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whisper-base-ko – AI Model by youmi301 | AlphaNeural AI
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whisper-base-ko
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transformers
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
openai/whisper-base
finetune
apache-2.0
endpoints_compatible
us
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whisper-base-ko
This model is a fine-tuned version of
openai/whisper-base
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.1055
Wer Ortho: 7.6796
Wer: 7.7097
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: 5e-05
train_batch_size: 32
eval_batch_size: 16
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 50
training_steps: 2000
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer Ortho
Wer
0.1597
0.7184
500
0.2067
17.8437
17.9190
0.057
1.4368
1000
0.1392
17.8437
17.8889
0.0155
2.1552
1500
0.1144
8.7336
8.7939
0.0128
2.8736
2000
0.1055
7.6796
7.7097
Framework versions
Transformers 4.49.0
Pytorch 2.6.0+cu124
Datasets 3.3.0
Tokenizers 0.21.0
