---
language:
- da
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
metrics:
- wer
model-index:
- name: Whisper Base Danish - 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: 39.73630725936735
---

<!-- 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 Base Danish - WasuratS

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the Common Voice 13 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9795
- Wer Ortho: 45.5986
- Wer: 39.7363

## 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: 6000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------:|
| 0.5156        | 1.61  | 500  | 0.7387          | 47.8293   | 42.2586 |
| 0.2086        | 3.22  | 1000 | 0.7157          | 46.7087   | 41.0652 |
| 0.1439        | 4.82  | 1500 | 0.7300          | 46.5367   | 40.9610 |
| 0.0514        | 6.43  | 2000 | 0.7804          | 45.2963   | 39.5279 |
| 0.027         | 8.04  | 2500 | 0.8314          | 46.3126   | 40.3825 |
| 0.0133        | 9.65  | 3000 | 0.8739          | 44.8585   | 39.2777 |
| 0.0053        | 11.25 | 3500 | 0.9081          | 45.4839   | 39.7103 |
| 0.0041        | 12.86 | 4000 | 0.9347          | 45.4110   | 39.7050 |
| 0.0028        | 14.47 | 4500 | 0.9535          | 46.0624   | 40.3096 |
| 0.0024        | 16.08 | 5000 | 0.9673          | 45.6351   | 39.8979 |
| 0.0021        | 17.68 | 5500 | 0.9762          | 45.7862   | 39.9187 |
| 0.002         | 19.29 | 6000 | 0.9795          | 45.5986   | 39.7363 |


### Framework versions

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