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--- |
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language: |
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- ko |
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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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- whisper-event |
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- generated_from_trainer |
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datasets: |
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- GGarri/customdataset |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Small ko |
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results: |
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- task: |
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name: Automatic Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: customdata |
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type: GGarri/customdataset |
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metrics: |
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- name: Wer |
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type: wer |
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value: 2.590564448188711 |
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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 ko |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the customdata dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0041 |
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- Cer: 2.4925 |
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- Wer: 2.5906 |
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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: 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: 500 |
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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 | Cer | Wer | |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:| |
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| 3.4996 | 0.89 | 25 | 3.1447 | 75.5887 | 19.7136 | |
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| 2.655 | 1.79 | 50 | 2.1647 | 74.1483 | 18.1761 | |
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| 1.7168 | 2.68 | 75 | 1.2822 | 71.8061 | 17.2283 | |
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| 0.9261 | 3.57 | 100 | 0.6754 | 63.5396 | 51.5586 | |
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| 0.4707 | 4.46 | 125 | 0.3511 | 40.5686 | 37.3842 | |
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| 0.2485 | 5.36 | 150 | 0.2027 | 27.9309 | 25.6950 | |
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| 0.1463 | 6.25 | 175 | 0.1315 | 24.7119 | 23.9890 | |
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| 0.1022 | 7.14 | 200 | 0.0881 | 21.1924 | 19.9242 | |
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| 0.0642 | 8.04 | 225 | 0.0501 | 18.7625 | 17.6917 | |
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| 0.0249 | 8.93 | 250 | 0.0144 | 27.2044 | 26.3479 | |
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| 0.0056 | 9.82 | 275 | 0.0082 | 12.4749 | 11.9208 | |
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| 0.0036 | 10.71 | 300 | 0.0067 | 8.5922 | 8.7616 | |
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| 0.0037 | 11.61 | 325 | 0.0119 | 6.4003 | 6.1500 | |
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| 0.0021 | 12.5 | 350 | 0.0054 | 3.7450 | 3.6015 | |
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| 0.0013 | 13.39 | 375 | 0.0052 | 2.8557 | 3.0329 | |
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| 0.0017 | 14.29 | 400 | 0.0062 | 9.0681 | 8.3825 | |
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| 0.0016 | 15.18 | 425 | 0.0081 | 4.9098 | 5.3917 | |
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| 0.0012 | 16.07 | 450 | 0.0108 | 14.5541 | 13.3530 | |
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| 0.0014 | 16.96 | 475 | 0.0033 | 3.4068 | 3.4120 | |
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| 0.0005 | 17.86 | 500 | 0.0041 | 2.4925 | 2.5906 | |
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### Framework versions |
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- Transformers 4.39.2 |
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- Pytorch 2.0.1 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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