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whisper_finetuning – AI Model by doongsae | AlphaNeural AI
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doongsae
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whisper_finetuning
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transformers
pytorch
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
kr
openai/whisper-base
finetune
apache-2.0
endpoints_compatible
us
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Fine-tuning whisper
This model is a fine-tuned version of
openai/whisper-base
on the TTS dataset for Capstone Design II project in Sogang University.
Training hyperparameters
The following hyperparameters were used during training:
learning_rate: 1e-05
train_batch_size: 16
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 10
training_steps: 100
mixed_precision_training: Native AMP
Framework versions
Transformers 4.36.0.dev0
Pytorch 2.1.0+cu118
Datasets 2.15.0
Tokenizers 0.15.0
