ArabicNewSplits7_usingWellWrittenEssays_FineTuningAraBERT_run3_AugV5_k1_task7_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: 0.9319
• Qwk: 0.0982
• Mse: 0.9319
• Rmse: 0.9653

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	4.2154	-0.0060	4.2154	2.0531
No log	1.3333	4	2.1734	-0.0316	2.1734	1.4742
No log	2.0	6	1.8642	0.0298	1.8642	1.3653
No log	2.6667	8	1.6716	0.0233	1.6716	1.2929
No log	3.3333	10	0.9513	0.0860	0.9513	0.9753
No log	4.0	12	1.3112	0.0390	1.3112	1.1451
No log	4.6667	14	1.7222	0.0049	1.7222	1.3123
No log	5.3333	16	1.2439	0.0686	1.2439	1.1153
No log	6.0	18	0.8313	0.2813	0.8313	0.9117
No log	6.6667	20	0.8361	0.2739	0.8361	0.9144
No log	7.3333	22	1.0473	0.1184	1.0473	1.0234
No log	8.0	24	1.5759	0.0898	1.5759	1.2554
No log	8.6667	26	1.2758	0.0312	1.2758	1.1295
No log	9.3333	28	0.9355	0.2339	0.9355	0.9672
No log	10.0	30	0.8571	0.2277	0.8571	0.9258
No log	10.6667	32	0.9790	0.1600	0.9790	0.9895
No log	11.3333	34	1.1933	0.1182	1.1933	1.0924
No log	12.0	36	1.0288	0.1641	1.0288	1.0143
No log	12.6667	38	0.9725	0.1531	0.9725	0.9862
No log	13.3333	40	1.0411	0.0752	1.0411	1.0203
No log	14.0	42	1.1477	0.1056	1.1477	1.0713
No log	14.6667	44	1.1977	0.0996	1.1977	1.0944
No log	15.3333	46	1.2576	-0.0026	1.2576	1.1214
No log	16.0	48	1.4412	0.0858	1.4412	1.2005
No log	16.6667	50	1.3153	0.0020	1.3153	1.1468
No log	17.3333	52	1.1836	0.0972	1.1836	1.0879
No log	18.0	54	1.0634	0.1653	1.0634	1.0312
No log	18.6667	56	1.1575	0.0671	1.1575	1.0759
No log	19.3333	58	1.3467	0.0858	1.3467	1.1605
No log	20.0	60	1.2003	0.0999	1.2003	1.0956
No log	20.6667	62	1.0722	0.1820	1.0722	1.0355
No log	21.3333	64	1.0590	0.1449	1.0590	1.0291
No log	22.0	66	1.1925	0.0966	1.1925	1.0920
No log	22.6667	68	1.2008	0.1281	1.2008	1.0958
No log	23.3333	70	1.1068	0.1472	1.1068	1.0521
No log	24.0	72	1.0672	0.0834	1.0672	1.0331
No log	24.6667	74	1.0327	0.1917	1.0327	1.0162
No log	25.3333	76	0.9911	0.1490	0.9911	0.9956
No log	26.0	78	0.9620	0.1234	0.9620	0.9808
No log	26.6667	80	0.8954	0.2449	0.8954	0.9462
No log	27.3333	82	0.8566	0.2809	0.8566	0.9255
No log	28.0	84	0.8661	0.2479	0.8661	0.9306
No log	28.6667	86	0.9168	0.1547	0.9168	0.9575
No log	29.3333	88	0.9412	0.2036	0.9412	0.9702
No log	30.0	90	0.9896	0.2238	0.9896	0.9948
No log	30.6667	92	1.0643	0.1479	1.0643	1.0317
No log	31.3333	94	1.0855	0.1545	1.0855	1.0419
No log	32.0	96	1.0320	0.1225	1.0320	1.0159
No log	32.6667	98	0.9797	0.1196	0.9797	0.9898
No log	33.3333	100	0.9685	0.1578	0.9685	0.9841
No log	34.0	102	0.9433	0.1231	0.9433	0.9712
No log	34.6667	104	0.9862	0.2164	0.9862	0.9931
No log	35.3333	106	1.0853	0.0443	1.0853	1.0418
No log	36.0	108	1.0853	0.0741	1.0853	1.0418
No log	36.6667	110	1.0564	0.0995	1.0564	1.0278
No log	37.3333	112	1.0430	0.0991	1.0430	1.0213
No log	38.0	114	1.0199	0.1600	1.0199	1.0099
No log	38.6667	116	1.0008	0.1682	1.0008	1.0004
No log	39.3333	118	0.9581	0.1682	0.9581	0.9788
No log	40.0	120	0.9366	0.2273	0.9366	0.9678
No log	40.6667	122	0.9447	0.2303	0.9447	0.9720
No log	41.3333	124	0.9732	0.1682	0.9732	0.9865
No log	42.0	126	0.9248	0.2652	0.9248	0.9617
No log	42.6667	128	0.9043	0.2061	0.9043	0.9509
No log	43.3333	130	0.9117	0.2495	0.9117	0.9548
No log	44.0	132	0.8953	0.2495	0.8953	0.9462
No log	44.6667	134	0.8936	0.2681	0.8936	0.9453
No log	45.3333	136	0.9254	0.2043	0.9254	0.9620
No log	46.0	138	0.9858	0.1846	0.9858	0.9929
No log	46.6667	140	0.9915	0.1814	0.9915	0.9957
No log	47.3333	142	1.0114	0.1446	1.0114	1.0057
No log	48.0	144	1.0252	0.1725	1.0252	1.0125
No log	48.6667	146	1.0566	0.1401	1.0566	1.0279
No log	49.3333	148	1.0272	0.1725	1.0272	1.0135
