ArabicNewSplits4_FineTuningAraBERT_run2_AugV5_k8_task1_organization

MayBashendy/ArabicNewSplits4_FineTuningAraBERT_run2_AugV5_k8_task1_organization

ArabicNewSplits4_FineTuningAraBERT_run2_AugV5_k8_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 9, 2024
Updated: Dec 9, 2024
SHA: 30863f8e

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Base models

aubmindlab/bert-base-arabertv02

Model card

From the Hugging Face model README

ArabicNewSplits4_FineTuningAraBERT_run2_AugV5_k8_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: 0.6066
Qwk: 0.7040
Mse: 0.6066
Rmse: 0.7788

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	0.0513	2	5.3090	-0.0485	5.3090	2.3041
No log	0.1026	4	3.0317	0.0796	3.0317	1.7412
No log	0.1538	6	1.9355	0.0926	1.9355	1.3912
No log	0.2051	8	1.6236	0.0576	1.6236	1.2742
No log	0.2564	10	1.2786	0.2107	1.2786	1.1308
No log	0.3077	12	1.1933	0.2310	1.1933	1.0924
No log	0.3590	14	1.4471	0.0224	1.4471	1.2030
No log	0.4103	16	1.6128	0.0085	1.6128	1.2700
No log	0.4615	18	1.7364	0.0187	1.7364	1.3177
No log	0.5128	20	1.5121	0.0170	1.5121	1.2297
No log	0.5641	22	1.2941	0.2161	1.2941	1.1376
No log	0.6154	24	1.2682	0.1895	1.2682	1.1261
No log	0.6667	26	1.2254	0.1517	1.2254	1.1070
No log	0.7179	28	1.1857	0.1517	1.1857	1.0889
No log	0.7692	30	1.1217	0.2296	1.1217	1.0591
No log	0.8205	32	1.0990	0.2954	1.0990	1.0483
No log	0.8718	34	1.4613	0.1478	1.4613	1.2088
No log	0.9231	36	2.2412	0.1243	2.2412	1.4971
No log	0.9744	38	2.1894	0.1244	2.1894	1.4797
No log	1.0256	40	1.6338	0.0860	1.6338	1.2782
No log	1.0769	42	1.1528	0.3588	1.1528	1.0737
No log	1.1282	44	1.0750	0.3399	1.0750	1.0368
No log	1.1795	46	1.1837	0.2655	1.1837	1.0880
No log	1.2308	48	1.2014	0.2454	1.2014	1.0961
No log	1.2821	50	1.1528	0.2987	1.1528	1.0737
No log	1.3333	52	1.1106	0.2734	1.1106	1.0538
No log	1.3846	54	1.1077	0.2889	1.1077	1.0525
No log	1.4359	56	1.1076	0.2837	1.1076	1.0524
No log	1.4872	58	1.1204	0.3288	1.1204	1.0585
No log	1.5385	60	1.1206	0.3316	1.1206	1.0586
No log	1.5897	62	1.0351	0.3408	1.0351	1.0174
No log	1.6410	64	0.9976	0.3816	0.9976	0.9988
No log	1.6923	66	0.9682	0.3869	0.9682	0.9840
No log	1.7436	68	0.9427	0.3848	0.9427	0.9709
No log	1.7949	70	1.0065	0.3476	1.0065	1.0032
No log	1.8462	72	1.0339	0.3754	1.0339	1.0168
No log	1.8974	74	1.2580	0.2773	1.2580	1.1216
No log	1.9487	76	1.4523	0.3167	1.4523	1.2051
No log	2.0	78	1.4960	0.3518	1.4960	1.2231
No log	2.0513	80	1.6753	0.3100	1.6753	1.2943
No log	2.1026	82	1.3846	0.3834	1.3846	1.1767
No log	2.1538	84	1.2452	0.4182	1.2452	1.1159
No log	2.2051	86	1.1395	0.4861	1.1395	1.0675
No log	2.2564	88	1.1377	0.4861	1.1377	1.0666
No log	2.3077	90	1.0063	0.5168	1.0063	1.0031
No log	2.3590	92	0.9708	0.5292	0.9708	0.9853
No log	2.4103	94	0.7911	0.5692	0.7911	0.8894
No log	2.4615	96	0.6903	0.6389	0.6903	0.8308
No log	2.5128	98	0.6617	0.6472	0.6617	0.8134
No log	2.5641	100	0.6765	0.6380	0.6765	0.8225
No log	2.6154	102	0.7835	0.5852	0.7835	0.8851
No log	2.6667	104	0.8734	0.5851	0.8734	0.9345
No log	2.7179	106	0.7224	0.6327	0.7224	0.8499
No log	2.7692	108	0.6289	0.7150	0.6289	0.7930
No log	2.8205	110	0.6273	0.7164	0.6273	0.7920
No log	2.8718	112	0.6147	0.7335	0.6147	0.7840
No log	2.9231	114	0.6305	0.6941	0.6305	0.7940
