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Audio Cls Lee

This model is a fine-tuned version of Kkonjeong/wav2vec2-base-korean on an unknown dataset. It achieves the following results on the evaluation set: Loss: 2.6544 Accuracy: 0.0672

TipoOtherModelo baseKkonjeong/wav2vec2-base-koreanVersiónRevision 16367c8Ccalidad

Fuente del modelo

Tipo
Other
Tamaño del archivo
361 MB
Modelo base
Kkonjeong/wav2vec2-base-korean
Versión
vRevision 16367c8
Actualizado
17 oct 2026
Descargas
4
Fuente
Hugging Face

Descripción de la fuente

audio_cls_lee

This model is a fine-tuned version of Kkonjeong/wav2vec2-base-korean on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 2.6544
  • Accuracy: 0.0672

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: 10
  • mixed_precision_training: Native AMP

Training results

Training LossEpochStepValidation LossAccuracy
No log1.0152.63600.1008
No log2.0302.66270.0420
No log3.0452.66690.0420
No log4.0602.65300.0840
No log5.0752.63590.0924
No log6.0902.66680.0504
No log7.01052.64690.0588
No log8.01202.66710.0504
No log9.01352.66960.0504
No log10.01502.65440.0672

Framework versions

  • Transformers 5.0.0
  • Pytorch 2.10.0+cu128
  • Datasets 4.0.0
  • Tokenizers 0.22.2

Fuentes

1 fuente
Hugging FacePrincipalVersión 16367c84ee221578d73b3b3f54db63dbd8aa24ce
huggingface.co/byhylee/audio_cls_lee/tree/16367c84ee221578d73b3b3f54db63dbd8aa24ce

Verificado 29 ago

Artefactos del modelo

1 artefacto

model.safetensors

safetensors · 361 MB · SHA-256 2de9bb28846a…810b · Hugging Face

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Extractos de fuentes

2 extractos

--- library_name: transformers base_model: Kkonjeong/wav2vec2-base-korean tags: - generated_from_trainer metrics: - accuracy model-index: - name: audio_cls_lee 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_lee 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: 2.6544 - Accuracy: 0.0672 ## 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: 10 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | No log | 1.0 | 15 | 2.6360 | 0.1008 | | No log | 2.0 | 30 | 2.6627 | 0.0420 | | No log | 3.0 | 45 | 2.6669 | 0.0420 | | No log | 4.0 | 60 | 2.6530 | 0.0840 | | No log | 5.0 | 75 | 2.6359 | 0.0924 | | No log | 6.0 | 90 | 2.6668 | 0.0504 | | No log | 7.0 | 105 | 2.6469 | 0.0588 | | No log | 8.0 | 120 | 2.6671 | 0.0504 | | No log | 9.0 | 135 | 2.6696 | 0.0504 | | No log | 10.0 | 150 | 2.6544 | 0.0672 | ### Framework versions - Transformers 5.0.0 - Pytorch 2.10.0+cu128 - Datasets 4.0.0 - Tokenizers 0.22.2

Source context: 4 downloads · 0 likes · Pipeline audio-classification · Library transformers · Repo byhylee/audio_cls_lee