---
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- google/fleurs
metrics:
- wer
model-index:
- name: whisper-small-af-ZA
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: google/fleurs
      type: google/fleurs
      config: af_za
      split: train+validation
      args: af_za
    metrics:
    - name: Wer
      type: wer
      value: 0.36644093303235514
---

<!-- 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-af-ZA

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the google/fleurs dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5728
- Wer: 0.3664
- Wer Ortho: 0.3943

## 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: 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: 5
- training_steps: 2000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    | Wer Ortho |
|:-------------:|:-----:|:----:|:---------------:|:------:|:---------:|
| 0.7731        | 1.45  | 100  | 0.7280          | 0.3740 | 0.3863    |
| 0.2103        | 2.9   | 200  | 0.5116          | 0.3661 | 0.3859    |
| 0.0633        | 4.35  | 300  | 0.4967          | 0.2810 | 0.3008    |
| 0.0249        | 5.8   | 400  | 0.5003          | 0.3299 | 0.3477    |
| 0.0143        | 7.25  | 500  | 0.5191          | 0.3510 | 0.3660    |
| 0.0053        | 8.7   | 600  | 0.5149          | 0.3070 | 0.3221    |
| 0.0035        | 10.14 | 700  | 0.5345          | 0.3266 | 0.3443    |
| 0.0027        | 11.59 | 800  | 0.5339          | 0.3175 | 0.3344    |
| 0.0026        | 13.04 | 900  | 0.5435          | 0.3134 | 0.3328    |
| 0.0037        | 14.49 | 1000 | 0.5346          | 0.2506 | 0.2714    |
| 0.0045        | 15.94 | 1100 | 0.5438          | 0.3220 | 0.3389    |
| 0.0028        | 17.39 | 1200 | 0.5588          | 0.2551 | 0.2740    |
| 0.0036        | 18.84 | 1300 | 0.5466          | 0.2728 | 0.2702    |
| 0.0035        | 20.29 | 1400 | 0.5364          | 0.3119 | 0.3332    |
| 0.0056        | 21.74 | 1500 | 0.5608          | 0.2506 | 0.2721    |
| 0.0037        | 23.19 | 1600 | 0.5443          | 0.2833 | 0.3027    |
| 0.0035        | 24.64 | 1700 | 0.5466          | 0.3631 | 0.3866    |
| 0.0024        | 26.09 | 1800 | 0.5628          | 0.3198 | 0.3416    |
| 0.0036        | 27.54 | 1900 | 0.5495          | 0.2946 | 0.3122    |
| 0.0016        | 28.99 | 2000 | 0.5728          | 0.3664 | 0.3943    |


### Framework versions

- Transformers 4.31.0.dev0
- Pytorch 1.12.1+cu116
- Datasets 2.4.0
- Tokenizers 0.12.1