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wav2vec2-surah-mulk-v2 – AI Model by tajcompany | AlphaNeural AI

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tajcompany/
wav2vec2-surah-mulk-v2

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automatic-speech-recognition

generated_from_trainer

jonatasgrosman/wav2vec2-large-xlsr-53-arabic

endpoints_compatible

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wav2vec2-surah-mulk-v2

This model is a fine-tuned version of jonatasgrosman/wav2vec2-large-xlsr-53-arabic on the None dataset.

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: 3e-05
train_batch_size: 1
eval_batch_size: 1
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 4
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 3
mixed_precision_training: Native AMP

Training results

Framework versions

Transformers 4.57.1
Pytorch 2.8.0+cu126
Datasets 4.0.0
Tokenizers 0.22.1