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whisper-turbo-ja – AI Model by oda-ai | AlphaNeural AI
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whisper-turbo-ja
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
generator
openai/whisper-large-v3-turbo
finetune
mit
endpoints_compatible
us
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whisper-turbo-ja
This model is a fine-tuned version of
openai/whisper-large-v3-turbo
on the generator 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: 16
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 32
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: constant_with_warmup
lr_scheduler_warmup_steps: 500
training_steps: 10
Training results
Training Loss
Epoch
Step
Validation Loss
Cer
No log
0.6452
10
1.2650
6.7568
Framework versions
Transformers 5.5.4
Pytorch 2.10.0+cu129
Datasets 3.3.0
Tokenizers 0.22.2
