diff --git a/haystack/modeling/data_handler/data_silo.py b/haystack/modeling/data_handler/data_silo.py
index 7d51193ec..5ce6bb6c0 100644
--- a/haystack/modeling/data_handler/data_silo.py
+++ b/haystack/modeling/data_handler/data_silo.py
@@ -150,7 +150,7 @@ class DataSilo:
         :return: None
         """
 
-        logger.info("\nLoading data into the data silo ..." "{}".format(TRACTOR_SMALL))
+        logger.info("\nLoading data into the data silo ... %s", TRACTOR_SMALL)
         # train data
         logger.info("LOADING TRAIN DATA")
         logger.info("==================")
@@ -161,7 +161,7 @@ class DataSilo:
         elif self.processor.train_filename:
             # or from a file (default)
             train_file = self.processor.data_dir / self.processor.train_filename
-            logger.info("Loading train set from: {} ".format(train_file))
+            logger.info("Loading train set from: %s ", train_file)
             self.data["train"], self.tensor_names = self._get_dataset(train_file)
         else:
             logger.info("No train set is being loaded")
@@ -178,7 +178,7 @@ class DataSilo:
         elif self.processor.dev_filename:
             # or from file (default)
             dev_file = self.processor.data_dir / self.processor.dev_filename
-            logger.info("Loading dev set from: {}".format(dev_file))
+            logger.info("Loading dev set from: %s", dev_file)
             self.data["dev"], _ = self._get_dataset(dev_file)
         elif self.processor.dev_split > 0.0:
             # or split it apart from train set
@@ -199,7 +199,7 @@ class DataSilo:
         elif self.processor.test_filename:
             # or from file (default)
             test_file = self.processor.data_dir / self.processor.test_filename
-            logger.info("Loading test set from: {}".format(test_file))
+            logger.info("Loading test set from: %s", test_file)
             if self.tensor_names:
                 self.data["test"], _ = self._get_dataset(test_file)
             else:
@@ -406,16 +406,16 @@ class DataSilo:
         else:
             self.counts["test"] = 0
 
-        logger.info("Examples in train: {}".format(self.counts["train"]))
-        logger.info("Examples in dev  : {}".format(self.counts["dev"]))
-        logger.info("Examples in test : {}".format(self.counts["test"]))
-        logger.info("Total examples   : {}".format(self.counts["train"] + self.counts["dev"] + self.counts["test"]))
+        logger.info("Examples in train: %s", self.counts["train"])
+        logger.info("Examples in dev  : %s", self.counts["dev"])
+        logger.info("Examples in test : %s", self.counts["test"])
+        logger.info("Total examples   : %s", self.counts["train"] + self.counts["dev"] + self.counts["test"])
         logger.info("")
         if self.data["train"]:
             if "input_ids" in self.tensor_names:
-                logger.info("Longest sequence length observed after clipping:     {}".format(max(seq_lens)))
-                logger.info("Average sequence length after clipping: {}".format(ave_len))
-                logger.info("Proportion clipped:      {}".format(clipped))
+                logger.info("Longest sequence length observed after clipping:     %s", max(seq_lens))
+                logger.info("Average sequence length after clipping: %s", ave_len)
+                logger.info("Proportion clipped:      %s", clipped)
                 if clipped > 0.5:
                     logger.info(
                         "[Haystack Tip] %s%% of your samples got cut down to %s tokens. "
@@ -429,20 +429,20 @@ class DataSilo:
                     )
             elif "query_input_ids" in self.tensor_names and "passage_input_ids" in self.tensor_names:
                 logger.info(
-                    "Longest query length observed after clipping: {}   - for max_query_len: {}".format(
-                        max(seq_lens[0]), max_seq_len[0]
-                    )
+                    "Longest query length observed after clipping: %s   - for max_query_len: %s",
+                    max(seq_lens[0]),
+                    max_seq_len[0],
                 )
-                logger.info("Average query length after clipping:          {}".format(ave_len[0]))
-                logger.info("Proportion queries clipped:                   {}".format(clipped[0]))
+                logger.info("Average query length after clipping:          %s", ave_len[0])
+                logger.info("Proportion queries clipped:                   %s", clipped[0])
                 logger.info("")
                 logger.info(
-                    "Longest passage length observed after clipping: {}   - for max_passage_len: {}".format(
-                        max(seq_lens[1]), max_seq_len[1]
-                    )
+                    "Longest passage length observed after clipping: %s   - for max_passage_len: %s",
+                    max(seq_lens[1]),
+                    max_seq_len[1],
                 )
-                logger.info("Average passage length after clipping:          {}".format(ave_len[1]))
-                logger.info("Proportion passages clipped:                    {}".format(clipped[1]))
+                logger.info("Average passage length after clipping:          %s", ave_len[1])
+                logger.info("Proportion passages clipped:                    %s", clipped[1])
 
