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whisper-large-v3-turbo-imdap4-bs32-grad4-dl4-2h200-splbat-8cpus-6e06LR-4800maxst-perstwkrs-6heg – AI Model by jayellho | AlphaNeural AI
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whisper-large-v3-turbo-imdap4-bs32-grad4-dl4-2h200-splbat-8cpus-6e06LR-4800maxst-perstwkrs-6heg
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
data_loading_script
endpoints_compatible
us
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whisper-large-v3-turbo-imdap4-bs32-grad4-dl4-2h200-splbat-8cpus-6e06LR-4800maxst-perstwkrs-6heg
This model was trained from scratch on the data_loading_script dataset.
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: 6.101137235931163e-06
train_batch_size: 32
eval_batch_size: 32
seed: 42
distributed_type: multi-GPU
num_devices: 2
gradient_accumulation_steps: 4
total_train_batch_size: 256
total_eval_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: 480
training_steps: 4800
mixed_precision_training: Native AMP
Training results
Framework versions
Transformers 4.51.3
Pytorch 2.4.1+cu121
Datasets 3.5.0
Tokenizers 0.21.1
