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---
language:
- nn
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-npsc
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 11.0
type: mozilla-foundation/common_voice_11_0
config: 16K_mp3_bokmaal
split: train
args: 16K_mp3_bokmaal
metrics:
- name: Wer
type: wer
value: 12.925418803583286
---
<!-- 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-npsc
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: 0.2028
- Wer: 12.9254
## 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: 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: 6000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.3922 | 0.18 | 500 | 0.3975 | 24.2055 |
| 0.2893 | 0.36 | 1000 | 0.3139 | 20.1507 |
| 0.2471 | 0.54 | 1500 | 0.2733 | 17.4449 |
| 0.2159 | 0.72 | 2000 | 0.2488 | 16.2681 |
| 0.2195 | 0.89 | 2500 | 0.2304 | 15.0577 |
| 0.1178 | 1.07 | 3000 | 0.2245 | 14.5968 |
| 0.1099 | 1.25 | 3500 | 0.2183 | 14.1118 |
| 0.1059 | 1.43 | 4000 | 0.2136 | 13.7914 |
| 0.1156 | 1.61 | 4500 | 0.2072 | 13.7491 |
| 0.1025 | 1.79 | 5000 | 0.2034 | 13.1515 |
| 0.1123 | 1.97 | 5500 | 0.2006 | 13.0284 |
| 0.0734 | 2.15 | 6000 | 0.2028 | 12.9254 |
### Framework versions
- Transformers 4.25.0.dev0
- Pytorch 1.12.1+cu113
- Datasets 2.6.1
- Tokenizers 0.13.1
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