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wav2vec2-base-dataset_asr-demo-colab
aminnaghavi/wav2vec2-base-dataset_asr-demo-colab
wav2vec2-base-dataset_asr-demo-colab is a automatic speech recognition model from aminnaghavi. 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
- hubert
- Access
- Public
- Created
- Jun 17, 2022
- Updated
- Jun 20, 2022
- SHA
- 9935df7d
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-base-dataset_asr-demo-colab
This model is a fine-tuned version of ntu-spml/distilhubert on the superb dataset. It achieves the following results on the evaluation set:
- Loss: 295.0834
- Wer: 0.8282
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: 0.001
- 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: 250
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 5638.536 | 1.6 | 500 | 409.4785 | 0.8556 |
| 2258.6455 | 3.19 | 1000 | 326.0520 | 0.8369 |
| 1389.4919 | 4.79 | 1500 | 295.0834 | 0.8282 |
Framework versions
- Transformers 4.20.0
- Pytorch 1.11.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- hubert
- License
- apache-2.0
- Created
- Jun 17, 2022
- Updated
- Jun 20, 2022