ArabicNewSplits7_usingWellWrittenEssays_FineTuningAraBERT_run3_AugV5_k1_task5_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: 1.1443
• Qwk: 0.2027
• Mse: 1.1443
• Rmse: 1.0697

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	3.8122	-0.0151	3.8122	1.9525
No log	1.3333	4	2.0388	0.1187	2.0388	1.4279
No log	2.0	6	1.5315	-0.0046	1.5315	1.2376
No log	2.6667	8	1.2591	0.1764	1.2591	1.1221
No log	3.3333	10	1.0440	0.2639	1.0440	1.0218
No log	4.0	12	1.0730	0.2316	1.0730	1.0359
No log	4.6667	14	1.0164	0.1837	1.0164	1.0082
No log	5.3333	16	1.0926	0.1707	1.0926	1.0453
No log	6.0	18	1.0984	0.2746	1.0984	1.0481
No log	6.6667	20	1.2769	0.1998	1.2769	1.1300
No log	7.3333	22	1.1892	0.2263	1.1892	1.0905
No log	8.0	24	1.2985	0.1821	1.2985	1.1395
No log	8.6667	26	1.7207	-0.1131	1.7207	1.3118
No log	9.3333	28	1.7079	-0.1669	1.7079	1.3069
No log	10.0	30	1.3301	0.1308	1.3301	1.1533
No log	10.6667	32	1.2664	0.2424	1.2664	1.1254
No log	11.3333	34	1.4418	0.0789	1.4418	1.2007
No log	12.0	36	1.6608	0.0178	1.6608	1.2887
No log	12.6667	38	1.6953	-0.0381	1.6953	1.3020
No log	13.3333	40	1.5227	0.0750	1.5227	1.2340
No log	14.0	42	1.5300	0.1000	1.5300	1.2369
No log	14.6667	44	1.6112	0.1112	1.6112	1.2693
No log	15.3333	46	1.5052	0.0911	1.5052	1.2269
No log	16.0	48	1.4857	0.0209	1.4857	1.2189
No log	16.6667	50	1.4487	0.0556	1.4487	1.2036
No log	17.3333	52	1.4518	0.0556	1.4518	1.2049
No log	18.0	54	1.2452	0.1048	1.2452	1.1159
No log	18.6667	56	1.2222	0.1462	1.2222	1.1055
No log	19.3333	58	1.4341	0.0673	1.4341	1.1975
No log	20.0	60	1.5396	-0.0116	1.5396	1.2408
No log	20.6667	62	1.4202	0.0147	1.4202	1.1917
No log	21.3333	64	1.2562	0.0033	1.2562	1.1208
No log	22.0	66	1.1886	0.0220	1.1886	1.0902
No log	22.6667	68	1.2403	0.0033	1.2403	1.1137
No log	23.3333	70	1.3505	0.1407	1.3505	1.1621
No log	24.0	72	1.3979	0.1832	1.3979	1.1823
No log	24.6667	74	1.2939	0.1670	1.2939	1.1375
No log	25.3333	76	1.2830	0.1165	1.2830	1.1327
No log	26.0	78	1.3012	0.1880	1.3012	1.1407
No log	26.6667	80	1.2107	0.0961	1.2107	1.1003
No log	27.3333	82	1.1493	0.1676	1.1493	1.0720
No log	28.0	84	1.2166	0.0541	1.2166	1.1030
No log	28.6667	86	1.2270	0.0401	1.2270	1.1077
No log	29.3333	88	1.2238	0.0401	1.2238	1.1063
No log	30.0	90	1.1802	0.0155	1.1802	1.0864
No log	30.6667	92	1.1454	0.0155	1.1454	1.0702
No log	31.3333	94	1.1953	0.0155	1.1953	1.0933
No log	32.0	96	1.2220	0.1255	1.2220	1.1054
No log	32.6667	98	1.2190	0.2250	1.2190	1.1041
No log	33.3333	100	1.1650	0.2522	1.1650	1.0794
No log	34.0	102	1.2360	0.2250	1.2360	1.1118
No log	34.6667	104	1.2970	0.1976	1.2970	1.1389
No log	35.3333	106	1.2402	0.1259	1.2402	1.1136
No log	36.0	108	1.1434	0.1893	1.1434	1.0693
No log	36.6667	110	1.1743	0.1605	1.1743	1.0837
No log	37.3333	112	1.2816	0.1700	1.2816	1.1321
No log	38.0	114	1.4368	0.1769	1.4368	1.1987
No log	38.6667	116	1.4980	0.1769	1.4980	1.2239
No log	39.3333	118	1.4745	0.2062	1.4745	1.2143
No log	40.0	120	1.3578	0.1892	1.3578	1.1653
No log	40.6667	122	1.1975	0.2410	1.1975	1.0943
No log	41.3333	124	1.1893	0.1817	1.1893	1.0906
No log	42.0	126	1.1842	0.1140	1.1842	1.0882
No log	42.6667	128	1.2486	0.1310	1.2486	1.1174
No log	43.3333	130	1.2647	0.1142	1.2647	1.1246
No log	44.0	132	1.2257	0.1142	1.2257	1.1071
No log	44.6667	134	1.1750	0.1202	1.1750	1.0840
No log	45.3333	136	1.1751	0.1697	1.1751	1.0840
No log	46.0	138	1.2257	0.2149	1.2257	1.1071
No log	46.6667	140	1.3893	0.2974	1.3893	1.1787
No log	47.3333	142	1.4408	0.2644	1.4408	1.2003
No log	48.0	144	1.3029	0.3052	1.3029	1.1415
No log	48.6667	146	1.1880	0.2926	1.1880	1.0899
No log	49.3333	148	1.2204	0.3199	1.2204	1.1047
