---
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- PolyAI/minds14
metrics:
- wer
model-index:
- name: whisper-small-af-ZA
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: PolyAI/minds14
      type: PolyAI/minds14
      config: af_za
      split: train+validation
      args: af_za
    metrics:
    - name: Wer
      type: wer
      value: 0.02925243770314193
---

<!-- 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-tiny](https://huggingface.co/openai/whisper-tiny) on the PolyAI/minds14 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0415
- Wer Ortho: 0.0529
- Wer: 0.0293

## 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: 700
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|
| 0.0054        | 1.45  | 100  | 0.0312          | 0.0449    | 0.0228 |
| 0.0025        | 2.9   | 200  | 0.0345          | 0.0456    | 0.0231 |
| 0.0021        | 4.35  | 300  | 0.0325          | 0.0445    | 0.0206 |
| 0.0018        | 5.8   | 400  | 0.0325          | 0.0449    | 0.0202 |
| 0.0033        | 7.25  | 500  | 0.0390          | 0.0905    | 0.0654 |
| 0.0043        | 8.7   | 600  | 0.0415          | 0.0577    | 0.0347 |
| 0.0026        | 10.14 | 700  | 0.0415          | 0.0529    | 0.0293 |


### Framework versions

- Transformers 4.38.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1