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---
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library_name: transformers
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language:
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- en
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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-squeezeformer-V9-mutliconv
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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-squeezeformer-V9-mutliconv
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the LibriSpeech dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1799
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- Wer: 11.3645
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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: 20
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- eval_batch_size: 8
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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: 2500
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- training_steps: 45000
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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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| 4.7863 | 1.0 | 2500 | 3.8844 | 119.2635 |
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| 3.9844 | 2.0 | 5000 | 3.7326 | 132.0431 |
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| 3.459 | 3.0 | 7500 | 1.2427 | 72.6510 |
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| 0.4598 | 4.0 | 10000 | 0.4232 | 23.4841 |
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| 0.1931 | 5.0 | 12500 | 0.3479 | 20.3629 |
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| 0.1096 | 6.0 | 15000 | 0.3255 | 17.5574 |
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| 0.0631 | 7.0 | 17500 | 0.3251 | 16.8252 |
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| 0.2473 | 8.0 | 20000 | 0.2452 | 14.4781 |
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| 0.1433 | 9.0 | 22500 | 0.2323 | 13.0782 |
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| 0.3067 | 10.0 | 25000 | 0.2224 | 14.5675 |
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| 0.2769 | 11.0 | 27500 | 0.2015 | 13.2323 |
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| 0.1853 | 12.0 | 30000 | 0.2004 | 14.1015 |
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| 0.1308 | 13.0 | 32500 | 0.2011 | 13.2494 |
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| 0.2435 | 14.0 | 35000 | 0.1830 | 11.9066 |
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| 0.1786 | 15.0 | 37500 | 0.1804 | 12.7948 |
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| 0.4194 | 16.0 | 40000 | 0.1833 | 10.3469 |
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| 0.3283 | 17.0 | 42500 | 0.1818 | 10.2785 |
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| 0.2936 | 18.0 | 45000 | 0.1799 | 11.3645 |
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### Framework versions
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- Transformers 4.45.2
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- Pytorch 2.4.0
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- Datasets 3.2.0
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- Tokenizers 0.20.3
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