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muk-english-digits-classification
dmusingu/muk-english-digits-classification
muk-english-digits-classification is a audio classification model from dmusingu. 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 mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Audio Classification
- Library
- transformers
- License
- mit
- Model type
- wav2vec2-bert
- Access
- Public
- Created
- Oct 7, 2025
- Updated
- Dec 1, 2025
- SHA
- dcb1d14e
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. -->
muk-english-digits-classification
This model is a fine-tuned version of facebook/w2v-bert-2.0 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.8012
- Accuracy: 1.0
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: 8
- eval_batch_size: 1
- seed: 42
- 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
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.3974 | 1.0 | 32 | 2.3805 | 0.1875 |
| 2.3542 | 2.0 | 64 | 2.3080 | 0.1875 |
| 2.2986 | 3.0 | 96 | 2.1997 | 0.3438 |
| 2.1947 | 4.0 | 128 | 2.0517 | 0.4062 |
| 2.0741 | 5.0 | 160 | 1.9182 | 0.4062 |
| 1.9479 | 6.0 | 192 | 1.8475 | 0.4688 |
| 1.8934 | 7.0 | 224 | 1.6724 | 0.5938 |
| 1.687 | 8.0 | 256 | 1.5422 | 0.6875 |
| 1.5745 | 9.0 | 288 | 1.3878 | 0.875 |
| 1.5288 | 10.0 | 320 | 1.2905 | 0.875 |
| 1.3518 | 11.0 | 352 | 1.1875 | 0.9375 |
| 1.2558 | 12.0 | 384 | 1.0936 | 0.9375 |
| 1.1538 | 13.0 | 416 | 1.0296 | 0.9688 |
| 1.186 | 14.0 | 448 | 0.9815 | 0.9688 |
| 1.033 | 15.0 | 480 | 0.9271 | 1.0 |
| 0.9828 | 16.0 | 512 | 0.8811 | 1.0 |
| 0.995 | 17.0 | 544 | 0.8454 | 0.9688 |
| 0.9213 | 18.0 | 576 | 0.8176 | 1.0 |
| 0.9313 | 19.0 | 608 | 0.8048 | 1.0 |
| 0.9029 | 20.0 | 640 | 0.8012 | 1.0 |
Framework versions
- Transformers 4.57.2
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1
- Task
- Audio Classification
- Library
- transformers
- Type
- wav2vec2-bert
- License
- mit
- Created
- Oct 7, 2025
- Updated
- Dec 1, 2025