mdd-arabic-e2-xlsr300m-unannotated-beam – AI Model by omarZACK | AlphaNeural AI

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omarZACK/
mdd-arabic-e2-xlsr300m-unannotated-beam

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automatic-speech-recognition

generated_from_trainer

facebook/wav2vec2-xls-r-300m

endpoints_compatible

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mdd-arabic-e2-xlsr300m-unannotated-beam

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 13.8083
Per: 0.8981

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: 0.0003
train_batch_size: 24
eval_batch_size: 24
seed: 42
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
lr_scheduler_warmup_steps: 0.1
num_epochs: 30
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Per
2.2295	1.0	970	6.8593	0.8932
1.0776	2.0	1940	9.1442	0.8745
0.9818	3.0	2910	10.4151	0.8742
0.7230	4.0	3880	11.1031	0.8738
0.6338	5.0	4850	11.9739	0.8840
0.4782	6.0	5820	12.2693	0.8844
0.4198	7.0	6790	12.8384	0.8755
0.3668	8.0	7760	13.4830	0.8831
0.3602	9.0	8730	13.8083	0.8981

Framework versions

Transformers 5.14.1
Pytorch 2.10.0+cu128
Datasets 5.0.1
Tokenizers 0.22.2