ArabicNewSplits_FineTuningAraBERT_AugV5_k10_task2_organization_fold0

MayBashendy/ArabicNewSplits_FineTuningAraBERT_AugV5_k10_task2_organization_fold0

ArabicNewSplits_FineTuningAraBERT_AugV5_k10_task2_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: 2b573329

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Base models

aubmindlab/bert-base-arabertv02

Model card

From the Hugging Face model README

ArabicNewSplits_FineTuningAraBERT_AugV5_k10_task2_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: 0.8845
Qwk: 0.3761
Mse: 0.8845
Rmse: 0.9405

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	0.0606	2	3.4787	0.0015	3.4787	1.8651
No log	0.1212	4	1.7789	0.0376	1.7789	1.3337
No log	0.1818	6	0.9660	0.1525	0.9660	0.9829
No log	0.2424	8	0.8512	0.1567	0.8512	0.9226
No log	0.3030	10	0.9987	0.0883	0.9987	0.9993
No log	0.3636	12	1.3826	0.1567	1.3826	1.1758
No log	0.4242	14	1.6606	0.0654	1.6606	1.2886
No log	0.4848	16	1.5158	0.1230	1.5158	1.2312
No log	0.5455	18	1.2911	0.1394	1.2911	1.1363
No log	0.6061	20	1.0920	0.0455	1.0920	1.0450
No log	0.6667	22	1.0941	0.0455	1.0941	1.0460
No log	0.7273	24	0.9738	0.0146	0.9738	0.9868
No log	0.7879	26	0.8735	0.0348	0.8735	0.9346
No log	0.8485	28	0.9888	-0.0063	0.9888	0.9944
No log	0.9091	30	1.2345	0.0731	1.2345	1.1111
No log	0.9697	32	1.2610	0.0731	1.2610	1.1230
No log	1.0303	34	1.3057	0.0296	1.3057	1.1427
No log	1.0909	36	1.1829	0.0597	1.1829	1.0876
No log	1.1515	38	1.0741	0.0597	1.0741	1.0364
No log	1.2121	40	0.7988	0.1072	0.7988	0.8938
No log	1.2727	42	0.7304	0.1664	0.7304	0.8547
No log	1.3333	44	0.7790	0.1968	0.7790	0.8826
No log	1.3939	46	0.7542	0.2855	0.7542	0.8685
No log	1.4545	48	0.7283	0.1733	0.7283	0.8534
No log	1.5152	50	0.8861	0.0645	0.8861	0.9413
No log	1.5758	52	0.9275	-0.0273	0.9275	0.9631
No log	1.6364	54	0.8312	0.0106	0.8312	0.9117
No log	1.6970	56	0.8456	0.1554	0.8456	0.9196
No log	1.7576	58	0.8560	0.1567	0.8560	0.9252
No log	1.8182	60	0.8427	0.1404	0.8427	0.9180
No log	1.8788	62	0.8100	0.1445	0.8100	0.9000
No log	1.9394	64	0.7584	0.1580	0.7584	0.8709
No log	2.0	66	0.7400	0.1650	0.7400	0.8603
No log	2.0606	68	0.7570	0.0962	0.7570	0.8701
No log	2.1212	70	0.7674	0.1583	0.7674	0.8760
No log	2.1818	72	0.7523	0.1596	0.7523	0.8673
No log	2.2424	74	0.7400	0.2280	0.7400	0.8602
No log	2.3030	76	0.7575	0.2444	0.7575	0.8703
No log	2.3636	78	0.7693	0.2420	0.7693	0.8771
No log	2.4242	80	0.7571	0.1939	0.7571	0.8701
No log	2.4848	82	0.7377	0.1775	0.7377	0.8589
No log	2.5455	84	0.7627	0.2155	0.7627	0.8733
No log	2.6061	86	0.9443	0.1794	0.9443	0.9718
No log	2.6667	88	1.0278	0.1640	1.0278	1.0138
No log	2.7273	90	0.9986	0.1794	0.9986	0.9993
No log	2.7879	92	0.8415	0.1962	0.8415	0.9173
No log	2.8485	94	0.6808	0.2819	0.6808	0.8251
