Update README.md

README.md

@@ -6,23 +6,64 @@ sample_rate: 8000
 
 ---
 
-This is an Audacity wrapper for the model, forked from the repository groadabike/ConvTasNet_DAMP-VSEP_enhboth, 
+This is an Audacity wrapper for the model, forked from the repository `groadabike/ConvTasNet_DAMP-VSEP_enhboth`, 
 This model was trained using the Asteroid library: https://github.com/asteroid-team/asteroid.
 
-metadata:
-``` json
-{   'author': 'groadabike',
-    'description': '\
-'
-                   'A vocals separation model, trained on the DAMP dataset. \
-'
-                   'Trained using Asteroid.\
-',
-    'domain': 'vocal-enhancement',
-    'effect': 'source-separation',
-    'id': 'groadabike/ConvTasNet_DAMP-VSEP_enhboth',
-    'labels': ['source-0', 'source-1'],
-    'multichannel': False,
-    'name': 'ConvTasNet-DAMP-Vocals',
-    'sample_rate': 8000}
-```
+The following info was copied directly from `groadabike/ConvTasNet_DAMP-VSEP_enhboth`: 
+
+### Description:
+This model was trained by Gerardo Roa Dabike using Asteroid. It was trained on the enh_both task of the DAMP-VSEP dataset.
+### Training config:
+```yaml
+data:
+    channels: 1
+    n_src: 2
+    root_path: data
+    sample_rate: 16000
+    samples_per_track: 10
+    segment: 3.0
+    task: enh_both
+filterbank:
+    kernel_size: 20
+    n_filters: 256
+    stride: 10
+main_args:
+    exp_dir: exp/train_convtasnet
+    help: None
+masknet:
+    bn_chan: 256
+    conv_kernel_size: 3
+    hid_chan: 512
+    mask_act: relu
+    n_blocks: 8
+    n_repeats: 4
+    n_src: 2
+    norm_type: gLN
+    skip_chan: 256
+optim:
+    lr: 0.0003
+    optimizer: adam
+    weight_decay: 0.0
+positional arguments:
+training:
+   batch_size: 12
+    early_stop: True
+    epochs: 50
+    half_lr: True
+    num_workers: 12
+```
+### Results:
+```yaml
+si_sdr: 14.018196157142519
+si_sdr_imp: 14.017103133809577
+sdr: 14.498517291333885
+sdr_imp: 14.463389151567865
+sir: 24.149634529133372
+sir_imp: 24.11450638936735
+sar: 15.338597389045935
+sar_imp: -137.30634122401517
+stoi: 0.7639416744417206
+stoi_imp: 0.1843383526963759
+```
+### License notice:
+This work "ConvTasNet_DAMP-VSEP_enhboth" is a derivative of DAMP-VSEP: Smule Digital Archive of Mobile Performances - Vocal Separation (Version 1.0.1) by Smule, Inc, used under Smule's Research Data License Agreement (Research only). "ConvTasNet_DAMP-VSEP_enhboth" is licensed under Attribution-ShareAlike 3.0 Unported by Gerardo Roa Dabike.