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wav2vec2-base-demo-colab
thyagosme/wav2vec2-base-demo-colab
wav2vec2-base-demo-colab is a automatic speech recognition model from thyagosme. 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
- Mar 2, 2022
- Updated
- Feb 13, 2022
- SHA
- bcdf199e
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-demo-colab
This model is a fine-tuned version of facebook/wav2vec2-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4657
- Wer: 0.3422
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: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 30
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 3.4477 | 4.0 | 500 | 1.3352 | 0.9039 |
| 0.5972 | 8.0 | 1000 | 0.4752 | 0.4509 |
| 0.2224 | 12.0 | 1500 | 0.4604 | 0.4052 |
| 0.1308 | 16.0 | 2000 | 0.4542 | 0.3866 |
| 0.0889 | 20.0 | 2500 | 0.4730 | 0.3589 |
| 0.0628 | 24.0 | 3000 | 0.4984 | 0.3657 |
| 0.0479 | 28.0 | 3500 | 0.4657 | 0.3422 |
Framework versions
- Transformers 4.11.3
- Pytorch 1.10.0+cu111
- Datasets 1.14.0
- Tokenizers 0.10.3
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- wav2vec2
- License
- apache-2.0
- Created
- Mar 2, 2022
- Updated
- Feb 13, 2022