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whisper-base-n-demo – AI Model by wandererupak | AlphaNeural AI
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whisper-base-n-demo
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transformers
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
ne
wandererupak/n-demo
openai/whisper-base
finetune
apache-2.0
model-index
endpoints_compatible
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Whisper Base N - Fine-Tuned
This model is a fine-tuned version of
openai/whisper-base
on the N Demo dataset. It achieves the following results on the evaluation set:
Loss: 0.8417
Wer: 85.6884
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
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
lr_scheduler_warmup_steps: 20
num_epochs: 2
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
1.9371
0.4717
25
1.2807
107.6087
1.1246
0.9434
50
0.9736
93.8406
0.8861
1.4151
75
0.8757
86.0507
0.8158
1.8868
100
0.8417
85.6884
Framework versions
Transformers 4.57.6
Pytorch 2.9.0+cu126
Datasets 4.5.0
Tokenizers 0.22.2
