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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-NSQU-whisper
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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-NSQU-whisper
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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: 0.1322
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- Wer: 5.6642
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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: 50000
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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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| 4.8718 | 1.0 | 2500 | 3.8609 | 111.8590 |
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| 2.5628 | 2.0 | 5000 | 0.2978 | 15.6193 |
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| 0.1698 | 3.0 | 7500 | 0.2218 | 11.0906 |
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| 0.0867 | 4.0 | 10000 | 0.2011 | 10.1891 |
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| 0.1697 | 5.0 | 12500 | 0.1641 | 8.9851 |
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| 0.0993 | 6.0 | 15000 | 0.1553 | 7.8039 |
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| 0.0651 | 7.0 | 17500 | 0.1555 | 7.2448 |
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| 0.0468 | 8.0 | 20000 | 0.1569 | 7.1497 |
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| 0.2168 | 9.0 | 22500 | 0.1509 | 7.0507 |
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| 0.1467 | 10.0 | 25000 | 0.1494 | 6.9671 |
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| 0.1113 | 11.0 | 27500 | 0.1493 | 6.7597 |
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| 0.0914 | 12.0 | 30000 | 0.1511 | 6.8035 |
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| 0.1946 | 13.0 | 32500 | 0.1391 | 6.4212 |
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| 0.1425 | 14.0 | 35000 | 0.1369 | 5.8753 |
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| 0.1145 | 15.0 | 37500 | 0.1368 | 5.7536 |
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| 0.1776 | 16.0 | 40000 | 0.1302 | 5.5995 |
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| 0.1416 | 17.0 | 42500 | 0.1298 | 5.6204 |
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| 0.1239 | 18.0 | 45000 | 0.1297 | 5.6204 |
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| 0.3373 | 19.0 | 47500 | 0.1353 | 5.7403 |
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| 0.2785 | 20.0 | 50000 | 0.1322 | 5.6642 |
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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 3.1.0
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- Tokenizers 0.20.0
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