ArabicNewSplits4_WithDuplicationsForScore5_FineTuningAraBERT_run1_AugV5_k5_task2_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: 1.0648
• Qwk: 0.5132
• Mse: 1.0648
• Rmse: 1.0319

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	0.0714	2	4.1340	-0.0134	4.1340	2.0332
No log	0.1429	4	2.1800	0.0424	2.1800	1.4765
No log	0.2143	6	1.2438	0.0424	1.2438	1.1153
No log	0.2857	8	0.8558	-0.1126	0.8558	0.9251
No log	0.3571	10	0.7392	0.2239	0.7392	0.8598
No log	0.4286	12	0.7716	0.1352	0.7716	0.8784
No log	0.5	14	0.7781	0.1442	0.7781	0.8821
No log	0.5714	16	0.7345	0.1585	0.7345	0.8570
No log	0.6429	18	0.6956	0.2069	0.6956	0.8340
No log	0.7143	20	0.7384	0.2292	0.7384	0.8593
No log	0.7857	22	0.7074	0.2247	0.7074	0.8411
No log	0.8571	24	0.6846	0.1977	0.6846	0.8274
No log	0.9286	26	0.7121	0.1918	0.7121	0.8439
No log	1.0	28	0.8262	0.1499	0.8262	0.9089
No log	1.0714	30	0.8814	0.1552	0.8814	0.9388
No log	1.1429	32	0.8592	0.2708	0.8592	0.9269
No log	1.2143	34	0.7440	0.2985	0.7440	0.8625
No log	1.2857	36	0.6508	0.2792	0.6508	0.8067
No log	1.3571	38	0.6081	0.3344	0.6081	0.7798
No log	1.4286	40	0.6143	0.3401	0.6143	0.7838
No log	1.5	42	0.6131	0.3547	0.6131	0.7830
No log	1.5714	44	0.5751	0.3548	0.5751	0.7583
No log	1.6429	46	0.5981	0.4481	0.5981	0.7734
No log	1.7143	48	0.6407	0.4145	0.6407	0.8005
No log	1.7857	50	0.7284	0.4531	0.7284	0.8534
No log	1.8571	52	0.7053	0.4555	0.7053	0.8398
No log	1.9286	54	0.6466	0.5027	0.6466	0.8041
No log	2.0	56	0.8035	0.4199	0.8035	0.8964
No log	2.0714	58	0.8386	0.4169	0.8386	0.9158
No log	2.1429	60	0.6310	0.4955	0.6310	0.7943
No log	2.2143	62	0.7127	0.4876	0.7127	0.8442
No log	2.2857	64	0.7533	0.5	0.7533	0.8679
No log	2.3571	66	0.7081	0.5436	0.7081	0.8415
No log	2.4286	68	0.6758	0.5392	0.6758	0.8221
No log	2.5	70	0.7218	0.4899	0.7218	0.8496
No log	2.5714	72	0.7427	0.5064	0.7427	0.8618
No log	2.6429	74	0.6951	0.5648	0.6951	0.8337
No log	2.7143	76	0.8836	0.5020	0.8836	0.9400
No log	2.7857	78	1.0525	0.4567	1.0525	1.0259
No log	2.8571	80	0.9715	0.4927	0.9715	0.9856
No log	2.9286	82	0.8462	0.5327	0.8462	0.9199
No log	3.0	84	0.8607	0.5567	0.8607	0.9278
No log	3.0714	86	0.9001	0.5543	0.9001	0.9487
No log	3.1429	88	0.9209	0.5357	0.9209	0.9596
No log	3.2143	90	0.9739	0.5485	0.9739	0.9869
No log	3.2857	92	0.9868	0.5200	0.9868	0.9934
No log	3.3571	94	0.9818	0.5419	0.9818	0.9909
No log	3.4286	96	0.9909	0.5306	0.9909	0.9954
No log	3.5	98	1.0381	0.5101	1.0380	1.0188
No log	3.5714	100	1.1269	0.4736	1.1269	1.0616
No log	3.6429	102	1.1923	0.4646	1.1923	1.0919
No log	3.7143	104	1.2656	0.4456	1.2656	1.1250
No log	3.7857	106	1.2508	0.4393	1.2508	1.1184
No log	3.8571	108	1.1542	0.4866	1.1542	1.0744
No log	3.9286	110	1.1126	0.4768	1.1126	1.0548
No log	4.0	112	1.0654	0.5073	1.0654	1.0322
No log	4.0714	114	1.0520	0.5093	1.0520	1.0257
No log	4.1429	116	1.0406	0.4969	1.0406	1.0201
No log	4.2143	118	1.0833	0.4984	1.0833	1.0408
No log	4.2857	120	1.0952	0.4943	1.0952	1.0465
No log	4.3571	122	1.0969	0.5042	1.0969	1.0473
No log	4.4286	124	1.0632	0.5188	1.0632	1.0311
No log	4.5	126	1.0579	0.4922	1.0579	1.0286
No log	4.5714	128	1.0752	0.5016	1.0752	1.0369
No log	4.6429	130	1.1085	0.5051	1.1085	1.0528
No log	4.7143	132	1.1296	0.5232	1.1296	1.0628
No log	4.7857	134	1.1931	0.4840	1.1931	1.0923
No log	4.8571	136	1.2428	0.4880	1.2428	1.1148
No log	4.9286	138	1.2794	0.4578	1.2794	1.1311
