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voice-clone-large-finetune-final
neuronbit/voice-clone-large-finetune-final
voice-clone-large-finetune-final is a automatic speech recognition model from neuronbit. 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
- Nov 27, 2024
- Updated
- Nov 28, 2024
- SHA
- 4ede8d53
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. -->
voice-clone-large-finetune-final
This model is a fine-tuned version of openai/whisper-large-v3 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4377
- Wer: 15.3572
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1607 | 0.8460 | 250 | 0.5163 | 25.9413 |
| 0.0598 | 1.6920 | 500 | 0.4849 | 24.8444 |
| 0.0257 | 2.5381 | 750 | 0.4450 | 30.4180 |
| 0.0141 | 3.3841 | 1000 | 0.4369 | 19.3003 |
| 0.0029 | 4.2301 | 1250 | 0.4267 | 16.0095 |
| 0.0015 | 5.0761 | 1500 | 0.4209 | 18.4109 |
| 0.0063 | 5.9222 | 1750 | 0.4259 | 19.3300 |
| 0.0016 | 6.7682 | 2000 | 0.4341 | 17.7587 |
| 0.0009 | 7.6142 | 2250 | 0.4121 | 17.0471 |
| 0.0013 | 8.4602 | 2500 | 0.4199 | 16.3653 |
| 0.0009 | 9.3063 | 2750 | 0.4233 | 16.5135 |
| 0.001 | 10.1523 | 3000 | 0.4237 | 16.0688 |
| 0.0019 | 10.9983 | 3250 | 0.4230 | 16.4542 |
| 0.0014 | 11.8443 | 3500 | 0.4292 | 15.8316 |
| 0.0007 | 12.6904 | 3750 | 0.4291 | 15.8316 |
| 0.0005 | 13.5364 | 4000 | 0.4321 | 15.3869 |
| 0.0009 | 14.3824 | 4250 | 0.4334 | 15.2980 |
| 0.001 | 15.2284 | 4500 | 0.4344 | 15.2980 |
| 0.0 | 16.0745 | 4750 | 0.4372 | 15.3572 |
| 0.0 | 16.9205 | 5000 | 0.4377 | 15.3572 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- whisper
- License
- apache-2.0
- Created
- Nov 27, 2024
- Updated
- Nov 28, 2024