---
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
      args: en-US
    metrics:
    - name: Wer
      type: wer
      value: 34.120425029515935
---

<!-- 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: 0.6900
- Wer Ortho: 35.9038
- Wer: 34.1204

## 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: linear
- lr_scheduler_warmup_steps: 150
- training_steps: 500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------:|
| 3.5847        | 1.79  | 50   | 2.5796          | 52.3751   | 40.2597 |
| 0.6921        | 3.57  | 100  | 0.6884          | 42.5663   | 37.1901 |
| 0.305         | 5.36  | 150  | 0.5833          | 39.1733   | 35.5962 |
| 0.1133        | 7.14  | 200  | 0.5980          | 36.8291   | 34.3566 |
| 0.0391        | 8.93  | 250  | 0.6228          | 37.3843   | 34.2385 |
| 0.0138        | 10.71 | 300  | 0.6522          | 39.4201   | 37.1311 |
| 0.0051        | 12.5  | 350  | 0.6699          | 35.7187   | 33.4711 |
| 0.0032        | 14.29 | 400  | 0.6826          | 36.0888   | 34.0024 |
| 0.0027        | 16.07 | 450  | 0.6881          | 36.2122   | 34.3566 |
| 0.0024        | 17.86 | 500  | 0.6900          | 35.9038   | 34.1204 |


### Framework versions

- Transformers 4.29.0.dev0
- Pytorch 2.0.0+cu117
- Datasets 2.11.0
- Tokenizers 0.13.3