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wav2vec2-base-sna-cleaned
CasperMuz/wav2vec2-base-sna-cleaned
wav2vec2-base-sna-cleaned is a automatic speech recognition model from CasperMuz. 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
- Jul 22, 2026
- Updated
- Jul 22, 2026
- SHA
- a02528e0
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 Base Shona - Cleaned
This model is a fine-tuned version of facebook/wav2vec2-base on the Cleaned Google WAXAL Shona dataset. It achieves the following results on the evaluation set:
- Loss: 0.3005
- Wer: 37.7326
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: 3e-05
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Use 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: 400
- training_steps: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 11.8984 | 0.2998 | 250 | 2.9574 | 99.9973 |
| 11.5445 | 0.5995 | 500 | 2.8993 | 99.9973 |
| 3.8440 | 0.8993 | 750 | 0.8141 | 98.7660 |
| 2.3326 | 1.1990 | 1000 | 0.5056 | 56.1276 |
| 1.9937 | 1.4988 | 1250 | 0.4354 | 49.7725 |
| 1.8639 | 1.7986 | 1500 | 0.3815 | 45.0764 |
| 1.5769 | 2.0983 | 1750 | 0.3492 | 43.6845 |
| 1.4288 | 2.3981 | 2000 | 0.3384 | 41.2247 |
| 1.3319 | 2.6978 | 2250 | 0.3376 | 40.4620 |
| 1.2553 | 2.9976 | 2500 | 0.3212 | 39.5059 |
| 1.2150 | 3.2974 | 2750 | 0.3165 | 39.0700 |
| 1.1343 | 3.5971 | 3000 | 0.3103 | 38.2229 |
| 1.1755 | 3.8969 | 3250 | 0.3044 | 38.5361 |
| 1.1932 | 4.1966 | 3500 | 0.3002 | 37.8551 |
| 1.3583 | 4.4964 | 3750 | 0.2995 | 37.7135 |
| 1.3055 | 4.7962 | 4000 | 0.3005 | 37.7326 |
Framework versions
- Transformers 5.14.1
- Pytorch 2.12.0+cu130
- Datasets 5.0.0
- Tokenizers 0.22.2
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- wav2vec2
- License
- apache-2.0
- Languages
- sna
- Created
- Jul 22, 2026
- Updated
- Jul 22, 2026