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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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model-index: |
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- name: Whisper Small ko-Yfreq-E - syp1229 |
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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-Yfreq-E - syp1229 |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the aihub Y E dialogue dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2157 |
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- Cer: 0.0491 |
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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: 2e-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: 5 |
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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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| 0.2455 | 0.3 | 100 | 0.2528 | 0.0663 | |
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| 0.2591 | 0.59 | 200 | 0.2452 | 0.0646 | |
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| 0.1702 | 0.89 | 300 | 0.2298 | 0.0628 | |
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| 0.0738 | 1.19 | 400 | 0.2136 | 0.0923 | |
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| 0.0957 | 1.48 | 500 | 0.2263 | 0.0618 | |
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| 0.0729 | 1.78 | 600 | 0.2139 | 0.0565 | |
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| 0.0242 | 2.07 | 700 | 0.2073 | 0.0520 | |
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| 0.028 | 2.37 | 800 | 0.2063 | 0.0482 | |
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| 0.0351 | 2.67 | 900 | 0.2162 | 0.0506 | |
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| 0.0239 | 2.96 | 1000 | 0.2075 | 0.0513 | |
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| 0.0088 | 3.26 | 1100 | 0.2194 | 0.0495 | |
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| 0.0079 | 3.56 | 1200 | 0.2187 | 0.0508 | |
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| 0.0072 | 3.85 | 1300 | 0.2217 | 0.0510 | |
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| 0.0046 | 4.15 | 1400 | 0.2164 | 0.0488 | |
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| 0.0038 | 4.44 | 1500 | 0.2149 | 0.0490 | |
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| 0.003 | 4.74 | 1600 | 0.2157 | 0.0491 | |
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### Framework versions |
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- Transformers 4.34.0.dev0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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