Arabic_FineTuningAraBERT_AugV5_k3_task1_organization_fold0

MayBashendy/Arabic_FineTuningAraBERT_AugV5_k3_task1_organization_fold0

Arabic_FineTuningAraBERT_AugV5_k3_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 18, 2024
Updated: Nov 24, 2024
SHA: 5955b69c

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Base models

aubmindlab/bert-base-arabertv02

Model card

From the Hugging Face model README

Arabic_FineTuningAraBERT_AugV5_k3_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: 0.7378
Qwk: 0.6943
Mse: 0.7378
Rmse: 0.8589

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	5.4054	-0.1511	5.4054	2.3250
No log	0.0976	4	2.9007	0.1393	2.9007	1.7032
No log	0.1463	6	2.2341	-0.0383	2.2341	1.4947
No log	0.1951	8	2.5767	-0.2328	2.5767	1.6052
No log	0.2439	10	1.7577	-0.0074	1.7577	1.3258
No log	0.2927	12	1.7273	-0.0370	1.7273	1.3143
No log	0.3415	14	1.5499	-0.0345	1.5499	1.2449
No log	0.3902	16	1.4362	0.3243	1.4362	1.1984
No log	0.4390	18	1.3119	0.3259	1.3119	1.1454
No log	0.4878	20	1.5416	0.0244	1.5416	1.2416
No log	0.5366	22	1.7297	0.0	1.7297	1.3152
No log	0.5854	24	1.7164	0.0244	1.7164	1.3101
No log	0.6341	26	1.6431	-0.0024	1.6431	1.2818
No log	0.6829	28	1.5800	-0.1080	1.5800	1.2570
No log	0.7317	30	1.4737	0.0667	1.4737	1.2140
No log	0.7805	32	1.4458	0.0667	1.4458	1.2024
No log	0.8293	34	1.3723	0.3026	1.3723	1.1715
No log	0.8780	36	1.2910	0.3292	1.2910	1.1362
No log	0.9268	38	1.2143	0.3292	1.2143	1.1020
No log	0.9756	40	1.1589	0.4310	1.1589	1.0765
No log	1.0244	42	1.2719	0.3026	1.2719	1.1278
No log	1.0732	44	1.5416	0.0490	1.5416	1.2416
No log	1.1220	46	1.2914	0.1744	1.2914	1.1364
No log	1.1707	48	1.1760	0.3026	1.1760	1.0845
No log	1.2195	50	1.1452	0.3778	1.1452	1.0701
No log	1.2683	52	1.1143	0.5068	1.1143	1.0556
No log	1.3171	54	1.0121	0.4815	1.0121	1.0060
No log	1.3659	56	1.0864	0.4627	1.0864	1.0423
No log	1.4146	58	1.2942	0.3488	1.2942	1.1376
No log	1.4634	60	1.6420	0.4767	1.6420	1.2814
No log	1.5122	62	1.2206	0.4931	1.2206	1.1048
No log	1.5610	64	0.7717	0.5305	0.7717	0.8784
No log	1.6098	66	0.8002	0.5697	0.8002	0.8945
No log	1.6585	68	1.0052	0.4552	1.0052	1.0026
No log	1.7073	70	1.1502	0.4298	1.1502	1.0725
No log	1.7561	72	1.0751	0.4298	1.0751	1.0369
No log	1.8049	74	0.8864	0.5300	0.8864	0.9415
No log	1.8537	76	0.7884	0.5283	0.7884	0.8879
No log	1.9024	78	0.8076	0.5283	0.8076	0.8987
No log	1.9512	80	0.7971	0.5494	0.7971	0.8928
No log	2.0	82	0.7312	0.7101	0.7312	0.8551
No log	2.0488	84	0.7021	0.6982	0.7021	0.8379
No log	2.0976	86	0.6866	0.6624	0.6866	0.8286
