Arabic_FineTuningAraBERT_AugV4_k2_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: 0.7142
• Qwk: 0.3636
• Mse: 0.7142
• Rmse: 0.8451

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	0.0625	2	3.5574	0.0	3.5574	1.8861
No log	0.125	4	2.5912	0.0648	2.5912	1.6097
No log	0.1875	6	1.1158	0.0	1.1158	1.0563
No log	0.25	8	0.8182	-0.0087	0.8182	0.9045
No log	0.3125	10	0.7208	0.1340	0.7208	0.8490
No log	0.375	12	0.7735	0.0679	0.7735	0.8795
No log	0.4375	14	0.6956	0.2184	0.6956	0.8340
No log	0.5	16	0.6741	0.1560	0.6741	0.8210
No log	0.5625	18	0.7210	0.0679	0.7210	0.8491
No log	0.625	20	0.8732	0.0	0.8732	0.9345
No log	0.6875	22	0.8785	0.0	0.8785	0.9373
No log	0.75	24	0.9320	0.0	0.9320	0.9654
No log	0.8125	26	1.0634	0.0386	1.0634	1.0312
No log	0.875	28	1.0673	0.0982	1.0673	1.0331
No log	0.9375	30	1.2105	0.1600	1.2105	1.1002
No log	1.0	32	1.2187	0.0418	1.2187	1.1039
No log	1.0625	34	1.0217	0.0	1.0217	1.0108
No log	1.125	36	0.8190	0.0	0.8190	0.9050
No log	1.1875	38	0.7905	0.0	0.7905	0.8891
No log	1.25	40	0.8653	0.0	0.8653	0.9302
No log	1.3125	42	0.8664	0.0	0.8664	0.9308
No log	1.375	44	0.6802	0.1558	0.6802	0.8247
No log	1.4375	46	0.6463	0.1563	0.6463	0.8039
No log	1.5	48	0.6016	0.1941	0.6016	0.7756
No log	1.5625	50	0.5745	0.2184	0.5745	0.7580
No log	1.625	52	0.7385	0.3731	0.7385	0.8593
No log	1.6875	54	1.0266	0.3345	1.0266	1.0132
No log	1.75	56	1.3054	0.0637	1.3054	1.1425
No log	1.8125	58	1.1787	0.3000	1.1787	1.0857
No log	1.875	60	0.8577	0.0386	0.8576	0.9261
No log	1.9375	62	0.6373	0.1340	0.6373	0.7983
No log	2.0	64	0.6061	0.1558	0.6061	0.7785
No log	2.0625	66	0.6471	0.2184	0.6471	0.8044
No log	2.125	68	0.6984	0.1765	0.6984	0.8357
No log	2.1875	70	0.6876	0.1765	0.6876	0.8292
No log	2.25	72	0.6744	0.0916	0.6744	0.8212
No log	2.3125	74	0.7117	0.0916	0.7117	0.8436
No log	2.375	76	0.7195	0.2355	0.7195	0.8482
No log	2.4375	78	0.6580	0.3396	0.6580	0.8112
No log	2.5	80	0.6356	0.1962	0.6356	0.7973
No log	2.5625	82	0.6420	0.1962	0.6420	0.8012
No log	2.625	84	0.6756	0.3121	0.6756	0.8220
No log	2.6875	86	0.8289	0.25	0.8289	0.9104
No log	2.75	88	0.9684	0.1848	0.9684	0.9841
No log	2.8125	90	0.9592	0.2948	0.9592	0.9794
No log	2.875	92	0.8611	0.1818	0.8611	0.9280
No log	2.9375	94	0.7899	-0.0553	0.7899	0.8887
No log	3.0	96	0.7626	-0.0553	0.7626	0.8733
No log	3.0625	98	0.7545	0.0916	0.7545	0.8686
No log	3.125	100	0.7883	0.2759	0.7883	0.8879
No log	3.1875	102	0.7863	0.3636	0.7863	0.8868
No log	3.25	104	0.7927	0.4280	0.7927	0.8903
No log	3.3125	106	0.8685	0.3877	0.8685	0.9319
