Hugging Face's logo

WasuratS
/
whisper-small-da

Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Danish
whisper
Generated from Trainer
Eval Results
Inference Endpoints
Model card Files Metrics Community
1
whisper-small-da
File size: 3,206 Bytes 
876ba12
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
eef969c
876ba12
 
 
 
eef969c
876ba12
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1eb8bf9
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
876ba12
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
 
---
language:
- da
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
metrics:
- wer
model-index:
- name: Whisper Small Da - WasuratS
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 13
      type: mozilla-foundation/common_voice_13_0
      config: da
      split: test
      args: da
    metrics:
    - name: Wer
      type: wer
      value: 23.39882224190943
---

<!-- 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 Da - WasuratS

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 13 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6393
- Wer Ortho: 29.0926
- Wer: 23.3988

## Model description

[openai/whisper-small](https://huggingface.co/openai/whisper-small)


## Training and evaluation data

[mozilla-foundation/common_voice_13_0](https://huggingface.co/datasets/mozilla-foundation/common_voice_13_0)

## 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
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 4000
- mixed_precision_training: Native AMP

``` %python
from transformers import Seq2SeqTrainingArguments

training_args = Seq2SeqTrainingArguments(
    output_dir="./whisper-small-da", 
    per_device_train_batch_size=16,
    gradient_accumulation_steps=1,  
    learning_rate=1e-5,
    lr_scheduler_type="linear",
    warmup_steps=50,
    max_steps=4000,  
    gradient_checkpointing=True,
    fp16=True,
    fp16_full_eval=True,
    evaluation_strategy="steps",
    per_device_eval_batch_size=16,
    predict_with_generate=True,
    generation_max_length=225,
    save_steps=500,
    eval_steps=500,
    logging_steps=25,
    report_to=["tensorboard"],
    load_best_model_at_end=True,
    metric_for_best_model="wer",
    greater_is_better=False,
    push_to_hub=True,
)
```

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------:|
| 0.218         | 1.61  | 500  | 0.4724          | 30.2496   | 24.7069 |
| 0.0628        | 3.22  | 1000 | 0.4825          | 28.8946   | 23.3154 |
| 0.0289        | 4.82  | 1500 | 0.5311          | 29.3376   | 23.4666 |
| 0.0078        | 6.43  | 2000 | 0.5740          | 29.4627   | 23.6542 |
| 0.0032        | 8.04  | 2500 | 0.6070          | 29.0613   | 23.2790 |
| 0.0025        | 9.65  | 3000 | 0.6274          | 29.1187   | 23.4770 |
| 0.0012        | 11.25 | 3500 | 0.6335          | 29.0978   | 23.3623 |
| 0.0011        | 12.86 | 4000 | 0.6393          | 29.0926   | 23.3988 |


### Framework versions

- Transformers 4.29.2
- Pytorch 1.13.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3