File size: 2,178 Bytes
dc7e7a3
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
---
library_name: transformers
language:
- ha
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- Seon25/common_voice_16_0_
metrics:
- wer
model-index:
- name: Whisper Small Ha - Eldad Akhaumere
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 16.0
      type: Seon25/common_voice_16_0_
      config: ha
      split: None
      args: 'config: ha, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 108.10546875
---

<!-- 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 Ha - Eldad Akhaumere

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 16.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 4.9575
- Wer Ortho: 110.3468
- Wer: 108.1055

## 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: 0.0005
- 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: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- num_epochs: 13.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer Ortho | Wer      |
|:-------------:|:-------:|:----:|:---------------:|:---------:|:--------:|
| 1.5785        | 3.1847  | 500  | 3.8839          | 99.5593   | 99.8438  |
| 1.1623        | 6.3694  | 1000 | 4.4847          | 97.7582   | 98.0078  |
| 0.9893        | 9.5541  | 1500 | 4.7922          | 108.7373  | 107.6172 |
| 0.8816        | 12.7389 | 2000 | 4.9575          | 110.3468  | 108.1055 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1