Hi, I have a question in Rossman part of this lesson. In the last step in the jupyter notebook, I see that there’re 2 attempts to fit the model. The first attempt is in the “Sample” section got the rmspe around 0.19 after the first epoch.

```
m = md.get_learner(emb_szs, len(df.columns)-len(cat_vars),
0.04, 1, [1000,500], [0.001,0.01], y_range=y_range)
lr = 1e-3
m.fit(lr, 3, metrics=[exp_rmspe])
```

[ 0. 0.02479 0.02205 **0.19309** ]

[ 1. 0.02044 0.01751 0.18301]

[ 2. 0.01598 0.01571 0.17248]

then after that, in “All” section, the similar code is run again but the rmspe is much lower as you see it around 0.11.

```
m = md.get_learner(emb_szs, len(df.columns)-len(cat_vars),
0.04, 1, [1000,500], [0.001,0.01], y_range=y_range)
lr = 1e-3
m.fit(lr, 1, metrics=[exp_rmspe])
```

[ 0. 0.01456 0.01544 **0.1148** ]

So I just wondering if this is because the model continues to train after the Sample section but m variable is reassigned in the All section then it couldn’t happen or it is just because that model just has better random number so it fits the data better after the first epoch of training.

Any help on this topic would be very much appreciated.

Thank you.