No log	2.9091	96	0.6661	0.2689	0.6661	0.8161
No log	2.9697	98	0.6626	0.3084	0.6626	0.8140
No log	3.0303	100	0.6697	0.2819	0.6697	0.8183
No log	3.0909	102	0.6897	0.3239	0.6897	0.8305
No log	3.1515	104	0.7506	0.2448	0.7506	0.8664
No log	3.2121	106	0.8196	0.2133	0.8196	0.9053
No log	3.2727	108	0.8407	0.2582	0.8407	0.9169
No log	3.3333	110	0.8075	0.2539	0.8075	0.8986
No log	3.3939	112	0.8473	0.2398	0.8473	0.9205
No log	3.4545	114	0.9741	0.3075	0.9741	0.9870
No log	3.5152	116	1.1326	0.2583	1.1326	1.0642
No log	3.5758	118	1.1144	0.2529	1.1144	1.0556
No log	3.6364	120	1.0004	0.2927	1.0004	1.0002
No log	3.6970	122	0.9945	0.2927	0.9945	0.9972
No log	3.7576	124	1.1072	0.3007	1.1072	1.0522
No log	3.8182	126	1.1440	0.1999	1.1440	1.0696
No log	3.8788	128	1.0889	0.2220	1.0889	1.0435
No log	3.9394	130	0.9451	0.3122	0.9451	0.9722
No log	4.0	132	0.8524	0.2691	0.8524	0.9232
No log	4.0606	134	0.7881	0.2550	0.7881	0.8878
No log	4.1212	136	0.7575	0.2702	0.7575	0.8704
No log	4.1818	138	0.7906	0.2157	0.7906	0.8892
No log	4.2424	140	0.7875	0.2302	0.7875	0.8874
No log	4.3030	142	0.7493	0.2157	0.7493	0.8656
No log	4.3636	144	0.7239	0.2169	0.7239	0.8508
No log	4.4242	146	0.6867	0.2516	0.6867	0.8287
No log	4.4848	148	0.6895	0.3045	0.6895	0.8304
No log	4.5455	150	0.7170	0.2583	0.7170	0.8468
No log	4.6061	152	0.7740	0.2853	0.7740	0.8798
No log	4.6667	154	0.9226	0.3325	0.9226	0.9605
No log	4.7273	156	1.0735	0.3345	1.0735	1.0361
No log	4.7879	158	1.0616	0.3378	1.0616	1.0304
No log	4.8485	160	0.9163	0.3466	0.9163	0.9573
No log	4.9091	162	0.8384	0.3045	0.8384	0.9156
No log	4.9697	164	0.7990	0.2712	0.7990	0.8939
No log	5.0303	166	0.7694	0.2712	0.7694	0.8772
No log	5.0909	168	0.8134	0.3173	0.8134	0.9019
No log	5.1515	170	0.8259	0.2658	0.8259	0.9088
No log	5.2121	172	0.8114	0.2658	0.8114	0.9008
No log	5.2727	174	0.7764	0.2983	0.7764	0.8812
No log	5.3333	176	0.7964	0.2669	0.7964	0.8924
No log	5.3939	178	0.8606	0.2720	0.8606	0.9277
No log	5.4545	180	0.8940	0.3056	0.8940	0.9455
No log	5.5152	182	0.8744	0.2658	0.8744	0.9351
No log	5.5758	184	0.8170	0.2658	0.8170	0.9039
No log	5.6364	186	0.8168	0.2658	0.8168	0.9037
No log	5.6970	188	0.8427	0.3056	0.8427	0.9180
No log	5.7576	190	0.9246	0.3374	0.9246	0.9616
No log	5.8182	192	0.9456	0.3412	0.9456	0.9724
No log	5.8788	194	0.8881	0.3374	0.8881	0.9424
No log	5.9394	196	0.8398	0.3684	0.8398	0.9164
No log	6.0	198	0.7755	0.2691	0.7755	0.8806
No log	6.0606	200	0.7484	0.2550	0.7484	0.8651
No log	6.1212	202	0.7689	0.2691	0.7689	0.8769
No log	6.1818	204	0.8368	0.3103	0.8368	0.9148
No log	6.2424	206	0.9035	0.3449	0.9035	0.9505
No log	6.3030	208	0.9980	0.3664	0.9980	0.9990
No log	6.3636	210	1.0118	0.3224	1.0118	1.0059
No log	6.4242	212	0.9613	0.3761	0.9613	0.9804
No log	6.4848	214	0.8568	0.3449	0.8568	0.9256
