File size: 1,871 Bytes
b73a07a
53b4b4e
 
b73a07a
 
53b4b4e
b73a07a
 
53b4b4e
ccbdbd9
 
b73a07a
53b4b4e
ccbdbd9
 
 
 
 
53b4b4e
 
ccbdbd9
 
 
 
 
 
 
b73a07a
 
 
 
 
53b4b4e
b73a07a
53b4b4e
ccbdbd9
 
 
b73a07a
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
ccbdbd9
 
b73a07a
 
 
 
ccbdbd9
b73a07a
 
 
 
ccbdbd9
 
 
b73a07a
 
 
 
 
 
 
 
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
---
language:
- vi
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Medium Vietnamese
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: mozilla-foundation/common_voice_11_0 vi
      type: mozilla-foundation/common_voice_11_0
      config: vi
      split: test
      args: vi
    metrics:
    - name: Wer
      type: wer
      value: 20.04825619653433
---

<!-- 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 Medium Vietnamese

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the mozilla-foundation/common_voice_11_0 vi dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5422
- Wer: 20.0483

## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.0241        | 4.01  | 1000 | 0.5422          | 20.0483 |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.11.0+cu102
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2