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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: 6.9309637730690365 |
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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: 0.0268 |
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- Cer: 6.5045 |
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- Wer: 6.9310 |
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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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| 3.6391 | 0.54 | 25 | 3.3230 | 83.6552 | 35.4340 | |
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| 2.7648 | 1.09 | 50 | 2.3011 | 81.2725 | 31.6473 | |
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| 1.8272 | 1.63 | 75 | 1.4490 | 85.9460 | 43.8688 | |
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| 1.0827 | 2.17 | 100 | 0.8137 | 72.8033 | 59.1524 | |
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| 0.6201 | 2.72 | 125 | 0.4756 | 50.5476 | 49.9522 | |
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| 0.3539 | 3.26 | 150 | 0.3005 | 31.1094 | 31.5926 | |
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| 0.2358 | 3.8 | 175 | 0.1969 | 29.5962 | 31.3192 | |
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| 0.1501 | 4.35 | 200 | 0.1352 | 21.1688 | 21.7772 | |
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| 0.0967 | 4.89 | 225 | 0.0846 | 18.6941 | 19.0431 | |
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| 0.0471 | 5.43 | 250 | 0.0350 | 18.3931 | 18.9200 | |
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| 0.0162 | 5.98 | 275 | 0.0335 | 18.9616 | 19.5215 | |
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| 0.0121 | 6.52 | 300 | 0.0324 | 14.1293 | 15.5707 | |
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| 0.011 | 7.07 | 325 | 0.0261 | 12.9755 | 14.3267 | |
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| 0.0078 | 7.61 | 350 | 0.0223 | 9.3220 | 10.5400 | |
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| 0.0075 | 8.15 | 375 | 0.0217 | 5.8106 | 6.5482 | |
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| 0.0052 | 8.7 | 400 | 0.0208 | 7.9926 | 8.6945 | |
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| 0.0048 | 9.24 | 425 | 0.0213 | 5.3424 | 5.7280 | |
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| 0.0053 | 9.78 | 450 | 0.0212 | 7.5328 | 7.9973 | |
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| 0.004 | 10.33 | 475 | 0.0213 | 5.7186 | 5.9740 | |
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| 0.0054 | 10.87 | 500 | 0.0268 | 6.5045 | 6.9310 | |
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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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