ArabicNewSplits7_usingALLEssays_FineTuningAraBERT_run3_AugV5_k1_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: 1.0623
• Qwk: 0.1406
• Mse: 1.0623
• Rmse: 1.0307

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	4.6292	0.0010	4.6292	2.1516
No log	1.3333	4	2.7353	0.0122	2.7353	1.6539
No log	2.0	6	2.0537	-0.0634	2.0537	1.4331
No log	2.6667	8	1.5990	-0.0758	1.5990	1.2645
No log	3.3333	10	1.3190	0.0390	1.3190	1.1485
No log	4.0	12	1.2666	0.0527	1.2666	1.1255
No log	4.6667	14	1.1853	0.1585	1.1853	1.0887
No log	5.3333	16	1.1854	0.1968	1.1854	1.0888
No log	6.0	18	1.1617	0.2180	1.1617	1.0778
No log	6.6667	20	1.1468	0.1812	1.1468	1.0709
No log	7.3333	22	1.1214	0.2083	1.1214	1.0589
No log	8.0	24	1.1205	0.1585	1.1205	1.0585
No log	8.6667	26	1.1264	0.1351	1.1264	1.0613
No log	9.3333	28	1.2030	0.1519	1.2030	1.0968
No log	10.0	30	1.1797	0.1519	1.1797	1.0862
No log	10.6667	32	1.0810	0.0841	1.0810	1.0397
No log	11.3333	34	1.0920	0.1808	1.0920	1.0450
No log	12.0	36	1.2875	0.1185	1.2875	1.1347
No log	12.6667	38	1.4214	0.1067	1.4214	1.1922
No log	13.3333	40	1.2003	0.1696	1.2003	1.0956
No log	14.0	42	1.0491	0.2417	1.0491	1.0243
No log	14.6667	44	1.0435	0.2333	1.0435	1.0215
No log	15.3333	46	1.0569	0.2100	1.0569	1.0280
No log	16.0	48	1.0718	0.1505	1.0718	1.0353
No log	16.6667	50	1.1286	0.1903	1.1286	1.0623
No log	17.3333	52	1.0540	0.2291	1.0540	1.0266
No log	18.0	54	0.9675	0.2492	0.9675	0.9836
No log	18.6667	56	1.0052	0.3144	1.0052	1.0026
No log	19.3333	58	0.9892	0.3663	0.9892	0.9946
No log	20.0	60	1.0276	0.2949	1.0276	1.0137
No log	20.6667	62	1.0125	0.3144	1.0125	1.0062
No log	21.3333	64	1.0014	0.3434	1.0014	1.0007
No log	22.0	66	1.0856	0.2037	1.0856	1.0419
No log	22.6667	68	1.1543	0.2387	1.1543	1.0744
No log	23.3333	70	1.1417	0.1020	1.1417	1.0685
No log	24.0	72	1.0091	0.2673	1.0091	1.0045
No log	24.6667	74	0.9562	0.2920	0.9562	0.9779
No log	25.3333	76	0.9634	0.3308	0.9634	0.9815
No log	26.0	78	1.0302	0.3502	1.0302	1.0150
No log	26.6667	80	1.1381	0.2494	1.1381	1.0668
No log	27.3333	82	1.2619	0.2410	1.2619	1.1233
No log	28.0	84	1.2891	0.1219	1.2891	1.1354
No log	28.6667	86	1.2247	0.1416	1.2247	1.1067
No log	29.3333	88	1.1174	0.1118	1.1174	1.0571
No log	30.0	90	1.0973	0.2348	1.0973	1.0475
No log	30.6667	92	1.1885	0.2447	1.1885	1.0902
No log	31.3333	94	1.2093	0.2447	1.2093	1.0997
No log	32.0	96	1.1962	0.2447	1.1962	1.0937
No log	32.6667	98	1.1312	0.1795	1.1312	1.0636
No log	33.3333	100	1.0503	0.2702	1.0503	1.0249
No log	34.0	102	1.0378	0.3097	1.0378	1.0187
No log	34.6667	104	1.0765	0.2651	1.0765	1.0375
No log	35.3333	106	1.1909	0.2460	1.1909	1.0913
No log	36.0	108	1.1776	0.2460	1.1776	1.0852
No log	36.6667	110	1.0443	0.2829	1.0443	1.0219
No log	37.3333	112	1.0133	0.2702	1.0133	1.0066
No log	38.0	114	1.0074	0.2207	1.0074	1.0037
No log	38.6667	116	1.0571	0.2633	1.0571	1.0281
No log	39.3333	118	1.0646	0.2633	1.0646	1.0318
No log	40.0	120	1.0980	0.2730	1.0980	1.0479
No log	40.6667	122	1.0522	0.1441	1.0522	1.0258
No log	41.3333	124	1.0327	0.2263	1.0327	1.0162
No log	42.0	126	1.0178	0.1927	1.0178	1.0089
No log	42.6667	128	1.0401	0.1853	1.0401	1.0199
No log	43.3333	130	1.1959	0.2410	1.1959	1.0936
No log	44.0	132	1.3330	0.1796	1.3330	1.1546
No log	44.6667	134	1.2978	0.1796	1.2978	1.1392
No log	45.3333	136	1.1507	0.2410	1.1507	1.0727
No log	46.0	138	1.0088	0.2704	1.0088	1.0044
No log	46.6667	140	0.9643	0.4158	0.9643	0.9820
No log	47.3333	142	0.9795	0.4237	0.9795	0.9897
No log	48.0	144	0.9695	0.4158	0.9695	0.9846
No log	48.6667	146	0.9607	0.3453	0.9607	0.9801
No log	49.3333	148	0.9934	0.2604	0.9934	0.9967
