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ft-whisper-ja-1 – AI Model by HuyHoang1977 | AlphaNeural AI
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ft-whisper-ja-1
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
openai/whisper-base
finetune
apache-2.0
endpoints_compatible
us
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ft-whisper-ja-1
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: 0.9157
Cer: 62.7156
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: 16
seed: 42
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: linear
training_steps: 4000
Training results
Training Loss
Epoch
Step
Validation Loss
Cer
0.7693
1.9608
1000
0.9398
66.2863
0.7211
3.9216
2000
0.9197
61.8758
0.7125
5.8824
3000
0.9160
60.7667
0.7119
7.8431
4000
0.9157
62.7156
Framework versions
Transformers 4.57.3
Pytorch 2.9.0+cu126
Datasets 4.0.0
Tokenizers 0.22.1
