ArabicNewSplits4_FineTuningAraBERT_run1_AugV5_k13_task5_organization

MayBashendy/ArabicNewSplits4_FineTuningAraBERT_run1_AugV5_k13_task5_organization

ArabicNewSplits4_FineTuningAraBERT_run1_AugV5_k13_task5_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 9, 2024
Updated: Dec 9, 2024
SHA: e64fc12e

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Base models

aubmindlab/bert-base-arabertv02

Model card

From the Hugging Face model README

ArabicNewSplits4_FineTuningAraBERT_run1_AugV5_k13_task5_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: 1.0742
Qwk: 0.6201
Mse: 1.0742
Rmse: 1.0364

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	0.0488	2	2.1372	0.0024	2.1372	1.4619
No log	0.0976	4	1.4794	0.1794	1.4794	1.2163
No log	0.1463	6	1.7194	-0.0237	1.7194	1.3113
No log	0.1951	8	1.7158	0.0357	1.7158	1.3099
No log	0.2439	10	1.6694	0.0828	1.6694	1.2921
No log	0.2927	12	1.5937	0.0910	1.5937	1.2624
No log	0.3415	14	1.5291	0.1106	1.5291	1.2366
No log	0.3902	16	1.5033	0.2006	1.5033	1.2261
No log	0.4390	18	1.6493	0.2322	1.6493	1.2843
No log	0.4878	20	1.6866	0.2089	1.6866	1.2987
No log	0.5366	22	1.7005	0.1582	1.7005	1.3040
No log	0.5854	24	1.7032	0.0791	1.7032	1.3051
No log	0.6341	26	1.7029	0.0791	1.7029	1.3050
No log	0.6829	28	1.8323	0.1677	1.8323	1.3536
No log	0.7317	30	2.3324	0.1852	2.3324	1.5272
No log	0.7805	32	2.1742	0.2187	2.1742	1.4745
No log	0.8293	34	1.6510	0.0460	1.6510	1.2849
No log	0.8780	36	1.5609	0.0683	1.5609	1.2494
No log	0.9268	38	1.6933	0.2365	1.6933	1.3013
No log	0.9756	40	1.9834	0.2908	1.9834	1.4083
No log	1.0244	42	1.9448	0.2676	1.9448	1.3945
No log	1.0732	44	1.7697	0.0977	1.7697	1.3303
No log	1.1220	46	1.6539	0.0682	1.6539	1.2860
No log	1.1707	48	1.5873	0.1208	1.5873	1.2599
No log	1.2195	50	1.5818	0.1054	1.5818	1.2577
No log	1.2683	52	1.5932	0.0779	1.5932	1.2622
No log	1.3171	54	1.5827	0.0709	1.5827	1.2581
No log	1.3659	56	1.5910	0.0426	1.5910	1.2614
No log	1.4146	58	1.6285	0.0709	1.6285	1.2761
No log	1.4634	60	1.7513	0.1595	1.7513	1.3234
No log	1.5122	62	1.7952	0.2087	1.7952	1.3399
No log	1.5610	64	1.6898	0.1811	1.6898	1.2999
No log	1.6098	66	1.6922	0.2300	1.6922	1.3008
No log	1.6585	68	1.6297	0.2365	1.6297	1.2766
No log	1.7073	70	1.6154	0.2365	1.6154	1.2710
No log	1.7561	72	1.5455	0.2162	1.5455	1.2432
No log	1.8049	74	1.4856	0.1159	1.4856	1.2188
No log	1.8537	76	1.4889	0.1461	1.4889	1.2202
No log	1.9024	78	1.5105	0.2162	1.5105	1.2290
No log	1.9512	80	1.4813	0.2287	1.4813	1.2171
No log	2.0	82	1.5077	0.2426	1.5077	1.2279
No log	2.0488	84	1.5271	0.3411	1.5271	1.2358
