<aside> <img src="https://s3-us-west-2.amazonaws.com/secure.notion-static.com/52e85db3-0847-4231-a3ed-8afc6f2124ba/0_JAXON_Logo_Mark.jpg" alt="https://s3-us-west-2.amazonaws.com/secure.notion-static.com/52e85db3-0847-4231-a3ed-8afc6f2124ba/0_JAXON_Logo_Mark.jpg" width="40px" /> We recommend running the model at least once without augmented data in order to establish a baseline for comparison.
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<aside> <img src="https://s3-us-west-2.amazonaws.com/secure.notion-static.com/52e85db3-0847-4231-a3ed-8afc6f2124ba/0_JAXON_Logo_Mark.jpg" alt="https://s3-us-west-2.amazonaws.com/secure.notion-static.com/52e85db3-0847-4231-a3ed-8afc6f2124ba/0_JAXON_Logo_Mark.jpg" width="40px" /> Only training data should be augmented. Polluting validation data with augmented examples may cause the model to appear more accurate than it really is (overfitting). We recommend testing your model exclusively on real data.
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<aside> <img src="https://s3-us-west-2.amazonaws.com/secure.notion-static.com/52e85db3-0847-4231-a3ed-8afc6f2124ba/0_JAXON_Logo_Mark.jpg" alt="https://s3-us-west-2.amazonaws.com/secure.notion-static.com/52e85db3-0847-4231-a3ed-8afc6f2124ba/0_JAXON_Logo_Mark.jpg" width="40px" /> We recommend giving the new dataset a descriptive name to avoid confusion in the future.
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