File size: 10,428 Bytes
99cf47b
1cd05c0
 
99cf47b
1cd05c0
 
99cf47b
 
 
 
 
 
 
 
 
 
 
 
1cd05c0
99cf47b
 
 
1cd05c0
99cf47b
 
 
1cd05c0
99cf47b
 
 
 
 
 
 
1cd05c0
99cf47b
 
1cd05c0
99cf47b
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
---
language:
- ur
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_11_0
- generated_from_trainer
datasets:
- common_voice_11_0
metrics:
- wer
model-index:
- name: wavlm-common_voice-ur
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: MOZILLA-FOUNDATION/COMMON_VOICE_11_0 - UR
      type: common_voice_11_0
      config: ur
      split: test
      args: 'Config: ur, Training split: train+validation, Eval split: test'
    metrics:
    - name: Wer
      type: wer
      value: 0.37805822235986375
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# wavlm-common_voice-ur

This model is a fine-tuned version of [microsoft/wavlm-large](https://huggingface.co/microsoft/wavlm-large) on the MOZILLA-FOUNDATION/COMMON_VOICE_11_0 - UR dataset.
It achieves the following results on the evaluation set:
- Loss: inf
- Wer: 0.3781

## 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: 0.0003
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 8
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 15.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 4.9073        | 0.11  | 100   | inf             | 1.0    |
| 3.3187        | 0.22  | 200   | inf             | 1.0    |
| 2.9683        | 0.32  | 300   | inf             | 0.9991 |
| 2.454         | 0.43  | 400   | inf             | 0.9915 |
| 1.1169        | 0.54  | 500   | inf             | 0.7906 |
| 1.5943        | 0.65  | 600   | inf             | 0.7260 |
| 0.9991        | 0.75  | 700   | inf             | 0.7305 |
| 1.0608        | 0.86  | 800   | inf             | 0.6655 |
| 1.4739        | 0.97  | 900   | inf             | 0.6120 |
| 0.8682        | 1.08  | 1000  | inf             | 0.6087 |
| 0.8025        | 1.18  | 1100  | inf             | 0.5991 |
| 0.8468        | 1.29  | 1200  | inf             | 0.5605 |
| 0.5896        | 1.4   | 1300  | inf             | 0.5550 |
| 0.6304        | 1.51  | 1400  | inf             | 0.5441 |
| 0.6533        | 1.61  | 1500  | inf             | 0.5297 |
| 0.7636        | 1.72  | 1600  | inf             | 0.5210 |
| 0.5155        | 1.83  | 1700  | inf             | 0.5331 |
| 0.6266        | 1.94  | 1800  | inf             | 0.5182 |
| 0.4286        | 2.05  | 1900  | inf             | 0.4956 |
| 0.527         | 2.15  | 2000  | inf             | 0.4935 |
| 0.4919        | 2.26  | 2100  | inf             | 0.4933 |
| 0.3977        | 2.37  | 2200  | inf             | 0.5015 |
| 0.5349        | 2.48  | 2300  | inf             | 0.4942 |
| 0.5066        | 2.58  | 2400  | inf             | 0.4684 |
| 0.6734        | 2.69  | 2500  | inf             | 0.4870 |
| 0.5411        | 2.8   | 2600  | inf             | 0.4919 |
| 0.3451        | 2.91  | 2700  | inf             | 0.4607 |
| 0.3913        | 3.01  | 2800  | inf             | 0.4558 |
| 0.3046        | 3.12  | 2900  | inf             | 0.4685 |
| 0.2954        | 3.23  | 3000  | inf             | 0.4638 |
| 0.5469        | 3.34  | 3100  | inf             | 0.4495 |
| 0.2334        | 3.44  | 3200  | inf             | 0.4547 |
| 0.3119        | 3.55  | 3300  | inf             | 0.4619 |
