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whisper-v4
This model is a fine-tuned version of ivrit-ai/whisper-large-v3-turbo on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3019
- Wer Ortho: 0.1547
- Wer: 0.1048
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: 16
- total_train_batch_size: 128
- 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_ratio: 0.1
- lr_scheduler_warmup_steps: 800
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|---|---|---|---|---|---|
| 0.3076 | 1.9608 | 100 | 0.3021 | 0.1497 | 0.0996 |
| 0.308 | 3.9216 | 200 | 0.3019 | 0.1547 | 0.1048 |
Framework versions
- PEFT 0.18.1
- Transformers 4.48.1
- Pytorch 2.9.1+cu128
- Datasets 3.6.0
- Tokenizers 0.21.4
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Model tree for abedNa/whisper-v4
Base model
openai/whisper-large-v3
Finetuned
openai/whisper-large-v3-turbo
Finetuned
ivrit-ai/whisper-large-v3-turbo