ArabicNewSplits6_WithDuplicationsForScore5_FineTuningAraBERT_run2_AugV5_k3_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: 0.6692
• Qwk: 0.2251
• Mse: 0.6692
• Rmse: 0.8180

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	0.1176	2	3.3749	-0.0267	3.3749	1.8371
No log	0.2353	4	1.7633	-0.0101	1.7633	1.3279
No log	0.3529	6	1.2460	0.0588	1.2460	1.1162
No log	0.4706	8	0.7977	0.1845	0.7977	0.8932
No log	0.5882	10	0.6418	0.0909	0.6418	0.8011
No log	0.7059	12	0.7788	0.1373	0.7788	0.8825
No log	0.8235	14	0.7636	0.0703	0.7636	0.8738
No log	0.9412	16	1.8554	0.0336	1.8554	1.3621
No log	1.0588	18	1.1996	0.0078	1.1996	1.0953
No log	1.1765	20	0.6004	0.0815	0.6004	0.7749
No log	1.2941	22	0.6924	0.2000	0.6924	0.8321
No log	1.4118	24	0.7431	0.2000	0.7431	0.8620
No log	1.5294	26	0.6014	0.1467	0.6014	0.7755
No log	1.6471	28	0.7044	0.0476	0.7044	0.8393
No log	1.7647	30	1.7345	-0.0034	1.7345	1.3170
No log	1.8824	32	2.0407	-0.0414	2.0407	1.4285
No log	2.0	34	1.3234	0.0431	1.3234	1.1504
No log	2.1176	36	0.6915	0.1186	0.6915	0.8316
No log	2.2353	38	0.5753	-0.0233	0.5753	0.7585
No log	2.3529	40	0.5900	0.1385	0.5900	0.7681
No log	2.4706	42	0.6059	0.1385	0.6059	0.7784
No log	2.5882	44	0.5930	0.0365	0.5930	0.7701
No log	2.7059	46	0.6104	0.0365	0.6104	0.7813
No log	2.8235	48	0.6361	0.1467	0.6361	0.7976
No log	2.9412	50	0.6796	0.1020	0.6796	0.8244
No log	3.0588	52	0.6766	0.0545	0.6766	0.8225
No log	3.1765	54	0.7825	0.0576	0.7825	0.8846
No log	3.2941	56	0.8351	0.1588	0.8351	0.9139
No log	3.4118	58	0.7179	0.2090	0.7179	0.8473
No log	3.5294	60	1.0099	0.0551	1.0099	1.0049
No log	3.6471	62	0.8349	0.1441	0.8349	0.9137
No log	3.7647	64	0.7394	0.2489	0.7394	0.8599
No log	3.8824	66	1.0672	0.1939	1.0672	1.0330
No log	4.0	68	0.8981	0.1673	0.8981	0.9477
No log	4.1176	70	0.6428	0.3846	0.6428	0.8018
No log	4.2353	72	0.6838	0.2850	0.6838	0.8269
No log	4.3529	74	0.8071	0.1453	0.8071	0.8984
No log	4.4706	76	0.6987	0.2165	0.6987	0.8359
No log	4.5882	78	0.6414	0.2093	0.6414	0.8009
No log	4.7059	80	0.6850	0.2265	0.6850	0.8276
No log	4.8235	82	0.6472	0.2626	0.6472	0.8045
No log	4.9412	84	0.6970	0.3398	0.6970	0.8349
No log	5.0588	86	0.7417	0.2566	0.7417	0.8612
No log	5.1765	88	0.7183	0.3363	0.7183	0.8475
No log	5.2941	90	0.7535	0.2579	0.7535	0.8680
No log	5.4118	92	0.8090	0.2150	0.8090	0.8995
No log	5.5294	94	0.7951	0.1538	0.7951	0.8917
No log	5.6471	96	0.7643	0.1828	0.7643	0.8742
No log	5.7647	98	0.7676	0.25	0.7676	0.8761
No log	5.8824	100	0.7245	0.1739	0.7245	0.8512
No log	6.0	102	0.9006	0.2000	0.9006	0.9490
No log	6.1176	104	1.0228	0.1673	1.0228	1.0113
No log	6.2353	106	0.8147	0.2390	0.8147	0.9026
No log	6.3529	108	0.6758	0.1345	0.6758	0.8221
No log	6.4706	110	0.7201	0.1135	0.7201	0.8486
No log	6.5882	112	0.7068	0.1910	0.7068	0.8407
No log	6.7059	114	0.6917	0.2169	0.6917	0.8317
No log	6.8235	116	0.8028	0.2536	0.8028	0.8960
No log	6.9412	118	1.1432	0.1389	1.1432	1.0692
No log	7.0588	120	1.1286	0.1628	1.1286	1.0624
No log	7.1765	122	0.8384	0.2423	0.8384	0.9157
No log	7.2941	124	0.7347	0.2579	0.7347	0.8571
No log	7.4118	126	0.7663	0.2469	0.7663	0.8754
No log	7.5294	128	0.7381	0.2542	0.7381	0.8591
No log	7.6471	130	0.7083	0.3010	0.7083	0.8416
No log	7.7647	132	0.7936	0.2069	0.7936	0.8908
No log	7.8824	134	0.8091	0.2140	0.8091	0.8995
No log	8.0	136	0.7442	0.3498	0.7442	0.8627
No log	8.1176	138	0.6992	0.2161	0.6992	0.8362
No log	8.2353	140	0.7585	0.2727	0.7585	0.8709
No log	8.3529	142	0.7770	0.2667	0.7770	0.8815
No log	8.4706	144	0.7265	0.2432	0.7265	0.8524
No log	8.5882	146	0.6915	0.2165	0.6915	0.8315
No log	8.7059	148	0.7126	0.3200	0.7126	0.8442
No log	8.8235	150	0.7572	0.2746	0.7572	0.8702
No log	8.9412	152	0.7768	0.2323	0.7768	0.8813
No log	9.0588	154	0.7761	0.2323	0.7761	0.8810
No log	9.1765	156	0.7583	0.2637	0.7583	0.8708
No log	9.2941	158	0.7289	0.2670	0.7289	0.8538
No log	9.4118	160	0.6977	0.2688	0.6977	0.8353
No log	9.5294	162	0.6837	0.1568	0.6837	0.8269
No log	9.6471	164	0.6744	0.1915	0.6744	0.8212
No log	9.7647	166	0.6714	0.2251	0.6714	0.8194
No log	9.8824	168	0.6700	0.2251	0.6700	0.8185
No log	10.0	170	0.6692	0.2251	0.6692	0.8180

Framework versions

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