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whisper – AI Model by Dan-Rosetta | AlphaNeural AI

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Dan-Rosetta/
whisper

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automatic-speech-recognition

hf-asr-leaderboard

generated_from_trainer

mozilla-foundation/common_voice_11_0

endpoints_compatible

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Whisper Medium SW - Daniel Rosetta Technlogies

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: 1e-05
train_batch_size: 2
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
training_steps: 4000
mixed_precision_training: Native AMP

Framework versions

Transformers 4.28.0
Pytorch 2.0.1+cu118
Datasets 2.14.5
Tokenizers 0.13.3