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SERENE
mali111222333/SERENE
SERENE is a audio classification model from mali111222333. Use it for the audio classification task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Audio Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- wav2vec2
- Access
- Public
- Created
- Aug 20, 2025
- Updated
- Oct 8, 2025
- SHA
- b0c390cb
Base models
Model card
From the Hugging Face model README
<!-- 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. -->
SERENE
This model is a fine-tuned version of facebook/wav2vec2-base on the mali111222333/SERENE_DATA dataset. It achieves the following results on the evaluation set:
- Loss: 0.5125
- Accuracy: 0.8262
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: 32
- eval_batch_size: 32
- seed: 0
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- 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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.001 | 1.0 | 103 | 2.0125 | 0.3141 |
| 1.4204 | 2.0 | 206 | 1.5098 | 0.5219 |
| 1.1139 | 3.0 | 309 | 1.1529 | 0.6792 |
| 0.9586 | 4.0 | 412 | 0.9849 | 0.7157 |
| 0.9062 | 5.0 | 515 | 0.9828 | 0.6956 |
| 0.8295 | 6.0 | 618 | 0.8643 | 0.7236 |
| 0.7713 | 7.0 | 721 | 0.7047 | 0.7722 |
| 0.7446 | 8.0 | 824 | 0.6894 | 0.7861 |
| 0.7021 | 9.0 | 927 | 0.6706 | 0.7837 |
| 0.7081 | 10.0 | 1030 | 0.6263 | 0.8026 |
| 0.646 | 11.0 | 1133 | 0.5994 | 0.7977 |
| 0.6489 | 12.0 | 1236 | 0.5866 | 0.8026 |
| 0.6152 | 13.0 | 1339 | 0.5655 | 0.8074 |
| 0.6346 | 14.0 | 1442 | 0.5525 | 0.8202 |
| 0.6076 | 15.0 | 1545 | 0.5299 | 0.8250 |
| 0.5924 | 16.0 | 1648 | 0.5210 | 0.8238 |
| 0.6078 | 17.0 | 1751 | 0.5254 | 0.8232 |
| 0.5703 | 18.0 | 1854 | 0.5128 | 0.8232 |
| 0.6421 | 19.0 | 1957 | 0.5197 | 0.8220 |
| 0.5085 | 20.0 | 2060 | 0.5125 | 0.8262 |
Framework versions
- Transformers 4.57.0.dev0
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1
- Task
- Audio Classification
- Library
- transformers
- Type
- wav2vec2
- License
- apache-2.0
- Created
- Aug 20, 2025
- Updated
- Oct 8, 2025