---
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- PolyAI/minds14
metrics:
- wer
model-index:
- name: whisper-tiny-finetuned-minds14
  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: 0.3370720188902007
---

<!-- 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-finetuned-minds14

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: 0.5953
- Wer Ortho: 0.3516
- Wer: 0.3371

## 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
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|
| 3.9735        | 0.89  | 25   | 2.8501          | 0.5281    | 0.3979 |
| 1.8774        | 1.79  | 50   | 0.8237          | 0.4405    | 0.4067 |
| 0.53          | 2.68  | 75   | 0.5823          | 0.3874    | 0.3695 |
| 0.2962        | 3.57  | 100  | 0.5374          | 0.3726    | 0.3642 |
| 0.1982        | 4.46  | 125  | 0.5273          | 0.3658    | 0.3571 |
| 0.1361        | 5.36  | 150  | 0.5435          | 0.3701    | 0.3548 |
| 0.0711        | 6.25  | 175  | 0.5489          | 0.3609    | 0.3483 |
| 0.0387        | 7.14  | 200  | 0.5826          | 0.3664    | 0.3566 |
| 0.0221        | 8.04  | 225  | 0.5953          | 0.3516    | 0.3371 |
| 0.0123        | 8.93  | 250  | 0.6145          | 0.3510    | 0.3418 |
| 0.0061        | 9.82  | 275  | 0.6406          | 0.3597    | 0.3542 |
| 0.0041        | 10.71 | 300  | 0.6311          | 0.3479    | 0.3406 |
| 0.003         | 11.61 | 325  | 0.6513          | 0.3701    | 0.3619 |
| 0.0019        | 12.5  | 350  | 0.6630          | 0.3652    | 0.3613 |
| 0.0025        | 13.39 | 375  | 0.6672          | 0.3634    | 0.3601 |
| 0.0023        | 14.29 | 400  | 0.6738          | 0.3442    | 0.3418 |
| 0.0011        | 15.18 | 425  | 0.6746          | 0.3461    | 0.3436 |
| 0.0012        | 16.07 | 450  | 0.6788          | 0.3442    | 0.3430 |
| 0.0013        | 16.96 | 475  | 0.6865          | 0.3448    | 0.3447 |
| 0.0009        | 17.86 | 500  | 0.6921          | 0.3467    | 0.3459 |


### Framework versions

- Transformers 4.37.0.dev0
- Pytorch 2.1.2+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0