ArabicNewSplits4_WithDuplicationsForScore5_FineTuningAraBERT_run3_AugV5_k4_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: 0.7451
• Qwk: 0.2372
• Mse: 0.7451
• Rmse: 0.8632

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	0.1	2	3.2078	-0.0028	3.2078	1.7910
No log	0.2	4	1.5451	0.0255	1.5451	1.2430
No log	0.3	6	1.0837	0.0335	1.0837	1.0410
No log	0.4	8	0.7208	0.1398	0.7208	0.8490
No log	0.5	10	0.5880	0.0909	0.5880	0.7668
No log	0.6	12	0.6068	0.0534	0.6068	0.7790
No log	0.7	14	0.6055	0.1278	0.6055	0.7782
No log	0.8	16	0.5965	0.0222	0.5965	0.7723
No log	0.9	18	0.6167	0.0897	0.6167	0.7853
No log	1.0	20	0.8301	0.0476	0.8301	0.9111
No log	1.1	22	0.7052	0.0429	0.7052	0.8398
No log	1.2	24	0.9406	0.0857	0.9406	0.9699
No log	1.3	26	0.9606	0.1333	0.9606	0.9801
No log	1.4	28	0.8483	0.1030	0.8483	0.9210
No log	1.5	30	0.6657	0.0625	0.6657	0.8159
No log	1.6	32	0.7859	0.1765	0.7859	0.8865
No log	1.7	34	1.5105	0.0833	1.5105	1.2290
No log	1.8	36	1.3564	0.0833	1.3564	1.1647
No log	1.9	38	0.7619	0.1919	0.7619	0.8729
No log	2.0	40	0.5993	0.0365	0.5993	0.7741
No log	2.1	42	0.6835	0.0638	0.6835	0.8268
No log	2.2	44	0.7053	0.1233	0.7053	0.8398
No log	2.3	46	0.6824	0.1667	0.6824	0.8261
No log	2.4	48	0.6650	0.0452	0.6650	0.8155
No log	2.5	50	0.7970	0.1414	0.7970	0.8928
No log	2.6	52	0.6954	0.1628	0.6954	0.8339
No log	2.7	54	0.6811	0.1565	0.6811	0.8253
No log	2.8	56	0.6948	0.1467	0.6948	0.8336
No log	2.9	58	0.7502	0.2169	0.7502	0.8662
No log	3.0	60	0.6620	0.1373	0.6620	0.8136
No log	3.1	62	0.6828	0.1351	0.6828	0.8263
No log	3.2	64	0.7646	0.0899	0.7646	0.8744
No log	3.3	66	0.8254	0.0531	0.8254	0.9085
No log	3.4	68	0.8442	0.0495	0.8442	0.9188
No log	3.5	70	0.8740	0.0359	0.8740	0.9349
No log	3.6	72	0.9018	0.0189	0.9018	0.9496
No log	3.7	74	0.9268	0.1131	0.9268	0.9627
No log	3.8	76	1.0730	0.0367	1.0730	1.0359
No log	3.9	78	1.6612	0.0327	1.6612	1.2889
No log	4.0	80	1.7462	0.0096	1.7462	1.3215
No log	4.1	82	1.1548	0.1161	1.1548	1.0746
No log	4.2	84	0.8773	0.0493	0.8773	0.9366
No log	4.3	86	0.8552	0.0707	0.8552	0.9248
No log	4.4	88	1.1661	0.0938	1.1661	1.0798
No log	4.5	90	1.6476	0.0809	1.6476	1.2836
No log	4.6	92	1.4166	0.0704	1.4166	1.1902
No log	4.7	94	0.8426	0.1304	0.8426	0.9180
No log	4.8	96	0.7782	0.0980	0.7782	0.8821
No log	4.9	98	0.7502	0.1230	0.7502	0.8661
No log	5.0	100	0.8006	0.2086	0.8006	0.8948
No log	5.1	102	1.2550	0.0365	1.2550	1.1203
No log	5.2	104	1.6616	0.0881	1.6616	1.2890
No log	5.3	106	1.5159	0.1068	1.5159	1.2312
No log	5.4	108	0.9728	0.1790	0.9728	0.9863
No log	5.5	110	0.7999	0.2850	0.7999	0.8943
No log	5.6	112	0.7470	0.2811	0.7470	0.8643
No log	5.7	114	0.7517	0.2593	0.7517	0.8670
No log	5.8	116	0.8336	0.1790	0.8336	0.9130
No log	5.9	118	0.8888	0.1718	0.8888	0.9427
No log	6.0	120	0.8924	0.2356	0.8924	0.9446
No log	6.1	122	0.9365	0.1351	0.9365	0.9677
No log	6.2	124	0.9828	0.1366	0.9828	0.9913
No log	6.3	126	0.9029	0.1579	0.9029	0.9502
No log	6.4	128	0.8717	0.2667	0.8717	0.9337
No log	6.5	130	0.9413	0.1652	0.9413	0.9702
No log	6.6	132	0.9378	0.1652	0.9378	0.9684
No log	6.7	134	0.9622	0.1074	0.9622	0.9809
No log	6.8	136	0.8508	0.2320	0.8508	0.9224
No log	6.9	138	0.7572	0.3004	0.7572	0.8702
No log	7.0	140	0.7830	0.2775	0.7830	0.8849
No log	7.1	142	0.8961	0.1441	0.8961	0.9466
No log	7.2	144	0.8296	0.1652	0.8296	0.9108
No log	7.3	146	0.7366	0.3455	0.7366	0.8583
No log	7.4	148	0.7631	0.2857	0.7631	0.8736
No log	7.5	150	0.8675	0.2000	0.8675	0.9314
No log	7.6	152	0.8519	0.1660	0.8519	0.9230
No log	7.7	154	0.8879	0.1724	0.8879	0.9423
No log	7.8	156	0.8568	0.1724	0.8568	0.9256
No log	7.9	158	0.7572	0.25	0.7572	0.8702
No log	8.0	160	0.7602	0.2579	0.7602	0.8719
No log	8.1	162	0.8581	0.1724	0.8581	0.9263
No log	8.2	164	1.0201	0.1746	1.0201	1.0100
No log	8.3	166	1.0133	0.1486	1.0133	1.0066
No log	8.4	168	0.8941	0.1441	0.8941	0.9456
No log	8.5	170	0.8047	0.1724	0.8047	0.8971
No log	8.6	172	0.7371	0.3846	0.7371	0.8585
No log	8.7	174	0.7254	0.3846	0.7254	0.8517
No log	8.8	176	0.7372	0.3171	0.7372	0.8586
No log	8.9	178	0.7668	0.1781	0.7668	0.8757
No log	9.0	180	0.7728	0.1781	0.7728	0.8791
No log	9.1	182	0.7669	0.2000	0.7669	0.8757
No log	9.2	184	0.7452	0.2762	0.7452	0.8632
No log	9.3	186	0.7199	0.4286	0.7199	0.8485
No log	9.4	188	0.7207	0.4286	0.7207	0.8489
No log	9.5	190	0.7273	0.4286	0.7273	0.8528
No log	9.6	192	0.7400	0.3427	0.7400	0.8602
No log	9.7	194	0.7377	0.3427	0.7377	0.8589
No log	9.8	196	0.7423	0.3427	0.7423	0.8615
No log	9.9	198	0.7450	0.2372	0.7450	0.8631
No log	10.0	200	0.7451	0.2372	0.7451	0.8632

Framework versions

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