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whisper-base-ps – AI Model by afaaaak | AlphaNeural AI
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whisper-base-ps
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
ps
SherwinDesouza/pashto-common-voice-20
openai/whisper-base
finetune
apache-2.0
model-index
endpoints_compatible
us
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Whisper Base Ps - ZFA
This model is a fine-tuned version of
openai/whisper-base
on the Common Voice 20.0 dataset. It achieves the following results on the evaluation set:
Loss: 0.6856
Wer: 54.0707
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: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 16
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: 500
training_steps: 1000
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.2602
5.9199
1000
0.6856
54.0707
Framework versions
Transformers 4.53.2
Pytorch 2.7.1+cu126
Datasets 4.0.0
Tokenizers 0.21.2
