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whisper-small-podcast-fillers – AI Model by joachim-pdm | AlphaNeural AI
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whisper-small-podcast-fillers
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
en
Podimo/podcast-fillers-audio
openai/whisper-small
finetune
apache-2.0
model-index
endpoints_compatible
us
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Whisper Small Podcast Fillers
This model is a fine-tuned version of
openai/whisper-small
on the Podcast Fillers dataset. It achieves the following results on the evaluation set:
Loss: 0.5077
Wer: 21.0899
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_BNB 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: 500
training_steps: 4000
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.1333
0.0575
1000
0.3405
20.8402
0.0489
0.1151
2000
0.3946
20.4906
0.0156
0.1726
3000
0.4630
20.7675
0.0141
0.2301
4000
0.5077
21.0899
Framework versions
Transformers 4.51.3
Pytorch 2.7.0+cu126
Datasets 3.5.0
Tokenizers 0.21.1
