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End of training

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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-large-v3
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+ tags:
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+ - hf-asr-leaderboard
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+ - generated_from_trainer
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+ metrics:
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+ - wer
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+ model-index:
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+ - name: whisper_finetune
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+ results: []
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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_finetune
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+
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+ This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the aihub_100000 dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.3754
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+ - Cer: 6.9474
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+ - Wer: 28.5714
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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-08
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+ - train_batch_size: 16
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+ - eval_batch_size: 16
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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: 2000
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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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+ | 0.4274 | 0.14 | 1000 | 0.3982 | 6.9437 | 28.4443 |
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+ | 0.3884 | 0.28 | 2000 | 0.3754 | 6.9474 | 28.5714 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.39.0.dev0
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+ - Pytorch 1.14.0a0+410ce96
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+ - Datasets 2.18.0
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+ - Tokenizers 0.15.2
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