Instructions to use newhuman333/audio_cls_1016 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use newhuman333/audio_cls_1016 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="newhuman333/audio_cls_1016")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("newhuman333/audio_cls_1016") model = AutoModelForAudioClassification.from_pretrained("newhuman333/audio_cls_1016", device_map="auto") - Notebooks
- Google Colab
- Kaggle
audio_cls_1016
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: 2.6623
- Accuracy: 0.0504
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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 8
- 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 | 2.6608 | 0.0588 |
| No log | 2.0 | 30 | 2.6641 | 0.0504 |
| No log | 3.0 | 45 | 2.6447 | 0.1008 |
| No log | 4.0 | 60 | 2.6730 | 0.0504 |
| No log | 5.0 | 75 | 2.6671 | 0.0504 |
| No log | 6.0 | 90 | 2.6588 | 0.0504 |
| No log | 7.0 | 105 | 2.6576 | 0.0504 |
| No log | 8.0 | 120 | 2.6617 | 0.0504 |
| No log | 9.0 | 135 | 2.6617 | 0.0504 |
| No log | 10.0 | 150 | 2.6623 | 0.0504 |
Framework versions
- Transformers 5.18.0
- Pytorch 2.11.0+cu130
- Datasets 4.8.5
- Tokenizers 0.23.2
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Model tree for newhuman333/audio_cls_1016
Base model
Kkonjeong/wav2vec2-base-korean