ArabicNewSplits2_FineTuningAraBERT_run4_AugV5_k1_task1_organization

MayBashendy/ArabicNewSplits2_FineTuningAraBERT_run4_AugV5_k1_task1_organization

ArabicNewSplits2_FineTuningAraBERT_run4_AugV5_k1_task1_organization is a text classification model from MayBashendy. Use it when you need a label for a piece of text. It is set up for transformers.

should probably proofread and complete it, then remove this comment. --

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At a glance

Task: Text Classification
Library: transformers
Model type: bert
Access: Public
Created: Dec 3, 2024
Updated: Dec 3, 2024
SHA: 76218226

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Base models

aubmindlab/bert-base-arabertv02

Model card

From the Hugging Face model README

ArabicNewSplits2_FineTuningAraBERT_run4_AugV5_k1_task1_organization

This model is a fine-tuned version of aubmindlab/bert-base-arabertv02 on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.7386
Qwk: 0.6565
Mse: 0.7386
Rmse: 0.8594

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: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Qwk	Mse	Rmse
No log	0.25	2	4.6562	-0.0238	4.6562	2.1578
No log	0.5	4	2.6711	0.0621	2.6711	1.6343
No log	0.75	6	1.5562	0.1657	1.5562	1.2475
No log	1.0	8	1.2919	0.1903	1.2919	1.1366
No log	1.25	10	1.9333	0.1786	1.9333	1.3904
No log	1.5	12	2.0751	0.1689	2.0751	1.4405
No log	1.75	14	1.3692	0.1949	1.3692	1.1701
No log	2.0	16	0.9804	0.4375	0.9804	0.9902
No log	2.25	18	0.9068	0.4333	0.9068	0.9523
No log	2.5	20	0.8557	0.5	0.8557	0.9250
No log	2.75	22	0.8835	0.4912	0.8835	0.9399
No log	3.0	24	1.1687	0.4062	1.1687	1.0811
No log	3.25	26	1.1372	0.4062	1.1372	1.0664
No log	3.5	28	1.0129	0.5072	1.0129	1.0065
No log	3.75	30	0.7113	0.6379	0.7113	0.8434
No log	4.0	32	0.7163	0.6358	0.7163	0.8464
No log	4.25	34	0.8920	0.5743	0.8920	0.9445
No log	4.5	36	0.7842	0.5743	0.7842	0.8856
No log	4.75	38	0.6398	0.7150	0.6398	0.7999
No log	5.0	40	0.6874	0.6279	0.6874	0.8291
No log	5.25	42	0.7339	0.7100	0.7339	0.8567
No log	5.5	44	0.6720	0.7045	0.6720	0.8197
No log	5.75	46	0.6325	0.6872	0.6325	0.7953
No log	6.0	48	0.6297	0.6932	0.6297	0.7935
No log	6.25	50	0.6599	0.7188	0.6599	0.8124
No log	6.5	52	0.6611	0.7130	0.6611	0.8131
No log	6.75	54	0.6542	0.7494	0.6542	0.8088
No log	7.0	56	0.6658	0.7194	0.6658	0.8160
No log	7.25	58	0.6996	0.6815	0.6996	0.8364
No log	7.5	60	0.7047	0.6815	0.7047	0.8395
No log	7.75	62	0.7004	0.7093	0.7004	0.8369
No log	8.0	64	0.6997	0.6705	0.6997	0.8365
No log	8.25	66	0.7226	0.6970	0.7226	0.8500
No log	8.5	68	0.7466	0.685	0.7466	0.8641
No log	8.75	70	0.7716	0.6342	0.7716	0.8784
No log	9.0	72	0.7852	0.6342	0.7852	0.8861
No log	9.25	74	0.7734	0.6342	0.7734	0.8794
No log	9.5	76	0.7577	0.6955	0.7577	0.8704
No log	9.75	78	0.7446	0.6970	0.7446	0.8629
No log	10.0	80	0.7386	0.6565	0.7386	0.8594

Framework versions

Transformers 4.44.2
Pytorch 2.4.0+cu118
Datasets 2.21.0
Tokenizers 0.19.1

Task: Text Classification
Library: transformers
Type: bert
Created: Dec 3, 2024
Updated: Dec 3, 2024