---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- PolyAI/minds14
metrics:
- wer
model-index:
- name: whisper-tiny-finetuned-minds14-en-v2
  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: 0.34297520661157027
---

<!-- 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-en-v2

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: 0.6386
- Wer Ortho: 0.3461
- Wer: 0.3430

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|
| 1.7971        | 1.79  | 50   | 0.7476          | 0.4411    | 0.4008 |
| 0.3112        | 3.57  | 100  | 0.4953          | 0.3560    | 0.3453 |
| 0.1214        | 5.36  | 150  | 0.5073          | 0.3763    | 0.3589 |
| 0.0359        | 7.14  | 200  | 0.5244          | 0.3442    | 0.3347 |
| 0.011         | 8.93  | 250  | 0.5569          | 0.3510    | 0.3371 |
| 0.0038        | 10.71 | 300  | 0.5903          | 0.3393    | 0.3329 |
| 0.0019        | 12.5  | 350  | 0.6068          | 0.3405    | 0.3353 |
| 0.0012        | 14.29 | 400  | 0.6175          | 0.3418    | 0.3377 |
| 0.0012        | 16.07 | 450  | 0.6253          | 0.3362    | 0.3329 |
| 0.0013        | 17.86 | 500  | 0.6386          | 0.3461    | 0.3430 |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.1+cu117
- Datasets 2.13.1
- Tokenizers 0.13.3