M8 – AI Model by aomar85 | AlphaNeural AI

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aomar85/
M8

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text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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fine_tuned_mix400k_arabert

This model is a fine-tuned version of aubmindlab/bert-base-arabertv02 on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.1851
Accuracy: 0.9674
Precision: 0.9835
Recall: 0.9723
F1: 0.9778

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: 2e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
0.113	1.0	42279	0.1089	0.9541	0.9962	0.9414	0.9680
0.0957	2.0	84558	0.1094	0.9639	0.9869	0.9638	0.9752
0.0833	3.0	126837	0.1061	0.9641	0.9900	0.9611	0.9753
0.0691	4.0	169116	0.1558	0.9677	0.9845	0.9716	0.9780
0.0552	5.0	211395	0.1193	0.9676	0.9843	0.9717	0.9780
0.0411	6.0	253674	0.1851	0.9674	0.9835	0.9723	0.9778

Framework versions

Transformers 4.19.2
Pytorch 1.11.0+cu113
Datasets 2.2.2
Tokenizers 0.12.1