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wav2vec2-base-timit-phoneme
oosawy/wav2vec2-base-timit-phoneme
wav2vec2-base-timit-phoneme is a automatic speech recognition model from oosawy. 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
- Oct 9, 2025
- Updated
- Oct 9, 2025
- SHA
- 6c2723ec
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-base-timit-phoneme
This model is a fine-tuned version of facebook/wav2vec2-base on the timit_asr dataset. It achieves the following results on the evaluation set:
- Loss: 6.2366
- Per: 0.9535
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: 16
- 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: 1000
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Per |
|---|---|---|---|---|
| No log | 1.0 | 13 | 6.8820 | 0.9999 |
| No log | 2.0 | 26 | 6.6526 | 0.9978 |
| No log | 3.0 | 39 | 6.2366 | 0.9535 |
Framework versions
- Transformers 4.56.2
- Pytorch 2.8.0+cu126
- Datasets 2.21.0
- Tokenizers 0.22.1
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- wav2vec2
- License
- apache-2.0
- Created
- Oct 9, 2025
- Updated
- Oct 9, 2025