| --- |
| library_name: transformers |
| base_model: Kkonjeong/wav2vec2-base-korean |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: audio_cls2 |
| 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_cls2 |
| |
| This model is a fine-tuned version of [Kkonjeong/wav2vec2-base-korean](https://huggingface.co/Kkonjeong/wav2vec2-base-korean) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 1.9947 |
| - Accuracy: 0.1538 |
| |
| ## 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: 3e-05 |
| - train_batch_size: 8 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - gradient_accumulation_steps: 4 |
| - total_train_batch_size: 32 |
| - 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 |
| - num_epochs: 10 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | No log | 1.0 | 2 | 1.9488 | 0.4615 | |
| | No log | 2.0 | 4 | 1.9549 | 0.0769 | |
| | No log | 3.0 | 6 | 1.9348 | 0.1538 | |
| | No log | 4.0 | 8 | 1.9568 | 0.1538 | |
| | No log | 5.0 | 10 | 1.9823 | 0.0 | |
| | No log | 6.0 | 12 | 1.9865 | 0.1538 | |
| | No log | 7.0 | 14 | 1.9931 | 0.1538 | |
| | No log | 8.0 | 16 | 1.9951 | 0.1538 | |
| | No log | 9.0 | 18 | 1.9933 | 0.1538 | |
| | No log | 10.0 | 20 | 1.9947 | 0.1538 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 5.10.2 |
| - Pytorch 2.12.0+cu130 |
| - Datasets 4.8.5 |
| - Tokenizers 0.22.2 |
| |
