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w2v2-lmk_updated
aconeil/w2v2-lmk_updated
w2v2-lmk_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 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
- Nov 19, 2025
- Updated
- Nov 21, 2025
- SHA
- d25ee00b
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. -->
w2v2-lmk_updated
This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the audiofolder dataset. It achieves the following results on the evaluation set:
- Loss: 1.0281
- Wer: 0.5749
- Cer: 0.2049
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: 0.0001
- 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 |
|---|---|---|---|---|---|
| 9.4495 | 6.25 | 100 | 4.3525 | 1.0 | 1.0 |
| 3.1633 | 12.5 | 200 | 2.9339 | 1.0 | 1.0 |
| 2.964 | 18.75 | 300 | 2.8446 | 1.0 | 1.0 |
| 2.8489 | 25.0 | 400 | 2.6748 | 1.0 | 1.0 |
| 2.409 | 31.25 | 500 | 1.9297 | 1.0 | 0.6824 |
| 1.6654 | 37.5 | 600 | 1.3226 | 0.9024 | 0.3686 |
| 1.2589 | 43.75 | 700 | 1.0957 | 0.7666 | 0.2749 |
| 1.0072 | 50.0 | 800 | 1.0241 | 0.6585 | 0.2445 |
| 0.818 | 56.25 | 900 | 1.0104 | 0.6132 | 0.2239 |
| 0.7072 | 62.5 | 1000 | 0.9941 | 0.5923 | 0.2155 |
| 0.5998 | 68.75 | 1100 | 1.0503 | 0.5749 | 0.2079 |
| 0.5677 | 75.0 | 1200 | 1.0376 | 0.5784 | 0.2049 |
| 0.5125 | 81.25 | 1300 | 1.0549 | 0.5819 | 0.2133 |
| 0.4983 | 87.5 | 1400 | 1.0222 | 0.5505 | 0.1988 |
| 0.4859 | 93.75 | 1500 | 1.0176 | 0.5575 | 0.1995 |
| 0.4436 | 100.0 | 1600 | 1.0281 | 0.5749 | 0.2049 |
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
- License
- apache-2.0
- Created
- Nov 19, 2025
- Updated
- Nov 21, 2025