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Audio Cls1

This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set: Loss: 0.9874 Accuracy: 0.8655

ArtOtherVersionRevision ccba835BBewertung

Modellquelle

Art
Other
Dateigröße
361 MB
Version
vRevision ccba835
Aktualisiert
31. Okt. 2026
Downloads
3
Quelle
Hugging Face

Quellenbeschreibung

audio_cls1

This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.9874
  • Accuracy: 0.8655

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 LossEpochStepValidation LossAccuracy
No log1.0151.74180.7311
No log2.0301.57770.8487
No log3.0451.39380.8487
No log4.0601.27070.8824
No log5.0751.20290.8739
No log6.0901.10320.8739
No log7.01051.05730.8739
No log8.01201.02370.8739
No log9.01350.99640.8739
No log10.01500.98740.8655

Framework versions

  • Transformers 5.0.0
  • Pytorch 2.11.0+cu128
  • Datasets 4.0.0
  • Tokenizers 0.22.2

Quellen

1 Quelle
Hugging FacePrimärVersion ccba835d470c62fbbd9b6963c823472e1605c66e
huggingface.co/sumini1/audio_cls1/tree/ccba835d470c62fbbd9b6963c823472e1605c66e

Verifiziert 31. Okt.

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Modellartefakte

1 Artefakt

model.safetensors

safetensors · FP32 (unverified) · 361 MB · SHA-256 db0eab0a62da…ad41 · Hugging Face

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--- library_name: transformers 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 was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.9874 - Accuracy: 0.8655 ## 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 | 1.7418 | 0.7311 | | No log | 2.0 | 30 | 1.5777 | 0.8487 | | No log | 3.0 | 45 | 1.3938 | 0.8487 | | No log | 4.0 | 60 | 1.2707 | 0.8824 | | No log | 5.0 | 75 | 1.2029 | 0.8739 | | No log | 6.0 | 90 | 1.1032 | 0.8739 | | No log | 7.0 | 105 | 1.0573 | 0.8739 | | No log | 8.0 | 120 | 1.0237 | 0.8739 | | No log | 9.0 | 135 | 0.9964 | 0.8739 | | No log | 10.0 | 150 | 0.9874 | 0.8655 | ### Framework versions - Transformers 5.0.0 - Pytorch 2.11.0+cu128 - Datasets 4.0.0 - Tokenizers 0.22.2

Source context: 3 downloads · 0 likes · Pipeline audio-classification · Library transformers · Repo sumini1/audio_cls1

Source context: 5 downloads · 0 likes · Pipeline audio-classification · Library transformers · Repo sumini1/audio_cls1