ArabicNewSplits7_usingWellWrittenEssays_FineTuningAraBERT_run2_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: 1.1430
• Qwk: 0.1654
• Mse: 1.1430
• Rmse: 1.0691

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	1.0081
No log	5.3333	16	1.0925	0.1707	1.0925	1.0452
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	1.3117
No log	9.3333	28	1.7078	-0.1669	1.7078	1.3068
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	1.2008
No log	12.0	36	1.6609	0.0178	1.6609	1.2888
No log	12.6667	38	1.6953	-0.0381	1.6953	1.3021
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	1.6113	0.1112	1.6113	1.2694
No log	15.3333	46	1.5054	0.0911	1.5054	1.2270
No log	16.0	48	1.4858	0.0209	1.4858	1.2189
No log	16.6667	50	1.4486	0.0556	1.4486	1.2036
No log	17.3333	52	1.4517	0.0556	1.4517	1.2049
No log	18.0	54	1.2452	0.1048	1.2452	1.1159
No log	18.6667	56	1.2224	0.1462	1.2224	1.1056
No log	19.3333	58	1.4343	0.0673	1.4343	1.1976
No log	20.0	60	1.5397	-0.0116	1.5397	1.2409
No log	20.6667	62	1.4203	0.0147	1.4203	1.1918
No log	21.3333	64	1.2561	0.0033	1.2561	1.1208
No log	22.0	66	1.1885	0.0220	1.1885	1.0902
No log	22.6667	68	1.2402	0.0033	1.2402	1.1136
No log	23.3333	70	1.3506	0.1407	1.3506	1.1622
No log	24.0	72	1.3978	0.1832	1.3978	1.1823
No log	24.6667	74	1.2933	0.1670	1.2933	1.1372
No log	25.3333	76	1.2824	0.1165	1.2824	1.1324
No log	26.0	78	1.3017	0.1880	1.3017	1.1409
No log	26.6667	80	1.2117	0.0961	1.2117	1.1008
No log	27.3333	82	1.1490	0.1676	1.1490	1.0719
No log	28.0	84	1.2157	0.0541	1.2157	1.1026
No log	28.6667	86	1.2265	0.0401	1.2265	1.1075
No log	29.3333	88	1.2239	0.0401	1.2239	1.1063
No log	30.0	90	1.1808	0.0155	1.1808	1.0867
No log	30.6667	92	1.1462	0.0155	1.1462	1.0706
No log	31.3333	94	1.1962	0.0155	1.1962	1.0937
No log	32.0	96	1.2224	0.1255	1.2224	1.1056
No log	32.6667	98	1.2192	0.2250	1.2192	1.1042
No log	33.3333	100	1.1642	0.2522	1.1642	1.0790
No log	34.0	102	1.2342	0.2250	1.2342	1.1109
No log	34.6667	104	1.2945	0.1976	1.2945	1.1378
No log	35.3333	106	1.2376	0.1259	1.2376	1.1125
No log	36.0	108	1.1414	0.1893	1.1414	1.0684
No log	36.6667	110	1.1727	0.1605	1.1727	1.0829
No log	37.3333	112	1.2858	0.1700	1.2858	1.1339
No log	38.0	114	1.4413	0.1769	1.4413	1.2005
No log	38.6667	116	1.5012	0.1769	1.5012	1.2252
No log	39.3333	118	1.4777	0.2062	1.4777	1.2156
No log	40.0	120	1.3615	0.1892	1.3615	1.1668
No log	40.6667	122	1.2005	0.2410	1.2005	1.0957
No log	41.3333	124	1.1920	0.2120	1.1920	1.0918
No log	42.0	126	1.1860	0.1140	1.1860	1.0890
No log	42.6667	128	1.2506	0.1310	1.2506	1.1183
No log	43.3333	130	1.2667	0.1142	1.2667	1.1255
No log	44.0	132	1.2279	0.1142	1.2279	1.1081
No log	44.6667	134	1.1771	0.1202	1.1771	1.0849
No log	45.3333	136	1.1748	0.1697	1.1748	1.0839
No log	46.0	138	1.2237	0.2149	1.2237	1.1062
No log	46.6667	140	1.3859	0.2940	1.3859	1.1772
No log	47.3333	142	1.4374	0.2644	1.4374	1.1989
No log	48.0	144	1.3027	0.3052	1.3027	1.1413
No log	48.6667	146	1.1883	0.2926	1.1883	1.0901
No log	49.3333	148	1.2202	0.3199	1.2202	1.1046
No log	50.0	150	1.2205	0.3711	1.2205	1.1048
No log	50.6667	152	1.2088	0.3528	1.2088	1.0994
No log	51.3333	154	1.1314	0.2306	1.1314	1.0637
No log	52.0	156	1.1376	0.2306	1.1376	1.0666
No log	52.6667	158	1.1531	0.2172	1.1531	1.0738
No log	53.3333	160	1.1153	0.1863	1.1153	1.0561
