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wav2vec2-xls-r-2b-5e-sw-asr
dennohpeter/wav2vec2-xls-r-2b-5e-sw-asr
wav2vec2-xls-r-2b-5e-sw-asr is a automatic speech recognition model from dennohpeter. 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
- Sep 20, 2025
- Updated
- Sep 21, 2025
- SHA
- e13c497a
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-xls-r-2b-5e-sw-asr
This model is a fine-tuned version of facebook/wav2vec2-xls-r-2b on the common_voice_17_0 dataset. It achieves the following results on the evaluation set:
- Loss: nan
- Wer: 0.9999
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: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- 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: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 1.7865 | 0.2179 | 400 | inf | 0.7489 |
| 0.599 | 0.4357 | 800 | inf | 0.7282 |
| 0.5505 | 0.6536 | 1200 | inf | 0.6650 |
| 0.5238 | 0.8715 | 1600 | inf | 0.7014 |
| 0.4933 | 1.0893 | 2000 | inf | 0.5907 |
| 0.4488 | 1.3072 | 2400 | inf | 0.5622 |
| 0.4442 | 1.5251 | 2800 | inf | 0.5664 |
| 0.4353 | 1.7429 | 3200 | inf | 0.5418 |
| 0.4059 | 1.9608 | 3600 | inf | 0.5334 |
| 0.3737 | 2.1786 | 4000 | inf | 0.5037 |
| 0.3547 | 2.3965 | 4400 | inf | 0.5097 |
| 0.3594 | 2.6144 | 4800 | inf | 0.5031 |
| 0.563 | 2.8322 | 5200 | inf | 0.8574 |
| 1.4779 | 3.0501 | 5600 | inf | 0.9908 |
| 2.4352 | 3.2680 | 6000 | nan | 0.9946 |
| 214.8165 | 3.4858 | 6400 | nan | 0.9998 |
| 0.0 | 3.7037 | 6800 | nan | 0.9996 |
| 0.0 | 3.9216 | 7200 | nan | 0.9999 |
| 0.0 | 4.1394 | 7600 | nan | 0.9997 |
| 0.0 | 4.3573 | 8000 | nan | 0.9997 |
| 0.0 | 4.5752 | 8400 | nan | 0.9996 |
| 0.0 | 4.7930 | 8800 | nan | 0.9999 |
Framework versions
- Transformers 4.56.2
- Pytorch 2.8.0+cu126
- Datasets 3.6.0
- Tokenizers 0.22.0
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- wav2vec2
- License
- apache-2.0
- Created
- Sep 20, 2025
- Updated
- Sep 21, 2025