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wav2vec2-large-960h-lv60-self-atc-uwb-atcc
suideepmax/wav2vec2-large-960h-lv60-self-atc-uwb-atcc
wav2vec2-large-960h-lv60-self-atc-uwb-atcc is a automatic speech recognition model from suideepmax. Use it when you need speech turned into text. 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
- License
- apache-2.0
- Model type
- wav2vec2
- Access
- Public
- Created
- Apr 7, 2026
- Updated
- Apr 7, 2026
- SHA
- df3b3930
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. -->
0.0ld_0.0ad_0.0attd_0.0fpd_0.01mtp_12mtl_0.0mfp_12mfl_16acc
This model is a fine-tuned version of facebook/wav2vec2-large-960h-lv60-self on the EXPERIMENTS/DATA/UWB_ATCC/TRAIN - NA dataset. It achieves the following results on the evaluation set:
- Loss: 0.9386
- Wer: 0.1507
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: 0.0005
- train_batch_size: 1
- eval_batch_size: 12
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- total_eval_batch_size: 48
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- training_steps: 10000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| No log | 2.78 | 500 | 0.6754 | 0.2799 |
| 1.9717 | 5.56 | 1000 | 0.5679 | 0.2050 |
| 1.9717 | 8.33 | 1500 | 0.5365 | 0.1873 |
| 0.6024 | 11.11 | 2000 | 0.5301 | 0.1898 |
| 0.6024 | 13.89 | 2500 | 0.5311 | 0.1736 |
| 0.4164 | 16.67 | 3000 | 0.5608 | 0.1726 |
| 0.4164 | 19.44 | 3500 | 0.6315 | 0.1777 |
| 0.3101 | 22.22 | 4000 | 0.6357 | 0.1773 |
| 0.3101 | 25.0 | 4500 | 0.6805 | 0.1623 |
| 0.2305 | 27.78 | 5000 | 0.7486 | 0.1639 |
| 0.2305 | 30.56 | 5500 | 0.7124 | 0.1620 |
| 0.1764 | 33.33 | 6000 | 0.7042 | 0.1587 |
| 0.1764 | 36.11 | 6500 | 0.7720 | 0.1628 |
| 0.1333 | 38.89 | 7000 | 0.8483 | 0.1580 |
| 0.1333 | 41.67 | 7500 | 0.8459 | 0.1624 |
| 0.0996 | 44.44 | 8000 | 0.8556 | 0.1547 |
| 0.0996 | 47.22 | 8500 | 0.9197 | 0.1545 |
| 0.076 | 50.0 | 9000 | 0.9336 | 0.1505 |
| 0.076 | 52.78 | 9500 | 0.9272 | 0.1509 |
| 0.0606 | 55.56 | 10000 | 0.9386 | 0.1507 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.13.0+cu117
- Datasets 2.14.0
- Tokenizers 0.13.3
- Task
- Automatic Speech Recognition
- Type
- wav2vec2
- License
- apache-2.0
- Created
- Apr 7, 2026
- Updated
- Apr 7, 2026