File size: 2,207 Bytes
61f98b1
3a07c93
 
61f98b1
 
3a07c93
da7645d
61f98b1
 
3a07c93
61f98b1
 
9e2b2a8
61f98b1
3a07c93
61f98b1
 
 
9e2b2a8
61f98b1
c598651
3a07c93
6bb65c2
9e2b2a8
61f98b1
9e2b2a8
61f98b1
9e2b2a8
61f98b1
 
 
 
 
3a07c93
61f98b1
3a07c93
61f98b1
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
---
language:
- cs
license: apache-2.0
tags:
- whisper-event
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
base_model: openai/whisper-large
model-index:
- name: Whisper Large Czech CV11
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: mozilla-foundation/common_voice_11_0
      type: mozilla-foundation/common_voice_11_0
      config: cs
      split: test
    metrics:
    - type: wer
      value: 10.82782615098577
      name: Wer
---

<!-- 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 Large Czech CV11

This model is a fine-tuned version of [openai/whisper-large](https://huggingface.co/openai/whisper-large) on the mozilla-foundation/common_voice_11_0 cs dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2528
- Wer: 10.8278

## 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: 8
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.0058        | 4.02  | 1000 | 0.2097          | 11.9563 |
| 0.0012        | 8.04  | 2000 | 0.2210          | 10.9751 |
| 0.001         | 13.01 | 3000 | 0.2405          | 11.3488 |
| 0.0002        | 17.02 | 4000 | 0.2467          | 10.8794 |
| 0.0001        | 21.04 | 5000 | 0.2528          | 10.8278 |


### Framework versions

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