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--- |
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language: |
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- hi |
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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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- hf-asr-leaderboard |
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- generated_from_trainer |
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datasets: |
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- aihub_adult_speed |
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model-index: |
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- name: whisper-small-ko-Yspeed2 |
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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-ko-Yspeed2 |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the aihub adult speed changed dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2744 |
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- Cer: 10.9845 |
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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: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 16 |
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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: 50 |
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- num_epochs: 2 |
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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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| 0.4529 | 0.13 | 100 | 0.3102 | 7.5952 | |
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| 0.2772 | 0.26 | 200 | 0.2821 | 9.2164 | |
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| 0.2264 | 0.39 | 300 | 0.2872 | 8.2942 | |
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| 0.2172 | 0.52 | 400 | 0.2665 | 7.7185 | |
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| 0.1956 | 0.64 | 500 | 0.2784 | 10.5263 | |
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| 0.17 | 0.77 | 600 | 0.2786 | 9.4866 | |
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| 0.1787 | 0.9 | 700 | 0.2761 | 11.3017 | |
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| 0.0818 | 1.03 | 800 | 0.2732 | 10.0270 | |
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| 0.0616 | 1.16 | 900 | 0.2732 | 9.1753 | |
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| 0.0721 | 1.29 | 1000 | 0.2763 | 10.6732 | |
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| 0.0661 | 1.42 | 1100 | 0.2798 | 15.2432 | |
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| 0.0768 | 1.55 | 1200 | 0.2730 | 13.8393 | |
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| 0.0602 | 1.68 | 1300 | 0.2714 | 11.5484 | |
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| 0.0667 | 1.81 | 1400 | 0.2730 | 13.0933 | |
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| 0.0675 | 1.93 | 1500 | 0.2744 | 10.9845 | |
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### Framework versions |
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- Transformers 4.36.0.dev0 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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