ArabicNewSplits6_WithDuplicationsForScore5_FineTuningAraBERT_run2_AugV5_k5_task1_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: 0.9883
• Qwk: 0.6700
• Mse: 0.9883
• Rmse: 0.9941

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	5.1974	-0.0024	5.1974	2.2798
No log	0.1333	4	3.0735	0.0791	3.0735	1.7531
No log	0.2	6	1.9063	0.1209	1.9063	1.3807
No log	0.2667	8	1.3142	0.1863	1.3142	1.1464
No log	0.3333	10	1.2867	0.2448	1.2867	1.1343
No log	0.4	12	1.1872	0.2010	1.1872	1.0896
No log	0.4667	14	1.1908	0.1446	1.1908	1.0912
No log	0.5333	16	1.1604	0.1445	1.1604	1.0772
No log	0.6	18	1.1147	0.1496	1.1147	1.0558
No log	0.6667	20	1.1382	0.2026	1.1382	1.0669
No log	0.7333	22	1.1240	0.2467	1.1240	1.0602
No log	0.8	24	1.0933	0.3335	1.0933	1.0456
No log	0.8667	26	1.1143	0.3808	1.1143	1.0556
No log	0.9333	28	1.0182	0.4839	1.0182	1.0091
No log	1.0	30	0.9827	0.4689	0.9827	0.9913
No log	1.0667	32	1.0901	0.4376	1.0901	1.0441
No log	1.1333	34	1.1447	0.4212	1.1447	1.0699
No log	1.2	36	0.8523	0.4796	0.8523	0.9232
No log	1.2667	38	0.8255	0.5792	0.8255	0.9086
No log	1.3333	40	0.8786	0.5752	0.8786	0.9373
No log	1.4	42	0.9758	0.5441	0.9758	0.9878
No log	1.4667	44	1.1348	0.4696	1.1348	1.0652
No log	1.5333	46	1.0486	0.4959	1.0486	1.0240
No log	1.6	48	0.8702	0.5869	0.8702	0.9329
No log	1.6667	50	0.9098	0.5776	0.9098	0.9538
No log	1.7333	52	0.8025	0.5670	0.8025	0.8959
No log	1.8	54	0.7442	0.6442	0.7442	0.8627
No log	1.8667	56	0.7770	0.5884	0.7770	0.8815
No log	1.9333	58	0.7903	0.5902	0.7903	0.8890
No log	2.0	60	0.7710	0.5949	0.7710	0.8781
No log	2.0667	62	0.8402	0.6105	0.8402	0.9166
No log	2.1333	64	0.8540	0.6267	0.8540	0.9241
No log	2.2	66	0.7554	0.6634	0.7554	0.8691
No log	2.2667	68	0.8108	0.6505	0.8108	0.9005
No log	2.3333	70	1.0951	0.6116	1.0951	1.0465
No log	2.4	72	1.3751	0.5336	1.3751	1.1727
No log	2.4667	74	1.2035	0.5774	1.2035	1.0970
No log	2.5333	76	0.8855	0.6317	0.8855	0.9410
No log	2.6	78	0.8555	0.6233	0.8555	0.9249
No log	2.6667	80	0.8549	0.6348	0.8549	0.9246
No log	2.7333	82	0.9634	0.6454	0.9634	0.9815
No log	2.8	84	0.9815	0.6503	0.9815	0.9907
No log	2.8667	86	1.1157	0.5865	1.1157	1.0563
No log	2.9333	88	1.1108	0.5995	1.1108	1.0539
No log	3.0	90	1.0411	0.6311	1.0411	1.0203
No log	3.0667	92	0.9471	0.6128	0.9471	0.9732
No log	3.1333	94	0.9256	0.6424	0.9256	0.9621
No log	3.2	96	0.9037	0.6311	0.9037	0.9506
No log	3.2667	98	0.7824	0.6459	0.7824	0.8845
No log	3.3333	100	0.8389	0.6133	0.8389	0.9159
No log	3.4	102	1.0962	0.6215	1.0962	1.0470
No log	3.4667	104	1.2560	0.5929	1.2560	1.1207
No log	3.5333	106	1.4020	0.5535	1.4020	1.1841
No log	3.6	108	1.6208	0.5072	1.6208	1.2731
No log	3.6667	110	1.4243	0.5879	1.4243	1.1934
No log	3.7333	112	1.0919	0.6246	1.0919	1.0449
No log	3.8	114	0.9670	0.6304	0.9670	0.9834
No log	3.8667	116	0.9135	0.6454	0.9135	0.9558
No log	3.9333	118	0.9447	0.6459	0.9447	0.9720
No log	4.0	120	1.1159	0.6311	1.1159	1.0564
No log	4.0667	122	1.4004	0.5790	1.4004	1.1834
No log	4.1333	124	1.3262	0.5908	1.3262	1.1516
No log	4.2	126	1.1887	0.6348	1.1887	1.0903
No log	4.2667	128	0.9107	0.6594	0.9107	0.9543
No log	4.3333	130	0.7931	0.7078	0.7931	0.8906
No log	4.4	132	0.8785	0.6615	0.8785	0.9373
No log	4.4667	134	1.2547	0.6361	1.2547	1.1202
No log	4.5333	136	1.4680	0.5467	1.4680	1.2116
No log	4.6	138	1.3616	0.5570	1.3616	1.1669
No log	4.6667	140	1.0650	0.6178	1.0650	1.0320
No log	4.7333	142	0.7740	0.6469	0.7740	0.8797
No log	4.8	144	0.7287	0.6695	0.7287	0.8536
No log	4.8667	146	0.8093	0.6463	0.8093	0.8996
No log	4.9333	148	0.9726	0.6552	0.9726	0.9862
