this will help I am trying to predict the OHLC values. Till now I have achieved this: , To have those metrics use:

code :

```
model.compile(loss='mean_squared_error',optimizer='sgd', metrics=['mae', 'acc'])
```

```
evaluate(self, x=None, y=None, batch_size=None, verbose=1, sample_weight=None, steps=None)
```

```
model_open.compile(loss='mse', optimizer='rmsprop')
model_high.compile(loss='mse', optimizer='rmsprop')
model_low.compile(loss='mse', optimizer='rmsprop')
model_close.compile(loss='mse', optimizer='rmsprop')
```

```
model_open.compile(loss='mse', optimizer='rmsprop', metrics=['mae', 'acc'])
model_high.compile(loss='mse', optimizer='rmsprop', metrics=['mae', 'acc'])
model_low.compile(loss='mse', optimizer='rmsprop', metrics=['mae', 'acc'])
model_close.compile(loss='mse', optimizer='rmsprop', metrics=['mae', 'acc'])
```

```
model_open.evaluate( testX_open, testY_open)
model_high.evaluate( testX_high, testY_high)
model_low.evaluate( testX_low, testY_low)
model_close.evaluate(testX_close,testY_close)
```