ArabicNewSplits7_usingWellWrittenEssays_FineTuningAraBERT_run1_AugV5_k1_task7_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: 0.9364
• Qwk: 0.2947
• Mse: 0.9364
• Rmse: 0.9677

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: 100

Training results

Training Loss	Epoch	Step	Validation Loss	Qwk	Mse	Rmse
No log	0.6667	2	3.4666	0.0606	3.4666	1.8619
No log	1.3333	4	2.1819	0.0388	2.1819	1.4771
No log	2.0	6	1.1895	0.1901	1.1895	1.0907
No log	2.6667	8	0.7463	0.3754	0.7463	0.8639
No log	3.3333	10	0.9200	0.0392	0.9200	0.9591
No log	4.0	12	1.1377	-0.1787	1.1377	1.0666
No log	4.6667	14	1.0855	-0.0764	1.0855	1.0419
No log	5.3333	16	0.8678	0.0295	0.8678	0.9315
No log	6.0	18	0.7943	0.1972	0.7943	0.8913
No log	6.6667	20	0.7554	0.1918	0.7554	0.8691
No log	7.3333	22	0.7546	0.1232	0.7546	0.8687
No log	8.0	24	0.7993	0.0426	0.7993	0.8940
No log	8.6667	26	0.7592	0.1846	0.7592	0.8713
No log	9.3333	28	0.7757	0.1846	0.7757	0.8807
No log	10.0	30	0.9190	0.3031	0.9190	0.9586
No log	10.6667	32	0.9476	0.3271	0.9476	0.9735
No log	11.3333	34	1.0098	0.2373	1.0098	1.0049
No log	12.0	36	0.9345	0.2414	0.9345	0.9667
No log	12.6667	38	1.0419	0.2245	1.0419	1.0208
No log	13.3333	40	1.0341	0.1344	1.0341	1.0169
No log	14.0	42	0.9617	0.0883	0.9617	0.9807
No log	14.6667	44	1.0447	0.0657	1.0447	1.0221
No log	15.3333	46	1.3436	0.1085	1.3436	1.1592
No log	16.0	48	1.3721	0.0843	1.3721	1.1714
No log	16.6667	50	1.0517	0.2055	1.0517	1.0255
No log	17.3333	52	0.8534	0.2257	0.8534	0.9238
No log	18.0	54	0.8686	0.1352	0.8686	0.9320
No log	18.6667	56	1.0192	0.2296	1.0192	1.0095
No log	19.3333	58	1.1603	0.1689	1.1603	1.0772
No log	20.0	60	1.1452	0.1422	1.1452	1.0701
No log	20.6667	62	1.0226	0.1863	1.0226	1.0112
No log	21.3333	64	1.0275	0.1863	1.0275	1.0136
No log	22.0	66	1.1891	0.1417	1.1891	1.0904
No log	22.6667	68	1.3946	-0.0020	1.3946	1.1809
No log	23.3333	70	1.2487	0.0116	1.2487	1.1174
No log	24.0	72	0.9471	0.2066	0.9471	0.9732
No log	24.6667	74	0.8982	0.1479	0.8982	0.9478
No log	25.3333	76	0.9423	0.1336	0.9423	0.9707
No log	26.0	78	1.0832	0.1458	1.0832	1.0408
No log	26.6667	80	1.1355	0.1146	1.1355	1.0656
No log	27.3333	82	1.0743	0.1155	1.0743	1.0365
No log	28.0	84	1.0556	0.0796	1.0556	1.0274
No log	28.6667	86	1.0475	0.1639	1.0475	1.0235
No log	29.3333	88	1.0584	0.0988	1.0584	1.0288
No log	30.0	90	1.1606	0.1324	1.1606	1.0773
No log	30.6667	92	1.3179	0.0813	1.3179	1.1480
No log	31.3333	94	1.3622	0.0418	1.3622	1.1671
No log	32.0	96	1.2078	0.1116	1.2078	1.0990
No log	32.6667	98	1.0430	0.0662	1.0430	1.0213
No log	33.3333	100	0.9905	0.1452	0.9905	0.9952
No log	34.0	102	0.9766	0.1452	0.9766	0.9883
No log	34.6667	104	0.9857	0.1432	0.9857	0.9928
No log	35.3333	106	1.0311	0.0832	1.0311	1.0154
No log	36.0	108	1.0603	0.0848	1.0603	1.0297
No log	36.6667	110	1.0752	0.1119	1.0752	1.0369
No log	37.3333	112	1.1725	0.1140	1.1725	1.0828
No log	38.0	114	1.1694	0.1112	1.1694	1.0814
No log	38.6667	116	1.0486	0.1855	1.0486	1.0240
No log	39.3333	118	0.9574	0.2287	0.9574	0.9785
No log	40.0	120	0.9554	0.2392	0.9554	0.9775
No log	40.6667	122	0.9851	0.1089	0.9851	0.9925
No log	41.3333	124	1.0507	0.1120	1.0507	1.0251
No log	42.0	126	1.0519	0.1120	1.0519	1.0256
No log	42.6667	128	1.0316	0.0724	1.0316	1.0157
No log	43.3333	130	1.0605	0.0730	1.0605	1.0298
No log	44.0	132	1.1273	0.0469	1.1273	1.0617
No log	44.6667	134	1.1656	0.0506	1.1656	1.0796
No log	45.3333	136	1.1544	0.0479	1.1544	1.0745
No log	46.0	138	1.1504	0.0777	1.1504	1.0725
No log	46.6667	140	1.0879	0.0161	1.0879	1.0430
No log	47.3333	142	0.9800	0.1361	0.9800	0.9900
No log	48.0	144	0.9167	0.2608	0.9167	0.9575
No log	48.6667	146	0.8972	0.2608	0.8972	0.9472
