File size: 6,895 Bytes
246d6b7
50a2865
 
246d6b7
 
 
50a2865
1323a17
246d6b7
9925b3b
50a2865
 
246d6b7
 
50a2865
1323a17
50a2865
 
 
 
9925b3b
50a2865
 
1323a17
 
 
 
 
 
 
6445416
 
 
 
 
 
 
1323a17
 
 
 
 
 
246d6b7
 
 
 
 
 
 
f4543f8
246d6b7
 
 
 
6445416
246d6b7
6445416
246d6b7
6445416
246d6b7
6445416
246d6b7
6445416
246d6b7
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
---
language:
- br
license: apache-2.0
tags:
- generated_from_trainer
- robust-speech-event
- hf-asr-leaderboard
datasets:
- mozilla-foundation/common_voice_8_0
metrics:
- wer
model-index:
- name: wav2vec2-large-xls-r-300m-br-d2
  results:
  - task:
      type: automatic-speech-recognition
      name: Speech Recognition
    dataset:
      type: mozilla-foundation/common_voice_8_0
      name: Common Voice 8
      args: br
    metrics:
    - type: wer
      value: 0.49770598355954887
      name: Test WER
    - name: Test CER
      type: cer
      value: 0.18090500890299605
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Robust Speech Event - Dev Data
      type: speech-recognition-community-v2/dev_data
      args: br
    metrics:
    - name: Test WER
      type: wer
      value: NA
    - name: Test CER
      type: cer
      value: NA
---

<!-- 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. -->

# wav2vec2-large-xls-r-300m-br-d2

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - BR dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1257
- Wer: 0.4631

### Evaluation Commands

1. To evaluate on mozilla-foundation/common_voice_8_0 with test split

python eval.py --model_id DrishtiSharma/wav2vec2-large-xls-r-300m-br-d2 --dataset mozilla-foundation/common_voice_8_0 --config br --split test --log_outputs

