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wav2vec-bert-ser-standard
MathRaaj/wav2vec-bert-ser-standard
wav2vec-bert-ser-standard is a machine learning model from MathRaaj. Use it for the machine learning 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
- Library
- transformers
- Model type
- w2v-bert-ser
- Access
- Public
- Created
- Apr 6, 2026
- Updated
- Apr 7, 2026
- SHA
- db67586d
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. -->
wav2vec-bert-ser-standard
This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.3597
- F1: 0.5549
- Accuracy: 0.564
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: 16
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- 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
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Accuracy |
|---|---|---|---|---|---|
| 30.8905 | 1.0 | 16 | 3.6367 | 0.1464 | 0.24 |
| 28.7614 | 2.0 | 32 | 3.5061 | 0.1679 | 0.256 |
| 27.0469 | 3.0 | 48 | 3.3160 | 0.3390 | 0.388 |
| 27.3445 | 4.0 | 64 | 3.0776 | 0.3525 | 0.396 |
| 24.3884 | 5.0 | 80 | 2.9147 | 0.4089 | 0.452 |
| 24.4721 | 6.0 | 96 | 2.7240 | 0.4445 | 0.472 |
| 22.5651 | 7.0 | 112 | 2.6093 | 0.5077 | 0.532 |
| 21.9695 | 8.0 | 128 | 2.6026 | 0.4392 | 0.476 |
| 21.3548 | 9.0 | 144 | 2.3849 | 0.5656 | 0.584 |
| 18.9157 | 10.0 | 160 | 2.3597 | 0.5549 | 0.564 |
Framework versions
- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.8.3
- Tokenizers 0.22.2
- Library
- transformers
- Type
- w2v-bert-ser
- Created
- Apr 6, 2026
- Updated
- Apr 7, 2026