---
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
      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-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: 0.7061
- Wer Ortho: 0.3640
- 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: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- training_steps: 500

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|
| 2.1622        | 1.79  | 50   | 0.9646          | 0.4510    | 0.3908 |
| 0.3628        | 3.57  | 100  | 0.5673          | 0.3812    | 0.3501 |
| 0.131         | 5.36  | 150  | 0.5827          | 0.3714    | 0.3436 |
| 0.0488        | 7.14  | 200  | 0.6058          | 0.3689    | 0.3383 |
| 0.0144        | 8.93  | 250  | 0.6444          | 0.3671    | 0.3430 |
| 0.0044        | 10.71 | 300  | 0.6652          | 0.3418    | 0.3282 |
| 0.0021        | 12.5  | 350  | 0.6827          | 0.3405    | 0.3306 |
| 0.0013        | 14.29 | 400  | 0.6956          | 0.3448    | 0.3341 |
| 0.0011        | 16.07 | 450  | 0.7061          | 0.3640    | 0.3542 |


### Framework versions

- Transformers 4.31.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3