File size: 1,966 Bytes
97e9230
 
 
799f02d
97e9230
 
 
 
 
 
 
 
 
799f02d
97e9230
 
 
 
 
 
 
 
 
 
 
af6d765
97e9230
 
 
 
 
799f02d
97e9230
 
 
af6d765
 
97e9230
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
2a8f585
 
97e9230
54fe194
 
97e9230
54fe194
af6d765
97e9230
 
 
 
4d128b5
 
af6d765
 
97e9230
 
 
 
 
2a8f585
97e9230
2a8f585
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
---
library_name: transformers
language:
- wo
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- IndabaxSenegal/asr-wolof-dataset
metrics:
- wer
model-index:
- name: Whisper small Wolof
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: ASR Wolof Dataset
      type: IndabaxSenegal/asr-wolof-dataset
      args: 'config: wo, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 51.21087255114581
---

<!-- 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 Wolof

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the ASR Wolof Dataset dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1760
- Wer: 51.2109

## 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: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- num_epochs: 2
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.0367        | 1.0   | 450  | 1.1685          | 50.4807 |
| 0.0191        | 2.0   | 900  | 1.1760          | 51.2109 |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.4.0
- Datasets 3.1.0
- Tokenizers 0.20.0