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wav2vec2_common_voice_accents_3
willcai/wav2vec2_common_voice_accents_3
wav2vec2_common_voice_accents_3 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 16, 2022
- Updated
- Mar 17, 2022
- SHA
- 32b35920
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_3
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: 0.0042
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: 48
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 384
- total_eval_batch_size: 32
- 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 |
|---|---|---|---|
| 4.584 | 1.27 | 400 | 1.1439 |
| 0.481 | 2.55 | 800 | 0.1986 |
| 0.2384 | 3.82 | 1200 | 0.1060 |
| 0.1872 | 5.1 | 1600 | 0.1016 |
| 0.158 | 6.37 | 2000 | 0.0942 |
| 0.1427 | 7.64 | 2400 | 0.0646 |
| 0.1306 | 8.92 | 2800 | 0.0612 |
| 0.1197 | 10.19 | 3200 | 0.0423 |
| 0.1129 | 11.46 | 3600 | 0.0381 |
| 0.1054 | 12.74 | 4000 | 0.0326 |
| 0.0964 | 14.01 | 4400 | 0.0293 |
| 0.0871 | 15.29 | 4800 | 0.0239 |
| 0.0816 | 16.56 | 5200 | 0.0168 |
| 0.0763 | 17.83 | 5600 | 0.0202 |
| 0.0704 | 19.11 | 6000 | 0.0224 |
| 0.0669 | 20.38 | 6400 | 0.0208 |
| 0.063 | 21.66 | 6800 | 0.0074 |
| 0.0585 | 22.93 | 7200 | 0.0126 |
| 0.0548 | 24.2 | 7600 | 0.0086 |
| 0.0512 | 25.48 | 8000 | 0.0080 |
| 0.0487 | 26.75 | 8400 | 0.0052 |
| 0.0455 | 28.03 | 8800 | 0.0062 |
| 0.0433 | 29.3 | 9200 | 0.0042 |
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 16, 2022
- Updated
- Mar 17, 2022