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whisper-medium-da – AI Model by n4jiDX | AlphaNeural AI
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whisper-medium-da
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
da
mozilla-foundation/common_voice_17_0
openai/whisper-medium
finetune
apache-2.0
endpoints_compatible
us
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whisper-medium da
This model is a fine-tuned version of
openai/whisper-medium
on the Common Voice 17.0 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: 1e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 16
optimizer: Use 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: 50
training_steps: 400
mixed_precision_training: Native AMP
Framework versions
Transformers 4.47.1
Pytorch 2.4.1+cu121
Datasets 3.2.0
Tokenizers 0.21.0
