---
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- PolyAI/minds14
metrics:
- wer
model-index:
- name: whisper-tiny-en-US
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: PolyAI/minds14
      type: PolyAI/minds14
      config: en-AU
      split: train
      args: en-AU
    metrics:
    - name: Wer
      type: wer
      value: 0.20146619603584034
---

<!-- 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-tiny-en-US

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the PolyAI/minds14 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6756
- Wer Ortho: 0.2044
- Wer: 0.2015

## 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: 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
- training_steps: 4000

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer Ortho | Wer    |
|:-------------:|:------:|:----:|:---------------:|:---------:|:------:|
| 0.0007        | 17.86  | 500  | 0.5138          | 0.1941    | 0.1920 |
| 0.0002        | 35.71  | 1000 | 0.5565          | 0.1958    | 0.1936 |
| 0.0001        | 53.57  | 1500 | 0.5851          | 0.1981    | 0.1958 |
| 0.0001        | 71.43  | 2000 | 0.6081          | 0.2030    | 0.1998 |
| 0.0           | 89.29  | 2500 | 0.6273          | 0.2038    | 0.2009 |
| 0.0           | 107.14 | 3000 | 0.6441          | 0.2021    | 0.1996 |
| 0.0           | 125.0  | 3500 | 0.6602          | 0.2035    | 0.2007 |
| 0.0           | 142.86 | 4000 | 0.6756          | 0.2044    | 0.2015 |


### Framework versions

- Transformers 4.31.0.dev0
- Pytorch 1.12.1+cu116
- Datasets 2.4.0
- Tokenizers 0.12.1