ArabicNewSplits7_usingALLEssays_FineTuningAraBERT_run2_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: 1.3404
• Qwk: 0.0692
• Mse: 1.3404
• Rmse: 1.1578

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	4.7288	0.0010	4.7288	2.1746
No log	1.3333	4	2.5879	0.0489	2.5879	1.6087
No log	2.0	6	1.8069	0.0062	1.8069	1.3442
No log	2.6667	8	1.3469	0.0676	1.3469	1.1605
No log	3.3333	10	1.2445	0.1110	1.2445	1.1156
No log	4.0	12	1.2129	0.1076	1.2129	1.1013
No log	4.6667	14	1.2158	0.1609	1.2158	1.1026
No log	5.3333	16	1.2360	0.1772	1.2360	1.1117
No log	6.0	18	1.2230	0.1772	1.2230	1.1059
No log	6.6667	20	1.1844	0.2408	1.1844	1.0883
No log	7.3333	22	1.2192	0.0527	1.2192	1.1042
No log	8.0	24	1.2564	0.0353	1.2564	1.1209
No log	8.6667	26	1.2397	0.0974	1.2397	1.1134
No log	9.3333	28	1.1871	0.1711	1.1871	1.0895
No log	10.0	30	1.2018	0.2124	1.2018	1.0963
No log	10.6667	32	1.3144	0.1622	1.3144	1.1465
No log	11.3333	34	1.3393	0.0955	1.3393	1.1573
No log	12.0	36	1.2841	0.0587	1.2841	1.1332
No log	12.6667	38	1.2054	0.1752	1.2054	1.0979
No log	13.3333	40	1.2701	0.2086	1.2701	1.1270
No log	14.0	42	1.3338	0.2417	1.3338	1.1549
No log	14.6667	44	1.3103	0.2904	1.3103	1.1447
No log	15.3333	46	1.3059	0.1898	1.3059	1.1427
No log	16.0	48	1.2807	0.0916	1.2807	1.1317
No log	16.6667	50	1.3007	0.1632	1.3007	1.1405
No log	17.3333	52	1.3606	0.1852	1.3606	1.1665
No log	18.0	54	1.3901	0.0997	1.3901	1.1790
No log	18.6667	56	1.4431	0.1501	1.4431	1.2013
No log	19.3333	58	1.4524	0.1027	1.4524	1.2051
No log	20.0	60	1.4052	0.125	1.4052	1.1854
No log	20.6667	62	1.3196	0.1246	1.3196	1.1488
No log	21.3333	64	1.3194	0.1570	1.3194	1.1487
No log	22.0	66	1.3539	0.0945	1.3539	1.1636
No log	22.6667	68	1.3936	0.0310	1.3936	1.1805
No log	23.3333	70	1.4256	0.0958	1.4256	1.1940
No log	24.0	72	1.3824	0.0647	1.3824	1.1758
No log	24.6667	74	1.3694	0.0647	1.3694	1.1702
No log	25.3333	76	1.3755	0.1500	1.3755	1.1728
No log	26.0	78	1.3971	0.1611	1.3971	1.1820
No log	26.6667	80	1.4551	0.0921	1.4551	1.2063
No log	27.3333	82	1.5099	0.1335	1.5099	1.2288
No log	28.0	84	1.4980	0.1585	1.4980	1.2239
No log	28.6667	86	1.4935	0.1851	1.4935	1.2221
No log	29.3333	88	1.5129	0.1807	1.5129	1.2300
No log	30.0	90	1.4085	0.1462	1.4085	1.1868
No log	30.6667	92	1.3245	0.1557	1.3245	1.1509
No log	31.3333	94	1.3109	0.1441	1.3109	1.1449
No log	32.0	96	1.3116	0.1026	1.3116	1.1453
No log	32.6667	98	1.3250	0.0843	1.3250	1.1511
No log	33.3333	100	1.3203	0.0843	1.3203	1.1491
No log	34.0	102	1.3353	0.0843	1.3353	1.1555
No log	34.6667	104	1.3518	0.1159	1.3518	1.1627
No log	35.3333	106	1.3010	-0.0120	1.3010	1.1406
No log	36.0	108	1.2692	-0.0218	1.2692	1.1266
No log	36.6667	110	1.2693	0.0228	1.2693	1.1266
No log	37.3333	112	1.3126	-0.0120	1.3126	1.1457
No log	38.0	114	1.3979	0.1345	1.3979	1.1823
No log	38.6667	116	1.4397	0.1159	1.4397	1.1999
No log	39.3333	118	1.4262	0.1005	1.4262	1.1943
No log	40.0	120	1.3587	0.1345	1.3587	1.1656
No log	40.6667	122	1.3100	0.0857	1.3100	1.1445
No log	41.3333	124	1.2847	-0.0218	1.2847	1.1334
No log	42.0	126	1.2997	0.0954	1.2997	1.1400
No log	42.6667	128	1.3573	0.1026	1.3573	1.1650
No log	43.3333	130	1.4133	0.1222	1.4133	1.1888
No log	44.0	132	1.4452	0.1222	1.4452	1.2022
No log	44.6667	134	1.4581	0.1222	1.4581	1.2075
No log	45.3333	136	1.4209	0.1222	1.4209	1.1920
No log	46.0	138	1.3228	0.0692	1.3228	1.1501
No log	46.6667	140	1.2397	0.0228	1.2397	1.1134
No log	47.3333	142	1.2227	0.0671	1.2227	1.1058
No log	48.0	144	1.2293	0.0700	1.2293	1.1087
No log	48.6667	146	1.2443	0.0700	1.2443	1.1155
No log	49.3333	148	1.2787	0.0780	1.2787	1.1308