| 0.6393        | 3.66  | 3400  | inf             | 0.4541 |
| 0.4133        | 3.77  | 3500  | inf             | 0.4456 |
| 0.4946        | 3.88  | 3600  | inf             | 0.4369 |
| 0.3484        | 3.98  | 3700  | inf             | 0.4335 |
| 0.3996        | 4.09  | 3800  | inf             | 0.4717 |
| 0.2754        | 4.2   | 3900  | inf             | 0.4414 |
| 0.3141        | 4.31  | 4000  | inf             | 0.4390 |
| 0.2231        | 4.41  | 4100  | inf             | 0.4353 |
| 0.2673        | 4.52  | 4200  | inf             | 0.4410 |
| 0.2911        | 4.63  | 4300  | inf             | 0.4337 |
| 0.3643        | 4.74  | 4400  | inf             | 0.4362 |
| 0.2706        | 4.84  | 4500  | inf             | 0.4359 |
| 0.2464        | 4.95  | 4600  | inf             | 0.4249 |
| 0.1453        | 5.06  | 4700  | inf             | 0.4293 |
| 0.2619        | 5.17  | 4800  | inf             | 0.4201 |
| 0.1888        | 5.27  | 4900  | inf             | 0.4222 |
| 0.2571        | 5.38  | 5000  | inf             | 0.4333 |
| 0.1653        | 5.49  | 5100  | inf             | 0.4192 |
| 0.2102        | 5.6   | 5200  | inf             | 0.4232 |
| 0.1456        | 5.71  | 5300  | inf             | 0.4198 |
| 0.3314        | 5.81  | 5400  | inf             | 0.4169 |
| 0.1703        | 5.92  | 5500  | inf             | 0.4118 |
| 0.1546        | 6.03  | 5600  | inf             | 0.4147 |
| 0.2065        | 6.14  | 5700  | inf             | 0.4291 |
| 0.1792        | 6.24  | 5800  | inf             | 0.4175 |
| 0.2433        | 6.35  | 5900  | inf             | 0.4157 |
| 0.352         | 6.46  | 6000  | inf             | 0.4083 |
| 0.2406        | 6.57  | 6100  | inf             | 0.4341 |
| 0.2397        | 6.67  | 6200  | inf             | 0.4185 |
| 0.2145        | 6.78  | 6300  | inf             | 0.4147 |
| 0.1733        | 6.89  | 6400  | inf             | 0.4150 |
| 0.1867        | 7.0   | 6500  | inf             | 0.4154 |
| 0.612         | 7.1   | 6600  | inf             | 0.4159 |
| 0.1413        | 7.21  | 6700  | inf             | 0.4162 |
| 0.2074        | 7.32  | 6800  | inf             | 0.4146 |
| 0.1362        | 7.43  | 6900  | inf             | 0.4087 |
| 0.2971        | 7.53  | 7000  | inf             | 0.4061 |
| 0.1443        | 7.64  | 7100  | inf             | 0.4132 |
| 0.3066        | 7.75  | 7200  | inf             | 0.4059 |
| 0.2163        | 7.86  | 7300  | inf             | 0.4026 |
| 0.1251        | 7.97  | 7400  | inf             | 0.4022 |
| 0.154         | 8.07  | 7500  | inf             | 0.3980 |
| 0.1809        | 8.18  | 7600  | inf             | 0.4030 |
| 0.0985        | 8.29  | 7700  | inf             | 0.3992 |
| 0.1672        | 8.4   | 7800  | inf             | 0.4049 |
| 0.1508        | 8.5   | 7900  | inf             | 0.3985 |
| 0.1893        | 8.61  | 8000  | inf             | 0.3999 |
| 0.1045        | 8.72  | 8100  | inf             | 0.4014 |
| 0.2569        | 8.83  | 8200  | inf             | 0.3976 |
| 0.2654        | 8.93  | 8300  | inf             | 0.4021 |
| 0.0641        | 9.04  | 8400  | inf             | 0.3964 |
| 0.1145        | 9.15  | 8500  | inf             | 0.3995 |
| 0.1808        | 9.26  | 8600  | inf             | 0.3960 |
| 0.0766        | 9.36  | 8700  | inf             | 0.3938 |