         tracker.track_params(
             {
diff --git a/haystack/modeling/data_handler/processor.py b/haystack/modeling/data_handler/processor.py
index 693eb5413..004b3eb92 100644
--- a/haystack/modeling/data_handler/processor.py
+++ b/haystack/modeling/data_handler/processor.py
@@ -2271,9 +2271,9 @@ def _download_extract_downstream_data(input_file: str, proxies=None):
     directory = full_path.parent
     taskname = directory.stem
     datadir = directory.parent
-    logger.info("downloading and extracting file {} to dir {}".format(taskname, datadir))
+    logger.info("downloading and extracting file %s to dir %s", taskname, datadir)
     if taskname not in DOWNSTREAM_TASK_MAP:
-        logger.error("Cannot download {}. Unknown data source.".format(taskname))
+        logger.error("Cannot download %s. Unknown data source.", taskname)
     else:
         if os.name == "nt":  # make use of NamedTemporaryFile compatible with Windows
             delete_tmp_file = False
diff --git a/haystack/modeling/evaluation/eval.py b/haystack/modeling/evaluation/eval.py
index 3e5979198..23a791f64 100644
--- a/haystack/modeling/evaluation/eval.py
+++ b/haystack/modeling/evaluation/eval.py
@@ -187,7 +187,7 @@ class Evaluator:
         logger.info(header)
 
         for head in results:
-            logger.info("\n _________ {} _________".format(head["task_name"]))
+            logger.info("\n _________ %s _________", head["task_name"])
             for metric_name, metric_val in head.items():
                 # log with experiment tracking framework (e.g. Mlflow)
                 if logging:
@@ -201,10 +201,10 @@ class Evaluator:
                     if metric_name == "report":
                         if isinstance(metric_val, str) and len(metric_val) > 8000:
                             metric_val = metric_val[:7500] + "\n ............................. \n" + metric_val[-500:]
-                        logger.info("{}: \n {}".format(metric_name, metric_val))
+                        logger.info("%s: \n %s", metric_name, metric_val)
                     else:
                         if not metric_name in ["preds", "labels"] and not metric_name.startswith("_"):
-                            logger.info("{}: {}".format(metric_name, metric_val))
+                            logger.info("%s: %s", metric_name, metric_val)
 
 
 def _to_numpy(container):
diff --git a/haystack/modeling/model/prediction_head.py b/haystack/modeling/model/prediction_head.py
index 5c10befb6..6b05dca53 100644
--- a/haystack/modeling/model/prediction_head.py
+++ b/haystack/modeling/model/prediction_head.py
@@ -110,7 +110,7 @@ class PredictionHead(nn.Module):
         prediction_head = cls.subclasses[config["name"]](**config)
         if load_weights:
             model_file = cls._get_model_file(config_file=config_file)
-            logger.info("Loading prediction head from {}".format(model_file))
+            logger.info("Loading prediction head from %s", model_file)
             prediction_head.load_state_dict(torch.load(model_file, map_location=torch.device("cpu")), strict=strict)
         return prediction_head
 
diff --git a/haystack/modeling/training/base.py b/haystack/modeling/training/base.py
index cef0a8ea7..15ee17a08 100644
--- a/haystack/modeling/training/base.py
+++ b/haystack/modeling/training/base.py
@@ -238,17 +238,13 @@ class Trainer:
                             do_stopping, save_model, eval_value = self.early_stopping.check_stopping(result)
                             if save_model:
                                 logger.info(
-                                    "Saving current best model to {}, eval={}".format(
-                                        self.early_stopping.save_dir, eval_value
-                                    )
+                                    "Saving current best model to %s, eval=%s", self.early_stopping.save_dir, eval_value
                                 )
                                 self.model.save(self.early_stopping.save_dir)
                                 self.data_silo.processor.save(self.early_stopping.save_dir)
                             if do_stopping:
                                 # log the stopping
-                                logger.info(
-                                    "STOPPING EARLY AT EPOCH {}, STEP {}, EVALUATION {}".format(epoch, step, evalnr)
-                                )
+                                logger.info("STOPPING EARLY AT EPOCH %s, STEP %s, EVALUATION %s", epoch, step, evalnr)
                 if do_stopping:
                     break
 
