File size: 3,668 Bytes
dc59786
2af2e4c
 
dc59786
 
2af2e4c
dc59786
 
2af2e4c
dc59786
 
659db69
dc59786
2af2e4c
dc59786
 
 
1c6c288
dc59786
2af2e4c
 
dc59786
 
 
 
1c6c288
298c45f
659db69
298c45f
 
 
 
 
 
 
 
 
 
dc09d0d
298c45f
659db69
1327cf4
 
 
 
dc09d0d
 
 
1327cf4
 
1c6c288
dc09d0d
659db69
cb7522c
 
659db69
dc59786
 
 
 
 
2af2e4c
dc59786
881d121
dc59786
1327cf4
 
 
dc59786
b6553d2
 
 
 
 
 
 
dc59786
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
---
language:
- be
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
base_model: openai/whisper-small
model-index:
- name: Whisper Small Belarusian
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: mozilla-foundation/common_voice_11_0 be
      type: mozilla-foundation/common_voice_11_0
      config: be
      split: validation
      args: be
    metrics:
    - type: wer
      value: 6.3671568743912
      name: WER
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: mozilla-foundation/common_voice_11_0 be
      type: mozilla-foundation/common_voice_11_0
      config: be
      split: test
      args: be
    metrics:
    - type: wer
      value: 6.79
      name: WER
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: google/fleurs
      type: google/fleurs
      config: be_by
      split: test
    metrics:
    - type: wer
      value: 43.615168811067036
      name: 'WER (reference column: transcription)'
    - type: wer
      value: 45.89674723962996
      name: 'WER (reference column: raw_transcription)'
---

<!-- 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. -->

# Whisper Small Belarusian

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the mozilla-foundation/common_voice_11_0 be dataset.
It achieves the following results on the evaluation set:
- Loss on validation: 0.0706
- WER on validation set: 6.3672
- WER on test set: 6.79

## Source code
All the source coude is located both in:
* [GitHub repository](https://github.com/yks72p/whisper-finetuning-be)
* and under `src` folder

Code in these 2 places should be the same. GitHub is used to make development and training of multiple models (small, base, etc.) easier.

## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 12000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer     |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.1907        | 0.08  | 1000  | 0.2546          | 25.4639 |
| 0.1482        | 0.17  | 2000  | 0.1641          | 17.1676 |
| 0.1175        | 0.25  | 3000  | 0.1454          | 15.5940 |
| 0.0958        | 0.33  | 4000  | 0.1261          | 13.2625 |
| 0.099         | 0.42  | 5000  | 0.1012          | 10.6143 |
| 0.028         | 1.05  | 6000  | 0.1053          | 9.8794  |
| 0.0473        | 1.13  | 7000  | 0.1029          | 10.3078 |
| 0.0391        | 1.21  | 8000  | 0.0924          | 9.2419  |
| 0.0423        | 1.3   | 9000  | 0.0797          | 7.9249  |
| 0.0604        | 1.38  | 10000 | 0.0688          | 7.0150  |
| 0.0121        | 2.01  | 11000 | 0.0696          | 6.4638  |
| 0.0155        | 2.1   | 12000 | 0.0706          | 6.3672  |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2