Audio Cls1
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: 2.0407 Accuracy: 0.5546
Model source
- Kind
- Other
- File size
- 361 MB
- Base model
- Kkonjeong/wav2vec2-base-korean
- Version
- vRevision 2b105b6
- Updated
- Oct 31, 2026
- Downloads
- 4
- Source
- Hugging Face
Source description
audio_cls1
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: 2.0407
- Accuracy: 0.5546
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 | 15 | 2.6522 | 0.0420 |
| No log | 2.0 | 30 | 2.6192 | 0.0672 |
| No log | 3.0 | 45 | 2.5423 | 0.2101 |
| No log | 4.0 | 60 | 2.4174 | 0.2437 |
| No log | 5.0 | 75 | 2.3224 | 0.3697 |
| No log | 6.0 | 90 | 2.2396 | 0.3866 |
| No log | 7.0 | 105 | 2.1535 | 0.4538 |
| No log | 8.0 | 120 | 2.1064 | 0.4790 |
| No log | 9.0 | 135 | 2.0601 | 0.5042 |
| No log | 10.0 | 150 | 2.0407 | 0.5546 |
Framework versions
- Transformers 5.0.0
- Pytorch 2.11.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2
Sources
1 source
Sources
1 sourceVerified Oct 31
Download files
Repository files
File inventory only; completeness is unverified.
Model artifacts
1 artifact
Model artifacts
1 artifactmodel.safetensors
safetensors · FP32 (unverified) · 361 MB · SHA-256 327909a04181…99e3 · Hugging Face
Download fileSource excerpts
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Source excerpts
3 excerpts--- library_name: transformers base_model: Kkonjeong/wav2vec2-base-korean tags: - generated_from_trainer metrics: - accuracy model-index: - name: audio_cls1 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_cls1 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: 2.0407 - Accuracy: 0.5546 ## 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 | 15 | 2.6522 | 0.0420 | | No log | 2.0 | 30 | 2.6192 | 0.0672 | | No log | 3.0 | 45 | 2.5423 | 0.2101 | | No log | 4.0 | 60 | 2.4174 | 0.2437 | | No log | 5.0 | 75 | 2.3224 | 0.3697 | | No log | 6.0 | 90 | 2.2396 | 0.3866 | | No log | 7.0 | 105 | 2.1535 | 0.4538 | | No log | 8.0 | 120 | 2.1064 | 0.4790 | | No log | 9.0 | 135 | 2.0601 | 0.5042 | | No log | 10.0 | 150 | 2.0407 | 0.5546 | ### Framework versions - Transformers 5.0.0 - Pytorch 2.11.0+cu128 - Datasets 4.0.0 - Tokenizers 0.22.2
Source context: 4 downloads · 3 likes · Pipeline audio-classification · Library transformers · Repo seging/audio_cls1
Source context: 5 downloads · 3 likes · Pipeline audio-classification · Library transformers · Repo seging/audio_cls1
