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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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## 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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