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End of training

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README.md ADDED
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+ ---
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+ library_name: transformers
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+ base_model: Kkonjeong/wav2vec2-base-korean
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: wks
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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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+ # wks
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+
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+ This model is a fine-tuned version of [Kkonjeong/wav2vec2-base-korean](https://huggingface.co/Kkonjeong/wav2vec2-base-korean) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.3852
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+ - Accuracy: 0.9474
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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: 0.0001
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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: 4
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+ - total_train_batch_size: 32
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+ - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: linear
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+ - num_epochs: 30
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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 | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | No log | 1.0 | 2 | 1.8512 | 0.1579 |
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+ | No log | 2.0 | 4 | 1.8512 | 0.1579 |
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+ | No log | 3.0 | 6 | 1.7512 | 0.4211 |
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+ | No log | 4.0 | 8 | 1.6830 | 0.3684 |
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+ | No log | 5.0 | 10 | 1.5444 | 0.6316 |
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+ | No log | 6.0 | 12 | 1.4469 | 0.4737 |
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+ | No log | 7.0 | 14 | 1.3275 | 0.6316 |
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+ | No log | 8.0 | 16 | 1.1882 | 0.8421 |
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+ | No log | 9.0 | 18 | 1.0719 | 0.8421 |
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+ | No log | 10.0 | 20 | 1.0585 | 0.8421 |
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+ | No log | 11.0 | 22 | 1.0017 | 0.8947 |
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+ | No log | 12.0 | 24 | 0.9294 | 0.8947 |
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+ | No log | 13.0 | 26 | 0.8423 | 0.8947 |
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+ | No log | 14.0 | 28 | 0.7696 | 0.8421 |
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+ | No log | 15.0 | 30 | 0.7280 | 0.8947 |
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+ | No log | 16.0 | 32 | 0.6871 | 0.9474 |
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+ | No log | 17.0 | 34 | 0.6423 | 0.9474 |
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+ | No log | 18.0 | 36 | 0.6102 | 0.9474 |
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+ | No log | 19.0 | 38 | 0.5863 | 0.9474 |
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+ | No log | 20.0 | 40 | 0.5561 | 0.9474 |
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+ | No log | 21.0 | 42 | 0.5284 | 0.9474 |
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+ | No log | 22.0 | 44 | 0.5049 | 0.9474 |
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+ | No log | 23.0 | 46 | 0.4834 | 0.9474 |
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+ | No log | 24.0 | 48 | 0.4601 | 0.9474 |
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+ | No log | 25.0 | 50 | 0.4384 | 0.9474 |
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+ | No log | 26.0 | 52 | 0.4260 | 0.9474 |
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+ | No log | 27.0 | 54 | 0.4083 | 0.9474 |
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+ | No log | 28.0 | 56 | 0.3979 | 0.9474 |
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+ | No log | 29.0 | 58 | 0.3931 | 0.9474 |
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+ | No log | 30.0 | 60 | 0.3852 | 0.9474 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.57.3
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+ - Pytorch 2.9.0+cu126
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+ - Datasets 4.0.0
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+ - Tokenizers 0.22.1
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