---
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: 0.3541912632821724
---

<!-- 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: 0.6875
- Wer Ortho: 0.3745
- Wer: 0.3542

## 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
- training_steps: 500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|
| 0.6838        | 1.79  | 50   | 0.6522          | 0.4028    | 0.3613 |
| 0.2778        | 3.57  | 100  | 0.5727          | 0.3880    | 0.3589 |
| 0.1313        | 5.36  | 150  | 0.5870          | 0.3794    | 0.3501 |
| 0.0539        | 7.14  | 200  | 0.6080          | 0.3726    | 0.3471 |
| 0.022         | 8.93  | 250  | 0.6380          | 0.3745    | 0.3477 |
| 0.0095        | 10.71 | 300  | 0.6629          | 0.3843    | 0.3595 |
| 0.0049        | 12.5  | 350  | 0.6715          | 0.3819    | 0.3583 |
| 0.0036        | 14.29 | 400  | 0.6811          | 0.3825    | 0.3595 |
| 0.0032        | 16.07 | 450  | 0.6858          | 0.3757    | 0.3554 |
| 0.0029        | 17.86 | 500  | 0.6875          | 0.3745    | 0.3542 |


### Framework versions

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