Audio Cls33
This model is a fine-tuned version of Kkonjeong/wav2vec2-base-korean on an unknown dataset.
Modellquelle
- Art
- Other
- Dateigröße
- 361 MB
- Basismodell
- Kkonjeong/wav2vec2-base-korean
- Version
- vRevision aac221c
- Aktualisiert
- 31. Okt. 2026
- Downloads
- 5
- Quelle
- Hugging Face
Quellenbeschreibung
audio_cls33
This model is a fine-tuned version of Kkonjeong/wav2vec2-base-korean on an unknown dataset.
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
Framework versions
- Transformers 5.0.0
- Pytorch 2.11.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2
Quellen
1 Quelle
Quellen
1 QuelleVerifiziert 31. Okt.
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Modellartefakte
1 Artefakt
Modellartefakte
1 Artefaktmodel.safetensors
safetensors · FP32 (unverified) · 361 MB · SHA-256 83a3d0b1ee77…c282 · Hugging Face
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Quellenauszüge
3 Auszüge--- library_name: transformers base_model: Kkonjeong/wav2vec2-base-korean tags: - generated_from_trainer model-index: - name: audio_cls33 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_cls33 This model is a fine-tuned version of [Kkonjeong/wav2vec2-base-korean](https://huggingface.co/Kkonjeong/wav2vec2-base-korean) on an unknown dataset. ## 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 ### Framework versions - Transformers 5.0.0 - Pytorch 2.11.0+cu128 - Datasets 4.0.0 - Tokenizers 0.22.2
Source context: 5 downloads · 1 likes · Pipeline audio-classification · Library transformers · Repo eunseonii/audio_cls33
Source context: 7 downloads · 1 likes · Pipeline audio-classification · Library transformers · Repo eunseonii/audio_cls33
