File size: 3,677 Bytes
d84f4ed
ef3cdad
 
61752de
d84f4ed
ef3cdad
d84f4ed
8236cf4
f165be0
8236cf4
 
 
d84f4ed
e3724b4
d84f4ed
f165be0
 
8236cf4
 
f165be0
 
 
 
 
 
8236cf4
 
 
 
 
 
 
f165be0
 
 
6cffcf0
 
f165be0
 
8236cf4
 
 
 
 
 
 
6cffcf0
 
 
 
 
 
 
8236cf4
 
 
 
 
 
a7f7ee8
 
 
d84f4ed
 
 
 
3042312
 
 
 
d84f4ed
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
55a2553
628520f
 
d84f4ed
074846f
628520f
d84f4ed
 
3042312
 
d84f4ed
 
 
 
55a2553
 
3042312
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
d84f4ed
 
 
 
628520f
 
 
d84f4ed
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
---
language:
- sv-SE
license: cc0-1.0
tags:
- automatic-speech-recognition
- generated_from_trainer
- hf-asr-leaderboard
- model_for_talk
- mozilla-foundation/common_voice_8_0
- robust-speech-event
- sv
datasets:
- mozilla-foundation/common_voice_8_0
model-index:
- name: XLS-R-300M - Swedish
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: mozilla-foundation/common_voice_8_0
      type: mozilla-foundation/common_voice_8_0
      args: sv-SE
    metrics:
    - name: Test WER
      type: wer
      value: 8.72
    - name: Test CER
      type: cer
      value: 3.05
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: speech-recognition-community-v2/eval_data
      type: speech-recognition-community-v2/eval_data
      args: sv
    metrics:
    - name: Validation WER
      type: wer
      value: 19.67
    - name: Validation CER
      type: cer
      value: 8.94
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: speech-recognition-community-v2/eval_data
      type: speech-recognition-community-v2/eval_data
      args: sv
    metrics:
    - name: Test WER
      type: wer
      value: 15.94
    - name: Test CER
      type: cer
      value: 7.71
widget:
- example_title: Swedish
  src: https://cdn-media.huggingface.co/speech_samples/cv_swedish_1.mp3
---

# 

This model is a fine-tuned version of [KBLab/wav2vec2-large-voxrex](https://huggingface.co/KBLab/wav2vec2-large-voxrex) on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - SV-SE dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1595
- Wer: 0.1200

## 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: 0.00025
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- 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: 0.25
- num_epochs: 100.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 3.0418        | 5.49  | 500  | 3.0176          | 1.0    |
| 1.1819        | 10.98 | 1000 | 0.2562          | 0.2168 |
| 1.0032        | 16.48 | 1500 | 0.1746          | 0.1546 |
| 0.9077        | 21.97 | 2000 | 0.1600          | 0.1339 |
| 0.8687        | 27.47 | 2500 | 0.1647          | 0.1378 |
| 0.8081        | 32.96 | 3000 | 0.1608          | 0.1353 |
| 0.7923        | 38.46 | 3500 | 0.1534          | 0.1277 |
| 0.7349        | 43.95 | 4000 | 0.1546          | 0.1303 |
| 0.7199        | 49.45 | 4500 | 0.1617          | 0.1277 |
| 0.7028        | 54.94 | 5000 | 0.1572          | 0.1287 |
| 0.6912        | 60.44 | 5500 | 0.1560          | 0.1249 |
| 0.6492        | 65.93 | 6000 | 0.1542          | 0.1260 |
| 0.6407        | 71.43 | 6500 | 0.1605          | 0.1240 |
| 0.6222        | 76.92 | 7000 | 0.1577          | 0.1219 |
| 0.6039        | 82.42 | 7500 | 0.1645          | 0.1249 |
| 0.5928        | 87.91 | 8000 | 0.1590          | 0.1214 |
| 0.6022        | 93.4  | 8500 | 0.1597          | 0.1213 |
| 0.5814        | 98.9  | 9000 | 0.1599          | 0.1199 |


### Framework versions

- Transformers 4.17.0.dev0
- Pytorch 1.10.2+cu102
- Datasets 1.18.3
- Tokenizers 0.11.0