---
tags:
- generated_from_trainer
datasets:
- afrispeech-200
metrics:
- wer
model-index:
- name: whisper-small-hi-2400_500_136
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: afrispeech-200
      type: afrispeech-200
      config: hausa
      split: train
      args: hausa
    metrics:
    - name: Wer
      type: wer
      value: 0.31118587047939444
---

<!-- 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-hi-2400_500_136

This model is a fine-tuned version of [saif-daoud/whisper-small-hi-2400_500_135](https://huggingface.co/saif-daoud/whisper-small-hi-2400_500_135) on the afrispeech-200 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7547
- Wer: 0.3112

## 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-07
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 400
- training_steps: 1362
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.7162        | 0.5   | 681  | 0.7551          | 0.3118 |
| 0.7109        | 1.5   | 1362 | 0.7547          | 0.3112 |


### Framework versions

- Transformers 4.28.0.dev0
- Pytorch 1.13.1+cu116
- Datasets 2.11.0
- Tokenizers 0.13.2