| | --- |
| | library_name: transformers |
| | base_model: Kkonjeong/wav2vec2-base-korean |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: korean_kws |
| | 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. --> |
| |
|
| | # korean_kws |
| | |
| | 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: 0.3329 |
| | - Accuracy: 1.0 |
| | |
| | ## 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: 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: 30 |
| | - mixed_precision_training: Native AMP |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | | No log | 1.0 | 2 | 1.9572 | 0.0769 | |
| | | No log | 2.0 | 4 | 1.9177 | 0.2308 | |
| | | No log | 3.0 | 6 | 1.8590 | 0.3077 | |
| | | No log | 4.0 | 8 | 1.7834 | 0.3846 | |
| | | No log | 5.0 | 10 | 1.7145 | 0.3846 | |
| | | No log | 6.0 | 12 | 1.5883 | 0.6154 | |
| | | No log | 7.0 | 14 | 1.4392 | 0.9231 | |
| | | No log | 8.0 | 16 | 1.3025 | 1.0 | |
| | | No log | 9.0 | 18 | 1.1472 | 1.0 | |
| | | No log | 10.0 | 20 | 1.0278 | 1.0 | |
| | | No log | 11.0 | 22 | 0.9255 | 1.0 | |
| | | No log | 12.0 | 24 | 0.8274 | 1.0 | |
| | | No log | 13.0 | 26 | 0.7610 | 1.0 | |
| | | No log | 14.0 | 28 | 0.6741 | 1.0 | |
| | | No log | 15.0 | 30 | 0.6269 | 1.0 | |
| | | No log | 16.0 | 32 | 0.6036 | 1.0 | |
| | | No log | 17.0 | 34 | 0.5516 | 1.0 | |
| | | No log | 18.0 | 36 | 0.5066 | 1.0 | |
| | | No log | 19.0 | 38 | 0.4697 | 1.0 | |
| | | No log | 20.0 | 40 | 0.4436 | 1.0 | |
| | | No log | 21.0 | 42 | 0.4216 | 1.0 | |
| | | No log | 22.0 | 44 | 0.4011 | 1.0 | |
| | | No log | 23.0 | 46 | 0.3842 | 1.0 | |
| | | No log | 24.0 | 48 | 0.3702 | 1.0 | |
| | | No log | 25.0 | 50 | 0.3588 | 1.0 | |
| | | No log | 26.0 | 52 | 0.3501 | 1.0 | |
| | | No log | 27.0 | 54 | 0.3434 | 1.0 | |
| | | No log | 28.0 | 56 | 0.3383 | 1.0 | |
| | | No log | 29.0 | 58 | 0.3348 | 1.0 | |
| | | No log | 30.0 | 60 | 0.3329 | 1.0 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.57.3 |
| | - Pytorch 2.9.0+cu126 |
| | - Datasets 4.0.0 |
| | - Tokenizers 0.22.1 |
| | |
