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wav2vec2-soninke
basaltedr/wav2vec2-soninke
wav2vec2-soninke is a automatic speech recognition model from basaltedr. Use it when you need speech turned into text. 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
- Task
- Automatic Speech Recognition
- Library
- transformers
- License
- apache-2.0
- Model type
- wav2vec2
- Access
- Public
- Created
- Mar 25, 2026
- Updated
- Mar 26, 2026
- SHA
- 8bf236db
Base models
Datasets
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. -->
wav2vec2-soninke
This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the audiofolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.3270
- Wer: 0.1829
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: 0.0003
- 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
- lr_scheduler_warmup_steps: 500
- num_epochs: 30
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 5.2113 | 1.1767 | 400 | 1.7410 | 0.9913 |
| 1.7439 | 2.3535 | 800 | 0.5347 | 0.5501 |
| 1.4710 | 3.5302 | 1200 | 0.4372 | 0.4206 |
| 1.2485 | 4.7069 | 1600 | 0.3799 | 0.3828 |
| 1.2148 | 5.8837 | 2000 | 0.3516 | 0.3523 |
| 1.0983 | 7.0589 | 2400 | 0.3203 | 0.3046 |
| 0.8259 | 8.2356 | 2800 | 0.3285 | 0.2942 |
| 0.6912 | 9.4124 | 3200 | 0.3193 | 0.2751 |
| 0.7422 | 10.5891 | 3600 | 0.3049 | 0.2551 |
| 0.6663 | 11.7658 | 4000 | 0.2963 | 0.2667 |
| 0.5808 | 12.9426 | 4400 | 0.2739 | 0.2437 |
| 0.5273 | 14.1178 | 4800 | 0.3011 | 0.2226 |
| 0.4595 | 15.2946 | 5200 | 0.2921 | 0.2336 |
| 0.4389 | 16.4713 | 5600 | 0.2870 | 0.2178 |
| 0.3840 | 17.6480 | 6000 | 0.3031 | 0.2202 |
| 0.4010 | 18.8247 | 6400 | 0.3058 | 0.2258 |
| 0.3712 | 20.0 | 6800 | 0.3151 | 0.2193 |
| 0.3377 | 21.1767 | 7200 | 0.3167 | 0.2008 |
| 0.2824 | 22.3535 | 7600 | 0.3275 | 0.2058 |
| 0.2756 | 23.5302 | 8000 | 0.3074 | 0.1981 |
| 0.2699 | 24.7069 | 8400 | 0.3133 | 0.1874 |
| 0.2307 | 25.8837 | 8800 | 0.3261 | 0.1912 |
| 0.2357 | 27.0589 | 9200 | 0.3304 | 0.1874 |
| 0.2249 | 28.2356 | 9600 | 0.3270 | 0.1829 |
| 0.2264 | 29.4124 | 10000 | 0.3339 | 0.1862 |
Framework versions
- Transformers 5.3.0
- Pytorch 2.10.0+cu128
- Datasets 4.8.4
- Tokenizers 0.22.2
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- wav2vec2
- License
- apache-2.0
- Created
- Mar 25, 2026
- Updated
- Mar 26, 2026