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wav2vec2-base-timit-demo-colab
ying-tina/wav2vec2-base-timit-demo-colab
wav2vec2-base-timit-demo-colab is a automatic speech recognition model from ying-tina. 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 2, 2022
- Updated
- Nov 30, 2021
- SHA
- 3127ccf8
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/wav2vec2-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5127
- Wer: 0.3082
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: 16
- 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 |
|---|---|---|---|---|
| 3.7645 | 2.01 | 500 | 2.5179 | 0.9999 |
| 1.1873 | 4.02 | 1000 | 0.5464 | 0.4798 |
| 0.46 | 6.02 | 1500 | 0.4625 | 0.4025 |
| 0.2869 | 8.03 | 2000 | 0.4252 | 0.3650 |
| 0.2213 | 10.04 | 2500 | 0.4340 | 0.3585 |
| 0.1905 | 12.05 | 3000 | 0.4310 | 0.3404 |
| 0.1545 | 14.06 | 3500 | 0.4547 | 0.3381 |
| 0.1206 | 16.06 | 4000 | 0.4902 | 0.3384 |
| 0.1116 | 18.07 | 4500 | 0.4767 | 0.3253 |
| 0.0925 | 20.08 | 5000 | 0.5248 | 0.3160 |
| 0.0897 | 22.09 | 5500 | 0.4960 | 0.3126 |
| 0.0687 | 24.1 | 6000 | 0.4876 | 0.3086 |
| 0.063 | 26.1 | 6500 | 0.4895 | 0.3065 |
| 0.0558 | 28.11 | 7000 | 0.5127 | 0.3082 |
Framework versions
- Transformers 4.11.3
- Pytorch 1.10.0+cu111
- Datasets 1.16.1
- Tokenizers 0.10.3
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- wav2vec2
- License
- apache-2.0
- Created
- Mar 2, 2022
- Updated
- Nov 30, 2021