No log	2.0976	86	1.5450	0.3733	1.5450	1.2430
No log	2.1463	88	1.6191	0.3965	1.6191	1.2724
No log	2.1951	90	1.4634	0.4566	1.4634	1.2097
No log	2.2439	92	1.0560	0.5381	1.0560	1.0276
No log	2.2927	94	0.9215	0.5470	0.9215	0.9599
No log	2.3415	96	0.9114	0.5634	0.9114	0.9547
No log	2.3902	98	0.8843	0.5808	0.8843	0.9404
No log	2.4390	100	0.9562	0.6034	0.9562	0.9779
No log	2.4878	102	1.1470	0.5456	1.1470	1.0710
No log	2.5366	104	1.4434	0.4324	1.4434	1.2014
No log	2.5854	106	1.2816	0.4538	1.2816	1.1321
No log	2.6341	108	0.9261	0.6060	0.9261	0.9624
No log	2.6829	110	0.8365	0.6308	0.8365	0.9146
No log	2.7317	112	0.8952	0.6330	0.8952	0.9461
No log	2.7805	114	1.1338	0.5440	1.1338	1.0648
No log	2.8293	116	1.2204	0.5095	1.2204	1.1047
No log	2.8780	118	1.1518	0.5412	1.1518	1.0732
No log	2.9268	120	0.9841	0.6075	0.9841	0.9920
No log	2.9756	122	0.9760	0.6302	0.9760	0.9879
No log	3.0244	124	1.0442	0.6021	1.0442	1.0219
No log	3.0732	126	1.2744	0.5478	1.2744	1.1289
No log	3.1220	128	1.5705	0.4935	1.5705	1.2532
No log	3.1707	130	1.8289	0.4390	1.8289	1.3524
No log	3.2195	132	1.7987	0.4647	1.7987	1.3412
No log	3.2683	134	1.5323	0.5160	1.5323	1.2378
No log	3.3171	136	1.1470	0.5911	1.1470	1.0710
No log	3.3659	138	1.0196	0.6579	1.0196	1.0097
No log	3.4146	140	1.1055	0.5923	1.1055	1.0514
No log	3.4634	142	1.2783	0.5626	1.2783	1.1306
No log	3.5122	144	1.2493	0.5540	1.2493	1.1177
No log	3.5610	146	0.9760	0.6039	0.9760	0.9879
No log	3.6098	148	0.9433	0.6039	0.9433	0.9712
No log	3.6585	150	1.0897	0.6077	1.0897	1.0439
No log	3.7073	152	1.2862	0.5533	1.2862	1.1341
No log	3.7561	154	1.3366	0.5286	1.3366	1.1561
No log	3.8049	156	1.1637	0.5801	1.1637	1.0787
No log	3.8537	158	1.1534	0.6077	1.1534	1.0740
No log	3.9024	160	1.1712	0.5840	1.1712	1.0822
No log	3.9512	162	1.3464	0.5457	1.3464	1.1603
No log	4.0	164	1.4041	0.5482	1.4041	1.1849
No log	4.0488	166	1.4604	0.5386	1.4604	1.2085
No log	4.0976	168	1.3277	0.5747	1.3277	1.1522
No log	4.1463	170	1.3136	0.5856	1.3136	1.1461
No log	4.1951	172	1.2429	0.5831	1.2429	1.1149
No log	4.2439	174	1.3810	0.5328	1.3810	1.1752
No log	4.2927	176	1.6544	0.4841	1.6544	1.2862
No log	4.3415	178	1.8254	0.4218	1.8254	1.3511
No log	4.3902	180	1.7357	0.4373	1.7357	1.3175
No log	4.4390	182	1.4606	0.4603	1.4606	1.2085
No log	4.4878	184	1.2156	0.5200	1.2156	1.1025
No log	4.5366	186	1.1464	0.5175	1.1464	1.0707
No log	4.5854	188	1.2924	0.4990	1.2924	1.1368
No log	4.6341	190	1.5869	0.4596	1.5869	1.2597
No log	4.6829	192	1.8070	0.4356	1.8070	1.3442
No log	4.7317	194	1.8105	0.4356	1.8105	1.3455
