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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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metrics: |
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- wer |
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model-index: |
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- name: Whisper Large 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: 6.248270773771097 |
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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 Large Indonesian |
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This model is a fine-tuned version of [openai/whisper-large](https://huggingface.co/openai/whisper-large) on the mozilla-foundation/common_voice_11_0, magic_data, titml id dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2034 |
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- Wer: 6.2483 |
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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: 12 |
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- eval_batch_size: 12 |
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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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| 0.1516 | 0.5 | 1000 | 0.1730 | 6.5664 | |
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| 0.1081 | 1.0 | 2000 | 0.1638 | 6.3682 | |
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| 0.0715 | 1.49 | 3000 | 0.1803 | 6.2713 | |
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| 0.1009 | 1.99 | 4000 | 0.1796 | 6.2667 | |
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| 0.0387 | 2.49 | 5000 | 0.2054 | 6.4927 | |
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| 0.0494 | 2.99 | 6000 | 0.2034 | 6.2483 | |
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| 0.0259 | 3.48 | 7000 | 0.2226 | 6.3497 | |
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| 0.0265 | 3.98 | 8000 | 0.2274 | 6.4004 | |
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| 0.0232 | 4.48 | 9000 | 0.2443 | 6.5618 | |
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| 0.015 | 4.98 | 10000 | 0.2413 | 6.4927 | |
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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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