README.md

---
language:
- en
license: apache-2.0
base_model: openai/whisper-base.en
tags:
- nyansapo_ai-asr-leaderboard
- generated_from_trainer
datasets:
- NyansapoAI/azure-dataset
metrics:
- wer
model-index:
- name: whisper-base-bungoma.en
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Azure-dataset
      type: NyansapoAI/azure-dataset
      args: 'split: test'
    metrics:
    - name: Wer
      type: wer
      value: 25.28041415012942
---

<!-- 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-base-bungoma.en

This model is a fine-tuned version of [openai/whisper-base.en](https://huggingface.co./openai/whisper-base.en) on the Azure-dataset dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0636
- Wer: 25.2804

## 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: 250
- training_steps: 1000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.7399        | 1.38  | 250  | 0.2390          | 29.3356 |
| 0.2829        | 2.76  | 500  | 0.0774          | 21.8292 |
| 0.1573        | 4.14  | 750  | 0.0921          | 22.8645 |
| 0.1373        | 5.52  | 1000 | 0.0636          | 25.2804 |


### Framework versions

- Transformers 4.39.1
- Pytorch 2.2.1
- Datasets 2.18.0
- Tokenizers 0.15.2