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wavlm-telugu-binary
ramesh070/wavlm-telugu-binary
wavlm-telugu-binary is a audio classification model from ramesh070. 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.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Audio Classification
- Library
- transformers
- Model type
- wavlm
- Access
- Public
- Created
- Dec 11, 2025
- Updated
- Dec 11, 2025
- SHA
- bd5d255a
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. -->
wavlm-telugu-binary
This model is a fine-tuned version of microsoft/wavlm-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.7316
- Accuracy: 0.8545
- F1: 0.8919
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 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
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.6782 | 1.0 | 14 | 0.6797 | 0.4727 | 0.3256 |
| 0.6535 | 2.0 | 28 | 0.5998 | 0.7818 | 0.8235 |
| 0.5762 | 3.0 | 42 | 0.4867 | 0.8 | 0.8358 |
| 0.4791 | 4.0 | 56 | 0.5116 | 0.8182 | 0.8611 |
| 0.426 | 5.0 | 70 | 0.5037 | 0.7818 | 0.8182 |
| 0.374 | 6.0 | 84 | 0.4857 | 0.8364 | 0.8696 |
| 0.3461 | 7.0 | 98 | 0.4698 | 0.8182 | 0.8529 |
| 0.3322 | 8.0 | 112 | 0.5055 | 0.8364 | 0.88 |
| 0.201 | 9.0 | 126 | 0.5055 | 0.8545 | 0.8919 |
| 0.1993 | 10.0 | 140 | 0.5239 | 0.8364 | 0.88 |
| 0.2025 | 11.0 | 154 | 0.5181 | 0.8545 | 0.8919 |
| 0.1417 | 12.0 | 168 | 0.6867 | 0.8364 | 0.8861 |
| 0.1162 | 13.0 | 182 | 0.7050 | 0.8364 | 0.8861 |
| 0.1124 | 14.0 | 196 | 0.5492 | 0.8545 | 0.8889 |
| 0.1183 | 15.0 | 210 | 0.7322 | 0.8545 | 0.8974 |
| 0.0693 | 16.0 | 224 | 0.7734 | 0.8545 | 0.8974 |
| 0.0625 | 17.0 | 238 | 0.6903 | 0.8545 | 0.8947 |
| 0.0803 | 18.0 | 252 | 0.7115 | 0.8727 | 0.9091 |
| 0.0354 | 19.0 | 266 | 0.7116 | 0.8364 | 0.88 |
| 0.0486 | 20.0 | 280 | 0.7316 | 0.8545 | 0.8919 |
Framework versions
- Transformers 4.53.3
- Pytorch 2.9.1+cu128
- Datasets 4.4.1
- Tokenizers 0.21.2
- Task
- Audio Classification
- Library
- transformers
- Type
- wavlm
- Created
- Dec 11, 2025
- Updated
- Dec 11, 2025