# A Novel Approach to Loss Landscape Characterization without Over-Parametrization

Our training of 3-layer LSTM is based on the code from [this repository](https://github.com/fhueb/parameter-agnostic-lzlo). 


## Training

For the considered algorithm (NSGD-M), simply run

```
python main_lstm.py --data [data_folder] --result_dir result/ --epochs 300 --algo nsgdm --lr 25.0 --lr_decay 0.75 --mom_decay 0.5 --seed 1970
```

Here the `[data_folder]` is the data folder containing the training set and validation set.

For other algorithms, change the `--algo` parameter.