No log	2.1463	88	0.7741	0.4842	0.7741	0.8799
No log	2.1951	90	0.7445	0.5082	0.7445	0.8629
No log	2.2439	92	0.6611	0.6182	0.6611	0.8131
No log	2.2927	94	0.6233	0.7316	0.6233	0.7895
No log	2.3415	96	0.5929	0.7316	0.5929	0.7700
No log	2.3902	98	0.6223	0.7316	0.6223	0.7889
No log	2.4390	100	0.6446	0.7316	0.6446	0.8028
No log	2.4878	102	0.6779	0.6752	0.6779	0.8233
No log	2.5366	104	0.7103	0.6627	0.7103	0.8428
No log	2.5854	106	0.7383	0.6225	0.7383	0.8593
No log	2.6341	108	0.8016	0.6394	0.8016	0.8953
No log	2.6829	110	0.8285	0.6388	0.8285	0.9102
No log	2.7317	112	0.8725	0.6902	0.8725	0.9341
No log	2.7805	114	0.8467	0.6902	0.8467	0.9201
No log	2.8293	116	0.8074	0.6902	0.8074	0.8986
No log	2.8780	118	0.7758	0.6394	0.7758	0.8808
No log	2.9268	120	0.8105	0.6345	0.8105	0.9003
No log	2.9756	122	0.8181	0.6345	0.8181	0.9045
No log	3.0244	124	0.8382	0.6388	0.8382	0.9156
No log	3.0732	126	0.8001	0.6394	0.8001	0.8945
No log	3.1220	128	0.8523	0.6388	0.8523	0.9232
No log	3.1707	130	0.8732	0.6345	0.8732	0.9345
No log	3.2195	132	0.9254	0.6345	0.9254	0.9620
No log	3.2683	134	0.9143	0.5843	0.9143	0.9562
No log	3.3171	136	0.8656	0.6345	0.8656	0.9304
No log	3.3659	138	0.8662	0.6382	0.8662	0.9307
No log	3.4146	140	0.8251	0.6382	0.8251	0.9084
No log	3.4634	142	0.7477	0.6802	0.7477	0.8647
No log	3.5122	144	0.7516	0.6738	0.7516	0.8669
No log	3.5610	146	0.7998	0.6841	0.7998	0.8943
No log	3.6098	148	0.8099	0.6841	0.8099	0.9000
No log	3.6585	150	0.8548	0.6841	0.8548	0.9245
No log	3.7073	152	0.8859	0.6841	0.8859	0.9412
No log	3.7561	154	0.8511	0.6305	0.8511	0.9226
No log	3.8049	156	0.8606	0.6631	0.8606	0.9277
No log	3.8537	158	0.8641	0.6631	0.8641	0.9296
No log	3.9024	160	0.8183	0.6799	0.8183	0.9046
No log	3.9512	162	0.7788	0.6525	0.7788	0.8825
No log	4.0	164	0.7760	0.6525	0.7760	0.8809
No log	4.0488	166	0.7754	0.6473	0.7754	0.8806
No log	4.0976	168	0.7330	0.6473	0.7330	0.8561
No log	4.1463	170	0.7376	0.6473	0.7376	0.8588
No log	4.1951	172	0.7394	0.6473	0.7394	0.8599
No log	4.2439	174	0.7515	0.6741	0.7515	0.8669
No log	4.2927	176	0.7797	0.6473	0.7797	0.8830
No log	4.3415	178	0.8134	0.7110	0.8134	0.9019
No log	4.3902	180	0.8697	0.7042	0.8697	0.9326
No log	4.4390	182	0.8770	0.7284	0.8770	0.9365
No log	4.4878	184	0.8452	0.7284	0.8452	0.9194
No log	4.5366	186	0.8361	0.7284	0.8361	0.9144
No log	4.5854	188	0.8499	0.6830	0.8499	0.9219
No log	4.6341	190	1.0127	0.6721	1.0127	1.0063
No log	4.6829	192	1.1341	0.6404	1.1341	1.0649
No log	4.7317	194	1.1177	0.5931	1.1177	1.0572
No log	4.7805	196	0.9893	0.6452	0.9893	0.9946
