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whisper-medium-ar – AI Model by MostafaKhidr | AlphaNeural AI
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Whisper Medium Ar - Mostafa Khedr
This model is a fine-tuned version of
openai/whisper-medium
on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
Loss: 0.2694
Wer: 38.0957
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
training_steps: 5000
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.2458
0.4156
1000
0.3291
42.8960
0.2301
0.8313
2000
0.2966
42.4461
0.1394
1.2469
3000
0.2905
41.3148
0.108
1.6625
4000
0.2722
38.6282
0.0534
2.0781
5000
0.2694
38.0957
Framework versions
Transformers 4.43.3
Pytorch 2.4.1+cu121
Datasets 3.1.0
Tokenizers 0.19.1