No log	3.375	108	0.8539	0.3877	0.8539	0.9241
No log	3.4375	110	0.8157	0.3846	0.8157	0.9032
No log	3.5	112	0.8007	0.3846	0.8007	0.8948
No log	3.5625	114	0.7879	0.3877	0.7879	0.8876
No log	3.625	116	0.6974	0.3811	0.6974	0.8351
No log	3.6875	118	0.6517	0.3811	0.6517	0.8073
No log	3.75	120	0.5624	0.3811	0.5624	0.7499
No log	3.8125	122	0.5221	0.3900	0.5221	0.7225
No log	3.875	124	0.5309	0.4394	0.5309	0.7287
No log	3.9375	126	0.5566	0.3900	0.5566	0.7461
No log	4.0	128	0.6189	0.3811	0.6189	0.7867
No log	4.0625	130	0.6431	0.3811	0.6431	0.8019
No log	4.125	132	0.6546	0.3811	0.6546	0.8091
No log	4.1875	134	0.6924	0.3846	0.6924	0.8321
No log	4.25	136	0.7577	0.3846	0.7577	0.8704
No log	4.3125	138	0.7593	0.4286	0.7593	0.8714
No log	4.375	140	0.7426	0.3980	0.7426	0.8617
No log	4.4375	142	0.7085	0.3931	0.7085	0.8417
No log	4.5	144	0.6920	0.3957	0.6920	0.8319
No log	4.5625	146	0.6624	0.3636	0.6624	0.8139
No log	4.625	148	0.6562	0.3957	0.6562	0.8101
No log	4.6875	150	0.6182	0.4483	0.6182	0.7863
No log	4.75	152	0.6121	0.4483	0.6121	0.7824
No log	4.8125	154	0.6634	0.3636	0.6634	0.8145
No log	4.875	156	0.7384	0.3521	0.7384	0.8593
No log	4.9375	158	0.7385	0.3521	0.7385	0.8593
No log	5.0	160	0.6926	0.3521	0.6926	0.8322
No log	5.0625	162	0.7180	0.3521	0.7180	0.8474
No log	5.125	164	0.6886	0.3201	0.6886	0.8298
No log	5.1875	166	0.6391	0.4064	0.6391	0.7994
No log	5.25	168	0.6655	0.3748	0.6655	0.8158
No log	5.3125	170	0.7081	0.4064	0.7081	0.8415
No log	5.375	172	0.7877	0.3201	0.7877	0.8875
No log	5.4375	174	0.8394	0.2563	0.8394	0.9162
No log	5.5	176	0.8145	0.3636	0.8145	0.9025
No log	5.5625	178	0.7880	0.4064	0.7880	0.8877
No log	5.625	180	0.7680	0.4064	0.7680	0.8764
No log	5.6875	182	0.7505	0.3201	0.7505	0.8663
No log	5.75	184	0.7213	0.2317	0.7213	0.8493
No log	5.8125	186	0.6852	0.2959	0.6852	0.8278
No log	5.875	188	0.6643	0.2959	0.6643	0.8150
No log	5.9375	190	0.6418	0.4615	0.6418	0.8011
No log	6.0	192	0.6414	0.4483	0.6414	0.8009
No log	6.0625	194	0.6435	0.4483	0.6435	0.8022
No log	6.125	196	0.6294	0.5318	0.6294	0.7934
No log	6.1875	198	0.6249	0.5024	0.6249	0.7905
No log	6.25	200	0.6305	0.4167	0.6305	0.7940
No log	6.3125	202	0.6881	0.4064	0.6881	0.8295
No log	6.375	204	0.7890	0.4288	0.7890	0.8883
No log	6.4375	206	0.8404	0.4288	0.8404	0.9167
No log	6.5	208	0.8045	0.4288	0.8045	0.8970
No log	6.5625	210	0.7138	0.4064	0.7138	0.8448
No log	6.625	212	0.6400	0.3748	0.6400	0.8000
No log	6.6875	214	0.6318	0.3748	0.6318	0.7949
