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indic-slid-mhubert-task2
Saad-Wazir24/indic-slid-mhubert-task2
indic-slid-mhubert-task2 is a audio classification model from Saad-Wazir24. 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 cc-by-nc-sa-4.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Audio Classification
- Library
- transformers
- License
- cc-by-nc-sa-4.0
- Model type
- hubert
- Access
- Public
- Created
- Mar 6, 2026
- Updated
- Mar 6, 2026
- SHA
- 26b2db9d
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. -->
indic-slid-mhubert
This model is a fine-tuned version of utter-project/mHuBERT-147 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.8465
- Accuracy: 0.6139
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: 2e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 16
- 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
- lr_scheduler_warmup_steps: 500
- num_epochs: 7
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 49.4727 | 0.3682 | 100 | 3.0906 | 0.0473 |
| 49.3094 | 0.7365 | 200 | 3.0860 | 0.0903 |
| 47.9158 | 1.1031 | 300 | 2.9682 | 0.22 |
| 45.1127 | 1.4713 | 400 | 2.8256 | 0.2988 |
| 42.5860 | 1.8396 | 500 | 2.7005 | 0.3612 |
| 41.5817 | 2.2062 | 600 | 2.5785 | 0.4191 |
| 40.0492 | 2.5745 | 700 | 2.4995 | 0.4279 |
| 37.1908 | 2.9427 | 800 | 2.3784 | 0.4967 |
| 33.6228 | 3.3093 | 900 | 2.2773 | 0.5282 |
| 33.5105 | 3.6776 | 1000 | 2.2024 | 0.5394 |
| 31.8522 | 4.0442 | 1100 | 2.1260 | 0.5421 |
| 31.5263 | 4.4124 | 1200 | 2.0781 | 0.55 |
| 26.6307 | 4.7807 | 1300 | 2.0186 | 0.5812 |
| 26.1449 | 5.1473 | 1400 | 1.9504 | 0.5827 |
| 24.5869 | 5.5155 | 1500 | 1.9050 | 0.6003 |
| 29.2614 | 5.8838 | 1600 | 1.8901 | 0.6067 |
| 25.2821 | 6.2504 | 1700 | 1.8729 | 0.6085 |
| 26.8669 | 6.6186 | 1800 | 1.8508 | 0.6079 |
| 24.7780 | 6.9869 | 1900 | 1.8465 | 0.6139 |
Framework versions
- Transformers 5.2.0
- Pytorch 2.9.0+cu126
- Datasets 2.21.0
- Tokenizers 0.22.2
- Task
- Audio Classification
- Library
- transformers
- Type
- hubert
- License
- cc-by-nc-sa-4.0
- Created
- Mar 6, 2026
- Updated
- Mar 6, 2026