"
] | /articles/cars-recognition/ | html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(23) | [
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[
"Fine Tuning Similar Cars Search - Qdrant",
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[
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"articles",
"articles/cars-recognition"
] | 4,805 |
[
"Fine Tuning Similar Cars Search - Qdrant",
"Training"
] | /articles/cars-recognition/ | html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > ul:nth-of-type(5) > li:nth-of-type(4) | [
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"articles",
"articles/cars-recognition"
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[
"Fine Tuning Similar Cars Search - Qdrant",
"Training"
] | /articles/cars-recognition/ | html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(25) | [
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] | p | We need to import a few objects to prepare all of these: | [
"articles",
"articles/cars-recognition"
] | 4,807 |
[
"Fine Tuning Similar Cars Search - Qdrant",
"Training"
] | /articles/cars-recognition/ | html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(26) | [
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] | p | The train() function in the following code snippet expects several hyperparameter values as arguments. | [
"articles",
"articles/cars-recognition"
] | 4,808 |
[
"Fine Tuning Similar Cars Search - Qdrant",
"Training"
] | /articles/cars-recognition/ | html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(26) | [
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] | p | They can be defined in a config.py or passed from the command line. | [
"articles",
"articles/cars-recognition"
] | 4,809 |
[
"Fine Tuning Similar Cars Search - Qdrant",
"Training"
] | /articles/cars-recognition/ | html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(26) | [
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"articles",
"articles/cars-recognition"
] | 4,810 |
[
"Fine Tuning Similar Cars Search - Qdrant",
"Training"
] | /articles/cars-recognition/ | html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(26) | [
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] | p | Instead let’s focus on how all the building blocks are initialized and passed to Quaterion.fit(), | [
"articles",
"articles/cars-recognition"
] | 4,811 |
[
"Fine Tuning Similar Cars Search - Qdrant",
"Training"
] | /articles/cars-recognition/ | html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(26) | [
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[
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] | p | When the training loop is complete, you can simply call TrainableModel.save_servable() | [
"articles",
"articles/cars-recognition"
] | 4,813 |
[
"Fine Tuning Similar Cars Search - Qdrant",
"Training"
] | /articles/cars-recognition/ | html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(26) | [
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] | p | to save the current state of the SimilarityModel instance: | [
"articles",
"articles/cars-recognition"
] | 4,814 |
[
"Fine Tuning Similar Cars Search - Qdrant"
] | /articles/cars-recognition/ | html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > h2:nth-of-type(6) | [
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] | p | evaluate.py has two functions to evaluate both the baseline model and the tuned similarity model. | [
"articles",
"articles/cars-recognition"
] | 4,817 |
[
"Fine Tuning Similar Cars Search - Qdrant",
"Evaluation"
] | /articles/cars-recognition/ | html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(27) | [
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"articles",
"articles/cars-recognition"
] | 4,818 |
[
"Fine Tuning Similar Cars Search - Qdrant",
"Evaluation"
] | /articles/cars-recognition/ | html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(27) | [
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] | p | In addition to the ease of restoring a SimilarityModel, this code snippet also shows | [
"articles",
"articles/cars-recognition"
] | 4,819 |
[
"Fine Tuning Similar Cars Search - Qdrant",
"Evaluation"
] | /articles/cars-recognition/ | html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(27) | [
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] | p | how to use Evaluator | [
"articles",
"articles/cars-recognition"
] | 4,820 |
[
"Fine Tuning Similar Cars Search - Qdrant",
"Evaluation"
] | /articles/cars-recognition/ | html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(27) | [
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"articles",
"articles/cars-recognition"
] | 4,821 |
[
"Fine Tuning Similar Cars Search - Qdrant",
"Evaluation"
] | /articles/cars-recognition/ | html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(27) | [
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"articles/cars-recognition"
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[
"Fine Tuning Similar Cars Search - Qdrant",
"Evaluation"
] | /articles/cars-recognition/ | html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > figure:nth-of-type(2) > figcaption > p | [
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"articles",
"articles/cars-recognition"
] | 4,825 |
[
"Fine Tuning Similar Cars Search - Qdrant",
"Evaluation"
] | /articles/cars-recognition/ | html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(28) | [
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"articles/cars-recognition"
