| --- |
| library_name: transformers |
| base_model: Kkonjeong/wav2vec2-base-korean |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: audio_cls |
| results: [] |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # audio_cls |
| |
| This model is a fine-tuned version of [Kkonjeong/wav2vec2-base-korean](https://huggingface.co/Kkonjeong/wav2vec2-base-korean) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.6208 |
| - Accuracy: 0.8824 |
| |
| ## Model description |
| |
| More information needed |
| |
| ## Intended uses & limitations |
| |
| More information needed |
| |
| ## Training and evaluation data |
| |
| More information needed |
| |
| ## Training procedure |
| |
| ### Training hyperparameters |
| |
| The following hyperparameters were used during training: |
| - learning_rate: 0.0001 |
| - train_batch_size: 8 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - gradient_accumulation_steps: 2 |
| - total_train_batch_size: 16 |
| - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_ratio: 0.1 |
| - num_epochs: 10 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | 2.6559 | 1.0 | 30 | 2.6296 | 0.0336 | |
| | 2.313 | 2.0 | 60 | 2.2968 | 0.3109 | |
| | 1.8612 | 3.0 | 90 | 1.9956 | 0.4034 | |
| | 1.3741 | 4.0 | 120 | 1.5669 | 0.6134 | |
| | 1.0378 | 5.0 | 150 | 1.2021 | 0.7563 | |
| | 0.7275 | 6.0 | 180 | 1.0009 | 0.7983 | |
| | 0.5482 | 7.0 | 210 | 0.9186 | 0.8235 | |
| | 0.3773 | 8.0 | 240 | 0.7413 | 0.8319 | |
| | 0.285 | 9.0 | 270 | 0.6497 | 0.8655 | |
| | 0.2348 | 10.0 | 300 | 0.6208 | 0.8824 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.56.1 |
| - Pytorch 2.8.0+cu126 |
| - Datasets 4.0.0 |
| - Tokenizers 0.22.0 |
|
|
