---
language:
- da
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- wer
model-index:
- name: Whisper Tiny Da - HollowVoice
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: audiofolder
      type: audiofolder
      config: default
      split: train[-20%:]
      args: default
    metrics:
    - name: Wer
      type: wer
      value: 86.49993452926542
---

<!-- 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 Da - HollowVoice

This model is a fine-tuned version of [openai/openai/whisper-tiny](https://huggingface.co/openai/openai/whisper-tiny) on the audiofolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5216
- Wer: 86.4999

## 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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.0319        | 24.39 | 1000 | 0.5216          | 86.4999 |
| 0.0031        | 48.78 | 2000 | 0.5156          | 89.3545 |
| 0.0017        | 73.17 | 3000 | 0.5267          | 89.7342 |
| 0.0013        | 97.56 | 4000 | 0.5312          | 90.9781 |


### Framework versions

- Transformers 4.27.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.10.1
- Tokenizers 0.13.2