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---
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
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