diff --git a/test/core/test_trainer.py b/test/core/test_trainer.py
new file mode 100644
index 00000000..7db861af
--- /dev/null
+++ b/test/core/test_trainer.py
@@ -0,0 +1,33 @@
+import os
+
+import torch.nn as nn
+import unittest
+
+from fastNLP.core.trainer import SeqLabelTrainer
+from fastNLP.core.loss import Loss
+from fastNLP.core.optimizer import Optimizer
+from fastNLP.models.sequence_modeling import SeqLabeling
+
+class TestTrainer(unittest.TestCase):
+    def test_case_1(self):
+        args = {"epochs": 3, "batch_size": 8, "validate": True, "use_cuda": True, "pickle_path": "./save/",
+                "save_best_dev": True, "model_name": "default_model_name.pkl",
+                "loss": Loss(None),
+                "optimizer": Optimizer("Adam", lr=0.001, weight_decay=0),
+                "vocab_size": 20,
+                "word_emb_dim": 100,
+                "rnn_hidden_units": 100,
+                "num_classes": 3
+                }
+        trainer = SeqLabelTrainer()
+        train_data = [
+            [[1, 2, 3, 4, 5, 6], [1, 0, 1, 0, 1, 2]],
+            [[2, 3, 4, 5, 1, 6], [0, 1, 0, 1, 0, 2]],
+            [[1, 4, 1, 4, 1, 6], [1, 0, 1, 0, 1, 2]],
+            [[1, 2, 3, 4, 5, 6], [1, 0, 1, 0, 1, 2]],
+            [[2, 3, 4, 5, 1, 6], [0, 1, 0, 1, 0, 2]],
+            [[1, 4, 1, 4, 1, 6], [1, 0, 1, 0, 1, 2]],
+        ]
+        dev_data = train_data
+        model = SeqLabeling(args)
+        trainer.train(network=model, train_data=train_data, dev_data=dev_data)
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