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clarify overfitting
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@ -2043,7 +2043,7 @@
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"metadata": {},
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"source": [
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"- We can see that the training and test set performances are practically identical\n",
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"- However, based on the slightly lower test set performance, we can see that the model overfits the training data to a very small degree\n",
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"- However, based on the slightly lower test set performance, we can see that the model overfits the training data to a very small degree, as well as the validation data that has been used for tweaking some of the hyperparameters, such as the learning rate\n",
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"- This is normal, however, and this gap could potentially be further reduced by increasing the model's dropout rate (`drop_rate`) or the `weight_decay` in the optimizer setting"
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]
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},
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@ -2265,7 +2265,7 @@
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.10.12"
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"version": "3.10.6"
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}
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},
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"nbformat": 4,
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