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whisper-base-TA-2025 – AI Model by EdwardFang09 | AlphaNeural AI
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whisper-base-TA-2025
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
id
EdwardFang09/IEE4912_Dataset
openai/whisper-base
finetune
apache-2.0
model-index
endpoints_compatible
us
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Model card
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CIT Smart Personal Assistant v1 2025
This model is a fine-tuned version of
openai/whisper-base
on the IEE4912_Dataset dataset. It achieves the following results on the evaluation set:
Loss: nan
Wer: 100.0
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 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: 125
training_steps: 1000
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.0
62.5
250
0.0048
0.0
0.0
125.0
500
nan
100.0
0.0
187.5
750
nan
100.0
0.0
250.0
1000
nan
100.0
Framework versions
Transformers 4.49.0
Pytorch 2.6.0+cu126
Datasets 3.4.1
Tokenizers 0.21.0
