Great! I tried running it in Google Colab, I uploaded my `collection.colpkg`

file to `My Drive/Colab Notebooks`

in Google Drive. Then I needed to modify the notebook

```
# Mount Google Drive
from google.colab import drive
drive.mount('/content/drive')
filename = "/content/drive/My Drive/Colab Notebooks/collection.colpkg"
# If you upload deck file, replace it with your deck filename. E.g., ALL__Learnig.apkg
# If you upload collection file, replace it with your colpgk filename. E.g., collection-2022-09-18@13-21-58.colpkg
...
```

for it to load my collection.

Building the trainset took about 5 minutes in Google Colab (I didn’t enable GPU acceleration in Google Colab). EDIT: I tried enabling GPU acceleration and it took 4 minutes.

```
100%|██████████| 24177/24177 [05:16<00:00, 76.43it/s]
Trainset saved
```

However, when I go to train the model, it seems like I get `NaN`

for the parameters after `30981`

iterations:

```
iteration: 1
f_s: Parameter containing:
tensor([1.9999], requires_grad=True)
f_d: Parameter containing:
tensor([4.9999], requires_grad=True)
s_w: Parameter containing:
tensor([ 3.0001, -0.6999, -0.1999, -0.2999], requires_grad=True)
iteration: 30981
f_s: Parameter containing:
tensor([nan], requires_grad=True)
f_d: Parameter containing:
tensor([nan], requires_grad=True)
s_w: Parameter containing:
tensor([nan, nan, nan, nan], requires_grad=True)
iteration: 61961
f_s: Parameter containing:
tensor([nan], requires_grad=True)
f_d: Parameter containing:
tensor([nan], requires_grad=True)
s_w: Parameter containing:
tensor([nan, nan, nan, nan], requires_grad=True)
iteration: 92941
f_s: Parameter containing:
tensor([nan], requires_grad=True)
f_d: Parameter containing:
tensor([nan], requires_grad=True)
s_w: Parameter containing:
tensor([nan, nan, nan, nan], requires_grad=True)
iteration: 123921
f_s: Parameter containing:
tensor([nan], requires_grad=True)
f_d: Parameter containing:
tensor([nan], requires_grad=True)
s_w: Parameter containing:
tensor([nan, nan, nan, nan], requires_grad=True)
iteration: 154901
f_s: Parameter containing:
tensor([nan], requires_grad=True)
f_d: Parameter containing:
tensor([nan], requires_grad=True)
s_w: Parameter containing:
tensor([nan, nan, nan, nan], requires_grad=True)
iteration: 185881
f_s: Parameter containing:
tensor([nan], requires_grad=True)
f_d: Parameter containing:
tensor([nan], requires_grad=True)
s_w: Parameter containing:
tensor([nan, nan, nan, nan], requires_grad=True)
iteration: 216861
f_s: Parameter containing:
tensor([nan], requires_grad=True)
f_d: Parameter containing:
tensor([nan], requires_grad=True)
s_w: Parameter containing:
tensor([nan, nan, nan, nan], requires_grad=True)
iteration: 247841
f_s: Parameter containing:
tensor([nan], requires_grad=True)
f_d: Parameter containing:
tensor([nan], requires_grad=True)
s_w: Parameter containing:
tensor([nan, nan, nan, nan], requires_grad=True)
iteration: 278821
f_s: Parameter containing:
tensor([nan], requires_grad=True)
f_d: Parameter containing:
tensor([nan], requires_grad=True)
s_w: Parameter containing:
tensor([nan, nan, nan, nan], requires_grad=True)
iteration: 309801
f_s: Parameter containing:
tensor([nan], requires_grad=True)
f_d: Parameter containing:
tensor([nan], requires_grad=True)
s_w: Parameter containing:
tensor([nan, nan, nan, nan], requires_grad=True)
Training finished!
```

The training took about 41 minutes on Google Colab (no GPU acceleration). EDIT: I tried enabling GPU acceleration and it took about 33 minutes.

Then I run the print commands:

```
const defaultDifficulty = nan;
const defaultStability = nan;
const difficultyDecay = nan;
const stabilityDecay = nan;
const increaseFactor = nan;
const lapsesBase = nan;
```

It seems something went wrong during the training, all the values are `nan`

I have uploaded my Anki collection here (media files removed): 23.06 MB file on MEGA

Also, I noticed you have recently changed the default `increaseFactor`

from `60`

to `3`

. Just curious as to why this was changed. In fsrs.js it is set to `60`

still