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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_17_0 |
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metrics: |
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- wer |
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model-index: |
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- name: whisper-small-id |
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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_17_0 id |
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type: mozilla-foundation/common_voice_17_0 |
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config: id |
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split: None |
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args: id |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.05902826117221217 |
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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-id |
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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_17_0 id dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0878 |
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- Wer: 0.0590 (5.9%) |
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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: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 32 |
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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: 20000 |
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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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| 0.1875 | 0.8457 | 1000 | 0.1400 | 0.1099 | |
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| 0.0852 | 1.6913 | 2000 | 0.1043 | 0.0857 | |
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| 0.0387 | 2.5370 | 3000 | 0.0914 | 0.0757 | |
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| 0.0153 | 3.3827 | 4000 | 0.0860 | 0.0818 | |
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| 0.008 | 4.2283 | 5000 | 0.0878 | 0.0698 | |
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| 0.005 | 5.0740 | 6000 | 0.0878 | 0.0745 | |
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| 0.0033 | 5.9197 | 7000 | 0.0834 | 0.0651 | |
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| 0.0029 | 6.7653 | 8000 | 0.0815 | 0.0627 | |
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| 0.0014 | 7.6110 | 9000 | 0.0853 | 0.0627 | |
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| 0.0013 | 8.4567 | 10000 | 0.0861 | 0.0641 | |
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| 0.0005 | 9.3023 | 11000 | 0.0857 | 0.0633 | |
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| 0.0005 | 10.1480 | 12000 | 0.0856 | 0.0620 | |
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| 0.0007 | 10.9937 | 13000 | 0.0866 | 0.0605 | |
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| 0.0005 | 11.8393 | 14000 | 0.0871 | 0.0614 | |
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| 0.0002 | 12.6850 | 15000 | 0.0850 | 0.0596 | |
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| 0.0004 | 13.5307 | 16000 | 0.0849 | 0.0600 | |
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| 0.0001 | 14.3763 | 17000 | 0.0868 | 0.0592 | |
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| 0.0002 | 15.2220 | 18000 | 0.0873 | 0.0593 | |
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| 0.0001 | 16.0677 | 19000 | 0.0875 | 0.0585 | |
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| 0.0001 | 16.9133 | 20000 | 0.0878 | 0.0590 | |
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### Framework versions |
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- Transformers 4.42.0.dev0 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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