arabic-alphabet-speech-classification – AI Model by ichsanheru | AlphaNeural AI

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arabic-alphabet-speech-classification

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ntu-spml/distilhubert

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arabic-alphabet-speech-classification

This model is a fine-tuned version of ntu-spml/distilhubert on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.0156
Accuracy: 0.9980

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: 8
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_ratio: 0.1
num_epochs: 10
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.0669	1.0	2220	0.9510	0.7601
0.2059	2.0	4440	0.0944	0.9718
0.0457	3.0	6660	0.0452	0.9863
0.0067	4.0	8880	0.0475	0.9903
0.0001	5.0	11100	0.0316	0.9923
0.0121	6.0	13320	0.0377	0.9926
0.0001	7.0	15540	0.0214	0.9950
0.0	8.0	17760	0.0226	0.9968
0.0	9.0	19980	0.0156	0.9980
0.0	10.0	22200	0.0117	0.9977

Framework versions

Transformers 4.42.3
Pytorch 2.1.2
Datasets 2.20.0
Tokenizers 0.19.1