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whisper-small-Sinhala-Fine_Tune – AI Model by Subhaka | AlphaNeural AI
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Subhaka
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whisper-small-Sinhala-Fine_Tune
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transformers
pytorch
tensorboard
whisper
automatic-speech-recognition
trnslation
generated_from_trainer
apache-2.0
endpoints_compatible
us
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whisper-small-Sinhala-Fine_Tune
This model is a fine-tuned version of
openai/whisper-small
on the None 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 10
mixed_precision_training: Native AMP
Training results
Framework versions
Transformers 4.28.1
Pytorch 2.0.0+cu118
Datasets 2.12.0
Tokenizers 0.13.3
