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---
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library_name: transformers
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language:
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- zh
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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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model-index:
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- name: Whisper-Small-squeezeformer-architecture
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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-squeezeformer-architecture
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Voice_Data_Collection_second_edition dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.5061
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- Cer: 28.1162
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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: 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: 3750
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- training_steps: 120000
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Cer | Validation Loss |
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|:-------------:|:-----:|:------:|:--------:|:---------------:|
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| 2.9532 | 1.0 | 3750 | 103.2182 | 2.9601 |
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| 1.6561 | 2.0 | 7500 | 85.2058 | 1.6430 |
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| 0.6747 | 3.0 | 11250 | 43.9073 | 0.7233 |
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| 0.4521 | 4.0 | 15000 | 33.8818 | 0.5573 |
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| 0.3412 | 5.0 | 18750 | 29.7393 | 0.4957 |
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| 0.2109 | 6.0 | 22500 | 27.6988 | 0.4640 |
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| 0.1365 | 7.0 | 26250 | 27.5348 | 0.4580 |
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| 0.105 | 8.0 | 30000 | 27.2348 | 0.4571 |
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| 0.4959 | 9.0 | 33750 | 24.2346 | 0.4091 |
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| 0.344 | 10.0 | 37500 | 22.3133 | 0.3801 |
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| 0.2431 | 11.0 | 41250 | 21.3667 | 0.3668 |
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| 0.1569 | 12.0 | 45000 | 21.1207 | 0.3665 |
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| 0.112 | 13.0 | 48750 | 21.1170 | 0.3702 |
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| 0.0716 | 14.0 | 52500 | 21.1263 | 0.3761 |
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| 0.052 | 15.0 | 56250 | 21.1822 | 0.3802 |
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| 0.038 | 16.0 | 60000 | 21.0778 | 0.3833 |
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| 0.2982 | 17.0 | 63750 | 24.5216 | 0.4189 |
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| 0.1896 | 18.0 | 67500 | 24.6688 | 0.4229 |
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| 0.155 | 19.0 | 71250 | 25.9154 | 0.4375 |
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| 0.1105 | 20.0 | 75000 | 26.1372 | 0.4476 |
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| 0.0727 | 21.0 | 78750 | 26.9087 | 0.4637 |
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| 0.0511 | 22.0 | 82500 | 26.7894 | 0.4706 |
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| 0.033 | 23.0 | 86250 | 27.2180 | 0.4808 |
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| 0.0246 | 24.0 | 90000 | 27.2870 | 0.4840 |
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| 0.2775 | 25.0 | 93750 | 26.0310 | 0.4465 |
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| 0.1631 | 26.0 | 97500 | 26.6068 | 0.4500 |
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| 0.1428 | 27.0 | 101250 | 26.9869 | 0.4609 |
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| 0.0955 | 28.0 | 105000 | 27.1919 | 0.4799 |
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| 0.0756 | 29.0 | 108750 | 27.6261 | 0.4870 |
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| 0.0584 | 30.0 | 112500 | 27.9634 | 0.4959 |
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| 0.0386 | 31.0 | 116250 | 0.5041 | 28.1907 |
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| 0.0367 | 32.0 | 120000 | 0.5061 | 28.1162 |
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### Framework versions
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- Transformers 4.44.2
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- Pytorch 2.4.0
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- Datasets 2.21.0
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- Tokenizers 0.19.1
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