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wav2vec2-base-timit-demo-colab
rkmt/wav2vec2-base-timit-demo-colab
wav2vec2-base-timit-demo-colab is a automatic speech recognition model from rkmt. 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
- Mar 2, 2022
- Updated
- Dec 30, 2021
- SHA
- 6fcbae8b
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-timit-demo-colab
This model is a fine-tuned version of facebook/hubert-large-ls960-ft on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0280
- Wer: 0.0082
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: 0.0001
- 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: 1000
- num_epochs: 30
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1152 | 1.42 | 500 | 0.0416 | 0.0159 |
| 0.0803 | 2.83 | 1000 | 0.0372 | 0.0144 |
| 0.0672 | 4.25 | 1500 | 0.0345 | 0.0119 |
| 0.0564 | 5.67 | 2000 | 0.0338 | 0.0106 |
| 0.0513 | 7.08 | 2500 | 0.0307 | 0.0100 |
| 0.0448 | 8.5 | 3000 | 0.0343 | 0.0098 |
| 0.0374 | 9.92 | 3500 | 0.0300 | 0.0084 |
| 0.0368 | 11.33 | 4000 | 0.0314 | 0.0086 |
| 0.0388 | 12.75 | 4500 | 0.0283 | 0.0089 |
| 0.0277 | 14.16 | 5000 | 0.0302 | 0.0089 |
| 0.0298 | 15.58 | 5500 | 0.0298 | 0.0089 |
| 0.0271 | 17.0 | 6000 | 0.0320 | 0.0098 |
| 0.024 | 18.41 | 6500 | 0.0286 | 0.0088 |
| 0.0236 | 19.83 | 7000 | 0.0284 | 0.0084 |
| 0.0238 | 21.25 | 7500 | 0.0290 | 0.0086 |
| 0.0227 | 22.66 | 8000 | 0.0284 | 0.0093 |
| 0.0198 | 24.08 | 8500 | 0.0280 | 0.0088 |
| 0.0225 | 25.5 | 9000 | 0.0281 | 0.0086 |
| 0.018 | 26.91 | 9500 | 0.0280 | 0.0082 |
| 0.0178 | 28.33 | 10000 | 0.0280 | 0.0082 |
| 0.0209 | 29.75 | 10500 | 0.0280 | 0.0082 |
Framework versions
- Transformers 4.15.0
- Pytorch 1.9.0+cu111
- Datasets 1.17.0
- Tokenizers 0.10.3
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- hubert
- License
- apache-2.0
- Created
- Mar 2, 2022
- Updated
- Dec 30, 2021