diff --git a/docs/freqai.md b/docs/freqai.md
index 48b8968a3..b2ee2407a 100644
--- a/docs/freqai.md
+++ b/docs/freqai.md
@@ -83,7 +83,7 @@ Mandatory parameters are marked as **Required**, which means that they are requi
| `backtest_period_days` | **Required.** Number of days to inference into the trained model before sliding the window and retraining. This can be fractional days, but beware that the user provided `timerange` will be divided by this number to yield the number of trainings necessary to complete the backtest.
**Datatype:** Float.
| `live_retrain_hours` | Frequency of retraining during dry/live runs. Default set to 0, which means it will retrain as often as possible. **Datatype:** Float > 0.
| `follow_mode` | If true, this instance of FreqAI will look for models associated with `identifier` and load those for inferencing. A `follower` will **not** train new models. `False` by default.
**Datatype:** boolean.
-| `live_trained_timestamp` | Useful if user wants to start from models trained during a *backtest*. The timestamp can be located in the `user_data/models` backtesting folder. This is not a commonly used parameter, leave undefined for most applications.
**Datatype:** positive integer.
+| `startup_candles` | Number of candles needed for *backtesting only* to ensure all indicators are non NaNs at the start of the first train period.
**Datatype:** positive integer.
| `fit_live_predictions_candles` | Computes target (label) statistics from prediction data, instead of from the training data set. Number of candles is the number of historical candles it uses to generate the statistics.
**Datatype:** positive integer.
| `purge_old_models` | Tell FreqAI to delete obsolete models. Otherwise, all historic models will remain on disk. Defaults to `False`.
**Datatype:** boolean.
| `expiration_hours` | Ask FreqAI to avoid making predictions if a model is more than `expiration_hours` old. Defaults to 0 which means models never expire.
**Datatype:** positive integer.
diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py
index 569cc0c22..e732649ff 100644
--- a/freqtrade/freqai/data_kitchen.py
+++ b/freqtrade/freqai/data_kitchen.py
@@ -76,6 +76,9 @@ class FreqaiDataKitchen:
self.keras = self.freqai_config.get("keras", False)
self.set_all_pairs()
if not self.live:
+ if not self.config["timerange"]:
+ raise OperationalException(
+ 'Please pass --timerange if you intend to use FreqAI for backtesting.')
self.full_timerange = self.create_fulltimerange(
self.config["timerange"], self.freqai_config.get("train_period_days")
)
diff --git a/freqtrade/freqai/prediction_models/CatboostPredictionModel.py b/freqtrade/freqai/prediction_models/CatboostPredictionModel.py
index fafb12abe..c69602025 100644
--- a/freqtrade/freqai/prediction_models/CatboostPredictionModel.py
+++ b/freqtrade/freqai/prediction_models/CatboostPredictionModel.py
@@ -38,8 +38,6 @@ class CatboostPredictionModel(BaseRegressionModel):
model = CatBoostRegressor(
allow_writing_files=False,
- verbose=100,
- early_stopping_rounds=400,
**self.model_training_parameters,
)
model.fit(X=train_data, eval_set=test_data)
diff --git a/freqtrade/freqai/prediction_models/CatboostPredictionMultiModel.py b/freqtrade/freqai/prediction_models/CatboostPredictionMultiModel.py
index becfb43eb..1b91fe0c6 100644
--- a/freqtrade/freqai/prediction_models/CatboostPredictionMultiModel.py
+++ b/freqtrade/freqai/prediction_models/CatboostPredictionMultiModel.py
@@ -27,9 +27,6 @@ class CatboostPredictionMultiModel(BaseRegressionModel):
cbr = CatBoostRegressor(
allow_writing_files=False,
- gpu_ram_part=0.5,
- verbose=100,
- early_stopping_rounds=400,
**self.model_training_parameters,
)