diff --git a/spacy/errors.py b/spacy/errors.py
index a206826ff..0e1a294c3 100644
--- a/spacy/errors.py
+++ b/spacy/errors.py
@@ -869,6 +869,8 @@ class Errors:
     E1019 = ("`noun_chunks` requires the pos tagging, which requires a "
              "statistical model to be installed and loaded. For more info, see "
              "the documentation:\nhttps://spacy.io/usage/models")
+    E1020 = ("No `epoch_resume` value specified and could not infer one from "
+             "filename. Specify an epoch to resume from.")
 
 
 # Deprecated model shortcuts, only used in errors and warnings
diff --git a/spacy/training/pretrain.py b/spacy/training/pretrain.py
index 6d7850212..0228f2947 100644
--- a/spacy/training/pretrain.py
+++ b/spacy/training/pretrain.py
@@ -41,10 +41,11 @@ def pretrain(
     optimizer = P["optimizer"]
     # Load in pretrained weights to resume from
     if resume_path is not None:
-        _resume_model(model, resume_path, epoch_resume, silent=silent)
+        epoch_resume = _resume_model(model, resume_path, epoch_resume, silent=silent)
     else:
         # Without '--resume-path' the '--epoch-resume' argument is ignored
         epoch_resume = 0
+
     objective = model.attrs["loss"]
     # TODO: move this to logger function?
     tracker = ProgressTracker(frequency=10000)
@@ -93,20 +94,25 @@ def ensure_docs(examples_or_docs: Iterable[Union[Doc, Example]]) -> List[Doc]:
 
 def _resume_model(
     model: Model, resume_path: Path, epoch_resume: int, silent: bool = True
-) -> None:
+) -> int:
     msg = Printer(no_print=silent)
     msg.info(f"Resume training tok2vec from: {resume_path}")
     with resume_path.open("rb") as file_:
         weights_data = file_.read()
         model.get_ref("tok2vec").from_bytes(weights_data)
-    # Parse the epoch number from the given weight file
-    model_name = re.search(r"model\d+\.bin", str(resume_path))
-    if model_name:
-        # Default weight file name so read epoch_start from it by cutting off 'model' and '.bin'
-        epoch_resume = int(model_name.group(0)[5:][:-4]) + 1
-        msg.info(f"Resuming from epoch: {epoch_resume}")
-    else:
-        msg.info(f"Resuming from epoch: {epoch_resume}")
+
+    if epoch_resume is None:
+        # Parse the epoch number from the given weight file
+        model_name = re.search(r"model\d+\.bin", str(resume_path))
+        if model_name:
+            # Default weight file name so read epoch_start from it by cutting off 'model' and '.bin'
+            epoch_resume = int(model_name.group(0)[5:][:-4]) + 1
+        else:
+            # No epoch given and couldn't infer it
+            raise ValueError(Errors.E1020)
+
+    msg.info(f"Resuming from epoch: {epoch_resume}")
+    return epoch_resume
 
 
 def make_update(