ArabicNewSplits7_usingWellWrittenEssays_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: 1.2022
• Qwk: 0.2310
• Mse: 1.2022
• Rmse: 1.0964

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	4.7015	0.0010	4.7015	2.1683
No log	1.3333	4	2.6419	-0.0084	2.6419	1.6254
No log	2.0	6	2.0221	-0.0303	2.0221	1.4220
No log	2.6667	8	1.6172	-0.0064	1.6172	1.2717
No log	3.3333	10	1.5607	-0.0880	1.5607	1.2493
No log	4.0	12	1.3936	-0.0422	1.3936	1.1805
No log	4.6667	14	1.2986	0.1207	1.2986	1.1396
No log	5.3333	16	1.3813	-0.0806	1.3813	1.1753
No log	6.0	18	1.3559	0.0077	1.3559	1.1644
No log	6.6667	20	1.2712	0.1658	1.2712	1.1275
No log	7.3333	22	1.2976	0.0894	1.2976	1.1391
No log	8.0	24	1.2969	0.0984	1.2969	1.1388
No log	8.6667	26	1.2242	0.1911	1.2242	1.1064
No log	9.3333	28	1.1934	0.2369	1.1934	1.0924
No log	10.0	30	1.2698	0.1108	1.2698	1.1269
No log	10.6667	32	1.4602	0.0057	1.4602	1.2084
No log	11.3333	34	1.3941	0.0831	1.3941	1.1807
No log	12.0	36	1.1957	0.1793	1.1957	1.0935
No log	12.6667	38	1.1901	0.1246	1.1901	1.0909
No log	13.3333	40	1.1931	0.1875	1.1931	1.0923
No log	14.0	42	1.3756	0.0731	1.3756	1.1729
No log	14.6667	44	1.5641	-0.0817	1.5641	1.2506
No log	15.3333	46	1.4320	0.1354	1.4320	1.1967
No log	16.0	48	1.2960	0.1362	1.2960	1.1384
No log	16.6667	50	1.3267	0.1423	1.3267	1.1518
No log	17.3333	52	1.4769	0.0421	1.4769	1.2153
No log	18.0	54	1.5276	0.0879	1.5276	1.2360
No log	18.6667	56	1.6142	0.1256	1.6142	1.2705
No log	19.3333	58	1.4390	0.2270	1.4390	1.1996
No log	20.0	60	1.4708	0.2131	1.4708	1.2128
No log	20.6667	62	1.2796	0.2592	1.2796	1.1312
No log	21.3333	64	1.2614	0.2287	1.2614	1.1231
No log	22.0	66	1.5376	0.1709	1.5376	1.2400
No log	22.6667	68	1.8144	0.0303	1.8144	1.3470
No log	23.3333	70	1.5253	0.1785	1.5253	1.2350
No log	24.0	72	1.2389	0.2555	1.2389	1.1131
No log	24.6667	74	1.2490	0.2939	1.2490	1.1176
No log	25.3333	76	1.3968	0.2511	1.3968	1.1819
No log	26.0	78	1.4691	0.1720	1.4691	1.2120
No log	26.6667	80	1.4560	0.2044	1.4560	1.2066
No log	27.3333	82	1.2788	0.3036	1.2788	1.1308
No log	28.0	84	1.1716	0.2306	1.1716	1.0824
No log	28.6667	86	1.1961	0.3036	1.1961	1.0936
No log	29.3333	88	1.2737	0.2920	1.2737	1.1286
No log	30.0	90	1.1768	0.3390	1.1768	1.0848
No log	30.6667	92	1.2005	0.3390	1.2005	1.0957
No log	31.3333	94	1.3476	0.3161	1.3476	1.1609
No log	32.0	96	1.3075	0.2805	1.3075	1.1435
No log	32.6667	98	1.2458	0.3304	1.2458	1.1162
No log	33.3333	100	1.3202	0.2989	1.3202	1.1490
No log	34.0	102	1.4514	0.2581	1.4514	1.2048
No log	34.6667	104	1.3708	0.2917	1.3708	1.1708
No log	35.3333	106	1.2833	0.2700	1.2833	1.1328
No log	36.0	108	1.1871	0.2775	1.1871	1.0896
No log	36.6667	110	1.1902	0.2941	1.1902	1.0910
No log	37.3333	112	1.2638	0.2651	1.2638	1.1242
No log	38.0	114	1.3649	0.2511	1.3649	1.1683
No log	38.6667	116	1.5672	0.1071	1.5672	1.2519
No log	39.3333	118	1.6968	0.1129	1.6968	1.3026
No log	40.0	120	1.5337	0.1991	1.5337	1.2384
No log	40.6667	122	1.3319	0.2902	1.3319	1.1541
No log	41.3333	124	1.3205	0.3012	1.3205	1.1491
No log	42.0	126	1.4665	0.1809	1.4665	1.2110
No log	42.6667	128	1.6600	0.0733	1.6600	1.2884
No log	43.3333	130	1.5462	0.0945	1.5462	1.2435
No log	44.0	132	1.3364	0.2358	1.3364	1.1560
No log	44.6667	134	1.2658	0.2661	1.2658	1.1251
No log	45.3333	136	1.2822	0.2661	1.2822	1.1323
No log	46.0	138	1.3276	0.2293	1.3276	1.1522
No log	46.6667	140	1.3411	0.2293	1.3411	1.1581
No log	47.3333	142	1.3092	0.2661	1.3092	1.1442
No log	48.0	144	1.2735	0.1794	1.2735	1.1285
No log	48.6667	146	1.2698	0.1928	1.2698	1.1269
No log	49.3333	148	1.2879	0.2661	1.2879	1.1349
