File size: 5,137 Bytes
62829c3
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
---
language:
- de
license: mit
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_9_0
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_9_0
model-index:
- name: wav2vec2-base-german-cv9
  results:   
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 6.1
      type: common_voice
      args: de
    metrics:
    - name: Test WER
      type: wer
      value: 10.565782902002716
    - name: Test CER
      type: cer
      value: 2.6226824852959657
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 6.1
      type: common_voice
      args: de
    metrics:
    - name: Test WER (+LM)
      type: wer
      value: 7.996088831362508
    - name: Test CER (+LM)
      type: cer
      value: 2.1515717711623326
---


# wav2vec2-base-german-cv9

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the MOZILLA-FOUNDATION/COMMON_VOICE_9_0 - DE dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1742
- Wer: 0.1209

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 16
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Wer    |
|:-------------:|:-----:|:------:|:---------------:|:------:|
| 0.6827        | 1.0   | 3557   | 0.6695          | 0.6247 |
| 0.3992        | 2.0   | 7114   | 0.3738          | 0.3936 |
| 0.2611        | 3.0   | 10671  | 0.3011          | 0.3177 |
| 0.2536        | 4.0   | 14228  | 0.2672          | 0.2749 |
| 0.1943        | 5.0   | 17785  | 0.2487          | 0.2480 |
| 0.2004        | 6.0   | 21342  | 0.2246          | 0.2268 |
| 0.1605        | 7.0   | 24899  | 0.2176          | 0.2120 |
| 0.1579        | 8.0   | 28456  | 0.2046          | 0.2024 |
| 0.1668        | 9.0   | 32013  | 0.2027          | 0.1944 |
| 0.1338        | 10.0  | 35570  | 0.1968          | 0.1854 |
| 0.1478        | 11.0  | 39127  | 0.1963          | 0.1823 |
| 0.1177        | 12.0  | 42684  | 0.1956          | 0.1800 |
| 0.1245        | 13.0  | 46241  | 0.1889          | 0.1732 |
| 0.1124        | 14.0  | 49798  | 0.1868          | 0.1714 |
| 0.1112        | 15.0  | 53355  | 0.1805          | 0.1650 |
| 0.1209        | 16.0  | 56912  | 0.1860          | 0.1614 |
| 0.1002        | 17.0  | 60469  | 0.1828          | 0.1604 |
| 0.118         | 18.0  | 64026  | 0.1832          | 0.1580 |
| 0.0974        | 19.0  | 67583  | 0.1771          | 0.1555 |
| 0.1007        | 20.0  | 71140  | 0.1812          | 0.1532 |
| 0.0866        | 21.0  | 74697  | 0.1752          | 0.1504 |
| 0.0901        | 22.0  | 78254  | 0.1690          | 0.1477 |
| 0.0964        | 23.0  | 81811  | 0.1773          | 0.1489 |
| 0.085         | 24.0  | 85368  | 0.1776          | 0.1456 |
| 0.0945        | 25.0  | 88925  | 0.1786          | 0.1428 |
| 0.0804        | 26.0  | 92482  | 0.1737          | 0.1429 |
| 0.0832        | 27.0  | 96039  | 0.1789          | 0.1394 |
| 0.0683        | 28.0  | 99596  | 0.1741          | 0.1390 |
| 0.0761        | 29.0  | 103153 | 0.1688          | 0.1379 |
| 0.0833        | 30.0  | 106710 | 0.1726          | 0.1370 |
| 0.0753        | 31.0  | 110267 | 0.1774          | 0.1353 |
| 0.08          | 32.0  | 113824 | 0.1734          | 0.1344 |
| 0.0644        | 33.0  | 117381 | 0.1737          | 0.1334 |
| 0.0745        | 34.0  | 120938 | 0.1763          | 0.1335 |
| 0.0629        | 35.0  | 124495 | 0.1761          | 0.1311 |
| 0.0654        | 36.0  | 128052 | 0.1718          | 0.1302 |
| 0.0656        | 37.0  | 131609 | 0.1697          | 0.1301 |
| 0.0643        | 38.0  | 135166 | 0.1716          | 0.1279 |
| 0.0683        | 39.0  | 138723 | 0.1777          | 0.1279 |
| 0.0587        | 40.0  | 142280 | 0.1735          | 0.1271 |
| 0.0693        | 41.0  | 145837 | 0.1780          | 0.1260 |
| 0.0532        | 42.0  | 149394 | 0.1724          | 0.1245 |
| 0.0594        | 43.0  | 152951 | 0.1736          | 0.1250 |
| 0.0544        | 44.0  | 156508 | 0.1744          | 0.1238 |
| 0.0559        | 45.0  | 160065 | 0.1770          | 0.1232 |
| 0.0557        | 46.0  | 163622 | 0.1766          | 0.1231 |
| 0.0521        | 47.0  | 167179 | 0.1751          | 0.1220 |
| 0.0591        | 48.0  | 170736 | 0.1724          | 0.1217 |
| 0.0507        | 49.0  | 174293 | 0.1753          | 0.1212 |
| 0.0577        | 50.0  | 177850 | 0.1742          | 0.1209 |


### Framework versions

- Transformers 4.20.1
- Pytorch 1.11.0+cu113
- Datasets 2.0.0
- Tokenizers 0.11.6