---
language:
- en
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- nyansapo_ai-asr-leaderboard
- generated_from_trainer
datasets:
- NyansapoAI/azure-dataset
metrics:
- wer
model-index:
- name: whisper-base.en
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Azure-dataset
      type: NyansapoAI/azure-dataset
      config: default
      split: test
      args: 'split: test'
    metrics:
    - name: Wer
      type: wer
      value: 8.585858585858585
---

<!-- 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.en

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Azure-dataset dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0237
- Wer: 8.5859

## 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: 2500

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.1945        | 3.11  | 500  | 0.0626          | 18.0808 |
| 0.0627        | 6.21  | 1000 | 0.0292          | 10.5051 |
| 0.0419        | 9.32  | 1500 | 0.0242          | 9.0909  |
| 0.0419        | 12.42 | 2000 | 0.0242          | 8.8889  |
| 0.0502        | 15.53 | 2500 | 0.0237          | 8.5859  |


### Framework versions

- Transformers 4.33.0.dev0
- Pytorch 2.0.1
- Datasets 2.14.4
- Tokenizers 0.13.3