No log	5.0	140	1.2919	0.4456	1.2919	1.1366
No log	5.0714	142	1.2849	0.4598	1.2849	1.1335
No log	5.1429	144	1.2694	0.4757	1.2694	1.1267
No log	5.2143	146	1.2888	0.4671	1.2888	1.1353
No log	5.2857	148	1.3187	0.4722	1.3187	1.1483
No log	5.3571	150	1.3693	0.4502	1.3693	1.1702
No log	5.4286	152	1.3452	0.4459	1.3452	1.1598
No log	5.5	154	1.2316	0.4659	1.2316	1.1098
No log	5.5714	156	1.1410	0.4983	1.1410	1.0682
No log	5.6429	158	1.1304	0.5249	1.1304	1.0632
No log	5.7143	160	1.2080	0.4854	1.2080	1.0991
No log	5.7857	162	1.2421	0.4563	1.2421	1.1145
No log	5.8571	164	1.2036	0.4795	1.2036	1.0971
No log	5.9286	166	1.1568	0.4825	1.1568	1.0756
No log	6.0	168	1.0890	0.5289	1.0890	1.0435
No log	6.0714	170	1.0702	0.4941	1.0702	1.0345
No log	6.1429	172	1.1391	0.5139	1.1391	1.0673
No log	6.2143	174	1.2273	0.4860	1.2273	1.1078
No log	6.2857	176	1.2473	0.4816	1.2473	1.1168
No log	6.3571	178	1.2915	0.4677	1.2915	1.1364
No log	6.4286	180	1.3069	0.4765	1.3069	1.1432
No log	6.5	182	1.2833	0.4788	1.2833	1.1328
No log	6.5714	184	1.3059	0.4815	1.3059	1.1428
No log	6.6429	186	1.3572	0.4545	1.3572	1.1650
No log	6.7143	188	1.3305	0.4672	1.3305	1.1535
No log	6.7857	190	1.2803	0.4773	1.2803	1.1315
No log	6.8571	192	1.2648	0.4858	1.2648	1.1246
No log	6.9286	194	1.2740	0.4762	1.2740	1.1287
No log	7.0	196	1.2837	0.4669	1.2837	1.1330
No log	7.0714	198	1.2661	0.4793	1.2661	1.1252
No log	7.1429	200	1.2081	0.4966	1.2081	1.0992
No log	7.2143	202	1.1781	0.5056	1.1781	1.0854
No log	7.2857	204	1.1332	0.4838	1.1332	1.0645
No log	7.3571	206	1.1234	0.5107	1.1234	1.0599
No log	7.4286	208	1.1504	0.4917	1.1504	1.0726
No log	7.5	210	1.1706	0.5006	1.1706	1.0819
No log	7.5714	212	1.1806	0.4963	1.1806	1.0866
No log	7.6429	214	1.1888	0.4957	1.1888	1.0903
No log	7.7143	216	1.2087	0.4719	1.2087	1.0994
No log	7.7857	218	1.2207	0.4623	1.2207	1.1049
No log	7.8571	220	1.1893	0.4983	1.1893	1.0905
No log	7.9286	222	1.1220	0.5066	1.1220	1.0592
No log	8.0	224	1.0648	0.5113	1.0648	1.0319
No log	8.0714	226	1.0423	0.4855	1.0423	1.0209
No log	8.1429	228	1.0453	0.4918	1.0453	1.0224
No log	8.2143	230	1.0539	0.4803	1.0539	1.0266
No log	8.2857	232	1.0752	0.4983	1.0752	1.0369
No log	8.3571	234	1.1259	0.5077	1.1259	1.0611
No log	8.4286	236	1.1759	0.4974	1.1759	1.0844
No log	8.5	238	1.2142	0.4902	1.2142	1.1019
No log	8.5714	240	1.2268	0.4909	1.2268	1.1076
No log	8.6429	242	1.2210	0.4909	1.2210	1.1050
No log	8.7143	244	1.2070	0.4974	1.2070	1.0987
No log	8.7857	246	1.1861	0.4937	1.1861	1.0891
No log	8.8571	248	1.1622	0.5002	1.1622	1.0780
No log	8.9286	250	1.1338	0.4913	1.1338	1.0648
No log	9.0	252	1.1136	0.5059	1.1136	1.0553
No log	9.0714	254	1.1060	0.5059	1.1060	1.0517
No log	9.1429	256	1.1095	0.4966	1.1095	1.0533
No log	9.2143	258	1.1074	0.5080	1.1074	1.0524
No log	9.2857	260	1.1043	0.5080	1.1043	1.0508
No log	9.3571	262	1.0967	0.5080	1.0967	1.0472
No log	9.4286	264	1.0881	0.5175	1.0881	1.0431
No log	9.5	266	1.0793	0.5048	1.0793	1.0389
No log	9.5714	268	1.0760	0.5048	1.0760	1.0373
No log	9.6429	270	1.0724	0.5048	1.0724	1.0356
No log	9.7143	272	1.0661	0.5015	1.0661	1.0325
No log	9.7857	274	1.0635	0.5015	1.0635	1.0312
No log	9.8571	276	1.0634	0.5139	1.0634	1.0312
No log	9.9286	278	1.0640	0.5132	1.0640	1.0315
No log	10.0	280	1.0648	0.5132	1.0648	1.0319

Framework versions

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