No log	50.0	150	1.1365	0.2213	1.1365	1.0661
No log	50.6667	152	1.1918	0.2213	1.1918	1.0917
No log	51.3333	154	1.1673	0.2131	1.1673	1.0804
No log	52.0	156	1.1402	0.2097	1.1402	1.0678
No log	52.6667	158	1.1145	0.2097	1.1145	1.0557
No log	53.3333	160	1.0384	0.1658	1.0384	1.0190
No log	54.0	162	0.9977	0.1775	0.9977	0.9989
No log	54.6667	164	0.9934	0.2313	0.9934	0.9967
No log	55.3333	166	1.0042	0.2686	1.0042	1.0021
No log	56.0	168	1.0243	0.2586	1.0243	1.0121
No log	56.6667	170	1.0492	0.2141	1.0492	1.0243
No log	57.3333	172	1.0710	0.2056	1.0710	1.0349
No log	58.0	174	1.0847	0.2056	1.0847	1.0415
No log	58.6667	176	1.0804	0.2056	1.0804	1.0394
No log	59.3333	178	1.0824	0.2056	1.0824	1.0404
No log	60.0	180	1.1235	0.1750	1.1235	1.0599
No log	60.6667	182	1.1545	0.1944	1.1545	1.0745
No log	61.3333	184	1.1589	0.2037	1.1589	1.0765
No log	62.0	186	1.1209	0.2238	1.1209	1.0587
No log	62.6667	188	1.0657	0.1090	1.0657	1.0323
No log	63.3333	190	1.0411	0.1878	1.0411	1.0203
No log	64.0	192	1.0408	0.1878	1.0408	1.0202
No log	64.6667	194	1.0477	0.1878	1.0477	1.0236
No log	65.3333	196	1.0605	0.1662	1.0605	1.0298
No log	66.0	198	1.0980	0.0675	1.0980	1.0478
No log	66.6667	200	1.1295	0.2238	1.1295	1.0628
No log	67.3333	202	1.1610	0.2334	1.1610	1.0775
No log	68.0	204	1.1716	0.2410	1.1716	1.0824
No log	68.6667	206	1.1607	0.2131	1.1607	1.0774
No log	69.3333	208	1.1109	0.1896	1.1109	1.0540
No log	70.0	210	1.0639	0.2207	1.0639	1.0315
No log	70.6667	212	1.0398	0.1525	1.0398	1.0197
No log	71.3333	214	1.0342	0.1927	1.0342	1.0170
No log	72.0	216	1.0249	0.2327	1.0249	1.0124
No log	72.6667	218	1.0252	0.1927	1.0252	1.0125
No log	73.3333	220	1.0412	0.2636	1.0412	1.0204
No log	74.0	222	1.0676	0.2195	1.0676	1.0332
No log	74.6667	224	1.0797	0.2090	1.0797	1.0391
No log	75.3333	226	1.0752	0.2090	1.0752	1.0369
No log	76.0	228	1.0562	0.2586	1.0562	1.0277
No log	76.6667	230	1.0320	0.2782	1.0320	1.0159
No log	77.3333	232	1.0143	0.2024	1.0143	1.0071
No log	78.0	234	1.0119	0.2477	1.0119	1.0059
No log	78.6667	236	1.0214	0.2024	1.0214	1.0106
No log	79.3333	238	1.0331	0.2260	1.0331	1.0164
No log	80.0	240	1.0341	0.1717	1.0341	1.0169
No log	80.6667	242	1.0266	0.1564	1.0266	1.0132
No log	81.3333	244	1.0233	0.2188	1.0233	1.0116
No log	82.0	246	1.0348	0.1308	1.0348	1.0173
No log	82.6667	248	1.0551	0.1244	1.0551	1.0272
No log	83.3333	250	1.0819	0.1081	1.0819	1.0401
No log	84.0	252	1.1094	0.0857	1.1094	1.0533
No log	84.6667	254	1.1377	0.1596	1.1377	1.0666
No log	85.3333	256	1.1504	0.1944	1.1504	1.0726
No log	86.0	258	1.1575	0.1944	1.1575	1.0759
No log	86.6667	260	1.1569	0.1944	1.1569	1.0756
No log	87.3333	262	1.1559	0.1944	1.1559	1.0751
No log	88.0	264	1.1375	0.1944	1.1375	1.0666
No log	88.6667	266	1.1131	0.1185	1.1131	1.0551
No log	89.3333	268	1.0930	0.0930	1.0930	1.0455
No log	90.0	270	1.0757	0.1248	1.0757	1.0372
No log	90.6667	272	1.0664	0.1717	1.0664	1.0327
No log	91.3333	274	1.0606	0.1406	1.0606	1.0298
No log	92.0	276	1.0572	0.1564	1.0572	1.0282
No log	92.6667	278	1.0584	0.1564	1.0584	1.0288
No log	93.3333	280	1.0579	0.1564	1.0579	1.0285
No log	94.0	282	1.0585	0.1564	1.0585	1.0289
No log	94.6667	284	1.0595	0.1406	1.0595	1.0293
No log	95.3333	286	1.0592	0.1564	1.0592	1.0292
No log	96.0	288	1.0597	0.1564	1.0597	1.0294
No log	96.6667	290	1.0602	0.1406	1.0602	1.0297
No log	97.3333	292	1.0604	0.1406	1.0604	1.0298
No log	98.0	294	1.0609	0.1406	1.0609	1.0300
No log	98.6667	296	1.0614	0.1406	1.0614	1.0302
No log	99.3333	298	1.0618	0.1406	1.0618	1.0304
No log	100.0	300	1.0623	0.1406	1.0623	1.0307

Framework versions

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