Arabic_FineTuningAraBERT_AugV4_k1_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: 0.5916
• Qwk: 0.8232
• Mse: 0.5916
• Rmse: 0.7692

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	0.0667	2	4.5600	-0.0258	4.5600	2.1354
No log	0.1333	4	3.1700	0.0546	3.1700	1.7805
No log	0.2	6	2.1798	0.0106	2.1798	1.4764
No log	0.2667	8	1.9763	-0.1710	1.9763	1.4058
No log	0.3333	10	2.2405	-0.2719	2.2405	1.4968
No log	0.4	12	1.6954	0.3209	1.6954	1.3021
No log	0.4667	14	1.1480	0.4044	1.1480	1.0715
No log	0.5333	16	1.0376	0.4603	1.0376	1.0186
No log	0.6	18	1.0373	0.4842	1.0373	1.0185
No log	0.6667	20	1.2897	0.4085	1.2897	1.1356
No log	0.7333	22	1.9307	0.2145	1.9307	1.3895
No log	0.8	24	1.9972	0.1600	1.9972	1.4132
No log	0.8667	26	1.8958	0.1600	1.8958	1.3769
No log	0.9333	28	1.5584	0.1163	1.5584	1.2484
No log	1.0	30	1.2713	0.4364	1.2713	1.1275
No log	1.0667	32	1.0851	0.3888	1.0851	1.0417
No log	1.1333	34	0.9924	0.4661	0.9924	0.9962
No log	1.2	36	0.9015	0.5295	0.9015	0.9495
No log	1.2667	38	0.8696	0.5295	0.8696	0.9325
No log	1.3333	40	0.8713	0.6169	0.8713	0.9334
No log	1.4	42	0.9382	0.6209	0.9382	0.9686
No log	1.4667	44	0.8959	0.6769	0.8959	0.9465
No log	1.5333	46	0.8052	0.5734	0.8052	0.8973
No log	1.6	48	0.8738	0.6829	0.8738	0.9347
No log	1.6667	50	0.8138	0.6829	0.8138	0.9021
No log	1.7333	52	0.6880	0.5876	0.6880	0.8294
No log	1.8	54	0.7091	0.6015	0.7091	0.8421
No log	1.8667	56	0.6546	0.6462	0.6546	0.8091
No log	1.9333	58	0.8143	0.6396	0.8143	0.9024
No log	2.0	60	1.0264	0.6576	1.0264	1.0131
No log	2.0667	62	0.9528	0.7172	0.9528	0.9761
No log	2.1333	64	0.7988	0.6875	0.7988	0.8938
No log	2.2	66	0.7390	0.7091	0.7390	0.8596
No log	2.2667	68	0.7324	0.7091	0.7324	0.8558
No log	2.3333	70	0.7081	0.7091	0.7081	0.8415
No log	2.4	72	0.6661	0.7177	0.6661	0.8162
No log	2.4667	74	0.7701	0.7522	0.7701	0.8775
No log	2.5333	76	0.7781	0.7601	0.7781	0.8821
No log	2.6	78	0.9388	0.7518	0.9388	0.9689
No log	2.6667	80	0.9064	0.7601	0.9064	0.9520
No log	2.7333	82	0.7554	0.7443	0.7554	0.8691
No log	2.8	84	0.6464	0.7447	0.6464	0.8040
No log	2.8667	86	0.5659	0.7282	0.5659	0.7522
No log	2.9333	88	0.6412	0.7955	0.6412	0.8008
No log	3.0	90	0.6628	0.8123	0.6628	0.8141
No log	3.0667	92	0.7536	0.7601	0.7536	0.8681
No log	3.1333	94	0.7426	0.7522	0.7426	0.8618
No log	3.2	96	0.6970	0.7	0.6970	0.8348
No log	3.2667	98	0.7009	0.7060	0.7009	0.8372
No log	3.3333	100	0.7877	0.7601	0.7877	0.8875
No log	3.4	102	0.8167	0.7354	0.8167	0.9037
No log	3.4667	104	0.6953	0.7779	0.6953	0.8338
No log	3.5333	106	0.5571	0.7529	0.5571	0.7464
No log	3.6	108	0.5783	0.7529	0.5783	0.7605
No log	3.6667	110	0.6764	0.7875	0.6764	0.8224
No log	3.7333	112	0.6860	0.8019	0.6860	0.8282
No log	3.8	114	0.7552	0.7875	0.7552	0.8690
No log	3.8667	116	0.6171	0.7064	0.6171	0.7856
No log	3.9333	118	0.6041	0.7132	0.6041	0.7773
No log	4.0	120	0.6846	0.8019	0.6846	0.8274
No log	4.0667	122	0.8722	0.7607	0.8722	0.9339
No log	4.1333	124	0.8171	0.7941	0.8171	0.9039
No log	4.2	126	0.5920	0.8022	0.5920	0.7694
No log	4.2667	128	0.5470	0.7277	0.5470	0.7396
No log	4.3333	130	0.5655	0.7382	0.5655	0.7520
No log	4.4	132	0.7368	0.7811	0.7368	0.8584
No log	4.4667	134	0.7864	0.7811	0.7864	0.8868
No log	4.5333	136	0.8216	0.7894	0.8216	0.9064
No log	4.6	138	0.7380	0.7811	0.7380	0.8591
No log	4.6667	140	0.6386	0.7526	0.6386	0.7991
No log	4.7333	142	0.6698	0.7689	0.6698	0.8184
No log	4.8	144	0.6025	0.7526	0.6025	0.7762
No log	4.8667	146	0.5483	0.7739	0.5483	0.7405
No log	4.9333	148	0.5418	0.7739	0.5418	0.7361
