I wrote a function which directly exports the data from the SummaryWriter.
In case somebody stumbles over it.
def export_jsondump(writer):

	assert isinstance(writer, torch.utils.tensorboard.SummaryWriter)

	tf_files = [] # -> list of paths from writer.log_dir to all files in that directory
	for root, dirs, files in os.walk(writer.log_dir):
		for file in files:
			tf_files.append(os.path.join(root,file)) # go over every file recursively in the directory

	for file_id, file in enumerate(tf_files):

		path = os.path.join('/'.join(file.split('/')[:-1])) # determine path to folder in which file lies
		name = os.path.join(file.split('/')[-2]) if file_id > 0 else os.path.join('data') # seperate file created by add_scalar from add_scalars

		# print(file, '->', path, '|', name)

		event_acc = event_accumulator.EventAccumulator(file)
		event_acc.Reload()
		data = {}

		hparam_file = False # I save hparam files as 'hparam/xyz_metric'
		for tag in sorted(event_acc.Tags()["scalars"]):
			if tag.split('/')[0] == 'hparam': hparam_file=True # check if its a hparam file
			step, value = [], []

			for scalar_event in event_acc.Scalars(tag):
				step.append(scalar_event.step)
				value.append(scalar_event.value)

			data[tag] = (step, value)

		if not hparam_file and bool(data): # if its not a hparam file and there is something in the data -> dump it
			with open(path+f'/{name}.json', "w") as f:
				json.dump(data, f)