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whisper-large-v3-turbo-verbatim-1
JacobLinCool/whisper-large-v3-turbo-verbatim-1
whisper-large-v3-turbo-verbatim-1 is a automatic speech recognition model from JacobLinCool. Use it when you need speech turned into text. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Automatic Speech Recognition
- Library
- transformers
- License
- mit
- Model type
- whisper
- Access
- Public
- Created
- Jan 15, 2025
- Updated
- Jan 15, 2025
- SHA
- c7430ca4
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-turbo-verbatim-3-lora
This model is a fine-tuned version of openai/whisper-large-v3-turbo on the JacobLinCool/ami-disfluent dataset. It achieves the following results on the evaluation set:
- Loss: 0.1459
- Wer: 7.7269
- Cer: 3.2519
- Decode Runtime: 111.0004
- Wer Runtime: 0.0705
- Cer Runtime: 0.0932
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: 5e-05
- train_batch_size: 4
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 1000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer | Decode Runtime | Wer Runtime | Cer Runtime |
|---|---|---|---|---|---|---|---|---|
| No log | 0 | 0 | 2.2169 | 32.7209 | 17.9205 | 106.5404 | 0.0825 | 0.1203 |
| 0.1681 | 0.1 | 100 | 0.1998 | 9.9454 | 4.1038 | 108.1653 | 0.0730 | 0.0960 |
| 0.1025 | 0.2 | 200 | 0.1693 | 8.6885 | 3.7458 | 109.6779 | 0.0707 | 0.0957 |
| 0.2508 | 0.3 | 300 | 0.1590 | 8.3897 | 3.4931 | 110.3209 | 0.0716 | 0.0947 |
| 0.1446 | 1.088 | 400 | 0.1571 | 8.2626 | 3.4939 | 110.1930 | 0.0718 | 0.0951 |
| 0.1833 | 1.188 | 500 | 0.1505 | 8.0463 | 3.4298 | 110.3821 | 0.0709 | 0.0950 |
| 0.1409 | 1.288 | 600 | 0.1489 | 7.9948 | 3.3401 | 110.6880 | 0.0709 | 0.0939 |
| 0.1184 | 2.076 | 700 | 0.1492 | 7.9124 | 3.3181 | 110.6153 | 0.0728 | 0.0946 |
| 0.1737 | 2.176 | 800 | 0.1468 | 7.8128 | 3.2583 | 110.7120 | 0.0714 | 0.0947 |
| 0.1522 | 2.276 | 900 | 0.1462 | 7.7887 | 3.2604 | 110.7694 | 0.0710 | 0.0937 |
| 0.1077 | 3.064 | 1000 | 0.1459 | 7.7269 | 3.2519 | 111.0004 | 0.0705 | 0.0932 |
Framework versions
- PEFT 0.14.0
- Transformers 4.48.0
- Pytorch 2.4.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- whisper
- License
- mit
- Languages
- en
- Created
- Jan 15, 2025
- Updated
- Jan 15, 2025