No log	6.5455	216	0.7860	0.3253	0.7860	0.8866
No log	6.6061	218	0.7721	0.3531	0.7721	0.8787
No log	6.6667	220	0.8247	0.3714	0.8247	0.9081
No log	6.7273	222	0.9336	0.3223	0.9336	0.9662
No log	6.7879	224	1.0138	0.2830	1.0138	1.0069
No log	6.8485	226	1.0187	0.2830	1.0187	1.0093
No log	6.9091	228	1.0280	0.2830	1.0280	1.0139
No log	6.9697	230	0.9785	0.3223	0.9785	0.9892
No log	7.0303	232	0.9611	0.3188	0.9611	0.9804
No log	7.0909	234	0.9436	0.3578	0.9436	0.9714
No log	7.1515	236	0.9668	0.3578	0.9668	0.9833
No log	7.2121	238	1.0428	0.2786	1.0428	1.0212
No log	7.2727	240	1.0737	0.2662	1.0737	1.0362
No log	7.3333	242	1.0455	0.2786	1.0455	1.0225
No log	7.3939	244	0.9599	0.3578	0.9599	0.9797
No log	7.4545	246	0.8834	0.3103	0.8834	0.9399
No log	7.5152	248	0.8720	0.3103	0.8720	0.9338
No log	7.5758	250	0.8287	0.3103	0.8287	0.9103
No log	7.6364	252	0.8205	0.3103	0.8205	0.9058
No log	7.6970	254	0.7990	0.3103	0.7990	0.8939
No log	7.7576	256	0.8080	0.3103	0.8080	0.8989
No log	7.8182	258	0.8386	0.3103	0.8386	0.9157
No log	7.8788	260	0.8604	0.3449	0.8604	0.9276
No log	7.9394	262	0.8689	0.3449	0.8689	0.9322
No log	8.0	264	0.8946	0.3761	0.8946	0.9458
No log	8.0606	266	0.9261	0.3578	0.9261	0.9623
No log	8.1212	268	0.9562	0.3188	0.9562	0.9779
No log	8.1818	270	0.9393	0.3150	0.9393	0.9692
No log	8.2424	272	0.9225	0.3150	0.9225	0.9605
No log	8.3030	274	0.8851	0.3548	0.8851	0.9408
No log	8.3636	276	0.8741	0.3548	0.8741	0.9349
No log	8.4242	278	0.8903	0.3548	0.8903	0.9436
No log	8.4848	280	0.9031	0.3111	0.9031	0.9503
No log	8.5455	282	0.9290	0.3150	0.9290	0.9639
No log	8.6061	284	0.9363	0.3150	0.9363	0.9676
No log	8.6667	286	0.9592	0.3188	0.9592	0.9794
No log	8.7273	288	0.9648	0.3188	0.9648	0.9823
No log	8.7879	290	0.9804	0.3223	0.9804	0.9901
No log	8.8485	292	0.9959	0.3291	0.9959	0.9979
No log	8.9091	294	1.0197	0.3322	1.0197	1.0098
No log	8.9697	296	1.0405	0.2950	1.0405	1.0201
No log	9.0303	298	1.0356	0.2950	1.0356	1.0176
No log	9.0909	300	1.0159	0.3291	1.0159	1.0079
No log	9.1515	302	1.0057	0.3291	1.0057	1.0029
No log	9.2121	304	0.9870	0.3223	0.9870	0.9935
No log	9.2727	306	0.9713	0.3150	0.9713	0.9855
No log	9.3333	308	0.9476	0.3150	0.9476	0.9734
No log	9.3939	310	0.9313	0.3548	0.9313	0.9650
No log	9.4545	312	0.9128	0.3548	0.9128	0.9554
No log	9.5152	314	0.8925	0.3761	0.8925	0.9447
No log	9.5758	316	0.8776	0.3761	0.8776	0.9368
No log	9.6364	318	0.8710	0.3761	0.8710	0.9333
No log	9.6970	320	0.8724	0.3761	0.8724	0.9340
No log	9.7576	322	0.8749	0.3761	0.8749	0.9354
No log	9.8182	324	0.8805	0.3761	0.8805	0.9383
No log	9.8788	326	0.8830	0.3761	0.8830	0.9397
No log	9.9394	328	0.8845	0.3761	0.8845	0.9405
No log	10.0	330	0.8845	0.3761	0.8845	0.9405

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