No log	5.0	150	0.5547	0.7739	0.5547	0.7448
No log	5.0667	152	0.6242	0.7689	0.6242	0.7901
No log	5.1333	154	0.6029	0.7924	0.6029	0.7765
No log	5.2	156	0.5723	0.7752	0.5723	0.7565
No log	5.2667	158	0.6118	0.8019	0.6118	0.7822
No log	5.3333	160	0.6356	0.8019	0.6356	0.7972
No log	5.4	162	0.6635	0.8019	0.6635	0.8145
No log	5.4667	164	0.5638	0.8019	0.5638	0.7508
No log	5.5333	166	0.5212	0.7603	0.5212	0.7219
No log	5.6	168	0.5127	0.7752	0.5127	0.7160
No log	5.6667	170	0.4815	0.7073	0.4815	0.6939
No log	5.7333	172	0.4983	0.7752	0.4983	0.7059
No log	5.8	174	0.6508	0.7875	0.6508	0.8067
No log	5.8667	176	0.8775	0.7607	0.8775	0.9367
No log	5.9333	178	1.0677	0.6934	1.0677	1.0333
No log	6.0	180	0.9886	0.6934	0.9886	0.9943
No log	6.0667	182	0.7427	0.8215	0.7427	0.8618
No log	6.1333	184	0.5546	0.8098	0.5546	0.7447
No log	6.2	186	0.4927	0.8060	0.4927	0.7019
No log	6.2667	188	0.5016	0.8060	0.5016	0.7082
No log	6.3333	190	0.5853	0.8098	0.5853	0.7651
No log	6.4	192	0.7791	0.8047	0.7791	0.8827
No log	6.4667	194	0.8691	0.8047	0.8691	0.9322
No log	6.5333	196	0.7710	0.7945	0.7710	0.8781
No log	6.6	198	0.6184	0.8079	0.6184	0.7864
No log	6.6667	200	0.5553	0.8105	0.5553	0.7452
No log	6.7333	202	0.6060	0.8079	0.6060	0.7784
No log	6.8	204	0.7222	0.8079	0.7222	0.8498
No log	6.8667	206	0.8430	0.7849	0.8430	0.9181
No log	6.9333	208	0.7805	0.8079	0.7805	0.8835
No log	7.0	210	0.6049	0.8079	0.6049	0.7778
No log	7.0667	212	0.5382	0.8022	0.5382	0.7336
No log	7.1333	214	0.5740	0.7985	0.5740	0.7577
No log	7.2	216	0.6530	0.8079	0.6530	0.8081
No log	7.2667	218	0.6055	0.7985	0.6055	0.7782
No log	7.3333	220	0.6070	0.7689	0.6070	0.7791
No log	7.4	222	0.6170	0.8079	0.6170	0.7855
No log	7.4667	224	0.6024	0.7779	0.6024	0.7761
No log	7.5333	226	0.6029	0.8232	0.6029	0.7765
No log	7.6	228	0.5856	0.8232	0.5856	0.7652
No log	7.6667	230	0.5914	0.8232	0.5914	0.7690
No log	7.7333	232	0.6357	0.7779	0.6357	0.7973
No log	7.8	234	0.6937	0.7779	0.6937	0.8329
No log	7.8667	236	0.7551	0.7982	0.7551	0.8690
No log	7.9333	238	0.8079	0.7982	0.8079	0.8988
No log	8.0	240	0.7878	0.7982	0.7878	0.8876
No log	8.0667	242	0.7225	0.7685	0.7225	0.8500
No log	8.1333	244	0.6565	0.7779	0.6565	0.8102
No log	8.2	246	0.6696	0.7779	0.6696	0.8183
No log	8.2667	248	0.6647	0.7779	0.6647	0.8153
No log	8.3333	250	0.6385	0.7779	0.6385	0.7991
No log	8.4	252	0.5867	0.7779	0.5867	0.7660
No log	8.4667	254	0.5501	0.8123	0.5501	0.7417
No log	8.5333	256	0.5540	0.8232	0.5540	0.7443
No log	8.6	258	0.5823	0.7779	0.5823	0.7631
No log	8.6667	260	0.6369	0.7779	0.6369	0.7981
No log	8.7333	262	0.6956	0.7779	0.6956	0.8340
No log	8.8	264	0.7769	0.8076	0.7769	0.8814
No log	8.8667	266	0.8041	0.7845	0.8041	0.8967
No log	8.9333	268	0.8230	0.7845	0.8230	0.9072
No log	9.0	270	0.7819	0.8076	0.7819	0.8842
No log	9.0667	272	0.7074	0.8180	0.7074	0.8411
No log	9.1333	274	0.6318	0.8232	0.6318	0.7949
No log	9.2	276	0.5712	0.8232	0.5712	0.7558
No log	9.2667	278	0.5315	0.8352	0.5315	0.7291
No log	9.3333	280	0.5248	0.8352	0.5248	0.7244
No log	9.4	282	0.5308	0.8352	0.5308	0.7286
No log	9.4667	284	0.5415	0.8352	0.5415	0.7359
No log	9.5333	286	0.5513	0.8465	0.5513	0.7425
No log	9.6	288	0.5653	0.8465	0.5653	0.7519
No log	9.6667	290	0.5766	0.8232	0.5766	0.7594
No log	9.7333	292	0.5763	0.8232	0.5763	0.7592
No log	9.8	294	0.5783	0.8232	0.5783	0.7605
No log	9.8667	296	0.5843	0.8232	0.5843	0.7644
No log	9.9333	298	0.5903	0.8232	0.5903	0.7683
No log	10.0	300	0.5916	0.8232	0.5916	0.7692

Framework versions

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