QA_FineTuned_Arabert – AI Model by gp-tar4 | AlphaNeural AI

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gp-tar4/
QA_FineTuned_Arabert

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question-answering

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aubmindlab/bert-base-arabert

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QA_FineTuned_Arabert

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

Loss: 2.8357

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: 0.0002
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
lr_scheduler_warmup_ratio: 0.1
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss
5.518	0.13	10	4.3573
4.254	0.27	20	3.8054
3.9915	0.4	30	3.5788
3.836	0.53	40	3.4054
3.6733	0.67	50	3.2506
3.4425	0.8	60	3.0882
3.2917	0.93	70	2.9934
2.9622	1.07	80	3.0029
2.3228	1.2	90	3.1190
2.4004	1.33	100	2.8613
2.3946	1.47	110	2.8983
2.3108	1.6	120	2.7711
2.3778	1.73	130	2.7062
2.3335	1.87	140	2.9916
2.4273	2.0	150	2.6713
1.4165	2.13	160	2.8003
1.1488	2.27	170	2.7959
1.2044	2.4	180	3.1311
1.2715	2.53	190	2.8319
1.1309	2.67	200	2.8048
1.3421	2.8	210	2.8158
0.9567	2.93	220	2.8357

Framework versions

Transformers 4.39.3
Pytorch 2.1.2
Datasets 2.18.0
Tokenizers 0.15.2