ArabicNewSplits_FineTuningAraBERT_AugV5_k1_task1_organization_fold0

MayBashendy/ArabicNewSplits_FineTuningAraBERT_AugV5_k1_task1_organization_fold0

ArabicNewSplits_FineTuningAraBERT_AugV5_k1_task1_organization_fold0 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: Nov 26, 2024
Updated: Nov 26, 2024
SHA: cd7d80e7

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Base models

aubmindlab/bert-base-arabertv02

Model card

From the Hugging Face model README

ArabicNewSplits_FineTuningAraBERT_AugV5_k1_task1_organization_fold0

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: 1.0991
Qwk: 0.5613
Mse: 1.0991
Rmse: 1.0484

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	0.2857	2	3.9444	-0.0064	3.9444	1.9860
No log	0.5714	4	2.6810	0.0236	2.6810	1.6374
No log	0.8571	6	1.8979	0.2145	1.8979	1.3777
No log	1.1429	8	1.9001	0.2959	1.9001	1.3784
No log	1.4286	10	1.3502	0.5079	1.3502	1.1620
No log	1.7143	12	0.9238	0.4740	0.9238	0.9612
No log	2.0	14	1.0110	0.4238	1.0110	1.0055
No log	2.2857	16	0.8625	0.5645	0.8625	0.9287
No log	2.5714	18	0.7905	0.6991	0.7905	0.8891
No log	2.8571	20	0.7841	0.6987	0.7841	0.8855
No log	3.1429	22	0.7586	0.7165	0.7586	0.8709
No log	3.4286	24	0.7830	0.6224	0.7830	0.8849
No log	3.7143	26	0.9189	0.5583	0.9189	0.9586
No log	4.0	28	0.8956	0.6045	0.8956	0.9464
No log	4.2857	30	0.8938	0.6604	0.8938	0.9454
No log	4.5714	32	0.9503	0.6469	0.9503	0.9748
No log	4.8571	34	1.0365	0.5578	1.0365	1.0181
No log	5.1429	36	1.0456	0.5423	1.0456	1.0226
No log	5.4286	38	1.0058	0.5783	1.0058	1.0029
No log	5.7143	40	1.0824	0.5448	1.0824	1.0404
No log	6.0	42	1.1258	0.5073	1.1258	1.0610
No log	6.2857	44	1.0725	0.5460	1.0725	1.0356
No log	6.5714	46	0.9974	0.5691	0.9974	0.9987
No log	6.8571	48	1.0161	0.5691	1.0161	1.0080
No log	7.1429	50	1.0610	0.5624	1.0610	1.0301
No log	7.4286	52	1.0936	0.5624	1.0936	1.0457
No log	7.7143	54	1.0812	0.5546	1.0812	1.0398
No log	8.0	56	1.1182	0.5624	1.1182	1.0575
No log	8.2857	58	1.1619	0.5184	1.1619	1.0779
No log	8.5714	60	1.1885	0.5184	1.1885	1.0902
No log	8.8571	62	1.1549	0.5365	1.1549	1.0747
No log	9.1429	64	1.1300	0.5613	1.1300	1.0630
No log	9.4286	66	1.1001	0.5613	1.1001	1.0489
No log	9.7143	68	1.0936	0.5862	1.0936	1.0457
No log	10.0	70	1.0991	0.5613	1.0991	1.0484

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: Nov 26, 2024
Updated: Nov 26, 2024