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mms-telugu-binary
ramesh070/mms-telugu-binary
mms-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. The card lists the license as cc-by-nc-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-4.0
- Model type
- wav2vec2
- Access
- Public
- Created
- Dec 11, 2025
- Updated
- Dec 11, 2025
- SHA
- c74b0c5e
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. -->
mms-telugu-binary
This model is a fine-tuned version of facebook/mms-300m on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6300
- Accuracy: 0.7455
- F1: 0.7742
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 |
|---|---|---|---|---|---|
| 0.6804 | 1.0 | 14 | 0.6916 | 0.6364 | 0.7778 |
| 0.6736 | 2.0 | 28 | 0.6765 | 0.6364 | 0.7778 |
| 0.6407 | 3.0 | 42 | 0.6302 | 0.7636 | 0.8060 |
| 0.578 | 4.0 | 56 | 0.6086 | 0.6182 | 0.6182 |
| 0.5428 | 5.0 | 70 | 0.5948 | 0.6364 | 0.6429 |
| 0.4916 | 6.0 | 84 | 0.6348 | 0.6 | 0.5926 |
| 0.4702 | 7.0 | 98 | 0.6147 | 0.6364 | 0.6429 |
| 0.4867 | 8.0 | 112 | 0.6111 | 0.6364 | 0.6429 |
| 0.4372 | 9.0 | 126 | 0.4891 | 0.8 | 0.8358 |
| 0.3984 | 10.0 | 140 | 0.5122 | 0.7455 | 0.7742 |
| 0.4102 | 11.0 | 154 | 0.5403 | 0.7091 | 0.7419 |
| 0.336 | 12.0 | 168 | 0.6108 | 0.6909 | 0.7119 |
| 0.3143 | 13.0 | 182 | 0.4587 | 0.8364 | 0.8696 |
| 0.323 | 14.0 | 196 | 0.6597 | 0.6909 | 0.7119 |
| 0.2945 | 15.0 | 210 | 0.6919 | 0.6909 | 0.7119 |
| 0.2852 | 16.0 | 224 | 0.6189 | 0.7455 | 0.7742 |
| 0.2899 | 17.0 | 238 | 0.6230 | 0.7273 | 0.7619 |
| 0.2582 | 18.0 | 252 | 0.6303 | 0.7455 | 0.7742 |
| 0.2653 | 19.0 | 266 | 0.6444 | 0.7273 | 0.7541 |
| 0.243 | 20.0 | 280 | 0.6300 | 0.7455 | 0.7742 |
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
- wav2vec2
- License
- cc-by-nc-4.0
- Created
- Dec 11, 2025
- Updated
- Dec 11, 2025