Skip to content
ModelListedExternal
Download

Korean Kws

This model is a fine-tuned version of Kkonjeong/wav2vec2-base-korean on the None dataset. It achieves the following results on the evaluation set: Loss: 0.3329 Accuracy: 1.0

KindOtherBase modelKkonjeong/wav2vec2-base-koreanVersionRevision 647d1ab

Model source

Kind
Other
File size
361 MB
Base model
Kkonjeong/wav2vec2-base-korean
Version
vRevision 647d1ab
Updated
Sep 19, 2026
Downloads
8
Source
Hugging Face

Source description

korean_kws

This model is a fine-tuned version of 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 LossEpochStepValidation LossAccuracy
No log1.021.95720.0769
No log2.041.91770.2308
No log3.061.85900.3077
No log4.081.78340.3846
No log5.0101.71450.3846
No log6.0121.58830.6154
No log7.0141.43920.9231
No log8.0161.30251.0
No log9.0181.14721.0
No log10.0201.02781.0
No log11.0220.92551.0
No log12.0240.82741.0
No log13.0260.76101.0
No log14.0280.67411.0
No log15.0300.62691.0
No log16.0320.60361.0
No log17.0340.55161.0
No log18.0360.50661.0
No log19.0380.46971.0
No log20.0400.44361.0
No log21.0420.42161.0
No log22.0440.40111.0
No log23.0460.38421.0
No log24.0480.37021.0
No log25.0500.35881.0
No log26.0520.35011.0
No log27.0540.34341.0
No log28.0560.33831.0
No log29.0580.33481.0
No log30.0600.33291.0

Framework versions

  • Transformers 4.57.3
  • Pytorch 2.9.0+cu126
  • Datasets 4.0.0
  • Tokenizers 0.22.1

Sources

1 source
Hugging FacePrimaryVersion 647d1ab9a6b029da0400426db28b0931b5b11005
huggingface.co/alwaysnotavailable/korean_kws/tree/647d1ab9a6b029da0400426db28b0931b5b11005

Verified Sep 19

Model artifacts

1 artifact

model.safetensors

safetensors · 361 MB · SHA-256 27a339fc0315…6f5a · Hugging Face

Download

Source excerpts

2 excerpts

--- 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 | |...

Source context: 8 downloads · 0 likes · Pipeline audio-classification · Library transformers · Repo alwaysnotavailable/korean_kws