2. To evaluate on speech-recognition-community-v2/dev_data

Breton language isn't available in speech-recognition-community-v2/dev_data

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.00034
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 750
- num_epochs: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 14.0379       | 0.68  | 100  | 5.6808          | 1.0    |
| 3.9145        | 1.35  | 200  | 3.1970          | 1.0    |
| 3.0293        | 2.03  | 300  | 2.9513          | 1.0    |
| 2.0927        | 2.7   | 400  | 1.4545          | 0.8887 |
| 1.1556        | 3.38  | 500  | 1.0966          | 0.7564 |
| 0.9628        | 4.05  | 600  | 0.9808          | 0.7364 |
| 0.7869        | 4.73  | 700  | 1.0488          | 0.7355 |
| 0.703         | 5.41  | 800  | 0.9500          | 0.6881 |
| 0.6657        | 6.08  | 900  | 0.9309          | 0.6259 |
| 0.5663        | 6.76  | 1000 | 0.9133          | 0.6357 |
| 0.496         | 7.43  | 1100 | 0.9890          | 0.6028 |
| 0.4748        | 8.11  | 1200 | 0.9469          | 0.5894 |
| 0.4135        | 8.78  | 1300 | 0.9270          | 0.6045 |
| 0.3579        | 9.46  | 1400 | 0.8818          | 0.5708 |
| 0.353         | 10.14 | 1500 | 0.9244          | 0.5781 |
| 0.334         | 10.81 | 1600 | 0.9009          | 0.5638 |
| 0.2917        | 11.49 | 1700 | 1.0132          | 0.5828 |
| 0.29          | 12.16 | 1800 | 0.9696          | 0.5668 |
| 0.2691        | 12.84 | 1900 | 0.9811          | 0.5455 |
| 0.25          | 13.51 | 2000 | 0.9951          | 0.5624 |
| 0.2467        | 14.19 | 2100 | 0.9653          | 0.5573 |
| 0.2242        | 14.86 | 2200 | 0.9714          | 0.5378 |
| 0.2066        | 15.54 | 2300 | 0.9829          | 0.5394 |
| 0.2075        | 16.22 | 2400 | 1.0547          | 0.5520 |
| 0.1923        | 16.89 | 2500 | 1.0014          | 0.5397 |
| 0.1919        | 17.57 | 2600 | 0.9978          | 0.5477 |
| 0.1908        | 18.24 | 2700 | 1.1064          | 0.5397 |
| 0.157         | 18.92 | 2800 | 1.0629          | 0.5238 |
| 0.159         | 19.59 | 2900 | 1.0642          | 0.5321 |
| 0.1652        | 20.27 | 3000 | 1.0207          | 0.5328 |
| 0.141         | 20.95 | 3100 | 0.9948          | 0.5312 |
| 0.1417        | 21.62 | 3200 | 1.0338          | 0.5328 |
| 0.1514        | 22.3  | 3300 | 1.0513          | 0.5313 |
| 0.1365        | 22.97 | 3400 | 1.0357          | 0.5291 |
| 0.1319        | 23.65 | 3500 | 1.0587          | 0.5167 |
| 0.1298        | 24.32 | 3600 | 1.0636          | 0.5236 |
| 0.1245        | 25.0  | 3700 | 1.1367          | 0.5280 |
| 0.1114        | 25.68 | 3800 | 1.0633          | 0.5200 |
| 0.1088        | 26.35 | 3900 | 1.0495          | 0.5210 |
| 0.1175        | 27.03 | 4000 | 1.0897          | 0.5095 |
| 0.1043        | 27.7  | 4100 | 1.0580          | 0.5309 |
| 0.0951        | 28.38 | 4200 | 1.0448          | 0.5067 |
| 0.1011        | 29.05 | 4300 | 1.0665          | 0.5137 |
| 0.0889        | 29.73 | 4400 | 1.0579          | 0.5026 |
| 0.0833        | 30.41 | 4500 | 1.0740          | 0.5037 |
| 0.0889        | 31.08 | 4600 | 1.0933          | 0.5083 |
| 0.0784        | 31.76 | 4700 | 1.0715          | 0.5089 |
| 0.0767        | 32.43 | 4800 | 1.0658          | 0.5049 |
| 0.0769        | 33.11 | 4900 | 1.1118          | 0.4979 |
| 0.0722        | 33.78 | 5000 | 1.1413          | 0.4986 |
| 0.0709        | 34.46 | 5100 | 1.0706          | 0.4885 |
| 0.0664        | 35.14 | 5200 | 1.1217          | 0.4884 |
| 0.0648        | 35.81 | 5300 | 1.1298          | 0.4941 |
| 0.0657        | 36.49 | 5400 | 1.1330          | 0.4920 |
| 0.0582        | 37.16 | 5500 | 1.0598          | 0.4835 |
| 0.0602        | 37.84 | 5600 | 1.1097          | 0.4943 |
| 0.0598        | 38.51 | 5700 | 1.0976          | 0.4876 |
| 0.0547        | 39.19 | 5800 | 1.0734          | 0.4825 |
| 0.0561        | 39.86 | 5900 | 1.0926          | 0.4850 |
| 0.0516        | 40.54 | 6000 | 1.1579          | 0.4751 |
| 0.0478        | 41.22 | 6100 | 1.1384          | 0.4706 |
| 0.0396        | 41.89 | 6200 | 1.1462          | 0.4739 |
| 0.0472        | 42.57 | 6300 | 1.1277          | 0.4732 |
| 0.0447        | 43.24 | 6400 | 1.1517          | 0.4752 |
| 0.0423        | 43.92 | 6500 | 1.1219          | 0.4784 |
| 0.0426        | 44.59 | 6600 | 1.1311          | 0.4724 |
| 0.0391        | 45.27 | 6700 | 1.1135          | 0.4692 |
| 0.0362        | 45.95 | 6800 | 1.0878          | 0.4645 |
| 0.0329        | 46.62 | 6900 | 1.1137          | 0.4668 |
| 0.0356        | 47.3  | 7000 | 1.1233          | 0.4687 |
| 0.0328        | 47.97 | 7100 | 1.1238          | 0.4653 |
| 0.0323        | 48.65 | 7200 | 1.1307          | 0.4646 |
| 0.0325        | 49.32 | 7300 | 1.1242          | 0.4645 |
| 0.03          | 50.0  | 7400 | 1.1257          | 0.4631 |


### Framework versions

- Transformers 4.16.2
- Pytorch 1.10.0+cu111
- Datasets 1.18.3
- Tokenizers 0.11.0