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wav2vec2-large-medical-speed
srujan00123/wav2vec2-large-medical-speed
wav2vec2-large-medical-speed is a automatic speech recognition model from srujan00123. 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
- Dec 17, 2023
- Updated
- Dec 18, 2023
- SHA
- a5da1685
Base models
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-large-medical-speed
This model is a fine-tuned version of facebook/wav2vec2-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4703
- Wer: 0.1992
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
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 3.9919 | 3.97 | 500 | 3.0791 | 0.9895 |
| 1.6651 | 7.94 | 1000 | 0.5613 | 0.4259 |
| 0.4694 | 11.9 | 1500 | 0.4658 | 0.2835 |
| 0.2812 | 15.87 | 2000 | 0.5245 | 0.2460 |
| 0.1923 | 19.84 | 2500 | 0.4438 | 0.2300 |
| 0.1406 | 23.81 | 3000 | 0.5112 | 0.2121 |
| 0.1082 | 27.78 | 3500 | 0.4703 | 0.1992 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0
- Datasets 2.14.6
- Tokenizers 0.14.1
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- wav2vec2
- License
- apache-2.0
- Created
- Dec 17, 2023
- Updated
- Dec 18, 2023