diff --git a/activation_store/collect.py b/activation_store/collect.py
index 919a9d5..259dd52 100644
--- a/activation_store/collect.py
+++ b/activation_store/collect.py
@@ -133,6 +133,9 @@ def output_dataset_hash(**kwargs):
             kwargs[k] = f"PreTrainedModel_{v.config._name_or_path}" # PretrainedConfig
         elif inspect.isfunction(v):
             kwargs[k] = "Function: %s.%s" % (v.__module__, v.__name__)
+        else:
+            # logger.debug(f"hashing {k} as {v} of type {type(v)}")
+            kwargs[k] = str(v)
     logger.debug(f"hashing {kwargs}")
     suffix = Hasher.hash(kwargs)
     return suffix
@@ -159,11 +162,11 @@ def activation_store(loader: DataLoader, model: PreTrainedModel, dataset_name=''
         f = activation_store(loader, model, layers=['transformer.h'])
         Dataset.from_parquet(f).with_format("torch")
     """
-    # FIXME I think this is the problem, instead of using a naive hash I will need to custom hash some key parts, model_name, dataset_name, layers, etc
-    hash = output_dataset_hash(generate_batches=generate_batches, loader=loader, model=model, layers=layers, postprocess_result=postprocess_result)
 
     if outfile is None:
-        outdir = Path(tempfile.mkdtemp(prefix='activation_store'))
+        # FIXME I think this is the problem, instead of using a naive hash I will need to custom hash some key parts, model_name, dataset_name, layers, etc
+        hash = output_dataset_hash(generate_batches=generate_batches, loader=loader, model=model, layers=layers, postprocess_result=postprocess_result)
+        outdir = Path(tempfile.gettempdir()) / 'activation_store'
         outfile = outdir / f"ds_act_{dataset_name}_{hash}.parquet"
     outfile.parent.mkdir(exist_ok=True, parents=True)
     logger.info(f"creating dataset {outfile}")