No log	4.8293	198	0.8106	0.6339	0.8106	0.9003
No log	4.8780	200	0.7536	0.6339	0.7536	0.8681
No log	4.9268	202	0.7038	0.6339	0.7038	0.8389
No log	4.9756	204	0.6804	0.6339	0.6804	0.8248
No log	5.0244	206	0.6879	0.6115	0.6879	0.8294
No log	5.0732	208	0.6883	0.6115	0.6883	0.8297
No log	5.1220	210	0.6837	0.6678	0.6837	0.8268
No log	5.1707	212	0.6865	0.6616	0.6865	0.8286
No log	5.2195	214	0.7428	0.6610	0.7428	0.8619
No log	5.2683	216	0.7881	0.6429	0.7881	0.8878
No log	5.3171	218	0.8320	0.6831	0.8320	0.9121
No log	5.3659	220	0.8194	0.6831	0.8194	0.9052
No log	5.4146	222	0.7729	0.7	0.7729	0.8791
No log	5.4634	224	0.6885	0.6673	0.6885	0.8298
No log	5.5122	226	0.6585	0.6616	0.6585	0.8115
No log	5.5610	228	0.6820	0.6907	0.6820	0.8258
No log	5.6098	230	0.7622	0.7071	0.7622	0.8731
No log	5.6585	232	0.8646	0.7260	0.8646	0.9298
No log	5.7073	234	0.8831	0.6944	0.8831	0.9397
No log	5.7561	236	0.8633	0.7147	0.8633	0.9291
No log	5.8049	238	0.8733	0.7147	0.8733	0.9345
No log	5.8537	240	0.8319	0.7360	0.8319	0.9121
No log	5.9024	242	0.7715	0.7434	0.7715	0.8783
No log	5.9512	244	0.7224	0.7079	0.7224	0.8499
No log	6.0	246	0.6893	0.6883	0.6893	0.8302
No log	6.0488	248	0.6759	0.7055	0.6759	0.8221
No log	6.0976	250	0.6737	0.6473	0.6737	0.8208
No log	6.1463	252	0.6904	0.7110	0.6904	0.8309
No log	6.1951	254	0.6986	0.6907	0.6986	0.8358
No log	6.2439	256	0.7036	0.6673	0.7036	0.8388
No log	6.2927	258	0.6828	0.6972	0.6828	0.8263
No log	6.3415	260	0.6531	0.6846	0.6531	0.8082
No log	6.3902	262	0.6398	0.7514	0.6398	0.7999
No log	6.4390	264	0.6278	0.7514	0.6278	0.7923
No log	6.4878	266	0.6298	0.6977	0.6298	0.7936
No log	6.5366	268	0.6600	0.6616	0.6600	0.8124
No log	6.5854	270	0.6625	0.6616	0.6625	0.8139
No log	6.6341	272	0.6934	0.6616	0.6934	0.8327
No log	6.6829	274	0.7090	0.6616	0.7090	0.8420
No log	6.7317	276	0.7412	0.6673	0.7412	0.8609
No log	6.7805	278	0.7350	0.6673	0.7350	0.8573
No log	6.8293	280	0.7018	0.6740	0.7018	0.8377
No log	6.8780	282	0.6842	0.7211	0.6842	0.8272
No log	6.9268	284	0.6708	0.7211	0.6708	0.8190
No log	6.9756	286	0.6440	0.7129	0.6440	0.8025
No log	7.0244	288	0.6544	0.7211	0.6544	0.8090
No log	7.0732	290	0.7089	0.6929	0.7089	0.8420
No log	7.1220	292	0.7542	0.5926	0.7542	0.8685
No log	7.1707	294	0.7526	0.6485	0.7526	0.8675
No log	7.2195	296	0.7140	0.6485	0.7140	0.8450
No log	7.2683	298	0.6730	0.6616	0.6730	0.8203
No log	7.3171	300	0.6520	0.6907	0.6520	0.8074
No log	7.3659	302	0.6661	0.7110	0.6661	0.8161
No log	7.4146	304	0.7108	0.7110	0.7108	0.8431
