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wav2vec2-base-timit-ms
saribalgar/wav2vec2-base-timit-ms
wav2vec2-base-timit-ms is a automatic speech recognition model from saribalgar. 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
- Apr 18, 2023
- Updated
- May 11, 2023
- SHA
- f55cb3cc
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-ms
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: 0.7589
- Wer: 0.3722
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: 8
- 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: 80
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 4.0088 | 3.7 | 500 | 2.4873 | 1.0 |
| 1.0451 | 7.41 | 1000 | 0.9286 | 0.5470 |
| 0.4081 | 11.11 | 1500 | 0.5935 | 0.4397 |
| 0.2564 | 14.81 | 2000 | 0.6525 | 0.4292 |
| 0.183 | 18.52 | 2500 | 0.6578 | 0.4486 |
| 0.1481 | 22.22 | 3000 | 0.6786 | 0.4231 |
| 0.1299 | 25.93 | 3500 | 0.6660 | 0.4121 |
| 0.1044 | 29.63 | 4000 | 0.7713 | 0.4209 |
| 0.0953 | 33.33 | 4500 | 0.6728 | 0.4038 |
| 0.0746 | 37.04 | 5000 | 0.7122 | 0.4165 |
| 0.0627 | 40.74 | 5500 | 0.6950 | 0.4126 |
| 0.0554 | 44.44 | 6000 | 0.8237 | 0.4082 |
| 0.0494 | 48.15 | 6500 | 0.7311 | 0.3955 |
| 0.0426 | 51.85 | 7000 | 0.7717 | 0.3899 |
| 0.0368 | 55.56 | 7500 | 0.7490 | 0.3933 |
| 0.0315 | 59.26 | 8000 | 0.7056 | 0.3877 |
| 0.0274 | 62.96 | 8500 | 0.7897 | 0.3850 |
| 0.0237 | 66.67 | 9000 | 0.7715 | 0.3850 |
| 0.0223 | 70.37 | 9500 | 0.7774 | 0.3789 |
| 0.0177 | 74.07 | 10000 | 0.7598 | 0.3744 |
| 0.0182 | 77.78 | 10500 | 0.7589 | 0.3722 |
Framework versions
- Transformers 4.24.0
- Pytorch 2.0.0+cu118
- Datasets 1.18.3
- Tokenizers 0.13.3
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- wav2vec2
- License
- apache-2.0
- Created
- Apr 18, 2023
- Updated
- May 11, 2023