File size: 2,466 Bytes
e78bd9e
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
---
library_name: transformers
language:
- es
license: apache-2.0
base_model: openai/whisper-small
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- atc-co-spanish
metrics:
- wer
model-index:
- name: whisper-small-atc-co-spanish
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: atc-co-spanish
      type: atc-co-spanish
      args: 'config: es, split: train'
    metrics:
    - name: Wer
      type: wer
      value: 55.55555555555556
---

<!-- 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-atc-co-spanish

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the atc-co-spanish dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4043
- Wer: 55.5556

## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch    | Step | Validation Loss | Wer     |
|:-------------:|:--------:|:----:|:---------------:|:-------:|
| 1.5633        | 14.2857  | 50   | 1.7417          | 65.0794 |
| 0.2582        | 28.5714  | 100  | 1.3265          | 60.3175 |
| 0.0009        | 42.8571  | 150  | 1.2653          | 52.3810 |
| 0.0003        | 57.1429  | 200  | 1.3243          | 53.9683 |
| 0.0002        | 71.4286  | 250  | 1.3494          | 53.9683 |
| 0.0002        | 85.7143  | 300  | 1.3700          | 53.9683 |
| 0.0001        | 100.0    | 350  | 1.3853          | 55.5556 |
| 0.0001        | 114.2857 | 400  | 1.3966          | 55.5556 |
| 0.0001        | 128.5714 | 450  | 1.4019          | 55.5556 |
| 0.0001        | 142.8571 | 500  | 1.4043          | 55.5556 |


### Framework versions

- Transformers 4.45.1
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0