---
language:
- ha
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- Seon25/common_voice_16_0_
metrics:
- wer
model-index:
- name: Whisper Small Ha adam_w v4 - Eldad Akhaumere
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 16.0
      type: Seon25/common_voice_16_0_
      config: ha
      split: None
      args: 'config: ha, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 78.86568308105001
---

<!-- 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 Ha adam_w v4 - Eldad Akhaumere

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 16.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2150
- Wer Ortho: 81.0547
- Wer: 78.8657

## 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: 5e-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: 50
- num_epochs: 15.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer Ortho | Wer     |
|:-------------:|:-------:|:----:|:---------------:|:---------:|:-------:|
| 0.0995        | 3.1847  | 500  | 1.7910          | 90.4297   | 88.1778 |
| 0.0468        | 6.3694  | 1000 | 1.9594          | 82.8320   | 81.1458 |
| 0.0394        | 9.5541  | 1500 | 2.0776          | 89.8438   | 87.7563 |
| 0.0314        | 12.7389 | 2000 | 2.2150          | 81.0547   | 78.8657 |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1