No log	5.0	150	1.1207	0.6511	1.1207	1.0586
No log	5.0667	152	1.1549	0.6571	1.1549	1.0747
No log	5.1333	154	1.0338	0.6844	1.0338	1.0168
No log	5.2	156	0.9410	0.6768	0.9410	0.9701
No log	5.2667	158	0.8632	0.6727	0.8632	0.9291
No log	5.3333	160	0.8781	0.6768	0.8781	0.9371
No log	5.4	162	0.9900	0.6570	0.9900	0.9950
No log	5.4667	164	1.0850	0.6233	1.0850	1.0416
No log	5.5333	166	0.9967	0.6454	0.9967	0.9984
No log	5.6	168	0.8793	0.6548	0.8793	0.9377
No log	5.6667	170	0.8098	0.6867	0.8098	0.8999
No log	5.7333	172	0.8570	0.6553	0.8570	0.9258
No log	5.8	174	0.9715	0.6250	0.9715	0.9856
No log	5.8667	176	1.0261	0.6076	1.0261	1.0130
No log	5.9333	178	0.9725	0.6215	0.9725	0.9861
No log	6.0	180	0.9201	0.6284	0.9201	0.9592
No log	6.0667	182	0.8596	0.6305	0.8596	0.9271
No log	6.1333	184	0.8169	0.6729	0.8169	0.9038
No log	6.2	186	0.8544	0.6620	0.8544	0.9243
No log	6.2667	188	0.9323	0.6410	0.9323	0.9655
No log	6.3333	190	0.9113	0.6493	0.9113	0.9546
No log	6.4	192	0.9112	0.6485	0.9112	0.9546
No log	6.4667	194	0.8678	0.6642	0.8678	0.9315
No log	6.5333	196	0.8971	0.6776	0.8971	0.9472
No log	6.6	198	0.9627	0.6754	0.9627	0.9812
No log	6.6667	200	1.1065	0.6565	1.1065	1.0519
No log	6.7333	202	1.1895	0.6427	1.1895	1.0906
No log	6.8	204	1.2353	0.6363	1.2353	1.1114
No log	6.8667	206	1.1769	0.6362	1.1769	1.0848
No log	6.9333	208	1.0584	0.6608	1.0584	1.0288
No log	7.0	210	0.9318	0.6636	0.9318	0.9653
No log	7.0667	212	0.8806	0.6578	0.8806	0.9384
No log	7.1333	214	0.9165	0.6665	0.9165	0.9573
No log	7.2	216	1.0241	0.6635	1.0241	1.0120
No log	7.2667	218	1.1137	0.6500	1.1137	1.0553
No log	7.3333	220	1.1910	0.6040	1.1910	1.0913
No log	7.4	222	1.1558	0.6296	1.1558	1.0751
No log	7.4667	224	1.0859	0.6500	1.0859	1.0421
No log	7.5333	226	1.0257	0.6673	1.0257	1.0127
No log	7.6	228	1.0040	0.6621	1.0040	1.0020
No log	7.6667	230	0.9346	0.6697	0.9346	0.9668
No log	7.7333	232	0.9176	0.6712	0.9176	0.9579
No log	7.8	234	0.9624	0.6596	0.9624	0.9810
No log	7.8667	236	1.0517	0.6557	1.0517	1.0255
No log	7.9333	238	1.1010	0.6424	1.1010	1.0493
No log	8.0	240	1.0809	0.6424	1.0809	1.0397
No log	8.0667	242	1.0557	0.6504	1.0557	1.0275
No log	8.1333	244	1.0021	0.6673	1.0021	1.0010
No log	8.2	246	1.0054	0.6659	1.0054	1.0027
No log	8.2667	248	1.0290	0.6600	1.0290	1.0144
No log	8.3333	250	1.0301	0.6600	1.0301	1.0149
No log	8.4	252	1.0601	0.6541	1.0601	1.0296
No log	8.4667	254	1.0869	0.6424	1.0869	1.0426
No log	8.5333	256	1.0777	0.6501	1.0777	1.0381
No log	8.6	258	1.0524	0.6580	1.0524	1.0259
No log	8.6667	260	1.0042	0.6547	1.0042	1.0021
No log	8.7333	262	0.9572	0.6700	0.9572	0.9784
No log	8.8	264	0.9259	0.6735	0.9259	0.9622
No log	8.8667	266	0.9209	0.6735	0.9209	0.9597
No log	8.9333	268	0.9556	0.6848	0.9556	0.9776
No log	9.0	270	1.0082	0.6745	1.0082	1.0041
No log	9.0667	272	1.0861	0.6533	1.0861	1.0421
No log	9.1333	274	1.1430	0.6439	1.1430	1.0691
No log	9.2	276	1.1608	0.6439	1.1608	1.0774
No log	9.2667	278	1.1469	0.6560	1.1469	1.0709
No log	9.3333	280	1.1097	0.6618	1.1097	1.0534
No log	9.4	282	1.0727	0.6653	1.0727	1.0357
No log	9.4667	284	1.0372	0.6585	1.0372	1.0184
No log	9.5333	286	1.0069	0.6745	1.0069	1.0034
No log	9.6	288	0.9896	0.6775	0.9896	0.9948
No log	9.6667	290	0.9834	0.6775	0.9834	0.9917
No log	9.7333	292	0.9865	0.6775	0.9865	0.9932
No log	9.8	294	0.9921	0.6775	0.9921	0.9961
No log	9.8667	296	0.9904	0.6700	0.9904	0.9952
No log	9.9333	298	0.9881	0.6700	0.9881	0.9940
No log	10.0	300	0.9883	0.6700	0.9883	0.9941

Framework versions

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