No log	49.3333	148	0.9042	0.2608	0.9042	0.9509
No log	50.0	150	0.9143	0.1558	0.9143	0.9562
No log	50.6667	152	0.9447	0.1168	0.9447	0.9720
No log	51.3333	154	0.9513	0.1538	0.9513	0.9753
No log	52.0	156	0.9392	0.1176	0.9392	0.9691
No log	52.6667	158	0.9479	0.1133	0.9479	0.9736
No log	53.3333	160	0.9789	0.0755	0.9789	0.9894
No log	54.0	162	1.0107	0.0043	1.0107	1.0053
No log	54.6667	164	1.0749	0.0498	1.0749	1.0368
No log	55.3333	166	1.0967	0.0498	1.0967	1.0472
No log	56.0	168	1.0716	0.0805	1.0716	1.0352
No log	56.6667	170	1.0535	0.0498	1.0535	1.0264
No log	57.3333	172	1.0135	0.1725	1.0135	1.0067
No log	58.0	174	0.9851	0.1419	0.9851	0.9925
No log	58.6667	176	0.9911	0.1159	0.9911	0.9955
No log	59.3333	178	0.9823	0.1159	0.9823	0.9911
No log	60.0	180	0.9975	0.0836	0.9975	0.9987
No log	60.6667	182	0.9961	0.1159	0.9961	0.9981
No log	61.3333	184	0.9787	0.1159	0.9787	0.9893
No log	62.0	186	0.9497	0.1475	0.9497	0.9745
No log	62.6667	188	0.9542	0.1475	0.9542	0.9768
No log	63.3333	190	0.9403	0.2160	0.9403	0.9697
No log	64.0	192	0.9193	0.2576	0.9193	0.9588
No log	64.6667	194	0.9130	0.2576	0.9130	0.9555
No log	65.3333	196	0.9349	0.2545	0.9349	0.9669
No log	66.0	198	0.9721	0.2171	0.9721	0.9859
No log	66.6667	200	1.0226	0.0498	1.0226	1.0112
No log	67.3333	202	1.0245	0.0498	1.0245	1.0122
No log	68.0	204	0.9915	0.1460	0.9915	0.9957
No log	68.6667	206	0.9745	0.1391	0.9745	0.9872
No log	69.3333	208	0.9555	0.2072	0.9555	0.9775
No log	70.0	210	0.9597	0.2072	0.9597	0.9796
No log	70.6667	212	0.9671	0.2072	0.9671	0.9834
No log	71.3333	214	0.9825	0.2053	0.9825	0.9912
No log	72.0	216	1.0044	0.1651	1.0044	1.0022
No log	72.6667	218	1.0332	0.0161	1.0332	1.0164
No log	73.3333	220	1.0440	0.0161	1.0440	1.0217
No log	74.0	222	1.0170	0.0161	1.0170	1.0084
No log	74.6667	224	0.9887	0.1054	0.9887	0.9943
No log	75.3333	226	0.9590	0.2053	0.9590	0.9793
No log	76.0	228	0.9507	0.2545	0.9507	0.9750
No log	76.6667	230	0.9412	0.2545	0.9412	0.9702
No log	77.3333	232	0.9453	0.1870	0.9453	0.9723
No log	78.0	234	0.9422	0.1887	0.9422	0.9707
No log	78.6667	236	0.9554	0.1870	0.9554	0.9774
No log	79.3333	238	0.9799	0.1460	0.9799	0.9899
No log	80.0	240	0.9974	0.0832	0.9974	0.9987
No log	80.6667	242	0.9917	0.0832	0.9917	0.9958
No log	81.3333	244	0.9691	0.1130	0.9691	0.9844
No log	82.0	246	0.9576	0.1500	0.9576	0.9786
No log	82.6667	248	0.9487	0.1887	0.9487	0.9740
No log	83.3333	250	0.9559	0.1887	0.9559	0.9777
No log	84.0	252	0.9516	0.1887	0.9516	0.9755
No log	84.6667	254	0.9478	0.2987	0.9478	0.9736
No log	85.3333	256	0.9511	0.2576	0.9511	0.9752
No log	86.0	258	0.9594	0.2576	0.9594	0.9795
No log	86.6667	260	0.9668	0.1789	0.9668	0.9833
No log	87.3333	262	0.9650	0.1789	0.9650	0.9823
No log	88.0	264	0.9572	0.2160	0.9572	0.9784
No log	88.6667	266	0.9514	0.2545	0.9514	0.9754
No log	89.3333	268	0.9406	0.2987	0.9406	0.9698
No log	90.0	270	0.9276	0.2987	0.9276	0.9631
No log	90.6667	272	0.9220	0.3289	0.9220	0.9602
No log	91.3333	274	0.9237	0.3289	0.9237	0.9611
No log	92.0	276	0.9227	0.3289	0.9227	0.9606
No log	92.6667	278	0.9194	0.3289	0.9194	0.9589
No log	93.3333	280	0.9190	0.2987	0.9190	0.9586
No log	94.0	282	0.9212	0.2987	0.9212	0.9598
No log	94.6667	284	0.9239	0.2987	0.9239	0.9612
No log	95.3333	286	0.9252	0.2987	0.9252	0.9619
No log	96.0	288	0.9290	0.2987	0.9290	0.9639
No log	96.6667	290	0.9327	0.2987	0.9327	0.9658
No log	97.3333	292	0.9338	0.2987	0.9338	0.9663
No log	98.0	294	0.9340	0.2987	0.9340	0.9664
No log	98.6667	296	0.9355	0.2947	0.9355	0.9672
No log	99.3333	298	0.9359	0.2947	0.9359	0.9674
No log	100.0	300	0.9364	0.2947	0.9364	0.9677

Framework versions

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