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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 10m |
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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: 64.62662626982713 |
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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 10m |
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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: 1.6643 |
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- Wer: 64.6266 |
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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: 1000 |
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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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| 2.0562 | 6.6667 | 100 | 2.2740 | 83.4860 | |
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| 0.9187 | 13.3333 | 200 | 1.7749 | 76.7385 | |
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| 0.4133 | 20.0 | 300 | 1.6576 | 69.3317 | |
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| 0.1671 | 26.6667 | 400 | 1.6334 | 67.2679 | |
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| 0.0603 | 33.3333 | 500 | 1.6319 | 66.2770 | |
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| 0.0245 | 40.0 | 600 | 1.6433 | 65.6496 | |
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| 0.0138 | 46.6667 | 700 | 1.6522 | 64.6730 | |
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| 0.0104 | 53.3333 | 800 | 1.6591 | 64.5019 | |
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| 0.0089 | 60.0 | 900 | 1.6632 | 64.4876 | |
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| 0.0083 | 66.6667 | 1000 | 1.6643 | 64.6266 | |
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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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