| 0.1537        | 9.47  | 8800  | inf             | 0.3909 |
| 0.2864        | 9.58  | 8900  | inf             | 0.4028 |
| 0.1372        | 9.69  | 9000  | inf             | 0.3970 |
| 0.06          | 9.8   | 9100  | inf             | 0.3911 |
| 0.0831        | 9.9   | 9200  | inf             | 0.3954 |
| 0.1469        | 10.01 | 9300  | inf             | 0.3952 |
| 0.0683        | 10.12 | 9400  | inf             | 0.3899 |
| 0.0694        | 10.23 | 9500  | inf             | 0.3918 |
| 0.0919        | 10.33 | 9600  | inf             | 0.3895 |
| 0.1842        | 10.44 | 9700  | inf             | 0.3945 |
| 0.0581        | 10.55 | 9800  | inf             | 0.3979 |
| 0.1397        | 10.66 | 9900  | inf             | 0.3911 |
| 0.0657        | 10.76 | 10000 | inf             | 0.3886 |
| 0.1316        | 10.87 | 10100 | inf             | 0.3877 |
| 0.1434        | 10.98 | 10200 | inf             | 0.3858 |
| 0.05          | 11.09 | 10300 | inf             | 0.3842 |
| 0.0565        | 11.19 | 10400 | inf             | 0.3873 |
| 0.1696        | 11.3  | 10500 | inf             | 0.3873 |
| 0.0819        | 11.41 | 10600 | inf             | 0.3901 |
| 0.0631        | 11.52 | 10700 | inf             | 0.3927 |
| 0.1276        | 11.63 | 10800 | inf             | 0.3868 |
| 0.1002        | 11.73 | 10900 | inf             | 0.3848 |
| 0.081         | 11.84 | 11000 | inf             | 0.3873 |
| 0.1745        | 11.95 | 11100 | inf             | 0.3895 |
| 0.097         | 12.06 | 11200 | inf             | 0.4021 |
| 0.0875        | 12.16 | 11300 | inf             | 0.3876 |
| 0.027         | 12.27 | 11400 | inf             | 0.3873 |
| 0.0859        | 12.38 | 11500 | inf             | 0.3863 |
| 0.1192        | 12.49 | 11600 | inf             | 0.3799 |
| 0.1055        | 12.59 | 11700 | inf             | 0.3795 |
| 0.0603        | 12.7  | 11800 | inf             | 0.3785 |
| 0.111         | 12.81 | 11900 | inf             | 0.3783 |
| 0.0313        | 12.92 | 12000 | inf             | 0.3800 |
| 0.0241        | 13.02 | 12100 | inf             | 0.3796 |
| 0.1072        | 13.13 | 12200 | inf             | 0.3803 |
| 0.1758        | 13.24 | 12300 | inf             | 0.3809 |
| 0.1334        | 13.35 | 12400 | inf             | 0.3794 |
| 0.1372        | 13.46 | 12500 | inf             | 0.3798 |
| 0.1919        | 13.56 | 12600 | inf             | 0.3791 |
| 0.1753        | 13.67 | 12700 | inf             | 0.3781 |
| 0.294         | 13.78 | 12800 | inf             | 0.3788 |
| 0.3132        | 13.89 | 12900 | inf             | 0.3786 |
| 0.0486        | 13.99 | 13000 | inf             | 0.3778 |
| 0.1199        | 14.1  | 13100 | inf             | 0.3777 |
| 0.0381        | 14.21 | 13200 | inf             | 0.3808 |
| 0.0875        | 14.32 | 13300 | inf             | 0.3795 |
| 0.0122        | 14.42 | 13400 | inf             | 0.3797 |
| 0.1417        | 14.53 | 13500 | inf             | 0.3780 |
| 0.1754        | 14.64 | 13600 | inf             | 0.3788 |
| 0.0426        | 14.75 | 13700 | inf             | 0.3780 |
| 0.0309        | 14.85 | 13800 | inf             | 0.3787 |
| 0.1447        | 14.96 | 13900 | inf             | 0.3796 |


### Framework versions

- Transformers 4.27.0.dev0
- Pytorch 1.13.1
- Datasets 2.8.0
- Tokenizers 0.13.2