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---
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language:
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- zh
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license: apache-2.0
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tags:
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- whisper
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- generated_from_trainer
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datasets:
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- '-'
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model-index:
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- name: whisper-base-zh-20230721 - au2a
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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-base-zh-20230721 - au2a
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This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the some hakka audio dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4546
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- Cer: 16.5974
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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: 5e-06
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- train_batch_size: 32
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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: 500
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- training_steps: 10000
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Cer |
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|:-------------:|:-----:|:-----:|:---------------:|:-------:|
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| 0.4669 | 0.65 | 1000 | 0.6528 | 25.0548 |
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| 0.2208 | 1.29 | 2000 | 0.5006 | 19.8761 |
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| 0.1452 | 1.94 | 3000 | 0.4546 | 17.9497 |
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| 0.0951 | 2.59 | 4000 | 0.4431 | 17.4511 |
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| 0.0526 | 3.24 | 5000 | 0.4450 | 17.3113 |
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| 0.0422 | 3.88 | 6000 | 0.4440 | 16.6201 |
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| 0.0271 | 4.53 | 7000 | 0.4471 | 17.0658 |
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| 0.0179 | 5.18 | 8000 | 0.4509 | 16.5823 |
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| 0.0166 | 5.83 | 9000 | 0.4535 | 16.8543 |
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| 0.0129 | 6.47 | 10000 | 0.4546 | 16.5974 |
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### Framework versions
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- Transformers 4.30.2
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- Pytorch 2.0.1+cu117
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- Datasets 2.13.1
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- Tokenizers 0.13.3
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