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whisper-v4 – AI Model by abedNa | AlphaNeural AI
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abedNa
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whisper-v4
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peft
safetensors
adapter
lora
transformers
ivrit-ai/whisper-large-v3-turbo
apache-2.0
us
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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