No log	50.0	150	1.0131	0.1725	1.0131	1.0065
No log	50.6667	152	0.9593	0.0685	0.9593	0.9795
No log	51.3333	154	0.9186	0.1253	0.9186	0.9584
No log	52.0	156	0.9174	0.1219	0.9174	0.9578
No log	52.6667	158	0.9301	0.1253	0.9301	0.9644
No log	53.3333	160	0.9585	0.0325	0.9585	0.9790
No log	54.0	162	0.9754	0.0685	0.9754	0.9876
No log	54.6667	164	0.9639	0.0912	0.9639	0.9818
No log	55.3333	166	0.9458	0.1871	0.9458	0.9725
No log	56.0	168	0.9432	0.1273	0.9432	0.9712
No log	56.6667	170	0.9894	0.1682	0.9894	0.9947
No log	57.3333	172	1.0290	0.1395	1.0290	1.0144
No log	58.0	174	1.0209	0.1395	1.0209	1.0104
No log	58.6667	176	0.9581	0.1682	0.9581	0.9788
No log	59.3333	178	0.9120	0.2203	0.9120	0.9550
No log	60.0	180	0.9185	0.2109	0.9185	0.9584
No log	60.6667	182	0.9187	0.2077	0.9187	0.9585
No log	61.3333	184	0.9137	0.1820	0.9137	0.9559
No log	62.0	186	0.9230	0.1888	0.9230	0.9607
No log	62.6667	188	0.9289	0.2486	0.9289	0.9638
No log	63.3333	190	0.9298	0.2192	0.9298	0.9643
No log	64.0	192	0.9246	0.2192	0.9246	0.9616
No log	64.6667	194	0.9413	0.2192	0.9413	0.9702
No log	65.3333	196	0.9668	0.1600	0.9668	0.9833
No log	66.0	198	0.9989	0.1600	0.9989	0.9994
No log	66.6667	200	0.9965	0.1600	0.9965	0.9983
No log	67.3333	202	0.9830	0.1600	0.9830	0.9914
No log	68.0	204	0.9687	0.1785	0.9687	0.9842
No log	68.6667	206	0.9718	0.2102	0.9718	0.9858
No log	69.3333	208	0.9771	0.2053	0.9771	0.9885
No log	70.0	210	0.9827	0.1825	0.9827	0.9913
No log	70.6667	212	0.9785	0.1825	0.9785	0.9892
No log	71.3333	214	0.9779	0.0627	0.9779	0.9889
No log	72.0	216	0.9670	0.0635	0.9670	0.9834
No log	72.6667	218	0.9447	0.0627	0.9447	0.9719
No log	73.3333	220	0.9350	0.0275	0.9350	0.9670
No log	74.0	222	0.9266	0.0602	0.9266	0.9626
No log	74.6667	224	0.9231	0.1506	0.9231	0.9608
No log	75.3333	226	0.9273	0.1179	0.9273	0.9630
No log	76.0	228	0.9238	0.1506	0.9238	0.9611
No log	76.6667	230	0.9227	0.0602	0.9227	0.9606
No log	77.3333	232	0.9349	0.0640	0.9349	0.9669
No log	78.0	234	0.9516	0.0692	0.9516	0.9755
No log	78.6667	236	0.9618	0.0692	0.9618	0.9807
No log	79.3333	238	0.9593	0.0692	0.9593	0.9795
No log	80.0	240	0.9582	0.0339	0.9582	0.9789
No log	80.6667	242	0.9522	0.0640	0.9522	0.9758
No log	81.3333	244	0.9438	0.0640	0.9438	0.9715
No log	82.0	246	0.9396	0.0640	0.9396	0.9693
No log	82.6667	248	0.9340	0.0640	0.9340	0.9665
No log	83.3333	250	0.9324	0.0912	0.9324	0.9656
No log	84.0	252	0.9336	0.1246	0.9336	0.9662
No log	84.6667	254	0.9296	0.1825	0.9296	0.9642
No log	85.3333	256	0.9219	0.1820	0.9219	0.9602
No log	86.0	258	0.9108	0.1487	0.9108	0.9543
No log	86.6667	260	0.8961	0.1487	0.8961	0.9466
No log	87.3333	262	0.8845	0.1820	0.8845	0.9405
No log	88.0	264	0.8800	0.2838	0.8800	0.9381
No log	88.6667	266	0.8824	0.2203	0.8824	0.9394
No log	89.3333	268	0.8902	0.1661	0.8902	0.9435
No log	90.0	270	0.9027	0.1016	0.9027	0.9501
No log	90.6667	272	0.9134	0.0982	0.9134	0.9557
No log	91.3333	274	0.9268	0.1307	0.9268	0.9627
No log	92.0	276	0.9343	0.1307	0.9343	0.9666
No log	92.6667	278	0.9366	0.1307	0.9366	0.9678
No log	93.3333	280	0.9405	0.1307	0.9405	0.9698
No log	94.0	282	0.9455	0.1307	0.9455	0.9724
No log	94.6667	284	0.9463	0.1307	0.9463	0.9728
No log	95.3333	286	0.9443	0.1307	0.9443	0.9718
No log	96.0	288	0.9403	0.1307	0.9403	0.9697
No log	96.6667	290	0.9371	0.1307	0.9371	0.9681
No log	97.3333	292	0.9352	0.1307	0.9352	0.9670
No log	98.0	294	0.9332	0.1307	0.9332	0.9660
No log	98.6667	296	0.9321	0.1307	0.9321	0.9655
No log	99.3333	298	0.9318	0.0982	0.9318	0.9653
No log	100.0	300	0.9319	0.0982	0.9319	0.9653

Framework versions

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