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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-base |
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tags: |
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- hf-asr-leaderboard |
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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_finetune |
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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_finetune |
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This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the aihub_1 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3707 |
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- Cer: 12.6289 |
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- Wer: 36.7564 |
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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: 16 |
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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: 4000 |
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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 | Wer | |
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|:-------------:|:-----:|:----:|:-------:|:---------------:|:-------:| |
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| 0.2787 | 0.32 | 500 | 14.5190 | 0.4086 | 39.9745 | |
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| 0.2996 | 0.64 | 1000 | 13.7403 | 0.3984 | 38.7252 | |
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| 0.3226 | 0.96 | 1500 | 13.8005 | 0.3772 | 38.4629 | |
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| 0.2281 | 1.28 | 2000 | 13.0192 | 0.3682 | 37.1511 | |
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| 0.2242 | 1.6 | 2500 | 12.9577 | 0.3762 | 37.2961 | |
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| 0.2284 | 1.92 | 3000 | 0.3733 | 12.7289 | 36.4465 | |
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| 0.1648 | 2.24 | 3500 | 0.3720 | 12.8054 | 36.9687 | |
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| 0.173 | 2.56 | 4000 | 0.3707 | 12.6289 | 36.7564 | |
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### Framework versions |
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- Transformers 4.37.0.dev0 |
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- Pytorch 1.12.1+cu113 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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