---
language:
- so
license: apache-2.0
base_model: steja/whisper-small-somali
tags:
- generated_from_trainer
datasets:
- google/fleurs
metrics:
- wer
model-index:
- name: Whisper Small So - kheder yusuf
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: google/fleurs
      type: google/fleurs
      config: so_so
      split: None
      args: 'config: so_so, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 21.001297668382936
---

<!-- 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 So - kheder yusuf

This model is a fine-tuned version of [steja/whisper-small-somali](https://huggingface.co/steja/whisper-small-somali) on the google/fleurs dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2840
- Wer: 21.0013

## 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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.257         | 3.47  | 1000 | 0.2840          | 21.0013 |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.15.2