voxxer commited on
Commit
b81762a
1 Parent(s): b5c8235

update model card README.md

Browse files
Files changed (1) hide show
  1. README.md +80 -0
README.md ADDED
@@ -0,0 +1,80 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: mit
3
+ tags:
4
+ - generated_from_trainer
5
+ datasets:
6
+ - voxpopuli
7
+ model-index:
8
+ - name: speecht5_finetuned_voxpopuli_nl
9
+ results: []
10
+ ---
11
+
12
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
13
+ should probably proofread and complete it, then remove this comment. -->
14
+
15
+ # speecht5_finetuned_voxpopuli_nl
16
+
17
+ This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the voxpopuli dataset.
18
+ It achieves the following results on the evaluation set:
19
+ - Loss: 0.4816
20
+
21
+ ## Model description
22
+
23
+ More information needed
24
+
25
+ ## Intended uses & limitations
26
+
27
+ More information needed
28
+
29
+ ## Training and evaluation data
30
+
31
+ More information needed
32
+
33
+ ## Training procedure
34
+
35
+ ### Training hyperparameters
36
+
37
+ The following hyperparameters were used during training:
38
+ - learning_rate: 1e-05
39
+ - train_batch_size: 4
40
+ - eval_batch_size: 2
41
+ - seed: 42
42
+ - gradient_accumulation_steps: 8
43
+ - total_train_batch_size: 32
44
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
45
+ - lr_scheduler_type: linear
46
+ - lr_scheduler_warmup_steps: 250
47
+ - training_steps: 1000
48
+
49
+ ### Training results
50
+
51
+ | Training Loss | Epoch | Step | Validation Loss |
52
+ |:-------------:|:-----:|:----:|:---------------:|
53
+ | 0.8188 | 0.85 | 50 | 0.7075 |
54
+ | 0.7124 | 1.71 | 100 | 0.6201 |
55
+ | 0.6763 | 2.56 | 150 | 0.5924 |
56
+ | 0.6367 | 3.42 | 200 | 0.5586 |
57
+ | 0.576 | 4.27 | 250 | 0.5216 |
58
+ | 0.5591 | 5.13 | 300 | 0.5097 |
59
+ | 0.5457 | 5.98 | 350 | 0.5027 |
60
+ | 0.5447 | 6.84 | 400 | 0.4999 |
61
+ | 0.5413 | 7.69 | 450 | 0.4933 |
62
+ | 0.5288 | 8.55 | 500 | 0.4913 |
63
+ | 0.5231 | 9.4 | 550 | 0.4881 |
64
+ | 0.5276 | 10.26 | 600 | 0.4874 |
65
+ | 0.52 | 11.11 | 650 | 0.4848 |
66
+ | 0.5238 | 11.97 | 700 | 0.4863 |
67
+ | 0.5163 | 12.82 | 750 | 0.4848 |
68
+ | 0.5191 | 13.68 | 800 | 0.4838 |
69
+ | 0.5163 | 14.53 | 850 | 0.4828 |
70
+ | 0.5126 | 15.38 | 900 | 0.4824 |
71
+ | 0.5155 | 16.24 | 950 | 0.4836 |
72
+ | 0.5193 | 17.09 | 1000 | 0.4816 |
73
+
74
+
75
+ ### Framework versions
76
+
77
+ - Transformers 4.31.0.dev0
78
+ - Pytorch 2.0.1+cu118
79
+ - Datasets 2.14.4
80
+ - Tokenizers 0.13.3