title: How to see results via `mlflow ui` for experiments logged on a other server?
body: <p>I was running ML experiments on a ssh server, the experiments were logged via mlflow and stored in local <code>mlruns</code> on the server.</p>
  <p>The code were just basic usage of mlflow and looks like this</p>
  <pre class="lang-py prettyprint-override"><code>import numpy as np
  import mlflow
  import matplotlib.pyplot as plt
  
  from pathlib import Path
  from sklearn.linear_model import LinearRegression
  from sklearn.metrics import r2_score
  
  
  if __name__ == '__main__':
      Path('./plot').mkdir(exist_ok = True)
      mlflow.set_experiment('demo-exp')
      with mlflow.start_run():
          x     = np.random.randn(10, 1)
          y     = np.random.randn(10, 1)
          model = LinearRegression().fit(x, y)
          py    = model.predict(x)
          r2    = r2_score(y, py)
          plt.plot(y, py, '+')
          plt.savefig('./plot/result.png')
          plt.close()
  
          mlflow.log_metric('r2', r2)
          mlflow.log_artifact('./plot/result.png')
  </code></pre>
  <p>Now I want to see the logged metrics and artifactos from my own laptop, so I tried</p>
  <pre><code>mlflow ui \
      --default-artifact-root=sftp:///USER_NAME@ADDRESS/path/to/experiment/mlruns \
      --port=8888 \
  
  </code></pre>
  <p>However, it looks like nothing showed in <code>localhost:8888</code> on my own laptop.</p>
  <p>Anything I did wrong about the code and <code>mlflow ui</code> command?</p>