---
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-US
      split: train[450:]
      args: en-US
    metrics:
    - name: Wer
      type: wer
      value: 0.3884297520661157
---

<!-- 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: 0.9670
- Wer Ortho: 0.3825
- Wer: 0.3884

## 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: 32
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 4000

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer Ortho | Wer    |
|:-------------:|:------:|:----:|:---------------:|:---------:|:------:|
| 0.1121        | 35.71  | 500  | 0.7395          | 0.3646    | 0.3660 |
| 0.0526        | 71.43  | 1000 | 0.8020          | 0.3615    | 0.3619 |
| 0.0263        | 107.14 | 1500 | 0.8685          | 0.3769    | 0.3790 |
| 0.0162        | 142.86 | 2000 | 0.9158          | 0.3782    | 0.3825 |
| 0.0152        | 178.57 | 2500 | 0.9300          | 0.3800    | 0.3831 |
| 0.0138        | 214.29 | 3000 | 0.9595          | 0.3905    | 0.3926 |
| 0.0127        | 250.0  | 3500 | 0.9687          | 0.3899    | 0.3949 |
| 0.0119        | 285.71 | 4000 | 0.9670          | 0.3825    | 0.3884 |


### Framework versions

- Transformers 4.34.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3