blob: 4a723c6cbffaebeb1a26a738ab5d0a520c21465b (
plain) (
blame)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
|
model:
n_cnn_layers: 3
n_rnn_layers: 5
rnn_dim: 512
n_feats: 128 # number of mel features
stride: 2
dropout: 0.25 # recommended to be around 0.4-0.6 for smaller datasets, 0.1 for really large datasets
training:
learning_rate: 0.0005
batch_size: 2 # recommended to maximum number that fits on the GPU (batch size of 32 fits on a 12GB GPU)
epochs: 3
eval_every_n: 1 # evaluate every n epochs
num_workers: 4 # number of workers for dataloader
device: "cuda" # device to run inference on if gpu is available, else "cpu" will be set automatically
dataset:
download: True
dataset_root_path: "/Volumes/pherkel 1/SWR2-ASR" # files will be downloaded into this dir
language_name: "mls_german_opus"
limited_supervision: True # set to True if you want to use limited supervision
dataset_percentage: 0.01 # percentage of dataset to use (1.0 = 100%)
shuffle: True
tokenizer:
tokenizer_path: "data/tokenizers/char_tokenizer_german.json"
checkpoints:
model_load_path: "data/runs/epoch30" # path to load model from
model_save_path: ~ # path to save model to
inference:
model_load_path: "data/runs/epoch30" # path to load model from
device: "cuda" # device to run inference on if gpu is available, else "cpu" will be set automatically
|
