diff --git a/README.md b/README.md
index dc0cf7a8..3146659f 100644
--- a/README.md
+++ b/README.md
@@ -23,7 +23,7 @@ Here are the [results](https://github.com/AntixK/PyTorch-VAE/blob/master/README.
 ### Requirements
 - Python >= 3.5
 - PyTorch >= 1.3
-- Pytorch Lightning >= 0.6.0 ([GitHub Repo](https://github.com/PyTorchLightning/pytorch-lightning/tree/deb1581e26b7547baf876b7a94361e60bb200d32))
+- Pytorch Lightning >= 1.0.0 ([GitHub Repo](https://github.com/PyTorchLightning/pytorch-lightning/tree/deb1581e26b7547baf876b7a94361e60bb200d32))
 - CUDA enabled computing device
 
 ### Installation
@@ -60,7 +60,7 @@ exp_params:
 
 trainer_params:
   gpus: 1         
-  max_nb_epochs: 50
+  max_epochs: 50
   gradient_clip_val: 1.5
     .
     .
diff --git a/run.py b/run.py
index d95dd657..5252a1f8 100644
--- a/run.py
+++ b/run.py
@@ -6,7 +6,7 @@
 from experiment import VAEXperiment
 import torch.backends.cudnn as cudnn
 from pytorch_lightning import Trainer
-from pytorch_lightning.logging import TestTubeLogger
+from pytorch_lightning.loggers import TestTubeLogger
 
 
 parser = argparse.ArgumentParser(description='Generic runner for VAE models')
@@ -42,14 +42,13 @@
                           config['exp_params'])
 
 runner = Trainer(default_save_path=f"{tt_logger.save_dir}",
-                 min_nb_epochs=1,
+                 min_epochs=1,
                  logger=tt_logger,
-                 log_save_interval=100,
-                 train_percent_check=1.,
-                 val_percent_check=1.,
+                 flush_logs_every_n_steps=100,
+                 limit_train_batches=1.,
+                 limit_val_batches=1.,
                  num_sanity_val_steps=5,
-                 early_stop_callback = False,
                  **config['trainer_params'])
 
 print(f"======= Training {config['model_params']['name']} =======")
-runner.fit(experiment)
\ No newline at end of file
+runner.fit(experiment)