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wav2vec2-base-arabic-finetuned-continued – AI Model by Mohammadawad1 | AlphaNeural AI
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Mohammadawad1
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wav2vec2-base-arabic-finetuned-continued
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transformers
tensorboard
safetensors
wav2vec2
automatic-speech-recognition
generated_from_trainer
common_voice_17_0
Mohammadawad1/wav2vec2-base-arabic-finetuned
finetune
apache-2.0
model-index
endpoints_compatible
us
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wav2vec2-base-arabic-finetuned-continued
This model is a fine-tuned version of
Mohammadawad1/wav2vec2-base-arabic-finetuned
on the common_voice_17_0 dataset. It achieves the following results on the evaluation set:
Loss: 0.6754
Wer: 0.5993
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: 32
eval_batch_size: 32
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 64
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: constant_with_warmup
lr_scheduler_warmup_steps: 50
num_epochs: 5
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.8112
1.0
444
0.8405
0.6893
0.7405
2.0
888
0.7649
0.6513
0.6785
3.0
1332
0.7303
0.6312
0.6484
4.0
1776
0.7013
0.6163
0.5973
4.9899
2215
0.6754
0.5993
Framework versions
Transformers 4.51.3
Pytorch 2.6.0+cu124
Datasets 2.18.0
Tokenizers 0.21.1
