diff --git a/CHANGELOG.md b/CHANGELOG.md
index 531563298..0d8f199e2 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -7,16 +7,36 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ## Unreleased
 ### Added
+- 
+- 
+- 
+- 
+- 
+
+### Changed
+- 
+- 
+- 
+- 
+
+### Fixed
+- 
+- 
+- 
+- 
+- 
+
+
+## [2.1.0] - 2023-06-30
+### Added
 - Notebook `forecast_interpretation.ipynb` with forecast decomposition ([#1220](https://github.com/tinkoff-ai/etna/pull/1220))
 - Exogenous variables shift transform `ExogShiftTransform`([#1254](https://github.com/tinkoff-ai/etna/pull/1254))
 - Parameter `start_timestamp` to forecast CLI command ([#1265](https://github.com/tinkoff-ai/etna/pull/1265))
 - `DeepStateModel` ([#1253](https://github.com/tinkoff-ai/etna/pull/1253))
 - Function `estimate_max_n_folds` for folds number estimation ([#1279](https://github.com/tinkoff-ai/etna/pull/1279))
 - Parameters `estimate_n_folds` and `context_size` to forecast and backtest CLI commands ([#1284](https://github.com/tinkoff-ai/etna/pull/1284))
--
 - Class `Tune` for hyperparameter optimization within existing pipeline ([#1200](https://github.com/tinkoff-ai/etna/pull/1200))
 - Add `etna.distributions` for using it instead of using `optuna.distributions` ([#1292](https://github.com/tinkoff-ai/etna/pull/1292))
-- 
 
 ### Changed
 - Set the default value of `final_model` to `LinearRegression(positive=True)` in the constructor of `StackingEnsemble` ([#1238](https://github.com/tinkoff-ai/etna/pull/1238))
@@ -27,8 +47,6 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 - Optimize `make_samples` of `RNNNet` and `MLPNet` ([#1281](https://github.com/tinkoff-ai/etna/pull/1281))
 - Remove `to_be_fixed` from inference tests on `SpecialDaysTransform` ([#1283](https://github.com/tinkoff-ai/etna/pull/1283))
 - Rewrite `TimeSeriesImputerTransform` to work without per-segment wrapper ([#1293](https://github.com/tinkoff-ai/etna/pull/1293))
-- 
-- 
 - Add default `params_to_tune` for catboost models ([#1185](https://github.com/tinkoff-ai/etna/pull/1185))
 - Add default `params_to_tune` for `ProphetModel` ([#1203](https://github.com/tinkoff-ai/etna/pull/1203))
 - Add default `params_to_tune` for `SARIMAXModel`, change default parameters for the model ([#1206](https://github.com/tinkoff-ai/etna/pull/1206))
@@ -65,6 +83,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 - Teach `BaseMixin.set_params` to work with nested `list` and `tuple` ([#1201](https://github.com/tinkoff-ai/etna/pull/1201))
 - Fix `get_anomalies_prediction_interval` to work when segments have different start date ([#1296](https://github.com/tinkoff-ai/etna/pull/1296))
 - Fix `classification` notebook to download `FordA` dataset without error ([#1299](https://github.com/tinkoff-ai/etna/pull/1299))
+- Fix signature of `Auto.fit`, `Tune.fit` to not have a breaking change ([#1300](https://github.com/tinkoff-ai/etna/pull/1300))
 
 ## [2.0.0] - 2023-04-11
 ### Added
@@ -126,6 +145,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 - Fix `DifferencingTransform` to raise error on new segments during `transform` and `inverse_transform` in inplace mode ([#1141](https://github.com/tinkoff-ai/etna/pull/1141))
 - Teach `DifferencingTransform` to `inverse_transform` with NaNs ([#1155](https://github.com/tinkoff-ai/etna/pull/1155))
 - Fixed `custom_transform_and_model.ipynb`([#1216](https://github.com/tinkoff-ai/etna/pull/1216))
+
 ### Removed
 - `sample_acf_plot`, `sample_pacf_plot`, `CatBoostModelPerSegment`, `CatBoostModelMultiSegment` ([#1118](https://github.com/tinkoff-ai/etna/pull/1118))
 - `PytorchForecastingTransform` ([#971](https://github.com/tinkoff-ai/etna/pull/971))
diff --git a/pyproject.toml b/pyproject.toml
index e72998f25..ed281ccb7 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "etna"
-version = "2.0.0"
+version = "2.1.0"
 repository = "https://github.com/tinkoff-ai/etna"
 readme = "README.md"
 description = "ETNA is the first python open source framework of Tinkoff.ru AI Center. It is designed to make working with time series simple, productive, and fun."