@@ -280,7 +276,7 @@ class Trainer:
 
         # With early stopping we want to restore the best model
         if self.early_stopping and self.early_stopping.save_dir:
-            logger.info("Restoring best model so far from {}".format(self.early_stopping.save_dir))
+            logger.info("Restoring best model so far from %s", self.early_stopping.save_dir)
             self.model = self.model.load(self.early_stopping.save_dir, self.device)
             self.model.connect_heads_with_processor(self.data_silo.processor.tasks, require_labels=True)
 
diff --git a/haystack/nodes/reader/farm.py b/haystack/nodes/reader/farm.py
index 6f8725ba7..56f74a6cd 100644
--- a/haystack/nodes/reader/farm.py
+++ b/haystack/nodes/reader/farm.py
@@ -787,7 +787,7 @@ class FARMReader(BaseReader):
                         large_files.append(rel_path)
 
             if len(large_files) > 0:
-                logger.info("Track files with git lfs: {}".format(", ".join(large_files)))
+                logger.info("Track files with git lfs: %s", ", ".join(large_files))
                 repo.lfs_track(large_files)
 
             logger.info("Push model to the hub. This might take a while")
diff --git a/haystack/utils/import_utils.py b/haystack/utils/import_utils.py
index 6c9fefd3e..97e28cbc0 100644
--- a/haystack/utils/import_utils.py
+++ b/haystack/utils/import_utils.py
@@ -112,8 +112,9 @@ def fetch_archive_from_http(
             tar_archive.extractall(output_dir)
         else:
             logger.warning(
-                "Skipped url {0} as file type is not supported here. "
-                "See haystack documentation for support of more file types".format(url)
+                "Skipped url %s as file type is not supported here. "
+                "See haystack documentation for support of more file types",
+                url,
             )
 
         return True
diff --git a/haystack/utils/preprocessing.py b/haystack/utils/preprocessing.py
index b9cc9659f..dea6b6d31 100644
--- a/haystack/utils/preprocessing.py
+++ b/haystack/utils/preprocessing.py
@@ -45,8 +45,10 @@ def convert_files_to_docs(
             suffix2paths[file_suffix].append(path)
         elif not path.is_dir():
             logger.warning(
-                "Skipped file {0} as type {1} is not supported here. "
-                "See haystack.file_converter for support of more file types".format(path, file_suffix)
+                "Skipped file %s as type %s is not supported here. "
+                "See haystack.file_converter for support of more file types",
+                path,
+                file_suffix,
             )
 
     # No need to initialize converter if file type not present
@@ -61,7 +63,7 @@ def convert_files_to_docs(
     documents = []
     for suffix, paths in suffix2paths.items():
         for path in paths:
-            logger.info("Converting {}".format(path))
+            logger.info("Converting %s", path)
             # PDFToTextConverter, TextConverter, and DocxToTextConverter return a list containing a single Document
             document = suffix2converter[suffix].convert(
                 file_path=path, meta=None, encoding=encoding, id_hash_keys=id_hash_keys
@@ -108,7 +110,7 @@ def tika_convert_files_to_docs(
     try:
         from haystack.nodes.file_converter import TikaConverter
     except Exception as ex:
-        logger.error("Tika not installed. Please install tika and try again. Error: {}".format(ex))
+        logger.error("Tika not installed. Please install tika and try again. Error: %s", ex)
         raise ex
     converter = TikaConverter()
     paths = [p for p in Path(dir_path).glob("**/*")]
@@ -121,13 +123,15 @@ def tika_convert_files_to_docs(
             file_paths.append(path)
         elif not path.is_dir():
             logger.warning(
-                "Skipped file {0} as type {1} is not supported here. "
-                "See haystack.file_converter for support of more file types".format(path, file_suffix)
+                "Skipped file %s as type %s is not supported here. "
+                "See haystack.file_converter for support of more file types",
+                path,
+                file_suffix,
             )
 
     documents = []
     for path in file_paths:
-        logger.info("Converting {}".format(path))
+        logger.info("Converting %s", path)
         # TikaConverter returns a list containing a single Document
         document = converter.convert(path)[0]
         meta = document.meta or {}
diff --git a/pyproject.toml b/pyproject.toml
index 0e0ee4f8f..f424a5ec9 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -273,7 +273,6 @@ disable = [
   "too-many-instance-attributes",
   "super-with-arguments",
   "redefined-builtin",
-  "logging-format-interpolation",
   "abstract-method",
   "too-many-branches",
   "unspecified-encoding",