Explain why there are more tokens, than reviews (huggingface#476)

* Explain why there are more tokens, than reviews

* Update chapters/en/chapter5/3.mdx

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Co-authored-by: lewtun <[email protected]>

chapters/en/chapter5/3.mdx

@@ -387,7 +387,7 @@ ArrowInvalid: Column 1 named condition expected length 1463 but got length 1000
 
 Oh no! That didn't work! Why not? Looking at the error message will give us a clue: there is a mismatch in the lengths of one of the columns, one being of length 1,463 and the other of length 1,000. If you've looked at the `Dataset.map()` [documentation](https://huggingface.co/docs/datasets/package_reference/main_classes.html#datasets.Dataset.map), you may recall that it's the number of samples passed to the function that we are mapping; here those 1,000 examples gave 1,463 new features, resulting in a shape error.
 
-The problem is that we're trying to mix two different datasets of different sizes: the `drug_dataset` columns will have a certain number of examples (the 1,000 in our error), but the `tokenized_dataset` we are building will have more (the 1,463 in the error message). That doesn't work for a `Dataset`, so we need to either remove the columns from the old dataset or make them the same size as they are in the new dataset. We can do the former with the `remove_columns` argument:
+The problem is that we're trying to mix two different datasets of different sizes: the `drug_dataset` columns will have a certain number of examples (the 1,000 in our error), but the `tokenized_dataset` we are building will have more (the 1,463 in the error message; it is more than 1,000 because we are tokenizing long reviews into more than one example by using `return_overflowing_tokens=True`). That doesn't work for a `Dataset`, so we need to either remove the columns from the old dataset or make them the same size as they are in the new dataset. We can do the former with the `remove_columns` argument:
 
 ```py
 tokenized_dataset = drug_dataset.map(