No log	50.0	150	1.2213	0.3711	1.2213	1.1051
No log	50.6667	152	1.2105	0.3849	1.2105	1.1002
No log	51.3333	154	1.1341	0.2306	1.1341	1.0649
No log	52.0	156	1.1400	0.2306	1.1400	1.0677
No log	52.6667	158	1.1550	0.2592	1.1550	1.0747
No log	53.3333	160	1.1157	0.1863	1.1157	1.0563
No log	54.0	162	1.0956	0.1750	1.0956	1.0467
No log	54.6667	164	1.1465	0.2120	1.1465	1.0708
No log	55.3333	166	1.2312	0.2084	1.2312	1.1096
No log	56.0	168	1.2259	0.2004	1.2259	1.1072
No log	56.6667	170	1.1467	0.1961	1.1467	1.0709
No log	57.3333	172	1.0955	0.1961	1.0955	1.0466
No log	58.0	174	1.1046	0.1961	1.1046	1.0510
No log	58.6667	176	1.1070	0.1961	1.1070	1.0521
No log	59.3333	178	1.1157	0.2105	1.1157	1.0563
No log	60.0	180	1.0830	0.1750	1.0830	1.0407
No log	60.6667	182	1.0695	0.2704	1.0695	1.0342
No log	61.3333	184	1.0164	0.2769	1.0164	1.0082
No log	62.0	186	1.0002	0.2918	1.0002	1.0001
No log	62.6667	188	1.0282	0.3043	1.0282	1.0140
No log	63.3333	190	1.0519	0.2748	1.0519	1.0256
No log	64.0	192	1.1096	0.2062	1.1096	1.0534
No log	64.6667	194	1.1231	0.1605	1.1231	1.0598
No log	65.3333	196	1.1722	0.1654	1.1722	1.0827
No log	66.0	198	1.1884	0.1886	1.1884	1.0901
No log	66.6667	200	1.1774	0.1552	1.1774	1.0851
No log	67.3333	202	1.1830	0.1316	1.1830	1.0877
No log	68.0	204	1.2126	0.1486	1.2126	1.1012
No log	68.6667	206	1.2144	0.1628	1.2144	1.1020
No log	69.3333	208	1.1861	0.1654	1.1861	1.0891
No log	70.0	210	1.1641	0.2250	1.1641	1.0789
No log	70.6667	212	1.1160	0.2386	1.1160	1.0564
No log	71.3333	214	1.0917	0.1845	1.0917	1.0448
No log	72.0	216	1.1068	0.2076	1.1068	1.0520
No log	72.6667	218	1.1578	0.1935	1.1578	1.0760
No log	73.3333	220	1.1969	0.1654	1.1969	1.0940
No log	74.0	222	1.2110	0.2027	1.2110	1.1005
No log	74.6667	224	1.1900	0.1552	1.1900	1.0909
No log	75.3333	226	1.1847	0.1202	1.1847	1.0884
No log	76.0	228	1.1558	0.1351	1.1558	1.0751
No log	76.6667	230	1.1175	0.0961	1.1175	1.0571
No log	77.3333	232	1.0989	0.1379	1.0989	1.0483
No log	78.0	234	1.0931	0.1259	1.0931	1.0455
No log	78.6667	236	1.0910	0.1259	1.0910	1.0445
No log	79.3333	238	1.1156	0.0961	1.1156	1.0562
No log	80.0	240	1.1540	0.1351	1.1540	1.0743
No log	80.6667	242	1.1953	0.1552	1.1953	1.0933
No log	81.3333	244	1.2129	0.1886	1.2129	1.1013
No log	82.0	246	1.2391	0.2506	1.2391	1.1132
No log	82.6667	248	1.2445	0.2506	1.2445	1.1156
No log	83.3333	250	1.2153	0.2506	1.2153	1.1024
No log	84.0	252	1.1922	0.2027	1.1922	1.0919
No log	84.6667	254	1.1598	0.1654	1.1598	1.0769
No log	85.3333	256	1.1153	0.1724	1.1153	1.0561
No log	86.0	258	1.0690	0.1259	1.0690	1.0339
No log	86.6667	260	1.0412	0.1259	1.0412	1.0204
No log	87.3333	262	1.0362	0.1259	1.0362	1.0179
No log	88.0	264	1.0365	0.1259	1.0365	1.0181
No log	88.6667	266	1.0312	0.1259	1.0312	1.0155
No log	89.3333	268	1.0355	0.1259	1.0355	1.0176
No log	90.0	270	1.0493	0.1259	1.0493	1.0244
No log	90.6667	272	1.0707	0.1379	1.0707	1.0347
No log	91.3333	274	1.0976	0.1379	1.0976	1.0477
No log	92.0	276	1.1179	0.1379	1.1179	1.0573
No log	92.6667	278	1.1286	0.1379	1.1286	1.0624
No log	93.3333	280	1.1389	0.1316	1.1389	1.0672
No log	94.0	282	1.1444	0.1697	1.1444	1.0698
No log	94.6667	284	1.1522	0.2027	1.1522	1.0734
No log	95.3333	286	1.1552	0.2027	1.1552	1.0748
No log	96.0	288	1.1580	0.1886	1.1580	1.0761
No log	96.6667	290	1.1555	0.1886	1.1555	1.0749
No log	97.3333	292	1.1541	0.2027	1.1541	1.0743
No log	98.0	294	1.1502	0.2027	1.1502	1.0725
No log	98.6667	296	1.1468	0.2027	1.1468	1.0709
No log	99.3333	298	1.1452	0.2027	1.1452	1.0702
No log	100.0	300	1.1443	0.2027	1.1443	1.0697

Framework versions

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