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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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datasets: |
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- SsongSsong/cp-final-project |
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model-index: |
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- name: whisper_ko_finetune100k |
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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_ko_finetune100k |
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This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the ksponspeech dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4177 |
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- Cer: 15.0287 |
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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: 500 |
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- training_steps: 5000 |
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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 | |
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|:-------------:|:-----:|:----:|:---------------:|:-------:| |
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| 0.7481 | 0.03 | 200 | 0.7555 | 44.8484 | |
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| 0.5393 | 0.06 | 400 | 0.5608 | 20.6969 | |
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| 0.5012 | 0.1 | 600 | 0.5293 | 17.3680 | |
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| 0.504 | 0.13 | 800 | 0.5075 | 17.5291 | |
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| 0.4934 | 0.16 | 1000 | 0.4927 | 15.6846 | |
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| 0.4958 | 0.19 | 1200 | 0.4838 | 17.7085 | |
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| 0.4697 | 0.22 | 1400 | 0.4768 | 18.5884 | |
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| 0.4501 | 0.26 | 1600 | 0.4688 | 16.5509 | |
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| 0.4505 | 0.29 | 1800 | 0.4617 | 17.2548 | |
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| 0.4434 | 0.32 | 2000 | 0.4566 | 15.7144 | |
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| 0.4482 | 0.35 | 2200 | 0.4515 | 16.0023 | |
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| 0.4333 | 0.38 | 2400 | 0.4465 | 14.8264 | |
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| 0.433 | 0.42 | 2600 | 0.4444 | 15.2950 | |
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| 0.4027 | 0.45 | 2800 | 0.4406 | 15.3715 | |
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| 0.4181 | 0.48 | 3000 | 0.4376 | 14.8904 | |
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| 0.4209 | 0.51 | 3200 | 0.4336 | 14.7853 | |
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| 0.4535 | 0.54 | 3400 | 0.4303 | 15.2584 | |
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| 0.4301 | 0.58 | 3600 | 0.4280 | 14.8824 | |
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| 0.4474 | 0.61 | 3800 | 0.4255 | 15.2287 | |
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| 0.4024 | 0.64 | 4000 | 0.4244 | 15.2515 | |
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| 0.3891 | 0.67 | 4200 | 0.4224 | 15.8675 | |
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| 0.411 | 0.7 | 4400 | 0.4206 | 15.0230 | |
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| 0.383 | 0.74 | 4600 | 0.4194 | 14.9293 | |
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| 0.4008 | 0.77 | 4800 | 0.4182 | 14.9818 | |
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| 0.4164 | 0.8 | 5000 | 0.4177 | 15.0287 | |
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### Framework versions |
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- Transformers 4.36.0 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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