minor docs changes (#7452)

Author: lhoestq

docs/source/use_with_polars.mdx

@@ -105,7 +105,7 @@ This also works for [`IterableDataset.map`] and [`IterableDataset.filter`].
 
 Many functions are available in Polars and for any data type: string, floats, integers, etc. You can find the full list [here](https://docs.pola.rs/api/python/stable/reference/expressions/functions.html). Those functions are written in Rust and run on batches of data which enables fast data processing.
 
-Here is an example that shows a 2.5x speed boost using Polars instead of a regular python function to extract solutions from a LLM reasoning dataset:
+Here is an example that shows a 5x speed boost using Polars instead of a regular python function to extract solutions from a LLM reasoning dataset:
 
 ```python
 from datasets import load_dataset

docs/source/video_dataset.mdx

@@ -99,9 +99,9 @@ It's possible to point to more than one video in each row in your dataset, for e
 You can also define lists of videos. In that case you need to name the field `file_names` or `*_file_names`. Here is an example:
 
 ```jsonl
-{"frames_file_names": ["0001_t0.mp4", "0001_t1.mp4"], label: "moving_up"}
-{"frames_file_names": ["0002_t0.mp4", "0002_t1.mp4"], label: "moving_down"}
-{"frames_file_names": ["0003_t0.mp4", "0003_t1.mp4"], label: "moving_right"}
+{"videos_file_names": ["0001_left.mp4", "0001_right.mp4"], "label": "moving_up"}
+{"videos_file_names": ["0002_left.mp4", "0002_right.mp4"], "label": "moving_down"}
+{"videos_file_names": ["0003_left.mp4", "0003_right.mp4"], "label": "moving_right"}
 ```
 
 ### Video captioning