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--- |
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language: |
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- id |
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license: apache-2.0 |
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tags: |
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- whisper-event |
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- generated_from_trainer |
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datasets: |
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- mozilla-foundation/common_voice_11_0 |
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- magic_data |
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- titml |
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- google/fleurs |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Tiny Indonesian |
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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: mozilla-foundation/common_voice_11_0 id |
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type: mozilla-foundation/common_voice_11_0 |
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config: id |
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split: test |
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metrics: |
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- name: Wer |
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type: wer |
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value: 18.28368532693904 |
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--- |
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# Whisper Tiny Indonesian |
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This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the mozilla-foundation/common_voice_11_0, magic_data, titml and google/fleurs dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2409 |
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- Wer: 18.2837 |
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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: 32 |
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- eval_batch_size: 16 |
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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: 500 |
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- training_steps: 10000 |
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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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| 0.4103 | 0.66 | 1000 | 0.3802 | 27.0497 | |
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| 0.2682 | 1.32 | 2000 | 0.3223 | 22.9365 | |
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| 0.2381 | 1.99 | 3000 | 0.2884 | 20.8245 | |
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| 0.1606 | 2.65 | 4000 | 0.2727 | 20.1928 | |
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| 0.1246 | 3.31 | 5000 | 0.2596 | 18.9984 | |
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| 0.1344 | 3.97 | 6000 | 0.2482 | 18.7540 | |
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| 0.0975 | 4.63 | 7000 | 0.2471 | 18.6388 | |
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| 0.0916 | 5.29 | 8000 | 0.2436 | 18.9615 | |
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| 0.0854 | 5.96 | 9000 | 0.2413 | 18.3114 | |
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| 0.0812 | 6.62 | 10000 | 0.2409 | 18.2837 | |
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### Framework versions |
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- Transformers 4.26.0.dev0 |
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- Pytorch 1.13.0+cu117 |
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- Datasets 2.7.1.dev0 |
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- Tokenizers 0.13.2 |
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