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whisper-small-ko-normalized-debug – AI Model by jangmin | AlphaNeural AI
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jangmin
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whisper-small-ko-normalized-debug
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transformers
pytorch
tensorboard
whisper
automatic-speech-recognition
generated_from_trainer
apache-2.0
endpoints_compatible
us
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whisper-small-ko-normalized-debug
This model is a fine-tuned version of
openai/whisper-small
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.6194
Wer: 0.3928
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: 32
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 100
num_epochs: 3
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
No log
1.0
4
0.6447
0.4031
No log
2.0
8
0.6389
0.3992
0.4891
3.0
12
0.6194
0.3928
Framework versions
Transformers 4.28.0.dev0
Pytorch 1.13.1+cu117
Datasets 2.11.0
Tokenizers 0.13.2