No log	7.4634	306	0.7555	0.7110	0.7555	0.8692
No log	7.5122	308	0.7619	0.6846	0.7619	0.8729
No log	7.5610	310	0.7360	0.7110	0.7360	0.8579
No log	7.6098	312	0.7077	0.7110	0.7077	0.8413
No log	7.6585	314	0.6955	0.7110	0.6955	0.8340
No log	7.7073	316	0.6850	0.7110	0.6850	0.8276
No log	7.7561	318	0.6896	0.7110	0.6896	0.8304
No log	7.8049	320	0.6913	0.6846	0.6913	0.8314
No log	7.8537	322	0.6888	0.6846	0.6888	0.8299
No log	7.9024	324	0.6997	0.6846	0.6997	0.8365
No log	7.9512	326	0.7211	0.7264	0.7211	0.8492
No log	8.0	328	0.7453	0.7264	0.7453	0.8633
No log	8.0488	330	0.7731	0.7071	0.7731	0.8793
No log	8.0976	332	0.7644	0.7071	0.7644	0.8743
No log	8.1463	334	0.7360	0.7005	0.7360	0.8579
No log	8.1951	336	0.6838	0.7196	0.6838	0.8269
No log	8.2439	338	0.6551	0.7590	0.6551	0.8094
No log	8.2927	340	0.6420	0.7590	0.6420	0.8012
No log	8.3415	342	0.6454	0.7590	0.6454	0.8034
No log	8.3902	344	0.6618	0.7196	0.6618	0.8135
No log	8.4390	346	0.6918	0.6943	0.6918	0.8318
No log	8.4878	348	0.7247	0.6943	0.7247	0.8513
No log	8.5366	350	0.7513	0.7005	0.7513	0.8668
No log	8.5854	352	0.7547	0.7005	0.7547	0.8687
No log	8.6341	354	0.7400	0.7005	0.7400	0.8602
No log	8.6829	356	0.7441	0.7005	0.7441	0.8626
No log	8.7317	358	0.7358	0.6943	0.7358	0.8578
No log	8.7805	360	0.7363	0.7005	0.7363	0.8581
No log	8.8293	362	0.7313	0.6943	0.7313	0.8552
No log	8.8780	364	0.7067	0.6943	0.7067	0.8407
No log	8.9268	366	0.6823	0.7196	0.6823	0.8260
No log	8.9756	368	0.6637	0.7590	0.6637	0.8147
No log	9.0244	370	0.6691	0.7590	0.6691	0.8180
No log	9.0732	372	0.6908	0.7196	0.6908	0.8312
No log	9.1220	374	0.7209	0.6943	0.7209	0.8490
No log	9.1707	376	0.7467	0.6943	0.7467	0.8641
No log	9.2195	378	0.7756	0.7005	0.7756	0.8807
No log	9.2683	380	0.7991	0.7005	0.7991	0.8939
No log	9.3171	382	0.8137	0.7005	0.8137	0.9020
No log	9.3659	384	0.8203	0.7005	0.8203	0.9057
No log	9.4146	386	0.8077	0.7005	0.8077	0.8987
No log	9.4634	388	0.7865	0.7005	0.7865	0.8868
No log	9.5122	390	0.7649	0.6943	0.7649	0.8746
No log	9.5610	392	0.7491	0.7196	0.7491	0.8655
No log	9.6098	394	0.7404	0.7196	0.7404	0.8605
No log	9.6585	396	0.7339	0.7196	0.7339	0.8567
No log	9.7073	398	0.7279	0.7196	0.7279	0.8531
No log	9.7561	400	0.7292	0.6943	0.7292	0.8539
No log	9.8049	402	0.7316	0.6943	0.7316	0.8554
No log	9.8537	404	0.7346	0.6943	0.7346	0.8571
No log	9.9024	406	0.7373	0.6943	0.7373	0.8587
No log	9.9512	408	0.7380	0.6943	0.7380	0.8591
No log	10.0	410	0.7378	0.6943	0.7378	0.8589

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 18, 2024
Updated: Nov 24, 2024