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wavlm-salt-eng
ajikadev/wavlm-salt-eng
wavlm-salt-eng is a automatic speech recognition model from ajikadev. Use it when you need speech turned into text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Automatic Speech Recognition
- Library
- transformers
- Model type
- wavlm
- Access
- Public
- Created
- Nov 26, 2025
- Updated
- Nov 26, 2025
- SHA
- 4bbe7a28
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. -->
wavlm-salt-eng
This model is a fine-tuned version of microsoft/wavlm-base on the SUNBIRD/SALT - MULTISPEAKER-ENG dataset. It achieves the following results on the evaluation set:
- Loss: 0.2244
- Wer: 0.2118
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
- distributed_type: multi-GPU
- 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: 500.0
- training_steps: 30000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.3803 | 3.3228 | 1000 | 0.3107 | 0.3624 |
| 0.1663 | 6.6456 | 2000 | 0.2740 | 0.3097 |
| 0.1206 | 9.9684 | 3000 | 0.2486 | 0.2903 |
| 0.0938 | 13.2895 | 4000 | 0.2588 | 0.2828 |
| 0.0816 | 16.6123 | 5000 | 0.2769 | 0.2785 |
| 0.0689 | 19.9351 | 6000 | 0.2457 | 0.2882 |
| 0.0642 | 23.2562 | 7000 | 0.2639 | 0.2914 |
| 0.0566 | 26.5790 | 8000 | 0.2954 | 0.2828 |
| 0.049 | 29.9018 | 9000 | 0.3172 | 0.2763 |
| 0.0454 | 33.2230 | 10000 | 0.3186 | 0.2828 |
| 0.0395 | 36.5458 | 11000 | 0.2782 | 0.2817 |
| 0.0389 | 39.8686 | 12000 | 0.2857 | 0.2828 |
| 0.0321 | 43.1897 | 13000 | 0.2692 | 0.2527 |
| 0.0282 | 46.5125 | 14000 | 0.2570 | 0.2559 |
| 0.0269 | 49.8353 | 15000 | 0.2446 | 0.2624 |
| 0.0233 | 53.1564 | 16000 | 0.2383 | 0.2473 |
| 0.0224 | 56.4792 | 17000 | 0.2805 | 0.2473 |
| 0.0198 | 59.8020 | 18000 | 0.2555 | 0.2516 |
| 0.0159 | 63.1231 | 19000 | 0.2097 | 0.2409 |
| 0.015 | 66.4459 | 20000 | 0.2367 | 0.2505 |
| 0.015 | 69.7687 | 21000 | 0.2486 | 0.2527 |
| 0.0122 | 73.0899 | 22000 | 0.2475 | 0.2527 |
| 0.0104 | 76.4126 | 23000 | 0.2377 | 0.2344 |
| 0.008 | 79.7354 | 24000 | 0.2363 | 0.2441 |
| 0.0081 | 83.0566 | 25000 | 0.2347 | 0.2333 |
| 0.0072 | 86.3794 | 26000 | 0.2232 | 0.2290 |
| 0.0064 | 89.7022 | 27000 | 0.2212 | 0.2280 |
| 0.0044 | 93.0233 | 28000 | 0.2287 | 0.2258 |
| 0.004 | 96.3461 | 29000 | 0.2295 | 0.2344 |
| 0.0037 | 99.6689 | 30000 | 0.2243 | 0.2204 |
Framework versions
- Transformers 5.0.0.dev0
- Pytorch 2.9.1+cu128
- Datasets 3.6.0
- Tokenizers 0.22.1
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- wavlm
- Created
- Nov 26, 2025
- Updated
- Nov 26, 2025