[Possible Bug] Running multiple initialization seeds

Hi,

I wanted to train a network with multiple `initial seeds` such as this

```py
cfg = TrainConfig(sae_config, optimizer=optimizer, init_seeds=[0,42],
batch_size=b_size, layers=['6'],
run_name=run_name, save_dir=save_dir)
trainer = Trainer(cfg, tokenized, gpt)
```

However I get the error `KeyError: 'h.6'` from line 375 `raw = self.saes[name]`, see log below

```log
File "script_training_sae.py", line 97, in
trainer.fit()
File "sparsify/sparsify/trainer.py", line 481, in fit
self.model(x)
File "lib/python3.11/site-packages/torch/nn/modules/module.py", line 1739, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "lib/python3.11/site-packages/torch/nn/modules/module.py", line 1750, in _call_impl
return forward_call(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "lib/python3.11/site-packages/transformers/models/gpt2/modeling_gpt2.py", line 1062, in forward
transformer_outputs = self.transformer(
^^^^^^^^^^^^^^^^^
File "lib/python3.11/site-packages/torch/nn/modules/module.py", line 1739, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "lib/python3.11/site-packages/torch/nn/modules/module.py", line 1750, in _call_impl
return forward_call(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "lib/python3.11/site-packages/transformers/models/gpt2/modeling_gpt2.py", line 922, in forward
outputs = block(
^^^^^^
File "lib/python3.11/site-packages/torch/nn/modules/module.py", line 1739, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "lib/python3.11/site-packages/torch/nn/modules/module.py", line 1845, in _call_impl
return inner()
^^^^^^^
File "/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1806, in inner
hook_result = hook(self, args, result)
^^^^^^^^^^^^^^^^^^^^^^^^
File "sparsify/sparsify/trainer.py", line 375, in hook
raw = self.saes[name]
~~~~~~~~~^^^^^^
KeyError: 'h.6'
```
Same error when training using hookpoints. (I was able to successfully train on layer 6 with a single initial_seed)

## Possible Bug
I think the problem might be the following:
On line 77
name = f"{hook}/seed{seed}" if len(cfg.init_seeds) > 1 else hook
self.saes[name] = SparseCoder(
input_widths[hook], cfg.sae, device, dtype=torch.float32
)
the dictionary sae is defined with the keys `name = f"{hook}/seed{seed}"`
and apparently in `fit()` (line 375) `raw=self.saes[name]` takes only `f"{hook}"`. The problem could be that the variable name is being reset from ` f"{hook}/seed{seed}"` to ` f"{hook}` in lines 328:

```py
name_to_module = {
name: self.model.base_model.get_submodule(name)
for name in self.cfg.hookpoints
}
```

I hope the error is reproducible.