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whisper-tiny-german-V2-HanNeurAI
HanCreation/whisper-tiny-german-V2-HanNeurAI
whisper-tiny-german-V2-HanNeurAI is a automatic speech recognition model from HanCreation. 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
- May 11, 2024
- Updated
- Jun 23, 2024
- SHA
- ca11239b
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. -->
whisper-tiny-german-V2-HanNeurAI
This model is a fine-tuned version of openai/whisper-tiny on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.5818
- Wer: 32.3327
This fine-tuning model is part of my school project. With limitation of my compute, I scale down the dataset from german common voice to shuffled 200k rows
Additional information can be found in this github: HanCreation/Whisper-Tiny-German
Model description
Model Parameter (pipe.model.num_parameters()): 37760640 (37M)
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- 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: 500
- training_steps: 8000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.2054 | 0.08 | 1000 | 0.7062 | 39.0698 |
| 0.1861 | 0.16 | 2000 | 0.6687 | 36.4857 |
| 0.1677 | 0.24 | 3000 | 0.6393 | 35.6849 |
| 0.2019 | 0.32 | 4000 | 0.6193 | 34.4385 |
| 0.1808 | 0.4 | 5000 | 0.6103 | 33.8459 |
| 0.1697 | 0.48 | 6000 | 0.5956 | 32.8519 |
| 0.1468 | 0.56 | 7000 | 0.5884 | 32.7029 |
| 0.1906 | 0.64 | 8000 | 0.5818 | 32.3327 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.3.0
- Datasets 2.19.1
- Tokenizers 0.19.1
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- whisper
- License
- apache-2.0
- Languages
- de
- Created
- May 11, 2024
- Updated
- Jun 23, 2024