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README.md
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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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base_model: openai/whisper-small
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tags:
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- generated_from_trainer
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datasets:
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- thisiskeithkwan/canto
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model-index:
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- name: whisper-small-canto
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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-canto
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the thisiskeithkwan/canto dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.5061
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- Cer: 0.4485
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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: 0.0003
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- train_batch_size: 2
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- eval_batch_size: 1
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- seed: 42
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- gradient_accumulation_steps: 16
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- total_train_batch_size: 32
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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: 5000
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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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| 1.5909 | 0.76 | 500 | 1.6890 | 0.7769 |
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| 1.2636 | 1.52 | 1000 | 1.4067 | 0.7641 |
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| 0.7889 | 2.27 | 1500 | 1.3118 | 0.5474 |
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| 0.6929 | 3.03 | 2000 | 1.2825 | 0.5516 |
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| 0.4827 | 3.79 | 2500 | 1.2360 | 0.5446 |
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| 0.236 | 4.55 | 3000 | 1.3457 | 0.5044 |
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| 0.0982 | 5.31 | 3500 | 1.4736 | 0.4841 |
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| 0.064 | 6.07 | 4000 | 1.5103 | 0.4809 |
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| 0.035 | 6.82 | 4500 | 1.5110 | 0.4563 |
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| 0.0103 | 7.58 | 5000 | 1.5061 | 0.4485 |
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### Framework versions
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- Transformers 4.32.0.dev0
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- Pytorch 2.0.1+cu118
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- Datasets 2.14.3
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- Tokenizers 0.13.3
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