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whisper-medium-ko – AI Model by JayYH | AlphaNeural AI
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whisper-medium-ko
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
ko
mozilla-foundation/common_voice_17_0
openai/whisper-medium
finetune
apache-2.0
endpoints_compatible
us
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Whisper Korean - whisper-medium
This model is a fine-tuned version of
openai/whisper-medium
on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:
Loss: 0.3709
Cer: 8.6970
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: 16
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
training_steps: 1000
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Cer
0.0045
11.1111
500
0.3555
8.8374
0.0006
22.2222
1000
0.3709
8.6970
Framework versions
Transformers 4.42.3
Pytorch 2.3.1+cu121
Datasets 2.20.0
Tokenizers 0.19.1
