ArabicNewSplits4_WithDuplicationsForScore5_FineTuningAraBERT_run1_AugV5_k5_task3_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: 0.6251
• Qwk: 0.4694
• Mse: 0.6251
• Rmse: 0.7906

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: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Qwk	Mse	Rmse
No log	0.0833	2	3.4150	-0.0160	3.4150	1.8480
No log	0.1667	4	1.7435	-0.0070	1.7435	1.3204
No log	0.25	6	1.0272	0.0335	1.0272	1.0135
No log	0.3333	8	1.0208	0.1405	1.0208	1.0104
No log	0.4167	10	0.9405	0.1736	0.9405	0.9698
No log	0.5	12	0.5890	0.0534	0.5890	0.7674
No log	0.5833	14	0.8211	0.1908	0.8211	0.9062
No log	0.6667	16	0.6020	0.1176	0.6020	0.7759
No log	0.75	18	0.6791	0.0739	0.6791	0.8241
No log	0.8333	20	0.5753	0.2516	0.5753	0.7585
No log	0.9167	22	0.5785	0.1756	0.5785	0.7606
No log	1.0	24	0.7771	0.1895	0.7771	0.8816
No log	1.0833	26	0.7128	0.1888	0.7128	0.8443
No log	1.1667	28	0.6123	0.0725	0.6123	0.7825
No log	1.25	30	0.6922	0.1732	0.6922	0.8320
No log	1.3333	32	0.7012	0.1605	0.7012	0.8374
No log	1.4167	34	0.7216	0.1707	0.7216	0.8495
No log	1.5	36	0.8159	0.1287	0.8159	0.9033
No log	1.5833	38	0.8331	0.1174	0.8331	0.9128
No log	1.6667	40	0.7404	0.0769	0.7404	0.8605
No log	1.75	42	1.2267	-0.0185	1.2267	1.1075
No log	1.8333	44	1.3862	-0.0196	1.3862	1.1774
No log	1.9167	46	0.8902	0.1675	0.8902	0.9435
No log	2.0	48	0.8758	0.1416	0.8758	0.9358
No log	2.0833	50	1.2631	0.1467	1.2631	1.1239
No log	2.1667	52	0.9452	0.1515	0.9452	0.9722
No log	2.25	54	0.7841	0.1759	0.7841	0.8855
No log	2.3333	56	1.0163	0.0968	1.0163	1.0081
No log	2.4167	58	0.8018	0.1759	0.8018	0.8954
No log	2.5	60	0.7952	0.1045	0.7952	0.8917
No log	2.5833	62	0.7564	0.1515	0.7564	0.8697
No log	2.6667	64	0.7492	0.1739	0.7492	0.8656
No log	2.75	66	0.8497	0.24	0.8497	0.9218
No log	2.8333	68	0.9383	0.1289	0.9383	0.9687
No log	2.9167	70	0.8001	0.2161	0.8001	0.8945
No log	3.0	72	0.8016	0.1636	0.8016	0.8953
No log	3.0833	74	0.8117	0.3214	0.8117	0.9010
No log	3.1667	76	1.0393	0.1373	1.0393	1.0194
No log	3.25	78	0.9866	0.1040	0.9866	0.9933
No log	3.3333	80	1.1142	0.0606	1.1142	1.0555
No log	3.4167	82	0.8770	0.2356	0.8770	0.9365
No log	3.5	84	0.9626	0.1304	0.9626	0.9811
No log	3.5833	86	0.8961	0.1273	0.8961	0.9466
No log	3.6667	88	0.8968	0.2579	0.8968	0.9470
No log	3.75	90	0.8813	0.1712	0.8813	0.9388
No log	3.8333	92	0.9067	0.1928	0.9067	0.9522
No log	3.9167	94	0.9232	0.2829	0.9232	0.9608
No log	4.0	96	0.9172	0.2520	0.9172	0.9577
No log	4.0833	98	0.8399	0.2340	0.8399	0.9164
No log	4.1667	100	0.8448	0.3147	0.8448	0.9191
No log	4.25	102	1.2333	0.1065	1.2333	1.1105
No log	4.3333	104	1.4294	0.1611	1.4294	1.1956
No log	4.4167	106	1.0128	0.1127	1.0128	1.0064
No log	4.5	108	0.8380	0.1852	0.8380	0.9154
No log	4.5833	110	0.9685	0.1417	0.9685	0.9841
No log	4.6667	112	0.8157	0.2212	0.8157	0.9031
No log	4.75	114	0.7523	0.3778	0.7523	0.8673
No log	4.8333	116	0.7262	0.3607	0.7262	0.8522
