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whisper-small-allSNR-v6
marccgrau/whisper-small-allSNR-v6
whisper-small-allSNR-v6 is a automatic speech recognition model from marccgrau. 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
- whisper
- Access
- Public
- Created
- Jan 12, 2023
- Updated
- Jan 12, 2023
- SHA
- c0118f6d
Datasets
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. -->
Whisper Small German SBB all SNR - v6
This model is a fine-tuned version of openai/whisper-small on the SBB Dataset 05.01.2023 dataset. It achieves the following results on the evaluation set:
- Loss: 0.0426
- Wer: 0.0266
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: 1e-05
- train_batch_size: 4
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 400
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 1.7233 | 0.04 | 100 | 0.4161 | 0.2232 |
| 0.1932 | 0.09 | 200 | 0.0665 | 0.0361 |
| 0.0615 | 0.13 | 300 | 0.0666 | 0.0361 |
| 0.0677 | 0.18 | 400 | 0.0426 | 0.0266 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.1
- Datasets 2.8.0
- Tokenizers 0.12.1
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- whisper
- License
- apache-2.0
- Languages
- de
- Created
- Jan 12, 2023
- Updated
- Jan 12, 2023