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--- |
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language: |
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- hu |
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license: apache-2.0 |
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base_model: openai/whisper-tiny |
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tags: |
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- generated_from_trainer |
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datasets: |
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- 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 Tiny Hu CV17 |
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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 17.0 |
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type: common_voice_11_0 |
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config: hu |
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split: None |
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args: hu |
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metrics: |
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- name: Wer |
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type: wer |
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value: 9.925882004150607 |
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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 Tiny Hu CV17 |
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This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Common Voice 17.0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1387 |
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- Wer Ortho: 10.7883 |
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- Wer: 9.9259 |
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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: 7.5e-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: 5000 |
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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 Ortho | Wer | |
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|:-------------:|:------:|:----:|:---------------:|:---------:|:-------:| |
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| 0.6432 | 0.3298 | 250 | 0.7031 | 59.9211 | 57.3051 | |
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| 0.4839 | 0.6596 | 500 | 0.5256 | 50.4185 | 47.3406 | |
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| 0.4127 | 0.9894 | 750 | 0.4089 | 40.9250 | 37.8002 | |
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| 0.2858 | 1.3193 | 1000 | 0.3434 | 34.4725 | 31.8885 | |
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| 0.2616 | 1.6491 | 1250 | 0.3027 | 32.2956 | 29.2203 | |
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| 0.2448 | 1.9789 | 1500 | 0.2571 | 28.1705 | 25.3780 | |
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| 0.1474 | 2.3087 | 1750 | 0.2318 | 25.4426 | 22.8343 | |
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| 0.1434 | 2.6385 | 2000 | 0.2112 | 22.7749 | 20.3647 | |
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| 0.14 | 2.9683 | 2250 | 0.1922 | 20.1102 | 17.7883 | |
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| 0.0768 | 3.2982 | 2500 | 0.1797 | 18.2344 | 15.9917 | |
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| 0.0764 | 3.6280 | 2750 | 0.1678 | 16.5573 | 14.6161 | |
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| 0.0737 | 3.9578 | 3000 | 0.1573 | 15.0337 | 13.6199 | |
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| 0.0375 | 4.2876 | 3250 | 0.1538 | 14.0130 | 12.3243 | |
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| 0.0357 | 4.6174 | 3500 | 0.1495 | 13.1970 | 11.7106 | |
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| 0.033 | 4.9472 | 3750 | 0.1435 | 11.9234 | 10.8005 | |
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| 0.0138 | 5.2770 | 4000 | 0.1422 | 11.8873 | 10.7026 | |
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| 0.0137 | 5.6069 | 4250 | 0.1398 | 11.4477 | 10.4684 | |
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| 0.0135 | 5.9367 | 4500 | 0.1381 | 11.1436 | 10.2639 | |
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| 0.0072 | 6.2665 | 4750 | 0.1388 | 10.7853 | 9.9140 | |
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| 0.0065 | 6.5963 | 5000 | 0.1387 | 10.7883 | 9.9259 | |
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### Framework versions |
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- Transformers 4.41.1 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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