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End of training

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  1. README.md +97 -0
  2. generation_config.json +265 -0
README.md ADDED
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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: 2.590564448188711
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+ ---
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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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+
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+ # Whisper Small ko
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+
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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: 0.0041
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+ - Cer: 2.4925
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+ - Wer: 2.5906
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Cer | Wer |
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+ |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
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+ | 3.4996 | 0.89 | 25 | 3.1447 | 75.5887 | 19.7136 |
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+ | 2.655 | 1.79 | 50 | 2.1647 | 74.1483 | 18.1761 |
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+ | 1.7168 | 2.68 | 75 | 1.2822 | 71.8061 | 17.2283 |
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+ | 0.9261 | 3.57 | 100 | 0.6754 | 63.5396 | 51.5586 |
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+ | 0.4707 | 4.46 | 125 | 0.3511 | 40.5686 | 37.3842 |
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+ | 0.2485 | 5.36 | 150 | 0.2027 | 27.9309 | 25.6950 |
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+ | 0.1463 | 6.25 | 175 | 0.1315 | 24.7119 | 23.9890 |
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+ | 0.1022 | 7.14 | 200 | 0.0881 | 21.1924 | 19.9242 |
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+ | 0.0642 | 8.04 | 225 | 0.0501 | 18.7625 | 17.6917 |
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+ | 0.0249 | 8.93 | 250 | 0.0144 | 27.2044 | 26.3479 |
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+ | 0.0056 | 9.82 | 275 | 0.0082 | 12.4749 | 11.9208 |
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+ | 0.0036 | 10.71 | 300 | 0.0067 | 8.5922 | 8.7616 |
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+ | 0.0037 | 11.61 | 325 | 0.0119 | 6.4003 | 6.1500 |
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+ | 0.0021 | 12.5 | 350 | 0.0054 | 3.7450 | 3.6015 |
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+ | 0.0013 | 13.39 | 375 | 0.0052 | 2.8557 | 3.0329 |
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+ | 0.0017 | 14.29 | 400 | 0.0062 | 9.0681 | 8.3825 |
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+ | 0.0016 | 15.18 | 425 | 0.0081 | 4.9098 | 5.3917 |
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+ | 0.0012 | 16.07 | 450 | 0.0108 | 14.5541 | 13.3530 |
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+ | 0.0014 | 16.96 | 475 | 0.0033 | 3.4068 | 3.4120 |
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+ | 0.0005 | 17.86 | 500 | 0.0041 | 2.4925 | 2.5906 |
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+
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+
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+ ### Framework versions
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+
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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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