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README.md
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---
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language:
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- da
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license: apache-2.0
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tags:
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- generated_from_trainer
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datasets:
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- mozilla-foundation/common_voice_13_0
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metrics:
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- wer
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model-index:
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- name: Whisper Base Danish - WasuratS
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results:
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- task:
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name: Automatic Speech Recognition
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type: automatic-speech-recognition
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dataset:
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name: Common Voice 13
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type: mozilla-foundation/common_voice_13_0
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config: da
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split: test
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args: da
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metrics:
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- name: Wer
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type: wer
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value: 39.73630725936735
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# Whisper Base Danish - WasuratS
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This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the Common Voice 13 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.9795
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- Wer Ortho: 45.5986
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- Wer: 39.7363
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 1e-05
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- train_batch_size: 16
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- eval_batch_size: 16
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- seed: 42
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- distributed_type: multi-GPU
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_steps: 50
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- training_steps: 6000
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------:|
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| 0.5156 | 1.61 | 500 | 0.7387 | 47.8293 | 42.2586 |
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| 0.2086 | 3.22 | 1000 | 0.7157 | 46.7087 | 41.0652 |
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| 0.1439 | 4.82 | 1500 | 0.7300 | 46.5367 | 40.9610 |
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| 0.0514 | 6.43 | 2000 | 0.7804 | 45.2963 | 39.5279 |
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| 0.027 | 8.04 | 2500 | 0.8314 | 46.3126 | 40.3825 |
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| 0.0133 | 9.65 | 3000 | 0.8739 | 44.8585 | 39.2777 |
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| 0.0053 | 11.25 | 3500 | 0.9081 | 45.4839 | 39.7103 |
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| 0.0041 | 12.86 | 4000 | 0.9347 | 45.4110 | 39.7050 |
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| 0.0028 | 14.47 | 4500 | 0.9535 | 46.0624 | 40.3096 |
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| 0.0024 | 16.08 | 5000 | 0.9673 | 45.6351 | 39.8979 |
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| 0.0021 | 17.68 | 5500 | 0.9762 | 45.7862 | 39.9187 |
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| 0.002 | 19.29 | 6000 | 0.9795 | 45.5986 | 39.7363 |
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### Framework versions
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- Transformers 4.29.2
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- Pytorch 1.13.1+cu117
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- Datasets 2.12.0
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- Tokenizers 0.13.3
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