---
language:
- da
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
metrics:
- wer
model-index:
- name: Whisper Small Da - WasuratS
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 13
      type: mozilla-foundation/common_voice_13_0
      config: da
      split: test
      args: da
    metrics:
    - name: Wer
      type: wer
      value: 23.39882224190943
---

<!-- 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 Small Da - WasuratS

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 13 dataset on Danish language
It achieves the following results on the evaluation set:
- Loss: 0.6393
- Wer Ortho: 29.0926
- Wer: 23.3988

## Model description

[openai/whisper-small](https://huggingface.co/openai/whisper-small)


## Training and evaluation data

[mozilla-foundation/common_voice_13_0](https://huggingface.co/datasets/mozilla-foundation/common_voice_13_0)

## 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
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 4000
- mixed_precision_training: Native AMP


### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------:|
| 0.218         | 1.61  | 500  | 0.4724          | 30.2496   | 24.7069 |
| 0.0628        | 3.22  | 1000 | 0.4825          | 28.8946   | 23.3154 |
| 0.0289        | 4.82  | 1500 | 0.5311          | 29.3376   | 23.4666 |
| 0.0078        | 6.43  | 2000 | 0.5740          | 29.4627   | 23.6542 |
| 0.0032        | 8.04  | 2500 | 0.6070          | 29.0613   | 23.2790 |
| 0.0025        | 9.65  | 3000 | 0.6274          | 29.1187   | 23.4770 |
| 0.0012        | 11.25 | 3500 | 0.6335          | 29.0978   | 23.3623 |
| 0.0011        | 12.86 | 4000 | 0.6393          | 29.0926   | 23.3988 |


### Framework versions

- Transformers 4.29.2
- Pytorch 1.13.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3