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w2v-bert-2.0-lmk_man_align_updated
aconeil/w2v-bert-2.0-lmk_man_align_updated
w2v-bert-2.0-lmk_man_align_updated is a automatic speech recognition model from aconeil. Use it when you need speech turned into text. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Automatic Speech Recognition
- Library
- transformers
- License
- mit
- Model type
- wav2vec2-bert
- Access
- Public
- Created
- Nov 10, 2025
- Updated
- Nov 20, 2025
- SHA
- d93c66c2
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. -->
w2v-bert-2.0-lmk_man_align_updated
This model is a fine-tuned version of facebook/w2v-bert-2.0 on the audiofolder dataset. It achieves the following results on the evaluation set:
- Loss: nan
- Wer: 1.0
- Cer: 1.0
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: 300
- num_epochs: 100
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 3.6561 | 6.25 | 100 | 3.1439 | 1.0 | 0.9246 |
| 5.5678 | 12.5 | 200 | 4.0590 | 1.1777 | 0.7807 |
| 5.583 | 18.75 | 300 | 4.0602 | 1.1533 | 0.7807 |
| 5.2971 | 25.0 | 400 | 4.0607 | 1.1498 | 0.7845 |
| 5.6771 | 31.25 | 500 | 4.0620 | 1.1568 | 0.7791 |
| 0.0 | 37.5 | 600 | nan | 1.0 | 1.0 |
| 0.0 | 43.75 | 700 | nan | 1.0 | 1.0 |
| 0.0 | 50.0 | 800 | nan | 1.0 | 1.0 |
| 0.0 | 56.25 | 900 | nan | 1.0 | 1.0 |
| 0.0 | 62.5 | 1000 | nan | 1.0 | 1.0 |
| 0.0 | 68.75 | 1100 | nan | 1.0 | 1.0 |
| 0.0 | 75.0 | 1200 | nan | 1.0 | 1.0 |
| 0.0 | 81.25 | 1300 | nan | 1.0 | 1.0 |
| 0.0 | 87.5 | 1400 | nan | 1.0 | 1.0 |
| 0.0 | 93.75 | 1500 | nan | 1.0 | 1.0 |
| 0.0 | 100.0 | 1600 | nan | 1.0 | 1.0 |
Framework versions
- Transformers 4.57.1
- Pytorch 2.8.0+cu128
- Datasets 3.0.0
- Tokenizers 0.22.1
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- wav2vec2-bert
- License
- mit
- Created
- Nov 10, 2025
- Updated
- Nov 20, 2025