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--- |
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license: apache-2.0 |
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base_model: openai/whisper-small |
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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_6_1 |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Small Frisian 1h |
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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 6.1 |
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type: mozilla-foundation/common_voice_6_1 |
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args: 'config: frisian, split: test' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 47.79183746212796 |
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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 Small Frisian 1h |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 6.1 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9900 |
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- Wer: 47.7918 |
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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-06 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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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: 2000 |
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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 | |
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|:-------------:|:-------:|:----:|:---------------:|:-------:| |
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| 2.4073 | 1.1236 | 100 | 2.2555 | 82.9549 | |
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| 1.5143 | 2.2472 | 200 | 1.6651 | 73.4557 | |
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| 1.1865 | 3.3708 | 300 | 1.4237 | 65.1256 | |
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| 0.9368 | 4.4944 | 400 | 1.2874 | 59.4832 | |
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| 0.8009 | 5.6180 | 500 | 1.1957 | 56.5461 | |
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| 0.6722 | 6.7416 | 600 | 1.1345 | 54.6890 | |
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| 0.5726 | 7.8652 | 700 | 1.0894 | 53.1919 | |
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| 0.5068 | 8.9888 | 800 | 1.0575 | 51.7769 | |
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| 0.4239 | 10.1124 | 900 | 1.0351 | 50.8002 | |
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| 0.3799 | 11.2360 | 1000 | 1.0197 | 49.9198 | |
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| 0.295 | 12.3596 | 1100 | 1.0110 | 49.3673 | |
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| 0.2852 | 13.4831 | 1200 | 1.0022 | 48.7507 | |
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| 0.2478 | 14.6067 | 1300 | 0.9965 | 48.3800 | |
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| 0.2267 | 15.7303 | 1400 | 0.9931 | 48.1911 | |
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| 0.1986 | 16.8539 | 1500 | 0.9916 | 48.1412 | |
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| 0.1922 | 17.9775 | 1600 | 0.9907 | 47.9558 | |
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| 0.1724 | 19.1011 | 1700 | 0.9905 | 47.8703 | |
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| 0.1709 | 20.2247 | 1800 | 0.9900 | 47.9059 | |
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| 0.1749 | 21.3483 | 1900 | 0.9900 | 47.7598 | |
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| 0.145 | 22.4719 | 2000 | 0.9900 | 47.7918 | |
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### Framework versions |
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- Transformers 4.40.1 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.0 |
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- Tokenizers 0.19.1 |
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