No log	54.0	162	1.0964	0.1750	1.0964	1.0471
No log	54.6667	164	1.1486	0.2120	1.1486	1.0717
No log	55.3333	166	1.2337	0.2084	1.2337	1.1107
No log	56.0	168	1.2255	0.1943	1.2255	1.1070
No log	56.6667	170	1.1440	0.1961	1.1440	1.0696
No log	57.3333	172	1.0918	0.1961	1.0918	1.0449
No log	58.0	174	1.1031	0.1961	1.1031	1.0503
No log	58.6667	176	1.1085	0.1961	1.1085	1.0529
No log	59.3333	178	1.1191	0.2105	1.1191	1.0579
No log	60.0	180	1.0877	0.1863	1.0877	1.0429
No log	60.6667	182	1.0740	0.2572	1.0740	1.0363
No log	61.3333	184	1.0187	0.2769	1.0187	1.0093
No log	62.0	186	1.0009	0.2918	1.0009	1.0005
No log	62.6667	188	1.0286	0.3043	1.0286	1.0142
No log	63.3333	190	1.0521	0.2748	1.0521	1.0257
No log	64.0	192	1.1097	0.2062	1.1097	1.0534
No log	64.6667	194	1.1235	0.1605	1.1235	1.0600
No log	65.3333	196	1.1715	0.1654	1.1715	1.0824
No log	66.0	198	1.1877	0.1552	1.1877	1.0898
No log	66.6667	200	1.1764	0.1552	1.1764	1.0846
No log	67.3333	202	1.1813	0.1316	1.1813	1.0869
No log	68.0	204	1.2108	0.1486	1.2108	1.1004
No log	68.6667	206	1.2123	0.1255	1.2123	1.1011
No log	69.3333	208	1.1834	0.1654	1.1834	1.0879
No log	70.0	210	1.1608	0.2250	1.1608	1.0774
No log	70.6667	212	1.1123	0.2386	1.1123	1.0546
No log	71.3333	214	1.0879	0.1845	1.0879	1.0430
No log	72.0	216	1.1036	0.2076	1.1036	1.0505
No log	72.6667	218	1.1556	0.1935	1.1556	1.0750
No log	73.3333	220	1.1957	0.1654	1.1957	1.0935
No log	74.0	222	1.2094	0.2027	1.2094	1.0997
No log	74.6667	224	1.1878	0.1697	1.1878	1.0899
No log	75.3333	226	1.1827	0.1202	1.1827	1.0875
No log	76.0	228	1.1541	0.1351	1.1541	1.0743
No log	76.6667	230	1.1158	0.0961	1.1158	1.0563
No log	77.3333	232	1.0977	0.1379	1.0977	1.0477
No log	78.0	234	1.0927	0.1259	1.0927	1.0453
No log	78.6667	236	1.0916	0.1259	1.0916	1.0448
No log	79.3333	238	1.1172	0.0961	1.1172	1.0570
No log	80.0	240	1.1550	0.1351	1.1550	1.0747
No log	80.6667	242	1.1944	0.1552	1.1944	1.0929
No log	81.3333	244	1.2102	0.1886	1.2102	1.1001
No log	82.0	246	1.2349	0.2506	1.2349	1.1113
No log	82.6667	248	1.2394	0.2506	1.2394	1.1133
No log	83.3333	250	1.2106	0.1952	1.2106	1.1003
No log	84.0	252	1.1886	0.2027	1.1886	1.0902
No log	84.6667	254	1.1573	0.1654	1.1573	1.0758
No log	85.3333	256	1.1137	0.1724	1.1137	1.0553
No log	86.0	258	1.0681	0.1259	1.0681	1.0335
No log	86.6667	260	1.0410	0.1259	1.0410	1.0203
No log	87.3333	262	1.0366	0.1259	1.0366	1.0181
No log	88.0	264	1.0375	0.1259	1.0375	1.0186
No log	88.6667	266	1.0324	0.1259	1.0324	1.0161
No log	89.3333	268	1.0369	0.1259	1.0369	1.0183
No log	90.0	270	1.0507	0.1259	1.0507	1.0250
No log	90.6667	272	1.0718	0.1379	1.0718	1.0353
No log	91.3333	274	1.0984	0.1379	1.0984	1.0480
No log	92.0	276	1.1180	0.1379	1.1180	1.0574
No log	92.6667	278	1.1281	0.1379	1.1281	1.0621
No log	93.3333	280	1.1379	0.1316	1.1379	1.0667
No log	94.0	282	1.1429	0.1316	1.1429	1.0691
No log	94.6667	284	1.1503	0.2027	1.1503	1.0725
No log	95.3333	286	1.1533	0.2027	1.1533	1.0739
No log	96.0	288	1.1561	0.1886	1.1561	1.0752
No log	96.6667	290	1.1537	0.2027	1.1537	1.0741
No log	97.3333	292	1.1524	0.2027	1.1524	1.0735
No log	98.0	294	1.1487	0.2027	1.1487	1.0718
No log	98.6667	296	1.1454	0.2027	1.1454	1.0702
No log	99.3333	298	1.1439	0.1654	1.1439	1.0695
No log	100.0	300	1.1430	0.1654	1.1430	1.0691

Framework versions

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