---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- PolyAI/minds14
metrics:
- wer
model-index:
- name: whisper-tiny-en-minds14
  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: 0.2744982290436836
---

<!-- 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-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: 0.5680
- Wer Ortho: 0.2721
- Wer: 0.2745

## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- 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    |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|
| 1.4576        | 1.79  | 50   | 0.9286          | 0.3128    | 0.3152 |
| 0.3694        | 3.57  | 100  | 0.5188          | 0.2776    | 0.2774 |
| 0.0466        | 5.36  | 150  | 0.4494          | 0.2640    | 0.2692 |
| 0.008         | 7.14  | 200  | 0.4855          | 0.2782    | 0.2816 |
| 0.0026        | 8.93  | 250  | 0.4892          | 0.2801    | 0.2845 |
| 0.0016        | 10.71 | 300  | 0.5116          | 0.2745    | 0.2774 |
| 0.0004        | 12.5  | 350  | 0.5383          | 0.2770    | 0.2798 |
| 0.0002        | 14.29 | 400  | 0.5471          | 0.2758    | 0.2774 |
| 0.0002        | 16.07 | 450  | 0.5590          | 0.2714    | 0.2733 |
| 0.0001        | 17.86 | 500  | 0.5680          | 0.2721    | 0.2745 |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3