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quran-recitation-errors-test – AI Model by cherifkhalifah | AlphaNeural AI
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quran-recitation-errors-test
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
ar
audiofolder
openai/whisper-small
finetune
apache-2.0
model-index
endpoints_compatible
us
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quran-recitation-errors-test
This model is a fine-tuned version of
openai/whisper-small
on the audiofolder dataset. It achieves the following results on the evaluation set:
Loss: 0.0732
Wer: 9.6192
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: 0.001
train_batch_size: 16
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 100
training_steps: 500
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.7162
1.6949
100
0.7662
89.5792
0.5519
3.3898
200
0.5851
96.9940
0.3149
5.0847
300
0.2195
59.9198
0.0931
6.7797
400
0.1326
36.6733
0.0072
8.4746
500
0.0732
9.6192
Framework versions
Transformers 4.44.2
Pytorch 2.4.0+cu121
Datasets 2.21.0
Tokenizers 0.19.1
