Repository: pykeen/pykeen
Issue: CheckpointMismatchError triggered with no change to training configurations
Root cause: Validation Gap

### Describe the bug

I was training an AutoSF model on the following setup :

```python
from pykeen.triples import TriplesFactory
from pykeen.pipeline import pipeline
from pykeen.models import AutoSF

training = TriplesFactory.from_path(
    './data/Xiangyu/train.txt',
    create_inverse_triples = True
)
testing = TriplesFactory.from_path(
    './data/Xiangyu/test.txt',
    entity_to_id=training.entity_to_id,
    relation_to_id=training.relation_to_id,
    #create_inverse_triples = True,
)
validation = TriplesFactory.from_path(
    path='./data/Xiangyu/valid.txt',
    entity_to_id=training.entity_to_id,
    relation_to_id=training.relation_to_id,
)

result = pipeline(
    training=training,
    testing=testing,
    model=AutoSF,
    evaluator='RankBasedEvaluator',
    stopper= 'early', 
    random_seed = 21159,
    lr_scheduler = 'ExponentialLR',
    lr_scheduler_kwargs=dict(
        gamma=0.99,
    ),
    validation= validation,
    training_kwargs=dict(
        num_epochs=300,
        checkpoint_name='XYcp.pt',
        checkpoint_directory='/home/checkpoint',
        checkpoint_frequency=5,
    ),
)

result.save_to_directory('Xiangyu_AutoSF')
```

In a Jupyter notebook, on a server provided by openbayes.com. A server disconnection occured, and I tried to resume training through the "simple re-run" feature. Though, before doing this, I made another precaution by using "checkpoint = torch.load(PYKEEN_CHECKPOINTS.joinpath('/home/checkpoint/XYcp.pt'))" to load the checkpoint manually, then dumping it with joblib for downloading the model. And then when I tried to resume, the "CheckpointMismatchError: The checkpoint file '/home/checkpoint/XYcp.pt' that was provided already exists, but seems to be from a different training loop setup.r" was triggered, despite the fact that the kernel containing the configurations was unaltered.



### How to reproduce

```python
import joblib
import torch
from pykeen.constants import PYKEEN_CHECKPOINTS
from pykeen.pipeline import pipeline
from pykeen.triples import TriplesFactory

checkpoint = torch.load(PYKEEN_CHECKPOINTS.joinpath('/home/checkpoint/XYcp.pt'))

joblib.dump(checkpoint,'xy.model')
```

### Environment

Unable to handle parameter in CooccurrenceFilteredModel: base
| Key             | Value                    |
|-----------------|--------------------------|
| OS              | posix                    |
| Platform        | Linux                    |
| Release         | 4.15.0-144-generic       |
| Time            | Tue Jul  5 12:33:48 2022 |
| Python          | 3.8.12                   |
| PyKEEN          | 1.8.3-dev                |
| PyKEEN Hash     | UNHASHED                 |
| PyKEEN Branch   |                          |
| PyTorch         | 1.11.0+cu113             |
| CUDA Available? | true                     |
| CUDA Version    | 11.3                     |
| cuDNN Version   | 8200                     |

### Additional information

_No response_

### Issue Template Checks

- [X] This is not a feature request (use a different issue template if it is)
- [X] This is not a question (use the [discussions](https://github.com/pykeen/pykeen/discussions/new) forum instead)
- [X] I've read the text explaining why including environment information is important and understand if I omit this information that my issue will be dismissed

We'll need the full stack trace to go along with the error you're getting otherwise it's not possible to give feedback.

Additionally, please either provide either the files you used for training, or try and come up with a minimal example demonstrates using one of the built-in datasets.

I'm going to close this since we never got a response from the submitter