---
language:
- en
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- PolyAI/minds14
metrics:
- wer
model-index:
- name: Whisper Tiny English
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Minds 14
      type: PolyAI/minds14
      config: en-US
      split: train
      args: en-US
    metrics:
    - name: Wer
      type: wer
      value: 0.258610624635143
---

<!-- 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 English

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Minds 14 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4154
- Wer Ortho: 0.2659
- Wer: 0.2586

## 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: 32
- 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: 20
- training_steps: 100

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|
| 4.2901        | 0.33  | 5    | 4.2556          | 0.4220    | 0.2919 |
| 4.3552        | 0.67  | 10   | 3.7784          | 0.4226    | 0.2931 |
| 3.453         | 1.0   | 15   | 2.9546          | 0.4152    | 0.2907 |
| 2.9147        | 1.33  | 20   | 2.4090          | 0.3988    | 0.2931 |
| 2.3042        | 1.67  | 25   | 1.7869          | 0.3701    | 0.3001 |
| 1.6056        | 2.0   | 30   | 1.1284          | 0.3494    | 0.3012 |
| 0.988         | 2.33  | 35   | 0.6892          | 0.3860    | 0.3403 |
| 0.6605        | 2.67  | 40   | 0.5611          | 0.3128    | 0.2849 |
| 0.4645        | 3.0   | 45   | 0.4982          | 0.3091    | 0.2901 |
| 0.4884        | 3.33  | 50   | 0.4640          | 0.2963    | 0.2855 |
| 0.404         | 3.67  | 55   | 0.4453          | 0.2884    | 0.2814 |
| 0.4745        | 4.0   | 60   | 0.4268          | 0.2762    | 0.2697 |
| 0.303         | 4.33  | 65   | 0.4182          | 0.2829    | 0.2720 |
| 0.2717        | 4.67  | 70   | 0.4119          | 0.2829    | 0.2750 |
| 0.3464        | 5.0   | 75   | 0.4080          | 0.2860    | 0.2761 |
| 0.2193        | 5.33  | 80   | 0.4054          | 0.2823    | 0.2750 |
| 0.2138        | 5.67  | 85   | 0.4064          | 0.2762    | 0.2680 |
| 0.1571        | 6.0   | 90   | 0.4102          | 0.2799    | 0.2715 |
| 0.1398        | 6.33  | 95   | 0.4146          | 0.2768    | 0.2697 |
| 0.1523        | 6.67  | 100  | 0.4154          | 0.2659    | 0.2586 |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3