wav2vec2-large-xls-r-300m-Arabic-MDD – AI Model by nrshoudi | AlphaNeural AI

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nrshoudi/
wav2vec2-large-xls-r-300m-Arabic-MDD

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wav2vec2-large-xls-r-300m-Arabic-MDD

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.0204
Per: 0.0096

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: 16
eval_batch_size: 6
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 64
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

Training results

Training Loss	Epoch	Step	Validation Loss	Per
8.4892	1.0	51	3.3287	1.0
2.5606	1.99	102	2.0472	1.0
2.0523	2.99	153	2.0184	1.0
1.9865	4.0	205	1.9865	1.0
1.9854	5.0	256	1.9408	0.9934
1.9603	5.99	307	1.9124	0.9937
1.8169	6.99	358	1.6965	0.9871
1.5596	8.0	410	1.4850	0.9779
1.3494	9.0	461	1.1074	0.9782
0.9242	9.99	512	0.6071	0.7359
0.5172	10.99	563	0.2910	0.2875
0.3105	12.0	615	0.1489	0.1075
0.186	13.0	666	0.0938	0.0342
0.1437	13.99	717	0.0809	0.0255
0.1185	14.99	768	0.0665	0.0127
0.0952	16.0	820	0.0409	0.0103
0.0721	17.0	871	0.0291	0.0107
0.0575	17.99	922	0.0228	0.0089
0.0503	18.99	973	0.0216	0.0100
0.0439	19.9	1020	0.0204	0.0096

Framework versions

Transformers 4.30.1
Pytorch 2.0.1+cu118
Datasets 1.18.3
Tokenizers 0.13.3