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whisper-medium-disfluency – AI Model by Alejomazov | AlphaNeural AI
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whisper-medium-disfluency
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
es
Disfluency/disfluency-es
openai/whisper-medium
finetune
apache-2.0
endpoints_compatible
us
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whisper-medium-disfluency
This model is a fine-tuned version of
openai/whisper-medium
on the disfluency-es 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: 4
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 8
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 7
mixed_precision_training: Native AMP
Training results
Framework versions
Transformers 4.44.2
Pytorch 2.4.0+cu121
Datasets 2.21.0
Tokenizers 0.19.1