No log	2.9744	116	0.6749	0.6865	0.6749	0.8215
No log	3.0256	118	0.6164	0.7168	0.6164	0.7851
No log	3.0769	120	0.6174	0.7127	0.6174	0.7858
No log	3.1282	122	0.6226	0.7127	0.6226	0.7890
No log	3.1795	124	0.6154	0.6993	0.6154	0.7845
No log	3.2308	126	0.6297	0.6662	0.6297	0.7936
No log	3.2821	128	0.6249	0.7047	0.6249	0.7905
No log	3.3333	130	0.6413	0.7008	0.6413	0.8008
No log	3.3846	132	0.6589	0.7051	0.6589	0.8117
No log	3.4359	134	0.6365	0.6964	0.6365	0.7978
No log	3.4872	136	0.6365	0.6756	0.6365	0.7978
No log	3.5385	138	0.6362	0.6692	0.6362	0.7976
No log	3.5897	140	0.6280	0.6727	0.6280	0.7925
No log	3.6410	142	0.6500	0.6815	0.6500	0.8062
No log	3.6923	144	0.7031	0.6983	0.7031	0.8385
No log	3.7436	146	0.6731	0.6954	0.6731	0.8204
No log	3.7949	148	0.6460	0.7206	0.6460	0.8037
No log	3.8462	150	0.6617	0.7120	0.6617	0.8134
No log	3.8974	152	0.6629	0.7255	0.6629	0.8142
No log	3.9487	154	0.6526	0.6984	0.6526	0.8078
No log	4.0	156	0.6467	0.7320	0.6467	0.8041
No log	4.0513	158	0.6678	0.6898	0.6678	0.8172
No log	4.1026	160	0.7052	0.6792	0.7052	0.8398
No log	4.1538	162	0.6615	0.7233	0.6615	0.8133
No log	4.2051	164	0.6790	0.7126	0.6790	0.8240
No log	4.2564	166	0.6728	0.7089	0.6728	0.8202
No log	4.3077	168	0.6834	0.7028	0.6834	0.8267
No log	4.3590	170	0.6891	0.6935	0.6891	0.8301
No log	4.4103	172	0.6574	0.7183	0.6574	0.8108
No log	4.4615	174	0.6451	0.7183	0.6451	0.8032
No log	4.5128	176	0.6363	0.7176	0.6363	0.7977
No log	4.5641	178	0.6287	0.7190	0.6287	0.7929
No log	4.6154	180	0.6256	0.7165	0.6256	0.7910
No log	4.6667	182	0.6246	0.6787	0.6246	0.7903
No log	4.7179	184	0.6272	0.6807	0.6272	0.7919
No log	4.7692	186	0.6280	0.7026	0.6280	0.7925
No log	4.8205	188	0.6360	0.6922	0.6360	0.7975
No log	4.8718	190	0.6323	0.6975	0.6323	0.7952
No log	4.9231	192	0.6411	0.7337	0.6411	0.8007
No log	4.9744	194	0.6560	0.7170	0.6560	0.8099
No log	5.0256	196	0.6308	0.7324	0.6308	0.7942
No log	5.0769	198	0.6284	0.7177	0.6284	0.7927
No log	5.1282	200	0.6375	0.7226	0.6375	0.7985
No log	5.1795	202	0.6542	0.7192	0.6542	0.8088
No log	5.2308	204	0.6259	0.7337	0.6259	0.7911
No log	5.2821	206	0.6126	0.7185	0.6126	0.7827
No log	5.3333	208	0.6197	0.7297	0.6197	0.7872
No log	5.3846	210	0.6566	0.7077	0.6566	0.8103
No log	5.4359	212	0.6727	0.6925	0.6727	0.8202
No log	5.4872	214	0.6513	0.7077	0.6513	0.8070
No log	5.5385	216	0.6082	0.7049	0.6082	0.7799
No log	5.5897	218	0.5678	0.7230	0.5678	0.7535
No log	5.6410	220	0.5918	0.7157	0.5918	0.7693
No log	5.6923	222	0.5727	0.7174	0.5727	0.7568
No log	5.7436	224	0.5584	0.7181	0.5584	0.7473
No log	5.7949	226	0.5737	0.7205	0.5737	0.7574
No log	5.8462	228	0.5613	0.7217	0.5613	0.7492
No log	5.8974	230	0.5951	0.7315	0.5951	0.7715
No log	5.9487	232	0.6359	0.7255	0.6359	0.7974
No log	6.0	234	0.5962	0.7560	0.5962	0.7721
No log	6.0513	236	0.5720	0.7413	0.5720	0.7563
No log	6.1026	238	0.5927	0.7089	0.5927	0.7699
No log	6.1538	240	0.5901	0.7228	0.5901	0.7682
No log	6.2051	242	0.6054	0.7382	0.6054	0.7781
No log	6.2564	244	0.5898	0.7282	0.5898	0.7680
No log	6.3077	246	0.6064	0.7488	0.6064	0.7787
No log	6.3590	248	0.6568	0.7240	0.6568	0.8105
No log	6.4103	250	0.6354	0.7330	0.6354	0.7971
No log	6.4615	252	0.6001	0.7499	0.6001	0.7747
No log	6.5128	254	0.6125	0.7349	0.6125	0.7826
