---
language:
- da
license: apache-2.0
tags:
- generated_from_trainer
- hf-asr-leaderboard
- whisper-event
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
base_model: openai/whisper-medium
model-index:
- name: Whisper Medium Danish (CV11 + FLEAURS)
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: mozilla-foundation/common_voice_11_0
      type: mozilla-foundation/common_voice_11_0
      config: da
      split: test
    metrics:
    - type: wer
      value: 13.708574434508153
      name: Wer
---

<!-- 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 Medium Danish (CV11 + FLEAURS)

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co./openai/whisper-medium) on the mozilla-foundation/common_voice_11_0,google/fleurs da,da_dk dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5814
- Wer: 13.7086

## 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: 8e-06
- train_batch_size: 32
- 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: 10000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer     |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.0265        | 3.14  | 1000  | 0.3690          | 14.7607 |
| 0.0063        | 6.29  | 2000  | 0.4342          | 14.0926 |
| 0.0016        | 9.43  | 3000  | 0.4847          | 14.3609 |
| 0.002         | 12.58 | 4000  | 0.4919          | 14.1715 |
| 0.0013        | 15.72 | 5000  | 0.5114          | 14.2294 |
| 0.0014        | 18.87 | 6000  | 0.5197          | 13.9137 |
| 0.0003        | 22.01 | 7000  | 0.5422          | 14.1978 |
| 0.0001        | 25.16 | 8000  | 0.5659          | 13.8716 |
| 0.0001        | 28.3  | 9000  | 0.5772          | 13.7296 |
| 0.0001        | 31.45 | 10000 | 0.5814          | 13.7086 |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2