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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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metrics: |
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- wer |
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model-index: |
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- name: whisper-small-Denoiser-enhanced-weight-05-05-hindi-10dB |
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results: [] |
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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-Denoiser-enhanced-weight-05-05-hindi-10dB |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5849 |
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- Wer: 34.2815 |
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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: 1650 |
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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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| 1.6592 | 0.61 | 50 | 1.3742 | 83.7973 | |
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| 0.8218 | 1.22 | 100 | 0.7806 | 57.9198 | |
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| 0.642 | 1.83 | 150 | 0.6349 | 58.6201 | |
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| 0.504 | 2.44 | 200 | 0.5347 | 54.5651 | |
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| 0.406 | 3.05 | 250 | 0.4393 | 43.1264 | |
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| 0.2617 | 3.66 | 300 | 0.3305 | 40.6277 | |
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| 0.1785 | 4.27 | 350 | 0.3107 | 39.2703 | |
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| 0.1634 | 4.88 | 400 | 0.2939 | 37.7313 | |
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| 0.1042 | 5.49 | 450 | 0.3005 | 37.7572 | |
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| 0.0913 | 6.1 | 500 | 0.3094 | 36.2528 | |
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| 0.0612 | 6.71 | 550 | 0.3192 | 36.3566 | |
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| 0.033 | 7.32 | 600 | 0.3379 | 35.8378 | |
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| 0.0332 | 7.93 | 650 | 0.3420 | 34.9818 | |
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| 0.021 | 8.54 | 700 | 0.3562 | 35.1288 | |
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| 0.0143 | 9.15 | 750 | 0.3713 | 35.3017 | |
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| 0.0109 | 9.76 | 800 | 0.3667 | 34.7657 | |
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| 0.0073 | 10.37 | 850 | 0.3885 | 35.6562 | |
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| 0.0075 | 10.98 | 900 | 0.3953 | 34.4631 | |
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| 0.0042 | 11.59 | 950 | 0.4094 | 34.5582 | |
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| 0.0036 | 12.2 | 1000 | 0.4179 | 34.1605 | |
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| 0.0028 | 12.8 | 1050 | 0.4307 | 34.3247 | |
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| 0.0028 | 13.41 | 1100 | 0.4399 | 34.2383 | |
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| 0.0014 | 14.02 | 1150 | 0.4490 | 34.1691 | |
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| 0.0015 | 14.63 | 1200 | 0.4682 | 34.6187 | |
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| 0.0005 | 15.24 | 1250 | 0.4833 | 34.3680 | |
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| 0.0008 | 15.85 | 1300 | 0.4916 | 34.0913 | |
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| 0.0005 | 16.46 | 1350 | 0.5065 | 33.9270 | |
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| 0.0004 | 17.07 | 1400 | 0.5176 | 34.1345 | |
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| 0.0002 | 17.68 | 1450 | 0.5429 | 34.2988 | |
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| 0.0001 | 18.29 | 1500 | 0.5548 | 33.8233 | |
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| 0.0 | 18.9 | 1550 | 0.5669 | 34.3075 | |
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| 0.0 | 19.51 | 1600 | 0.5814 | 34.4631 | |
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| 0.0 | 20.12 | 1650 | 0.5849 | 34.2815 | |
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### Framework versions |
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- Transformers 4.37.0.dev0 |
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- Pytorch 1.12.0+cu113 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
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