No log	50.0	150	1.3270	0.0343	1.3270	1.1519
No log	50.6667	152	1.3721	0.0692	1.3721	1.1714
No log	51.3333	154	1.3702	0.0692	1.3702	1.1706
No log	52.0	156	1.3514	0.0692	1.3514	1.1625
No log	52.6667	158	1.3329	0.1026	1.3329	1.1545
No log	53.3333	160	1.2949	0.1441	1.2949	1.1379
No log	54.0	162	1.2611	0.1441	1.2611	1.1230
No log	54.6667	164	1.2583	0.1441	1.2583	1.1217
No log	55.3333	166	1.2759	0.1557	1.2759	1.1296
No log	56.0	168	1.2945	0.1557	1.2945	1.1378
No log	56.6667	170	1.2956	0.125	1.2956	1.1383
No log	57.3333	172	1.2890	0.1118	1.2890	1.1353
No log	58.0	174	1.2892	0.0780	1.2892	1.1354
No log	58.6667	176	1.2992	0.1118	1.2992	1.1398
No log	59.3333	178	1.3085	0.125	1.3085	1.1439
No log	60.0	180	1.3120	0.125	1.3120	1.1454
No log	60.6667	182	1.3472	0.0843	1.3472	1.1607
No log	61.3333	184	1.3960	0.0981	1.3960	1.1815
No log	62.0	186	1.4017	0.0981	1.4017	1.1839
No log	62.6667	188	1.3471	0.1371	1.3471	1.1607
No log	63.3333	190	1.3056	0.1557	1.3056	1.1426
No log	64.0	192	1.2652	0.1156	1.2652	1.1248
No log	64.6667	194	1.2610	0.1344	1.2610	1.1230
No log	65.3333	196	1.2556	0.1755	1.2556	1.1205
No log	66.0	198	1.2624	0.1344	1.2624	1.1236
No log	66.6667	200	1.2936	0.125	1.2936	1.1374
No log	67.3333	202	1.3199	0.0843	1.3199	1.1489
No log	68.0	204	1.3340	0.1159	1.3340	1.1550
No log	68.6667	206	1.3300	0.1159	1.3300	1.1533
No log	69.3333	208	1.3142	0.1557	1.3142	1.1464
No log	70.0	210	1.3020	0.125	1.3020	1.1411
No log	70.6667	212	1.2847	0.125	1.2847	1.1335
No log	71.3333	214	1.2682	0.1857	1.2682	1.1261
No log	72.0	216	1.2667	0.1857	1.2667	1.1255
No log	72.6667	218	1.2925	0.1557	1.2925	1.1369
No log	73.3333	220	1.3096	0.1557	1.3096	1.1444
No log	74.0	222	1.3328	0.1557	1.3328	1.1545
No log	74.6667	224	1.3455	0.1557	1.3455	1.1600
No log	75.3333	226	1.3648	0.1557	1.3648	1.1683
No log	76.0	228	1.3542	0.1557	1.3542	1.1637
No log	76.6667	230	1.3346	0.125	1.3346	1.1553
No log	77.3333	232	1.3038	0.125	1.3038	1.1419
No log	78.0	234	1.2910	0.125	1.2910	1.1362
No log	78.6667	236	1.2899	0.125	1.2899	1.1357
No log	79.3333	238	1.2880	0.1118	1.2880	1.1349
No log	80.0	240	1.3012	0.0692	1.3012	1.1407
No log	80.6667	242	1.3097	0.0692	1.3097	1.1444
No log	81.3333	244	1.3112	0.0692	1.3112	1.1451
No log	82.0	246	1.3140	0.0692	1.3140	1.1463
No log	82.6667	248	1.3278	0.0692	1.3278	1.1523
No log	83.3333	250	1.3401	0.1026	1.3401	1.1576
No log	84.0	252	1.3604	0.0843	1.3604	1.1664
No log	84.6667	254	1.3884	0.0843	1.3884	1.1783
No log	85.3333	256	1.4053	0.0981	1.4053	1.1855
No log	86.0	258	1.4036	0.0981	1.4036	1.1848
No log	86.6667	260	1.3927	0.0668	1.3927	1.1801
No log	87.3333	262	1.3912	0.0668	1.3912	1.1795
No log	88.0	264	1.3876	0.0668	1.3876	1.1780
No log	88.6667	266	1.3731	0.0668	1.3731	1.1718
No log	89.3333	268	1.3603	0.0843	1.3603	1.1663
No log	90.0	270	1.3417	0.0692	1.3417	1.1583
No log	90.6667	272	1.3310	0.0692	1.3310	1.1537
No log	91.3333	274	1.3260	0.0596	1.3260	1.1515
No log	92.0	276	1.3208	0.0596	1.3208	1.1493
No log	92.6667	278	1.3236	0.0596	1.3236	1.1505
No log	93.3333	280	1.3258	0.0692	1.3258	1.1514
No log	94.0	282	1.3287	0.0692	1.3287	1.1527
No log	94.6667	284	1.3333	0.0692	1.3333	1.1547
No log	95.3333	286	1.3373	0.0692	1.3373	1.1564
No log	96.0	288	1.3398	0.0692	1.3398	1.1575
No log	96.6667	290	1.3420	0.0692	1.3420	1.1585
No log	97.3333	292	1.3432	0.0692	1.3432	1.1590
No log	98.0	294	1.3421	0.0692	1.3421	1.1585
No log	98.6667	296	1.3414	0.0692	1.3414	1.1582
No log	99.3333	298	1.3407	0.0692	1.3407	1.1579
No log	100.0	300	1.3404	0.0692	1.3404	1.1578

Framework versions

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