wav2vec_arabic_mdd_experiment2 – AI Model by nrshoudi | AlphaNeural AI

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nrshoudi/
wav2vec_arabic_mdd_experiment2

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automatic-speech-recognition

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facebook/wav2vec2-xls-r-300m

endpoints_compatible

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wav2vec_arabic_mdd_experiment2

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: 0.2053
Per: 0.1078

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: 0.0005
train_batch_size: 8
eval_batch_size: 6
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 250
num_epochs: 20.0
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Per
6.6285	1.0	102	2.6113	1.0
2.3387	2.0	205	2.3622	1.0
2.3181	3.0	307	2.3030	0.9825
2.1968	4.0	410	1.9821	0.9555
1.7187	5.0	512	1.6775	0.9242
1.6233	6.0	615	1.6232	0.9440
1.5713	7.0	717	1.5419	0.9139
1.4064	8.0	820	1.3078	0.8956
1.2103	9.0	922	1.1363	0.8763
0.898	10.0	1025	0.8109	0.8318
0.6426	11.0	1127	0.6708	0.5635
0.4305	12.0	1230	0.4225	0.2889
0.2961	13.0	1332	0.3487	0.1892
0.1856	14.0	1435	0.2493	0.1223
0.137	15.0	1537	0.2439	0.1198
0.1115	16.0	1640	0.2321	0.1196
0.0923	17.0	1742	0.2226	0.1145
0.0796	18.0	1845	0.2115	0.1120
0.0742	19.0	1947	0.2082	0.1078
0.0684	19.9	2040	0.2053	0.1078

Framework versions

Transformers 4.35.0
Pytorch 2.1.0+cu118
Datasets 2.14.6
Tokenizers 0.14.1