diff --git a/spacy/cli/train.py b/spacy/cli/train.py
index 96233406d..d71523a9c 100644
--- a/spacy/cli/train.py
+++ b/spacy/cli/train.py
@@ -18,6 +18,7 @@ from ..gold import GoldParse, merge_sents
 from ..gold import GoldCorpus, minibatch
 from ..util import prints
 from .. import util
+from .. import about
 from .. import displacy
 from ..compat import json_dumps
 
@@ -35,10 +36,11 @@ from ..compat import json_dumps
     no_parser=("Don't train parser", "flag", "P", bool),
     no_entities=("Don't train NER", "flag", "N", bool),
     gold_preproc=("Use gold preprocessing", "flag", "G", bool),
+    meta_path=("Optional path to meta.json. All relevant properties will be overwritten.", "option", "m", Path)
 )
 def train(cmd, lang, output_dir, train_data, dev_data, n_iter=20, n_sents=0,
           use_gpu=-1, vectors=None, no_tagger=False, no_parser=False, no_entities=False,
-          gold_preproc=False):
+          gold_preproc=False, meta_path=None):
     """
     Train a model. Expects data in spaCy's JSON format.
     """
@@ -47,13 +49,19 @@ def train(cmd, lang, output_dir, train_data, dev_data, n_iter=20, n_sents=0,
     output_path = util.ensure_path(output_dir)
     train_path = util.ensure_path(train_data)
     dev_path = util.ensure_path(dev_data)
+    meta_path = util.ensure_path(meta_path)
     if not output_path.exists():
         output_path.mkdir()
     if not train_path.exists():
         prints(train_path, title="Training data not found", exits=1)
     if dev_path and not dev_path.exists():
         prints(dev_path, title="Development data not found", exits=1)
-
+    if meta_path is not None and not meta_path.exists():
+        prints(meta_path, title="meta.json not found", exits=1)
+    meta = util.read_json(meta_path) if meta_path else {}
+    if not isinstance(meta, dict):
+        prints("Expected dict but got: {}".format(type(meta)),
+               title="Not a valid meta.json format", exits=1)
 
     pipeline = ['token_vectors', 'tags', 'dependencies', 'entities']
     if no_tagger and 'tags' in pipeline: pipeline.remove('tags')
@@ -105,9 +113,16 @@ def train(cmd, lang, output_dir, train_data, dev_data, n_iter=20, n_sents=0,
                             corpus.dev_docs(
                                 nlp,
                                 gold_preproc=gold_preproc))
-                acc_loc =(output_path / ('model%d' % i) / 'accuracy.json')
-                with acc_loc.open('w') as file_:
-                    file_.write(json_dumps(scorer.scores))
+                meta_loc = output_path / ('model%d' % i) / 'meta.json'
+                meta['accuracy'] = scorer.scores
+                meta['lang'] = nlp.lang
+                meta['pipeline'] = pipeline
+                meta['spacy_version'] = '>=%s' % about.__version__
+                meta.setdefault('name', 'model%d' % i)
+                meta.setdefault('version', '0.0.0')
+
+                with meta_loc.open('w') as file_:
+                    file_.write(json_dumps(meta))
                 util.set_env_log(True)
             print_progress(i, losses, scorer.scores)
     finally: