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wav2vec2-large-mms-1b-aft-led
robertp408/wav2vec2-large-mms-1b-aft-led
wav2vec2-large-mms-1b-aft-led is a automatic speech recognition model from robertp408. Use it when you need speech turned into text. It is set up for transformers. The card lists the license as cc-by-nc-4.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Automatic Speech Recognition
- Library
- transformers
- License
- cc-by-nc-4.0
- Model type
- wav2vec2
- Access
- Public
- Created
- Sep 29, 2025
- Updated
- Oct 7, 2025
- SHA
- 08665204
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-large-mms-1b-aft-led
This model is a fine-tuned version of facebook/mms-1b-all on the audiofolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.4923
- Wer: 0.3307
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: 0.001
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- 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: 100
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 7.8608 | 0.1361 | 100 | 1.8473 | 0.9437 |
| 1.3703 | 0.2721 | 200 | 1.0214 | 0.6846 |
| 0.9658 | 0.4082 | 300 | 0.8563 | 0.5411 |
| 0.8803 | 0.5442 | 400 | 0.8306 | 0.5752 |
| 0.9234 | 0.6803 | 500 | 0.7605 | 0.5431 |
| 0.8064 | 0.8163 | 600 | 0.7326 | 0.4793 |
| 0.7492 | 0.9524 | 700 | 0.7121 | 0.4692 |
| 0.8054 | 1.0884 | 800 | 0.6845 | 0.4151 |
| 0.7078 | 1.2245 | 900 | 0.6491 | 0.4141 |
| 0.6766 | 1.3605 | 1000 | 0.6145 | 0.4033 |
| 0.665 | 1.4966 | 1100 | 0.6198 | 0.4052 |
| 0.6308 | 1.6327 | 1200 | 0.6079 | 0.3905 |
| 0.6869 | 1.7687 | 1300 | 0.5892 | 0.4030 |
| 0.6207 | 1.9048 | 1400 | 0.5757 | 0.3786 |
| 0.5922 | 2.0408 | 1500 | 0.5647 | 0.3802 |
| 0.6242 | 2.1769 | 1600 | 0.5670 | 0.3717 |
| 0.5857 | 2.3129 | 1700 | 0.5658 | 0.3941 |
| 0.5197 | 2.4490 | 1800 | 0.5544 | 0.3684 |
| 0.5493 | 2.5850 | 1900 | 0.5420 | 0.3554 |
| 0.5614 | 2.7211 | 2000 | 0.5271 | 0.3633 |
| 0.5574 | 2.8571 | 2100 | 0.5271 | 0.3552 |
| 0.5387 | 2.9932 | 2200 | 0.5182 | 0.3572 |
| 0.4993 | 3.1293 | 2300 | 0.5225 | 0.3494 |
| 0.4719 | 3.2653 | 2400 | 0.5178 | 0.3593 |
| 0.4438 | 3.4014 | 2500 | 0.5182 | 0.3505 |
| 0.5668 | 3.5374 | 2600 | 0.5071 | 0.3486 |
| 0.4859 | 3.6735 | 2700 | 0.5064 | 0.3371 |
| 0.4871 | 3.8095 | 2800 | 0.5077 | 0.3448 |
| 0.4706 | 3.9456 | 2900 | 0.5042 | 0.3447 |
| 0.4661 | 4.0816 | 3000 | 0.4995 | 0.3490 |
| 0.4369 | 4.2177 | 3100 | 0.5021 | 0.3452 |
| 0.4899 | 4.3537 | 3200 | 0.4987 | 0.3371 |
| 0.4404 | 4.4898 | 3300 | 0.4964 | 0.3395 |
| 0.4347 | 4.6259 | 3400 | 0.4929 | 0.3369 |
| 0.4327 | 4.7619 | 3500 | 0.4930 | 0.3340 |
| 0.4328 | 4.8980 | 3600 | 0.4923 | 0.3307 |
Framework versions
- Transformers 4.57.0
- Pytorch 2.8.0+cu128
- Datasets 4.1.1
- Tokenizers 0.22.1
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- wav2vec2
- License
- cc-by-nc-4.0
- Created
- Sep 29, 2025
- Updated
- Oct 7, 2025