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[
"Fine Tuning Similar Cars Search - Qdrant",
"Evaluation"
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"articles",
"articles/cars-recognition"
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[
"Fine Tuning Similar Cars Search - Qdrant",
"Evaluation"
] | /articles/cars-recognition/ | html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(28) | [
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] | p | Similar to Quaterion.fit() used for training, Quaterion.evaluate() | [
"articles",
"articles/cars-recognition"
] | 4,828 |
[
"Fine Tuning Similar Cars Search - Qdrant",
"Evaluation"
] | /articles/cars-recognition/ | html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(28) | [
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] | p | runs a complete evaluation loop. | [
"articles",
"articles/cars-recognition"
] | 4,829 |
[
"Fine Tuning Similar Cars Search - Qdrant",
"Evaluation"
] | /articles/cars-recognition/ | html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(28) | [
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] | p | It takes the following as arguments: | [
"articles",
"articles/cars-recognition"
] | 4,830 |
[
"Fine Tuning Similar Cars Search - Qdrant",
"Evaluation"
] | /articles/cars-recognition/ | html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > ul:nth-of-type(6) > li:nth-of-type(1) | [
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] | li | An Evaluator instance created with given evaluation metrics and a Sampler, | [
"articles",
"articles/cars-recognition"
] | 4,831 |
[
"Fine Tuning Similar Cars Search - Qdrant",
"Evaluation"
] | /articles/cars-recognition/ | html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > ul:nth-of-type(6) > li:nth-of-type(2) | [
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] | li | The SimilarityModel to be evaluated, | [
"articles",
"articles/cars-recognition"
] | 4,832 |
[
"Fine Tuning Similar Cars Search - Qdrant",
"Evaluation"
] | /articles/cars-recognition/ | html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > ul:nth-of-type(6) > li:nth-of-type(3) | [
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"articles",
"articles/cars-recognition"
] | 4,833 |
[
"Fine Tuning Similar Cars Search - Qdrant"
] | /articles/cars-recognition/ | html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > h2:nth-of-type(7) | [
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[
"Fine Tuning Similar Cars Search - Qdrant",
"Conclusion"
] | /articles/cars-recognition/ | html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(29) | [
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] | p | In this tutorial, we trained a similarity model to search for similar cars from novel categories unseen in the training phase. | [
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[
"Fine Tuning Similar Cars Search - Qdrant",
"Conclusion"
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] | p | Then, we evaluated it on a test dataset by the Retrieval R-Precision metric. | [
"articles",
"articles/cars-recognition"
] | 4,836 |
[
"Fine Tuning Similar Cars Search - Qdrant",
"Conclusion"
] | /articles/cars-recognition/ | html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(29) | [
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] | p | The base model scored 0.1207, | [
"articles",
"articles/cars-recognition"
] | 4,837 |
[
"Fine Tuning Similar Cars Search - Qdrant",
"Conclusion"
] | /articles/cars-recognition/ | html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(29) | [
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] | p | and our tuned model hit 0.2540, a twice higher score. | [
"articles",
"articles/cars-recognition"
] | 4,838 |
[
"Fine Tuning Similar Cars Search - Qdrant",
"Conclusion"
] | /articles/cars-recognition/ | html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(29) | [
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[
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] | li | The configuration is not persistent therefore it is necessary to lock again following a restart. | [
"documentation",
"documentation/guides",
"documentation/guides/administration"
] | 4,846 |
[
"Administration - Qdrant",
"Locking"
] | /documentation/guides/administration/ | html > body > div:nth-of-type(1) > section > div > div > div:nth-of-type(2) > article > ul > li:nth-of-type(2) | [
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[
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[
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[
"Administration - Qdrant",
"Recovery mode"
] | /documentation/guides/administration/ | html > body > div:nth-of-type(1) > section > div > div > div:nth-of-type(2) > article > p:nth-of-type(7) | [
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[
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"documentation",
"documentation/guides",
"documentation/guides/administration"
] | 4,868 |
[
"Administration - Qdrant",
"Recovery mode"
] | /documentation/guides/administration/ | html > body > div:nth-of-type(1) > section > div > div > div:nth-of-type(2) > article > p:nth-of-type(9) | [
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[
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] | p | to start normally first, and restarts in recovery mode if initialisation fails | [
"documentation",
"documentation/guides",
"documentation/guides/administration"
] | 4,871 |
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