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---
language:
- sv-SE
license: apache-2.0
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small Hi - Swedish
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 11.0
type: mozilla-foundation/common_voice_11_0
config: null
split: None
args: 'config: sv-SE, split: test'
metrics:
- name: Wer
type: wer
value: 51.31886746793579
---
<!-- 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 Hi - Swedish
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 11.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0765
- Wer: 51.3189
## 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: 0.0005
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-06
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 1.5005 | 1.29 | 1000 | 1.7517 | 84.8861 |
| 0.8752 | 2.59 | 2000 | 1.2958 | 68.8688 |
| 0.4382 | 3.88 | 3000 | 1.1835 | 60.4152 |
| 0.0694 | 5.17 | 4000 | 1.1659 | 55.8442 |
| 0.0091 | 6.47 | 5000 | 1.0765 | 51.3189 |
### Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.9.0+cu102
- Datasets 2.7.1
- Tokenizers 0.13.2
|