No log	50.0	150	1.3486	0.2158	1.3486	1.1613
No log	50.6667	152	1.2973	0.2584	1.2973	1.1390
No log	51.3333	154	1.2180	0.2468	1.2180	1.1036
No log	52.0	156	1.2081	0.2468	1.2081	1.0991
No log	52.6667	158	1.2190	0.2447	1.2190	1.1041
No log	53.3333	160	1.2739	0.2211	1.2739	1.1287
No log	54.0	162	1.3011	0.2306	1.3011	1.1406
No log	54.6667	164	1.3042	0.2306	1.3042	1.1420
No log	55.3333	166	1.2878	0.2293	1.2878	1.1348
No log	56.0	168	1.2882	0.2241	1.2882	1.1350
No log	56.6667	170	1.2974	0.2007	1.2974	1.1390
No log	57.3333	172	1.3201	0.1817	1.3201	1.1489
No log	58.0	174	1.3642	0.0988	1.3642	1.1680
No log	58.6667	176	1.3466	0.1576	1.3466	1.1605
No log	59.3333	178	1.3075	0.2211	1.3075	1.1435
No log	60.0	180	1.2664	0.1805	1.2664	1.1253
No log	60.6667	182	1.2585	0.2145	1.2585	1.1218
No log	61.3333	184	1.2694	0.1992	1.2694	1.1267
No log	62.0	186	1.2839	0.2211	1.2839	1.1331
No log	62.6667	188	1.2944	0.2211	1.2944	1.1377
No log	63.3333	190	1.2928	0.2211	1.2928	1.1370
No log	64.0	192	1.2818	0.2211	1.2818	1.1322
No log	64.6667	194	1.2943	0.2113	1.2943	1.1377
No log	65.3333	196	1.3177	0.2113	1.3177	1.1479
No log	66.0	198	1.3130	0.2113	1.3130	1.1458
No log	66.6667	200	1.2807	0.1709	1.2807	1.1317
No log	67.3333	202	1.2657	0.2187	1.2657	1.1250
No log	68.0	204	1.2602	0.2038	1.2602	1.1226
No log	68.6667	206	1.2531	0.2145	1.2531	1.1194
No log	69.3333	208	1.2685	0.2113	1.2685	1.1263
No log	70.0	210	1.3129	0.1519	1.3129	1.1458
No log	70.6667	212	1.3115	0.1519	1.3115	1.1452
No log	71.3333	214	1.2682	0.2016	1.2682	1.1262
No log	72.0	216	1.2533	0.2462	1.2533	1.1195
No log	72.6667	218	1.2322	0.2156	1.2322	1.1100
No log	73.3333	220	1.2218	0.2145	1.2218	1.1054
No log	74.0	222	1.2267	0.1992	1.2267	1.1076
No log	74.6667	224	1.2411	0.2296	1.2411	1.1140
No log	75.3333	226	1.2560	0.2113	1.2560	1.1207
No log	76.0	228	1.2849	0.1919	1.2849	1.1335
No log	76.6667	230	1.3086	0.1576	1.3086	1.1439
No log	77.3333	232	1.3190	0.1687	1.3190	1.1485
No log	78.0	234	1.2845	0.2016	1.2845	1.1333
No log	78.6667	236	1.2543	0.2016	1.2543	1.1200
No log	79.3333	238	1.2210	0.2199	1.2210	1.1050
No log	80.0	240	1.1957	0.2296	1.1957	1.0935
No log	80.6667	242	1.1791	0.2336	1.1791	1.0859
No log	81.3333	244	1.1742	0.2187	1.1742	1.0836
No log	82.0	246	1.1685	0.2187	1.1685	1.0810
No log	82.6667	248	1.1641	0.2296	1.1641	1.0790
No log	83.3333	250	1.1642	0.2001	1.1642	1.0790
No log	84.0	252	1.1679	0.2409	1.1679	1.0807
No log	84.6667	254	1.1686	0.2409	1.1686	1.0810
No log	85.3333	256	1.1657	0.2409	1.1657	1.0797
No log	86.0	258	1.1606	0.2001	1.1606	1.0773
No log	86.6667	260	1.1670	0.2001	1.1670	1.0803
No log	87.3333	262	1.1783	0.2562	1.1783	1.0855
No log	88.0	264	1.1875	0.2113	1.1875	1.0897
No log	88.6667	266	1.1961	0.2113	1.1961	1.0937
No log	89.3333	268	1.2034	0.2113	1.2034	1.0970
No log	90.0	270	1.2091	0.2113	1.2091	1.0996
No log	90.6667	272	1.2057	0.2113	1.2057	1.0980
No log	91.3333	274	1.2017	0.2462	1.2017	1.0962
No log	92.0	276	1.1989	0.2310	1.1989	1.0950
No log	92.6667	278	1.1978	0.1903	1.1978	1.0945
No log	93.3333	280	1.1980	0.1903	1.1980	1.0945
No log	94.0	282	1.1973	0.2001	1.1973	1.0942
No log	94.6667	284	1.1972	0.2001	1.1972	1.0942
No log	95.3333	286	1.1984	0.1903	1.1984	1.0947
No log	96.0	288	1.2000	0.1903	1.2000	1.0955
No log	96.6667	290	1.2001	0.1903	1.2001	1.0955
No log	97.3333	292	1.2001	0.1903	1.2001	1.0955
No log	98.0	294	1.2014	0.1903	1.2014	1.0961
No log	98.6667	296	1.2020	0.2310	1.2020	1.0964
No log	99.3333	298	1.2022	0.2310	1.2022	1.0964
No log	100.0	300	1.2022	0.2310	1.2022	1.0964

Framework versions

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