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whisper-small-da – AI Model by HollowVoice | AlphaNeural AI
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HollowVoice
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whisper-small-da
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transformers
pytorch
tensorboard
whisper
automatic-speech-recognition
generated_from_trainer
da
audiofolder
endpoints_compatible
us
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Whisper Small Da - HollowVoice
This model is a fine-tuned version of
openai/openai/whisper-small
on the audiofolder dataset. It achieves the following results on the evaluation set:
eval_loss: 0.4597
eval_wer: 22.9176
eval_runtime: 248.1301
eval_samples_per_second: 3.514
eval_steps_per_second: 0.439
epoch: 9.17
step: 2000
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: 4
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 4.27.0.dev0
Pytorch 1.13.1+cu117
Datasets 2.10.1
Tokenizers 0.13.2
