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wav2vec2_common_voice_accents
willcai/wav2vec2_common_voice_accents
wav2vec2_common_voice_accents is a automatic speech recognition model from willcai. 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 10, 2022
- Updated
- Mar 13, 2022
- SHA
- 90769000
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_common_voice_accents
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common_voice dataset. It achieves the following results on the evaluation set:
- Loss: 0.9095
- Wer: 0.4269
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: 16
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 30
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 4.0135 | 5.33 | 400 | 1.3259 | 0.8067 |
| 0.5608 | 10.67 | 800 | 0.7832 | 0.5024 |
| 0.1441 | 16.0 | 1200 | 0.9309 | 0.4698 |
| 0.0724 | 21.33 | 1600 | 0.9750 | 0.4461 |
| 0.0444 | 26.67 | 2000 | 0.9095 | 0.4269 |
Framework versions
- Transformers 4.17.0
- Pytorch 1.10.2+cu102
- Datasets 1.18.4
- Tokenizers 0.11.6
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- wav2vec2
- License
- apache-2.0
- Created
- Mar 10, 2022
- Updated
- Mar 13, 2022