Arabic_FineTuningAraBERT_run3_AugV5_k2_task1_organization_fold0

MayBashendy/Arabic_FineTuningAraBERT_run3_AugV5_k2_task1_organization_fold0

Arabic_FineTuningAraBERT_run3_AugV5_k2_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 28, 2024
Updated: Nov 28, 2024
SHA: ec4373af

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Base models

aubmindlab/bert-base-arabertv02

Model card

From the Hugging Face model README

Arabic_FineTuningAraBERT_run3_AugV5_k2_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: 0.7314
Qwk: 0.7354
Mse: 0.7314
Rmse: 0.8552

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	0.0645	2	5.4947	-0.1511	5.4947	2.3441
No log	0.1290	4	2.9524	0.0820	2.9524	1.7183
No log	0.1935	6	1.6834	0.2282	1.6834	1.2975
No log	0.2581	8	1.2740	0.2894	1.2740	1.1287
No log	0.3226	10	1.2374	0.3527	1.2374	1.1124
No log	0.3871	12	1.2230	0.3793	1.2230	1.1059
No log	0.4516	14	1.2797	0.3793	1.2797	1.1312
No log	0.5161	16	1.2714	0.4059	1.2714	1.1275
No log	0.5806	18	1.2719	0.3808	1.2719	1.1278
No log	0.6452	20	1.2855	0.4074	1.2855	1.1338
No log	0.7097	22	1.2268	0.4324	1.2268	1.1076
No log	0.7742	24	1.1128	0.4310	1.1128	1.0549
No log	0.8387	26	1.1011	0.4310	1.1011	1.0494
No log	0.9032	28	1.0303	0.4562	1.0303	1.0150
No log	0.9677	30	0.9620	0.4296	0.9620	0.9808
No log	1.0323	32	0.8269	0.5753	0.8269	0.9093
No log	1.0968	34	0.8078	0.6414	0.8078	0.8988
No log	1.1613	36	0.7540	0.7422	0.7540	0.8683
No log	1.2258	38	0.8354	0.4615	0.8354	0.9140
No log	1.2903	40	0.9730	0.5305	0.9730	0.9864
No log	1.3548	42	0.8187	0.6016	0.8187	0.9048
No log	1.4194	44	0.6978	0.6369	0.6978	0.8353
No log	1.4839	46	1.0276	0.4825	1.0276	1.0137
No log	1.5484	48	1.2678	0.3865	1.2678	1.1260
No log	1.6129	50	1.1434	0.3936	1.1434	1.0693
No log	1.6774	52	1.3203	0.1259	1.3203	1.1491
No log	1.7419	54	1.6164	0.1725	1.6164	1.2714
No log	1.8065	56	1.4141	0.3000	1.4141	1.1892
No log	1.8710	58	1.0414	0.5859	1.0414	1.0205
No log	1.9355	60	0.8127	0.7277	0.8127	0.9015
No log	2.0	62	0.8706	0.7451	0.8706	0.9331
No log	2.0645	64	0.7808	0.7028	0.7808	0.8836
No log	2.1290	66	0.7871	0.6951	0.7871	0.8872
No log	2.1935	68	0.8363	0.5672	0.8363	0.9145
No log	2.2581	70	0.8273	0.7327	0.8273	0.9095
No log	2.3226	72	0.7874	0.6509	0.7874	0.8874
No log	2.3871	74	0.7635	0.6951	0.7635	0.8738
No log	2.4516	76	0.7695	0.7139	0.7695	0.8772
No log	2.5161	78	0.7589	0.7139	0.7589	0.8712
No log	2.5806	80	0.7407	0.7239	0.7407	0.8606
No log	2.6452	82	0.7132	0.7239	0.7132	0.8445
No log	2.7097	84	0.6914	0.6909	0.6914	0.8315
No log	2.7742	86	0.7795	0.6100	0.7795	0.8829
No log	2.8387	88	0.7723	0.6454	0.7723	0.8788