No log	6.75	216	0.6582	0.3748	0.6582	0.8113
No log	6.8125	218	0.7157	0.3201	0.7157	0.8460
No log	6.875	220	0.7699	0.3521	0.7699	0.8774
No log	6.9375	222	0.7587	0.3521	0.7587	0.8711
No log	7.0	224	0.6961	0.3201	0.6961	0.8343
No log	7.0625	226	0.6309	0.3748	0.6309	0.7943
No log	7.125	228	0.6090	0.5301	0.6090	0.7804
No log	7.1875	230	0.6062	0.5318	0.6062	0.7786
No log	7.25	232	0.6094	0.5301	0.6094	0.7806
No log	7.3125	234	0.6263	0.3748	0.6263	0.7914
No log	7.375	236	0.6427	0.3636	0.6427	0.8017
No log	7.4375	238	0.6521	0.3636	0.6521	0.8075
No log	7.5	240	0.6698	0.3521	0.6698	0.8184
No log	7.5625	242	0.6665	0.3201	0.6665	0.8164
No log	7.625	244	0.6839	0.3201	0.6839	0.8270
No log	7.6875	246	0.6894	0.3636	0.6894	0.8303
No log	7.75	248	0.6720	0.3748	0.6720	0.8198
No log	7.8125	250	0.6553	0.3748	0.6553	0.8095
No log	7.875	252	0.6516	0.3748	0.6516	0.8072
No log	7.9375	254	0.6576	0.3748	0.6576	0.8109
No log	8.0	256	0.6688	0.4064	0.6688	0.8178
No log	8.0625	258	0.6884	0.3636	0.6884	0.8297
No log	8.125	260	0.6927	0.3201	0.6927	0.8323
No log	8.1875	262	0.6890	0.3201	0.6890	0.8300
No log	8.25	264	0.6693	0.4064	0.6693	0.8181
No log	8.3125	266	0.6538	0.5618	0.6538	0.8086
No log	8.375	268	0.6542	0.5618	0.6542	0.8088
No log	8.4375	270	0.6551	0.5618	0.6551	0.8094
No log	8.5	272	0.6612	0.5618	0.6612	0.8131
No log	8.5625	274	0.6698	0.5618	0.6698	0.8184
No log	8.625	276	0.6819	0.4483	0.6819	0.8258
No log	8.6875	278	0.6870	0.4064	0.6870	0.8288
No log	8.75	280	0.6918	0.4064	0.6918	0.8318
No log	8.8125	282	0.6862	0.4064	0.6862	0.8283
No log	8.875	284	0.6770	0.4483	0.6770	0.8228
No log	8.9375	286	0.6665	0.4563	0.6665	0.8164
No log	9.0	288	0.6615	0.5618	0.6615	0.8133
No log	9.0625	290	0.6615	0.5618	0.6615	0.8133
No log	9.125	292	0.6652	0.4563	0.6652	0.8156
No log	9.1875	294	0.6737	0.4064	0.6737	0.8208
No log	9.25	296	0.6825	0.4064	0.6825	0.8261
No log	9.3125	298	0.6930	0.4064	0.6930	0.8325
No log	9.375	300	0.6972	0.4064	0.6972	0.8350
No log	9.4375	302	0.6963	0.4064	0.6963	0.8344
No log	9.5	304	0.6982	0.4064	0.6982	0.8356
No log	9.5625	306	0.7016	0.4064	0.7016	0.8376
No log	9.625	308	0.7074	0.4064	0.7074	0.8411
No log	9.6875	310	0.7109	0.3636	0.7109	0.8432
No log	9.75	312	0.7146	0.3201	0.7146	0.8453
No log	9.8125	314	0.7158	0.3201	0.7158	0.8460
No log	9.875	316	0.7157	0.3636	0.7157	0.8460
No log	9.9375	318	0.7146	0.3636	0.7146	0.8453
No log	10.0	320	0.7142	0.3636	0.7142	0.8451

Framework versions

• Transformers 4.44.2
• Pytorch 2.4.0+cu118
• Datasets 2.21.0
• Tokenizers 0.19.1