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---
language:
- da
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
metrics:
- wer
model-index:
- name: Whisper Small Da - 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: 23.39882224190943
---
<!-- 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 Da - WasuratS
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 13 dataset on Danish language
It achieves the following results on the evaluation set:
- Loss: 0.6393
- Wer Ortho: 29.0926
- Wer: 23.3988
## Model description
[openai/whisper-small](https://huggingface.co/openai/whisper-small)
## Training and evaluation data
[mozilla-foundation/common_voice_13_0](https://huggingface.co/datasets/mozilla-foundation/common_voice_13_0)
## 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: 4000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------:|
| 0.218 | 1.61 | 500 | 0.4724 | 30.2496 | 24.7069 |
| 0.0628 | 3.22 | 1000 | 0.4825 | 28.8946 | 23.3154 |
| 0.0289 | 4.82 | 1500 | 0.5311 | 29.3376 | 23.4666 |
| 0.0078 | 6.43 | 2000 | 0.5740 | 29.4627 | 23.6542 |
| 0.0032 | 8.04 | 2500 | 0.6070 | 29.0613 | 23.2790 |
| 0.0025 | 9.65 | 3000 | 0.6274 | 29.1187 | 23.4770 |
| 0.0012 | 11.25 | 3500 | 0.6335 | 29.0978 | 23.3623 |
| 0.0011 | 12.86 | 4000 | 0.6393 | 29.0926 | 23.3988 |
### Framework versions
- Transformers 4.29.2
- Pytorch 1.13.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3
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