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--- |
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language: |
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- ckb |
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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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metrics: |
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- wer |
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model-index: |
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- name: Whisper Small Ckb - Razhan Hameed |
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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 11.0 |
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type: mozilla-foundation/common_voice_11_0 |
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config: ckb |
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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: 33.2192952446117 |
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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 Ckb - Razhan Hameed |
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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 11.0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3825 |
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- Wer: 33.2193 |
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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: 64 |
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- eval_batch_size: 32 |
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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: 12000 |
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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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| 0.1693 | 2.49 | 1000 | 0.2060 | 39.1265 | |
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| 0.0722 | 4.98 | 2000 | 0.2124 | 36.3173 | |
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| 0.0127 | 7.46 | 3000 | 0.2736 | 36.5568 | |
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| 0.008 | 9.95 | 4000 | 0.3131 | 35.7015 | |
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| 0.0032 | 12.44 | 5000 | 0.3434 | 35.3936 | |
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| 0.0028 | 14.93 | 6000 | 0.3453 | 35.9258 | |
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| 0.003 | 17.41 | 7000 | 0.3558 | 34.9565 | |
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| 0.0022 | 19.9 | 8000 | 0.3593 | 34.2722 | |
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| 0.0016 | 22.39 | 9000 | 0.3639 | 34.3369 | |
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| 0.0015 | 24.88 | 10000 | 0.3785 | 34.0062 | |
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| 0.0009 | 27.36 | 11000 | 0.3915 | 34.2951 | |
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| 0.0001 | 29.85 | 12000 | 0.3825 | 33.2193 | |
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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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