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README.md
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---
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library_name: transformers
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license: mit
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base_model: facebook/w2v-bert-2.0
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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: wav2vec-bert-korean-dialect-recognition
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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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# wav2vec-bert-korean-dialect-recognition
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This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.7014
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- Accuracy: 0.7415
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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: 5e-05
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- train_batch_size: 4
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- eval_batch_size: 4
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- seed: 42
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- optimizer: Use OptimizerNames.ADAMW_TORCH 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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- lr_scheduler_warmup_steps: 500
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- num_epochs: 10
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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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| 1.1772 | 1.0 | 32734 | 0.9692 | 0.6393 |
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| 1.1915 | 2.0 | 65468 | 0.8570 | 0.6765 |
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| 1.198 | 3.0 | 98202 | 0.7810 | 0.7097 |
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| 1.2072 | 4.0 | 130936 | 0.7748 | 0.7121 |
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| 1.2897 | 5.0 | 163670 | 0.7394 | 0.7252 |
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| 1.206 | 6.0 | 196404 | 0.7457 | 0.7196 |
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| 1.0204 | 7.0 | 229138 | 0.7299 | 0.7273 |
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| 1.1207 | 8.0 | 261872 | 0.7225 | 0.7330 |
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| 1.3417 | 9.0 | 294606 | 0.6936 | 0.7450 |
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| 1.1021 | 10.0 | 327340 | 0.7014 | 0.7415 |
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### Framework versions
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- Transformers 4.47.1
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- Pytorch 2.5.1+cu124
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- Datasets 3.2.0
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- Tokenizers 0.21.0
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