No log	2.9032	90	0.6796	0.7823	0.6796	0.8244
No log	2.9677	92	0.7380	0.6309	0.7380	0.8591
No log	3.0323	94	0.7967	0.5869	0.7967	0.8926
No log	3.0968	96	0.7410	0.5571	0.7410	0.8608
No log	3.1613	98	0.7028	0.7986	0.7028	0.8383
No log	3.2258	100	0.7207	0.7986	0.7207	0.8489
No log	3.2903	102	0.7362	0.7520	0.7362	0.8580
No log	3.3548	104	0.7461	0.7221	0.7461	0.8638
No log	3.4194	106	0.7667	0.6388	0.7667	0.8756
No log	3.4839	108	0.9291	0.5869	0.9291	0.9639
No log	3.5484	110	1.0069	0.5837	1.0069	1.0035
No log	3.6129	112	0.9295	0.6388	0.9295	0.9641
No log	3.6774	114	0.8981	0.6468	0.8981	0.9477
No log	3.7419	116	0.8874	0.6468	0.8874	0.9420
No log	3.8065	118	0.8760	0.6468	0.8760	0.9359
No log	3.8710	120	0.8714	0.6468	0.8714	0.9335
No log	3.9355	122	0.8378	0.6385	0.8378	0.9153
No log	4.0	124	0.8455	0.6468	0.8455	0.9195
No log	4.0645	126	0.8339	0.6947	0.8339	0.9132
No log	4.1290	128	0.7996	0.6889	0.7996	0.8942
No log	4.1935	130	0.7435	0.6385	0.7435	0.8622
No log	4.2581	132	0.7118	0.7358	0.7118	0.8437
No log	4.3226	134	0.6866	0.7268	0.6866	0.8286
No log	4.3871	136	0.6969	0.7086	0.6969	0.8348
No log	4.4516	138	0.8244	0.6256	0.8244	0.9079
No log	4.5161	140	0.9056	0.6256	0.9056	0.9516
No log	4.5806	142	0.8258	0.6726	0.8258	0.9087
No log	4.6452	144	0.7081	0.6736	0.7081	0.8415
No log	4.7097	146	0.7030	0.6861	0.7030	0.8385
No log	4.7742	148	0.7181	0.7191	0.7181	0.8474
No log	4.8387	150	0.7195	0.6741	0.7195	0.8483
No log	4.9032	152	0.7725	0.6884	0.7725	0.8789
No log	4.9677	154	0.8770	0.6339	0.8770	0.9365
No log	5.0323	156	0.8910	0.6339	0.8910	0.9440
No log	5.0968	158	0.7973	0.6339	0.7973	0.8929
No log	5.1613	160	0.7160	0.7273	0.7160	0.8462
No log	5.2258	162	0.7105	0.6794	0.7105	0.8429
No log	5.2903	164	0.7549	0.6884	0.7549	0.8688
No log	5.3548	166	0.8357	0.6339	0.8357	0.9142
No log	5.4194	168	0.9071	0.6339	0.9071	0.9524
No log	5.4839	170	0.9126	0.6339	0.9126	0.9553
No log	5.5484	172	0.8466	0.6974	0.8466	0.9201
No log	5.6129	174	0.8274	0.6974	0.8274	0.9096
No log	5.6774	176	0.7461	0.6736	0.7461	0.8638
No log	5.7419	178	0.7105	0.6799	0.7105	0.8429
No log	5.8065	180	0.6966	0.7191	0.6966	0.8346
No log	5.8710	182	0.6859	0.7191	0.6859	0.8282
No log	5.9355	184	0.6773	0.7268	0.6773	0.8230
No log	6.0	186	0.6904	0.6794	0.6904	0.8309
No log	6.0645	188	0.7110	0.7273	0.7110	0.8432
No log	6.1290	190	0.7731	0.7106	0.7731	0.8793
No log	6.1935	192	0.8512	0.6170	0.8512	0.9226
No log	6.2581	194	0.8328	0.6672	0.8328	0.9126
No log	6.3226	196	0.7596	0.7014	0.7596	0.8716
No log	6.3871	198	0.7060	0.6856	0.7060	0.8402
No log	6.4516	200	0.6954	0.6856	0.6954	0.8339
