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whisper-base-en-w-pcd-10-4 – AI Model by navin-kumar-j | AlphaNeural AI
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whisper-base-en-w-pcd-10-4
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
en
openai/whisper-base.en
finetune
apache-2.0
endpoints_compatible
us
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Whisper Base English with Phone Control Data - Navin Kumar J
This model is a fine-tuned version of
openai/whisper-base.en
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.0133
Wer: 0.0046
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: 0.0001
train_batch_size: 16
eval_batch_size: 8
seed: 42
optimizer: Use 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: 10
training_steps: 200
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.0438
0.9091
40
0.0558
0.0107
0.002
1.8182
80
0.0117
0.0046
0.0
2.7273
120
0.0123
0.0031
0.0
3.6364
160
0.0132
0.0046
0.0
4.5455
200
0.0133
0.0046
Framework versions
Transformers 4.51.3
Pytorch 2.7.0+cu126
Datasets 3.5.0
Tokenizers 0.21.1
