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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 10h |
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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: 22.427374799500978 |
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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 10h |
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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: 0.3402 |
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- Wer: 22.4274 |
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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: 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: 1500 |
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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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| 1.0548 | 0.1070 | 100 | 1.0200 | 52.0620 | |
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| 0.6944 | 0.2139 | 200 | 0.7126 | 39.6222 | |
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| 0.6024 | 0.3209 | 300 | 0.6052 | 36.0791 | |
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| 0.4697 | 0.4278 | 400 | 0.5303 | 32.5040 | |
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| 0.4222 | 0.5348 | 500 | 0.4780 | 30.0766 | |
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| 0.4075 | 0.6417 | 600 | 0.4458 | 28.4691 | |
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| 0.374 | 0.7487 | 700 | 0.4151 | 26.9292 | |
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| 0.3381 | 0.8556 | 800 | 0.3949 | 25.4678 | |
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| 0.3235 | 0.9626 | 900 | 0.3764 | 24.8904 | |
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| 0.1861 | 1.0695 | 1000 | 0.3643 | 23.5716 | |
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| 0.1554 | 1.1765 | 1100 | 0.3608 | 23.4183 | |
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| 0.1639 | 1.2834 | 1200 | 0.3511 | 23.0298 | |
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| 0.1453 | 1.3904 | 1300 | 0.3449 | 22.6591 | |
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| 0.1531 | 1.4973 | 1400 | 0.3419 | 22.4452 | |
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| 0.1299 | 1.6043 | 1500 | 0.3402 | 22.4274 | |
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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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