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whisper-ckm-3
ninninz/whisper-ckm-3
whisper-ckm-3 is a automatic speech recognition model from ninninz. 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
- Dec 17, 2023
- Updated
- Dec 17, 2023
- SHA
- f5104d04
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-large-v3-croarian-v2
This model is a fine-tuned version of openai/whisper-large-v3 on the audiofolder dataset. It achieves the following results on the evaluation set:
- Loss: 2.1863
- Wer: 56.7937
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 | Wer |
|---|---|---|---|---|
| 0.0163 | 22.73 | 1000 | 1.7344 | 61.5900 |
| 0.0007 | 45.45 | 2000 | 2.0005 | 56.4520 |
| 0.0002 | 68.18 | 3000 | 2.1566 | 59.7635 |
| 0.0002 | 90.91 | 4000 | 2.1863 | 56.7937 |
Framework versions
- Transformers 4.36.1
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- whisper
- License
- apache-2.0
- Created
- Dec 17, 2023
- Updated
- Dec 17, 2023