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--- |
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library_name: transformers |
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base_model: fleek/wav2vec-large-xlsr-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: wav2vec2-xlsr-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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# wav2vec2-xlsr-korean-dialect-recognition |
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This model is a fine-tuned version of [fleek/wav2vec-large-xlsr-korean](https://huggingface.co/fleek/wav2vec-large-xlsr-korean) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5291 |
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- Accuracy: 0.8063 |
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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: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 8 |
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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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- num_epochs: 1 |
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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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| 2.8542 | 0.0681 | 100 | 1.4936 | 0.3803 | |
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| 1.9555 | 0.1362 | 200 | 1.1916 | 0.5237 | |
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| 2.3132 | 0.2043 | 300 | 0.9826 | 0.6180 | |
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| 1.8724 | 0.2724 | 400 | 0.9512 | 0.6411 | |
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| 1.9331 | 0.3405 | 500 | 0.8138 | 0.6857 | |
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| 1.6761 | 0.4086 | 600 | 0.7749 | 0.6932 | |
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| 1.7902 | 0.4767 | 700 | 0.7694 | 0.7028 | |
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| 1.9041 | 0.5448 | 800 | 0.7199 | 0.7194 | |
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| 1.8659 | 0.6129 | 900 | 0.7010 | 0.7382 | |
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| 1.9123 | 0.6810 | 1000 | 0.6067 | 0.7753 | |
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| 1.2564 | 0.7491 | 1100 | 0.6073 | 0.7726 | |
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| 0.8368 | 0.8172 | 1200 | 0.6203 | 0.7729 | |
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| 1.1841 | 0.8853 | 1300 | 0.5312 | 0.7988 | |
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| 1.0372 | 0.9534 | 1400 | 0.5291 | 0.8063 | |
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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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