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output – AI Model by Jadeja08 | AlphaNeural AI
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
hf-asr-leaderboard
generated_from_trainer
hi
mozilla-foundation/common_voice_11_0
openai/whisper-medium
finetune
apache-2.0
endpoints_compatible
us
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Whisper Medium Hi - Aditya Agrawal
This model is a fine-tuned version of
openai/whisper-medium
on the Common Voice 11.0 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: 5e-05
train_batch_size: 1
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2945340432158418383223693624588738123559693482299075088767878449688292160397327779966295692450325070170031945807812908771881611572255401942922812303597144053805349165872996110766935565946816006053119311086960734516644260779498911850068592403100913453684334767056261910363295677456051671938422478104563288264146944
total_train_batch_size: 2945340432158418383223693624588738123559693482299075088767878449688292160397327779966295692450325070170031945807812908771881611572255401942922812303597144053805349165872996110766935565946816006053119311086960734516644260779498911850068592403100913453684334767056261910363295677456051671938422478104563288264146944
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3.0
Framework versions
Transformers 4.38.0.dev0
Pytorch 2.1.0+cu121
Datasets 2.17.0
Tokenizers 0.15.2
