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whisper-noise
Dearlie/whisper-noise
whisper-noise is a automatic speech recognition model from Dearlie. 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 1, 2024
- Updated
- May 1, 2024
- SHA
- 3582b333
Base models
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 Base Noise Ko - Dearlie
This model is a fine-tuned version of openai/whisper-base on the Noise Data dataset. It achieves the following results on the evaluation set:
- Loss: 2.7443
- Cer: 75.4471
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: 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: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Cer |
|---|---|---|---|---|
| 2.9811 | 0.8780 | 1000 | 2.9947 | 76.6578 |
| 2.8567 | 1.7559 | 2000 | 2.8397 | 75.8959 |
| 2.7019 | 2.6339 | 3000 | 2.7677 | 75.6193 |
| 2.7047 | 3.5119 | 4000 | 2.7443 | 75.4471 |
Framework versions
- Transformers 4.41.0.dev0
- Pytorch 2.3.0+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- whisper
- License
- apache-2.0
- Languages
- ko
- Created
- May 1, 2024
- Updated
- May 1, 2024