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wav2vec2_common_voice_accents_indian_only_rerun
willcai/wav2vec2_common_voice_accents_indian_only_rerun
wav2vec2_common_voice_accents_indian_only_rerun 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 27, 2022
- Updated
- Mar 27, 2022
- SHA
- ccea57f2
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_indian_only_rerun
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: 1.2807
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: 588
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 4.6205 | 25.0 | 400 | 1.4584 |
| 0.3427 | 50.0 | 800 | 1.8377 |
| 0.1213 | 75.0 | 1200 | 1.6086 |
| 0.0643 | 100.0 | 1600 | 1.5136 |
| 0.0433 | 125.0 | 2000 | 1.4882 |
| 0.0323 | 150.0 | 2400 | 1.2204 |
| 0.0265 | 175.0 | 2800 | 1.3034 |
| 0.0206 | 200.0 | 3200 | 1.2866 |
| 0.0191 | 225.0 | 3600 | 1.2337 |
| 0.0148 | 250.0 | 4000 | 1.1729 |
| 0.0121 | 275.0 | 4400 | 1.2059 |
| 0.0105 | 300.0 | 4800 | 1.1246 |
| 0.01 | 325.0 | 5200 | 1.1397 |
| 0.0098 | 350.0 | 5600 | 1.1684 |
| 0.0073 | 375.0 | 6000 | 1.1030 |
| 0.0061 | 400.0 | 6400 | 1.2077 |
| 0.0049 | 425.0 | 6800 | 1.2653 |
| 0.0044 | 450.0 | 7200 | 1.1587 |
| 0.0037 | 475.0 | 7600 | 1.2283 |
| 0.0033 | 500.0 | 8000 | 1.1897 |
| 0.0026 | 525.0 | 8400 | 1.2633 |
| 0.0023 | 550.0 | 8800 | 1.2571 |
| 0.002 | 575.0 | 9200 | 1.2807 |
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 27, 2022
- Updated
- Mar 27, 2022