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mst_hp3
Sjdan/mst_hp3
mst_hp3 is a automatic speech recognition model from Sjdan. 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
- Feb 23, 2023
- Updated
- Feb 23, 2023
- SHA
- 3e5ec394
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. -->
mst_hp3
This model is a fine-tuned version of Sjdan/mst_1 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0270
- Wer: 1.4050
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: 7
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 3.3299 | 1.36 | 500 | 0.5122 | 1.8785 |
| 0.6247 | 2.72 | 1000 | 0.1506 | 1.5639 |
| 0.3223 | 4.09 | 1500 | 0.0540 | 1.7539 |
| 0.1549 | 5.45 | 2000 | 0.0296 | 1.5265 |
| 0.0893 | 6.81 | 2500 | 0.0270 | 1.4050 |
Framework versions
- Transformers 4.17.0
- Pytorch 1.13.1+cu116
- Datasets 1.18.3
- Tokenizers 0.13.2
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- wav2vec2
- License
- apache-2.0
- Created
- Feb 23, 2023
- Updated
- Feb 23, 2023