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--- |
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language: |
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- id |
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license: cc |
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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 Small 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: 6.059208706077654 |
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--- |
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# Whisper Small Indonesian |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co./openai/whisper-small) on the mozilla-foundation/common_voice_11_0, magic_data, titml, google/fleurs dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1022 |
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- Wer: 6.0592 |
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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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| 0.173 | 0.66 | 1000 | 0.1654 | 9.8773 | |
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| 0.0771 | 1.32 | 2000 | 0.1290 | 7.7515 | |
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| 0.0569 | 1.99 | 3000 | 0.1056 | 7.1475 | |
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| 0.0274 | 2.65 | 4000 | 0.1044 | 6.6264 | |
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| 0.0072 | 3.31 | 5000 | 0.1023 | 6.3543 | |
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| 0.009 | 3.97 | 6000 | 0.1000 | 6.3359 | |
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| 0.0033 | 4.63 | 7000 | 0.1022 | 6.0592 | |
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| 0.002 | 5.29 | 8000 | 0.1051 | 6.1560 | |
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| 0.0028 | 5.96 | 9000 | 0.1052 | 6.1007 | |
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| 0.0013 | 6.62 | 10000 | 0.1063 | 6.1376 | |
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### Framework versions |
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- Transformers 4.26.0.dev0 |
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- Pytorch 1.10.2+cu102 |
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- Datasets 2.7.0 |
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- Tokenizers 0.13.1 |
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