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experts_3split_wav2vec2-large-xls-r-300m-dm32
dpraitality/experts_3split_wav2vec2-large-xls-r-300m-dm32
experts_3split_wav2vec2-large-xls-r-300m-dm32 is a machine learning model from dpraitality. 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. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- transformers
- License
- apache-2.0
- Model type
- wav2vec2
- Access
- Public
- Created
- Dec 7, 2025
- Updated
- Dec 8, 2025
- SHA
- b78f4ffd
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. -->
experts_3split_wav2vec2-large-xls-r-300m-dm32
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.6181
- Accuracy: 0.4149
- Acc Dem 0: 0.0
- Acc Dem 10: 0.0
- Acc Dem 15: 0.0
- Acc Dem 5: 0.0833
- Acc No 1: 0.6190
- Acc No 2: 0.3158
- Acc No 3: 0.7308
- Binary Dem Accuracy: 1.0
- Binary Dem F1: 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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- 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: 22
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Acc Dem 0 | Acc Dem 10 | Acc Dem 15 | Acc Dem 5 | Acc No 1 | Acc No 2 | Acc No 3 | Binary Dem Accuracy | Binary Dem F1 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| No log | 2.0 | 34 | 1.7914 | 0.2660 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.9615 | 1.0 | 1.0 |
| No log | 4.0 | 68 | 1.7699 | 0.2553 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1053 | 0.8462 | 1.0 | 1.0 |
| No log | 6.0 | 102 | 1.7839 | 0.2660 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1053 | 0.8846 | 1.0 | 1.0 |
| 1.7786 | 8.0 | 136 | 1.7959 | 0.2021 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 |
| 1.7786 | 10.0 | 170 | 1.7681 | 0.2234 | 0.0 | 0.0 | 0.0 | 0.0 | 0.3333 | 0.7368 | 0.0 | 1.0 | 1.0 |
| 1.7786 | 12.0 | 204 | 1.7108 | 0.3404 | 0.0 | 0.0 | 0.0 | 0.0 | 0.3333 | 0.1053 | 0.8846 | 1.0 | 1.0 |
| 1.7376 | 14.0 | 238 | 1.7089 | 0.3830 | 0.0 | 0.0 | 0.0 | 0.0 | 0.3810 | 0.1579 | 0.9615 | 1.0 | 1.0 |
| 1.7376 | 16.0 | 272 | 1.6353 | 0.4362 | 0.0 | 0.0 | 0.0 | 0.0 | 0.6190 | 0.2105 | 0.9231 | 1.0 | 1.0 |
| 1.7376 | 18.0 | 306 | 1.6161 | 0.4362 | 0.0 | 0.0 | 0.0 | 0.0833 | 0.5714 | 0.2105 | 0.9231 | 1.0 | 1.0 |
| 1.5323 | 20.0 | 340 | 1.6172 | 0.3936 | 0.0 | 0.0 | 0.0 | 0.0 | 0.6190 | 0.2632 | 0.7308 | 1.0 | 1.0 |
| 1.5323 | 22.0 | 374 | 1.6181 | 0.4149 | 0.0 | 0.0 | 0.0 | 0.0833 | 0.6190 | 0.3158 | 0.7308 | 1.0 | 1.0 |
Framework versions
- Transformers 4.57.2
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1
- Library
- transformers
- Type
- wav2vec2
- License
- apache-2.0
- Created
- Dec 7, 2025
- Updated
- Dec 8, 2025