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wav2vec2_common_voice_accents_5
willcai/wav2vec2_common_voice_accents_5
wav2vec2_common_voice_accents_5 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 19, 2022
- Updated
- Mar 20, 2022
- SHA
- f23f75cb
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_5
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: 0.0027
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 |
|---|---|---|---|
| 4.4163 | 1.34 | 400 | 0.5520 |
| 0.3305 | 2.68 | 800 | 0.1698 |
| 0.2138 | 4.03 | 1200 | 0.1104 |
| 0.1714 | 5.37 | 1600 | 0.0944 |
| 0.1546 | 6.71 | 2000 | 0.0700 |
| 0.1434 | 8.05 | 2400 | 0.0610 |
| 0.1272 | 9.4 | 2800 | 0.0493 |
| 0.1183 | 10.74 | 3200 | 0.0371 |
| 0.1113 | 12.08 | 3600 | 0.0468 |
| 0.1013 | 13.42 | 4000 | 0.0336 |
| 0.0923 | 14.77 | 4400 | 0.0282 |
| 0.0854 | 16.11 | 4800 | 0.0410 |
| 0.0791 | 17.45 | 5200 | 0.0252 |
| 0.0713 | 18.79 | 5600 | 0.0128 |
| 0.0662 | 20.13 | 6000 | 0.0252 |
| 0.0635 | 21.48 | 6400 | 0.0080 |
| 0.0607 | 22.82 | 6800 | 0.0098 |
| 0.0557 | 24.16 | 7200 | 0.0069 |
| 0.0511 | 25.5 | 7600 | 0.0057 |
| 0.0474 | 26.85 | 8000 | 0.0046 |
| 0.045 | 28.19 | 8400 | 0.0037 |
| 0.0426 | 29.53 | 8800 | 0.0027 |
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 19, 2022
- Updated
- Mar 20, 2022