No log	4.9167	118	0.6950	0.3514	0.6950	0.8337
No log	5.0	120	0.6715	0.3267	0.6715	0.8195
No log	5.0833	122	0.6618	0.3077	0.6618	0.8135
No log	5.1667	124	0.6773	0.3571	0.6773	0.8230
No log	5.25	126	0.6314	0.3077	0.6314	0.7946
No log	5.3333	128	0.6562	0.3035	0.6562	0.8101
No log	5.4167	130	0.6540	0.3462	0.6540	0.8087
No log	5.5	132	0.8712	0.2829	0.8712	0.9334
No log	5.5833	134	0.9910	0.1746	0.9910	0.9955
No log	5.6667	136	0.7723	0.2900	0.7723	0.8788
No log	5.75	138	0.6677	0.2390	0.6677	0.8172
No log	5.8333	140	0.7710	0.1925	0.7710	0.8781
No log	5.9167	142	0.7060	0.2075	0.7060	0.8402
No log	6.0	144	0.6660	0.2709	0.6660	0.8161
No log	6.0833	146	0.9235	0.2000	0.9235	0.9610
No log	6.1667	148	0.9464	0.2000	0.9464	0.9728
No log	6.25	150	0.7273	0.2692	0.7273	0.8528
No log	6.3333	152	0.6478	0.2990	0.6478	0.8049
No log	6.4167	154	0.7990	0.1930	0.7990	0.8939
No log	6.5	156	0.7753	0.1930	0.7753	0.8805
No log	6.5833	158	0.6508	0.3271	0.6508	0.8067
No log	6.6667	160	0.6905	0.2161	0.6905	0.8309
No log	6.75	162	0.6997	0.2161	0.6997	0.8365
No log	6.8333	164	0.6698	0.3077	0.6698	0.8184
No log	6.9167	166	0.6526	0.3171	0.6526	0.8078
No log	7.0	168	0.6578	0.28	0.6578	0.8110
No log	7.0833	170	0.6475	0.3469	0.6475	0.8047
No log	7.1667	172	0.6495	0.3469	0.6495	0.8059
No log	7.25	174	0.6659	0.2709	0.6659	0.8161
No log	7.3333	176	0.6826	0.2233	0.6826	0.8262
No log	7.4167	178	0.6776	0.3143	0.6776	0.8232
No log	7.5	180	0.6768	0.3143	0.6768	0.8227
No log	7.5833	182	0.6695	0.3831	0.6695	0.8183
No log	7.6667	184	0.6714	0.2871	0.6714	0.8194
No log	7.75	186	0.6615	0.4	0.6615	0.8133
No log	7.8333	188	0.6626	0.3860	0.6626	0.8140
No log	7.9167	190	0.6843	0.3267	0.6843	0.8272
No log	8.0	192	0.6983	0.2850	0.6983	0.8356
No log	8.0833	194	0.6823	0.2780	0.6823	0.8260
No log	8.1667	196	0.6635	0.3860	0.6635	0.8146
No log	8.25	198	0.6599	0.3860	0.6599	0.8123
No log	8.3333	200	0.6571	0.4341	0.6571	0.8106
No log	8.4167	202	0.6531	0.3548	0.6531	0.8082
No log	8.5	204	0.6511	0.3786	0.6511	0.8069
No log	8.5833	206	0.6460	0.4229	0.6460	0.8038
No log	8.6667	208	0.6398	0.4229	0.6398	0.7999
No log	8.75	210	0.6360	0.4694	0.6360	0.7975
No log	8.8333	212	0.6462	0.3333	0.6462	0.8038
No log	8.9167	214	0.6817	0.2727	0.6817	0.8256
No log	9.0	216	0.7541	0.2632	0.7541	0.8684
No log	9.0833	218	0.8069	0.2618	0.8069	0.8983
No log	9.1667	220	0.8150	0.2618	0.8150	0.9028
No log	9.25	222	0.8003	0.2618	0.8003	0.8946
No log	9.3333	224	0.7516	0.2632	0.7516	0.8670
No log	9.4167	226	0.7090	0.3303	0.7090	0.8420
No log	9.5	228	0.6721	0.2332	0.6721	0.8198
No log	9.5833	230	0.6432	0.3333	0.6432	0.8020
No log	9.6667	232	0.6287	0.4694	0.6287	0.7929
No log	9.75	234	0.6237	0.4694	0.6237	0.7898
No log	9.8333	236	0.6236	0.4694	0.6236	0.7897
No log	9.9167	238	0.6247	0.4694	0.6247	0.7903
No log	10.0	240	0.6251	0.4694	0.6251	0.7906

Framework versions

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