---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- PolyAI/minds14
metrics:
- wer
model-index:
- name: whisper-tiny-en
  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: 0.3252656434474616
---

<!-- 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

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: 0.8008
- Wer Ortho: 0.3523
- Wer: 0.3253

## 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: 8
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- 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: 500

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|
| 1.593         | 1.79  | 50   | 1.0054          | 0.5003    | 0.4185 |
| 0.3982        | 3.57  | 100  | 0.7250          | 0.4121    | 0.3554 |
| 0.2075        | 5.36  | 150  | 0.6898          | 0.4226    | 0.3518 |
| 0.0957        | 7.14  | 200  | 0.6909          | 0.4028    | 0.3371 |
| 0.0412        | 8.93  | 250  | 0.7296          | 0.3695    | 0.3300 |
| 0.0186        | 10.71 | 300  | 0.7522          | 0.3627    | 0.3270 |
| 0.008         | 12.5  | 350  | 0.7703          | 0.3584    | 0.3288 |
| 0.0049        | 14.29 | 400  | 0.7756          | 0.3553    | 0.3294 |
| 0.0032        | 16.07 | 450  | 0.7889          | 0.3516    | 0.3235 |
| 0.0023        | 17.86 | 500  | 0.8008          | 0.3523    | 0.3253 |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3