---
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: 0.296010296010296
---

<!-- 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: 0.4990
- Wer Ortho: 0.2965
- Wer: 0.2960

## 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: 5e-07
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 100
- training_steps: 500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer Ortho | Wer    |
|:-------------:|:------:|:----:|:---------------:|:---------:|:------:|
| 0.0244        | 0.8969 | 50   | 0.5282          | 0.3012    | 0.3005 |
| 0.0178        | 1.7937 | 100  | 0.5213          | 0.2985    | 0.2986 |
| 0.0171        | 2.6906 | 150  | 0.5147          | 0.2979    | 0.2967 |
| 0.0121        | 3.5874 | 200  | 0.5092          | 0.2925    | 0.2915 |
| 0.0071        | 4.4843 | 250  | 0.5057          | 0.3072    | 0.3069 |
| 0.0073        | 5.3812 | 300  | 0.5034          | 0.2945    | 0.2941 |
| 0.003         | 6.2780 | 350  | 0.5014          | 0.2945    | 0.2934 |
| 0.0036        | 7.1749 | 400  | 0.5003          | 0.2972    | 0.2967 |
| 0.0034        | 8.0717 | 450  | 0.4997          | 0.2965    | 0.2960 |
| 0.0034        | 8.9686 | 500  | 0.4990          | 0.2965    | 0.2960 |


### Framework versions

- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1