No log	4.7805	196	1.6097	0.4581	1.6097	1.2688
No log	4.8293	198	1.2786	0.4961	1.2786	1.1308
No log	4.8780	200	1.0268	0.5783	1.0268	1.0133
No log	4.9268	202	0.9455	0.6138	0.9455	0.9724
No log	4.9756	204	0.9438	0.6176	0.9438	0.9715
No log	5.0244	206	1.0420	0.6046	1.0420	1.0208
No log	5.0732	208	1.1554	0.5716	1.1554	1.0749
No log	5.1220	210	1.1898	0.5489	1.1898	1.0908
No log	5.1707	212	1.0657	0.5638	1.0657	1.0323
No log	5.2195	214	0.9311	0.6237	0.9311	0.9649
No log	5.2683	216	0.9638	0.6127	0.9638	0.9817
No log	5.3171	218	1.0705	0.6097	1.0705	1.0346
No log	5.3659	220	1.2634	0.5606	1.2634	1.1240
No log	5.4146	222	1.3224	0.5614	1.3224	1.1500
No log	5.4634	224	1.2395	0.5863	1.2395	1.1133
No log	5.5122	226	1.2422	0.5863	1.2422	1.1145
No log	5.5610	228	1.2796	0.5719	1.2796	1.1312
No log	5.6098	230	1.2097	0.5996	1.2097	1.0999
No log	5.6585	232	1.1538	0.5778	1.1538	1.0742
No log	5.7073	234	1.1588	0.5664	1.1588	1.0765
No log	5.7561	236	1.2907	0.5256	1.2907	1.1361
No log	5.8049	238	1.4681	0.4924	1.4681	1.2116
No log	5.8537	240	1.4737	0.4816	1.4737	1.2139
No log	5.9024	242	1.3364	0.5061	1.3364	1.1560
No log	5.9512	244	1.2394	0.5271	1.2394	1.1133
No log	6.0	246	1.2907	0.5154	1.2907	1.1361
No log	6.0488	248	1.3597	0.5096	1.3597	1.1661
No log	6.0976	250	1.5197	0.4951	1.5197	1.2328
No log	6.1463	252	1.5608	0.4980	1.5608	1.2493
No log	6.1951	254	1.4461	0.5302	1.4461	1.2025
No log	6.2439	256	1.2746	0.5737	1.2746	1.1290
No log	6.2927	258	1.2507	0.5817	1.2507	1.1183
No log	6.3415	260	1.2769	0.5797	1.2769	1.1300
No log	6.3902	262	1.2158	0.5758	1.2158	1.1026
No log	6.4390	264	1.2899	0.5502	1.2899	1.1357
No log	6.4878	266	1.3492	0.5353	1.3492	1.1615
No log	6.5366	268	1.2958	0.5353	1.2958	1.1383
No log	6.5854	270	1.2154	0.5643	1.2154	1.1025
No log	6.6341	272	1.1862	0.5760	1.1862	1.0891
No log	6.6829	274	1.2398	0.5414	1.2398	1.1134
No log	6.7317	276	1.2252	0.5414	1.2252	1.1069
No log	6.7805	278	1.2744	0.5462	1.2744	1.1289
No log	6.8293	280	1.2346	0.5485	1.2346	1.1111
No log	6.8780	282	1.1740	0.5552	1.1740	1.0835
No log	6.9268	284	1.1388	0.5820	1.1388	1.0671
No log	6.9756	286	1.0674	0.5990	1.0674	1.0332
No log	7.0244	288	1.0167	0.6226	1.0167	1.0083
No log	7.0732	290	1.0063	0.6302	1.0063	1.0032
No log	7.1220	292	1.0495	0.5985	1.0495	1.0244
No log	7.1707	294	1.1440	0.5456	1.1440	1.0696
No log	7.2195	296	1.2331	0.5389	1.2331	1.1104
No log	7.2683	298	1.2339	0.5566	1.2339	1.1108
No log	7.3171	300	1.1905	0.5638	1.1905	1.0911
No log	7.3659	302	1.1875	0.5718	1.1875	1.0897
No log	7.4146	304	1.1612	0.5687	1.1612	1.0776