No log	6.5641	256	0.6578	0.6885	0.6578	0.8111
No log	6.6154	258	0.6527	0.6733	0.6527	0.8079
No log	6.6667	260	0.6057	0.7112	0.6057	0.7783
No log	6.7179	262	0.5838	0.7306	0.5838	0.7641
No log	6.7692	264	0.5985	0.7291	0.5985	0.7736
No log	6.8205	266	0.6159	0.7308	0.6159	0.7848
No log	6.8718	268	0.6121	0.7205	0.6121	0.7824
No log	6.9231	270	0.6036	0.7304	0.6036	0.7769
No log	6.9744	272	0.6152	0.6974	0.6152	0.7844
No log	7.0256	274	0.6515	0.6588	0.6515	0.8072
No log	7.0769	276	0.6687	0.6438	0.6687	0.8178
No log	7.1282	278	0.6832	0.6390	0.6832	0.8265
No log	7.1795	280	0.6477	0.6379	0.6477	0.8048
No log	7.2308	282	0.6189	0.7562	0.6189	0.7867
No log	7.2821	284	0.6147	0.7271	0.6147	0.7841
No log	7.3333	286	0.6180	0.7133	0.6180	0.7861
No log	7.3846	288	0.6142	0.7316	0.6142	0.7837
No log	7.4359	290	0.6239	0.7420	0.6239	0.7899
No log	7.4872	292	0.6495	0.7092	0.6495	0.8059
No log	7.5385	294	0.6695	0.6781	0.6695	0.8182
No log	7.5897	296	0.6530	0.7092	0.6530	0.8081
No log	7.6410	298	0.6179	0.7369	0.6179	0.7861
No log	7.6923	300	0.6114	0.7378	0.6114	0.7819
No log	7.7436	302	0.6170	0.7147	0.6170	0.7855
No log	7.7949	304	0.6196	0.7201	0.6196	0.7872
No log	7.8462	306	0.6230	0.7099	0.6230	0.7893
No log	7.8974	308	0.6380	0.7114	0.6380	0.7988
No log	7.9487	310	0.6540	0.7082	0.6540	0.8087
No log	8.0	312	0.6405	0.7050	0.6405	0.8003
No log	8.0513	314	0.6199	0.7131	0.6199	0.7873
No log	8.1026	316	0.6095	0.7108	0.6095	0.7807
No log	8.1538	318	0.6094	0.7196	0.6094	0.7807
No log	8.2051	320	0.6121	0.7335	0.6121	0.7824
No log	8.2564	322	0.6146	0.7457	0.6146	0.7840
No log	8.3077	324	0.6148	0.7217	0.6148	0.7841
No log	8.3590	326	0.6215	0.7118	0.6215	0.7883
No log	8.4103	328	0.6386	0.7097	0.6386	0.7992
No log	8.4615	330	0.6492	0.7105	0.6492	0.8057
No log	8.5128	332	0.6439	0.7105	0.6439	0.8024
No log	8.5641	334	0.6409	0.7042	0.6409	0.8006
No log	8.6154	336	0.6273	0.7223	0.6273	0.7920
No log	8.6667	338	0.6141	0.7166	0.6141	0.7836
No log	8.7179	340	0.6112	0.7181	0.6112	0.7818
No log	8.7692	342	0.6181	0.7284	0.6181	0.7862
No log	8.8205	344	0.6217	0.7284	0.6217	0.7885
No log	8.8718	346	0.6204	0.7284	0.6204	0.7876
No log	8.9231	348	0.6158	0.7230	0.6158	0.7848
No log	8.9744	350	0.6098	0.6884	0.6098	0.7809
No log	9.0256	352	0.6074	0.6764	0.6074	0.7794
No log	9.0769	354	0.6081	0.6942	0.6081	0.7798
No log	9.1282	356	0.6098	0.6922	0.6098	0.7809
No log	9.1795	358	0.6097	0.6922	0.6097	0.7808
No log	9.2308	360	0.6075	0.6942	0.6075	0.7794
No log	9.2821	362	0.6050	0.6923	0.6050	0.7778
No log	9.3333	364	0.6028	0.6923	0.6028	0.7764
No log	9.3846	366	0.6018	0.7026	0.6018	0.7758
No log	9.4359	368	0.6024	0.6993	0.6024	0.7761
No log	9.4872	370	0.6042	0.7040	0.6042	0.7773
No log	9.5385	372	0.6057	0.6959	0.6057	0.7783
No log	9.5897	374	0.6080	0.6919	0.6080	0.7797
No log	9.6410	376	0.6101	0.7124	0.6101	0.7811
No log	9.6923	378	0.6097	0.7190	0.6097	0.7808
No log	9.7436	380	0.6080	0.6919	0.6080	0.7798
No log	9.7949	382	0.6070	0.7000	0.6070	0.7791
No log	9.8462	384	0.6066	0.7000	0.6066	0.7789
No log	9.8974	386	0.6065	0.7040	0.6065	0.7788
No log	9.9487	388	0.6065	0.7040	0.6065	0.7788
No log	10.0	390	0.6066	0.7040	0.6066	0.7788

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