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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: korean_kws2 |
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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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# korean_kws2 |
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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: 0.2420 |
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- Accuracy: 1.0 |
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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: 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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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| No log | 1.0 | 2 | 1.9137 | 0.0526 | |
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| No log | 2.0 | 4 | 1.7865 | 0.2105 | |
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| No log | 3.0 | 6 | 1.6936 | 0.6842 | |
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| No log | 4.0 | 8 | 1.4829 | 0.6842 | |
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| No log | 5.0 | 10 | 1.2932 | 0.7895 | |
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| No log | 6.0 | 12 | 1.1308 | 0.9474 | |
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| No log | 7.0 | 14 | 1.0253 | 1.0 | |
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| No log | 8.0 | 16 | 0.9139 | 1.0 | |
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| No log | 9.0 | 18 | 0.8465 | 1.0 | |
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| No log | 10.0 | 20 | 0.7344 | 1.0 | |
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| No log | 11.0 | 22 | 0.6424 | 1.0 | |
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| No log | 12.0 | 24 | 0.5767 | 1.0 | |
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| No log | 13.0 | 26 | 0.5231 | 1.0 | |
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| No log | 14.0 | 28 | 0.4666 | 1.0 | |
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| No log | 15.0 | 30 | 0.4239 | 1.0 | |
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| No log | 16.0 | 32 | 0.3941 | 1.0 | |
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| No log | 17.0 | 34 | 0.3693 | 1.0 | |
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| No log | 18.0 | 36 | 0.3435 | 1.0 | |
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| No log | 19.0 | 38 | 0.3264 | 1.0 | |
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| No log | 20.0 | 40 | 0.3090 | 1.0 | |
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| No log | 21.0 | 42 | 0.2942 | 1.0 | |
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| No log | 22.0 | 44 | 0.2827 | 1.0 | |
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| No log | 23.0 | 46 | 0.2750 | 1.0 | |
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| No log | 24.0 | 48 | 0.2666 | 1.0 | |
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| No log | 25.0 | 50 | 0.2599 | 1.0 | |
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| No log | 26.0 | 52 | 0.2537 | 1.0 | |
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| No log | 27.0 | 54 | 0.2482 | 1.0 | |
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| No log | 28.0 | 56 | 0.2446 | 1.0 | |
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| No log | 29.0 | 58 | 0.2427 | 1.0 | |
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| No log | 30.0 | 60 | 0.2420 | 1.0 | |
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### Framework versions |
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- Transformers 4.56.1 |
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- Pytorch 2.8.0+cu126 |
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- Datasets 4.0.0 |
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- Tokenizers 0.22.0 |
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