---
language:
- se
license: apache-2.0
base_model: openai/whisper-small
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Swedish
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Swedish voice 1.0
      type: mozilla-foundation/common_voice_11_0
      config: sv-SE
      split: test
      args: 'config: se, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 34.02704955499986
---

<!-- 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 Swedish

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Swedish voice 1.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3715
- Wer: 34.0270

## 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: 4000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.1191        | 1.29  | 1000 | 0.3000          | 28.7973 |
| 0.0506        | 2.59  | 2000 | 0.3083          | 32.0911 |
| 0.0298        | 3.88  | 3000 | 0.3339          | 42.4242 |
| 0.0073        | 5.17  | 4000 | 0.3715          | 34.0270 |


### Framework versions

- Transformers 4.36.0.dev0
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0