docs: Fix format used for backtesting-predictions

Author: xmatthias

docs/freqai-running.md

@@ -73,11 +73,11 @@ Backtesting mode requires [downloading the necessary data](#downloading-data-to-
 
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-### Saving prediction data
+### Saving backtesting prediction data
 
 To allow for tweaking your strategy (**not** the features!), FreqAI will automatically save the predictions during backtesting so that they can be reused for future backtests and live runs using the same `identifier` model. This provides a performance enhancement geared towards enabling **high-level hyperopting** of entry/exit criteria.
 
-An additional directory called `backtesting_predictions`, which contains all the predictions stored in `hdf` format, will be created in the `unique-id` folder.
+An additional directory called `backtesting_predictions`, which contains all the predictions stored in `feather` format, will be created in the `unique-id` folder.
 
 To change your **features**, you **must** set a new `identifier` in the config to signal to FreqAI to train new models.
 
@@ -89,7 +89,6 @@ FreqAI allow you to reuse live historic predictions through the backtest paramet
 
 The `--timerange` parameter must not be informed, as it will be automatically calculated through the data in the historic predictions file.
 
-
 ### Downloading data to cover the full backtest period
 
 For live/dry deployments, FreqAI will download the necessary data automatically. However, to use backtesting functionality, you need to download the necessary data using `download-data` (details [here](data-download.md#data-downloading)). You need to pay careful attention to understanding how much *additional* data needs to be downloaded to ensure that there is a sufficient amount of training data *before* the start of the backtesting time range. The amount of additional data can be roughly estimated by moving the start date of the time range backwards by `train_period_days` and the `startup_candle_count` (see the [parameter table](freqai-parameter-table.md) for detailed descriptions of these parameters) from the beginning of the desired backtesting time range.