No log	6.5161	202	0.6956	0.6799	0.6956	0.8340
No log	6.5806	204	0.7031	0.7268	0.7031	0.8385
No log	6.6452	206	0.7102	0.6799	0.7102	0.8427
No log	6.7097	208	0.7084	0.6799	0.7084	0.8417
No log	6.7742	210	0.7052	0.6856	0.7052	0.8398
No log	6.8387	212	0.7143	0.7350	0.7143	0.8452
No log	6.9032	214	0.7369	0.7350	0.7369	0.8584
No log	6.9677	216	0.7318	0.7086	0.7318	0.8554
No log	7.0323	218	0.7264	0.7086	0.7264	0.8523
No log	7.0968	220	0.7148	0.7086	0.7148	0.8455
No log	7.1613	222	0.7211	0.7086	0.7211	0.8492
No log	7.2258	224	0.7455	0.7086	0.7455	0.8634
No log	7.2903	226	0.7342	0.7086	0.7342	0.8569
No log	7.3548	228	0.7071	0.6574	0.7071	0.8409
No log	7.4194	230	0.7012	0.6856	0.7012	0.8374
No log	7.4839	232	0.6971	0.6856	0.6971	0.8349
No log	7.5484	234	0.6927	0.6856	0.6927	0.8323
No log	7.6129	236	0.6926	0.6856	0.6926	0.8322
No log	7.6774	238	0.7066	0.7014	0.7066	0.8406
No log	7.7419	240	0.7251	0.7014	0.7251	0.8515
No log	7.8065	242	0.7451	0.7014	0.7451	0.8632
No log	7.8710	244	0.7447	0.7014	0.7447	0.8630
No log	7.9355	246	0.7230	0.7273	0.7230	0.8503
No log	8.0	248	0.7156	0.7273	0.7156	0.8459
No log	8.0645	250	0.7030	0.7273	0.7030	0.8384
No log	8.1290	252	0.7157	0.7273	0.7157	0.8460
No log	8.1935	254	0.7262	0.7273	0.7262	0.8522
No log	8.2581	256	0.7194	0.7273	0.7194	0.8482
No log	8.3226	258	0.7274	0.7273	0.7274	0.8529
No log	8.3871	260	0.7502	0.72	0.7502	0.8661
No log	8.4516	262	0.7890	0.6947	0.7890	0.8883
No log	8.5161	264	0.8150	0.7106	0.8150	0.9028
No log	8.5806	266	0.8115	0.7106	0.8115	0.9008
No log	8.6452	268	0.7935	0.7281	0.7935	0.8908
No log	8.7097	270	0.7696	0.7586	0.7696	0.8773
No log	8.7742	272	0.7654	0.7586	0.7654	0.8749
No log	8.8387	274	0.7577	0.7586	0.7577	0.8705
No log	8.9032	276	0.7406	0.7586	0.7406	0.8606
No log	8.9677	278	0.7354	0.7512	0.7354	0.8575
No log	9.0323	280	0.7410	0.7586	0.7410	0.8608
No log	9.0968	282	0.7459	0.7586	0.7459	0.8637
No log	9.1613	284	0.7584	0.7586	0.7584	0.8709
No log	9.2258	286	0.7623	0.7586	0.7623	0.8731
No log	9.2903	288	0.7601	0.7586	0.7601	0.8718
No log	9.3548	290	0.7552	0.7586	0.7552	0.8690
No log	9.4194	292	0.7587	0.7354	0.7587	0.8710
No log	9.4839	294	0.7659	0.7354	0.7659	0.8751
No log	9.5484	296	0.7631	0.7354	0.7631	0.8735
No log	9.6129	298	0.7548	0.7354	0.7548	0.8688
No log	9.6774	300	0.7485	0.7354	0.7485	0.8652
No log	9.7419	302	0.7419	0.7354	0.7419	0.8613
No log	9.8065	304	0.7392	0.7354	0.7392	0.8598
No log	9.8710	306	0.7361	0.7354	0.7361	0.8580
No log	9.9355	308	0.7331	0.7354	0.7331	0.8562
No log	10.0	310	0.7314	0.7354	0.7314	0.8552

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 28, 2024
Updated: Nov 28, 2024