No log	7.4634	306	1.2280	0.5558	1.2280	1.1082
No log	7.5122	308	1.2819	0.5495	1.2819	1.1322
No log	7.5610	310	1.3144	0.5519	1.3144	1.1465
No log	7.6098	312	1.2999	0.5566	1.2999	1.1401
No log	7.6585	314	1.3204	0.5406	1.3204	1.1491
No log	7.7073	316	1.2969	0.5197	1.2969	1.1388
No log	7.7561	318	1.2728	0.5317	1.2728	1.1282
No log	7.8049	320	1.2209	0.5333	1.2209	1.1049
No log	7.8537	322	1.1749	0.5247	1.1749	1.0839
No log	7.9024	324	1.1184	0.5381	1.1184	1.0576
No log	7.9512	326	1.0851	0.5595	1.0851	1.0417
No log	8.0	328	1.0884	0.5789	1.0884	1.0432
No log	8.0488	330	1.1023	0.5905	1.1023	1.0499
No log	8.0976	332	1.1746	0.5718	1.1746	1.0838
No log	8.1463	334	1.2451	0.5607	1.2451	1.1158
No log	8.1951	336	1.2956	0.5480	1.2956	1.1382
No log	8.2439	338	1.2950	0.5480	1.2950	1.1380
No log	8.2927	340	1.2560	0.5558	1.2560	1.1207
No log	8.3415	342	1.1506	0.5868	1.1506	1.0726
No log	8.3902	344	1.0150	0.6382	1.0150	1.0075
No log	8.4390	346	0.9117	0.6531	0.9117	0.9549
No log	8.4878	348	0.8679	0.6449	0.8679	0.9316
No log	8.5366	350	0.8663	0.6449	0.8663	0.9308
No log	8.5854	352	0.8940	0.6496	0.8940	0.9455
No log	8.6341	354	0.9433	0.6561	0.9433	0.9712
No log	8.6829	356	0.9962	0.6464	0.9962	0.9981
No log	8.7317	358	1.0778	0.6201	1.0778	1.0382
No log	8.7805	360	1.1275	0.5990	1.1275	1.0618
No log	8.8293	362	1.1329	0.6021	1.1329	1.0644
No log	8.8780	364	1.1062	0.6201	1.1062	1.0518
No log	8.9268	366	1.0554	0.6201	1.0554	1.0273
No log	8.9756	368	1.0018	0.6282	1.0018	1.0009
No log	9.0244	370	0.9616	0.6475	0.9616	0.9806
No log	9.0732	372	0.9506	0.6463	0.9506	0.9750
No log	9.1220	374	0.9619	0.6475	0.9619	0.9808
No log	9.1707	376	0.9702	0.6475	0.9702	0.9850
No log	9.2195	378	0.9696	0.6441	0.9696	0.9847
No log	9.2683	380	0.9676	0.6441	0.9676	0.9837
No log	9.3171	382	0.9766	0.6529	0.9766	0.9882
No log	9.3659	384	0.9952	0.6449	0.9952	0.9976
No log	9.4146	386	1.0196	0.6337	1.0196	1.0098
No log	9.4634	388	1.0380	0.6287	1.0380	1.0188
No log	9.5122	390	1.0498	0.6201	1.0498	1.0246
No log	9.5610	392	1.0544	0.6201	1.0544	1.0268
No log	9.6098	394	1.0667	0.6201	1.0667	1.0328
No log	9.6585	396	1.0807	0.6201	1.0807	1.0396
No log	9.7073	398	1.0899	0.6201	1.0899	1.0440
No log	9.7561	400	1.0885	0.6201	1.0885	1.0433
No log	9.8049	402	1.0845	0.6201	1.0845	1.0414
No log	9.8537	404	1.0786	0.6201	1.0786	1.0386
No log	9.9024	406	1.0763	0.6201	1.0763	1.0374
No log	9.9512	408	1.0752	0.6201	1.0752	1.0369
No log	10.0	410	1.0742	0.6201	1.0742	1.0364

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 9, 2024
Updated: Dec 9, 2024