ArabicNewSplits4_WithDuplicationsForScore5_FineTuningAraBERT_run2_AugV5_k7_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: 0.5997
• Qwk: 0.3706
• Mse: 0.5997
• Rmse: 0.7744

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	0.0625	2	3.4620	-0.0066	3.4620	1.8606
No log	0.125	4	1.8841	-0.0101	1.8841	1.3726
No log	0.1875	6	1.4848	0.0255	1.4848	1.2185
No log	0.25	8	1.2536	0.0632	1.2536	1.1197
No log	0.3125	10	0.6960	0.0058	0.6960	0.8343
No log	0.375	12	0.7420	-0.0595	0.7420	0.8614
No log	0.4375	14	0.6481	0.0	0.6481	0.8050
No log	0.5	16	0.7361	-0.1429	0.7361	0.8580
No log	0.5625	18	0.8658	0.0609	0.8658	0.9305
No log	0.625	20	0.6212	0.0145	0.6212	0.7882
No log	0.6875	22	0.6185	0.0569	0.6185	0.7865
No log	0.75	24	0.7106	0.0	0.7106	0.8430
No log	0.8125	26	0.7430	0.0	0.7430	0.8620
No log	0.875	28	0.5899	0.0388	0.5899	0.7681
No log	0.9375	30	0.8958	0.1111	0.8958	0.9464
No log	1.0	32	1.1842	0.0977	1.1842	1.0882
No log	1.0625	34	0.8141	0.0476	0.8141	0.9023
No log	1.125	36	0.6261	0.0222	0.6261	0.7913
No log	1.1875	38	0.5969	0.0303	0.5969	0.7726
No log	1.25	40	0.5678	0.0569	0.5678	0.7535
No log	1.3125	42	0.5813	0.0476	0.5813	0.7624
No log	1.375	44	0.5959	0.0365	0.5959	0.7720
No log	1.4375	46	0.6171	0.0199	0.6171	0.7856
No log	1.5	48	0.7946	0.1456	0.7946	0.8914
No log	1.5625	50	0.7107	0.1917	0.7107	0.8430
No log	1.625	52	0.8208	0.1443	0.8208	0.9060
No log	1.6875	54	1.0163	0.1318	1.0163	1.0081
No log	1.75	56	0.6687	0.1910	0.6687	0.8178
No log	1.8125	58	1.7561	0.0435	1.7561	1.3252
No log	1.875	60	2.4596	0.0606	2.4596	1.5683
No log	1.9375	62	1.7324	0.0404	1.7324	1.3162
No log	2.0	64	0.7525	0.1619	0.7525	0.8674
No log	2.0625	66	0.5613	0.2644	0.5613	0.7492
No log	2.125	68	0.6354	0.1364	0.6354	0.7971
No log	2.1875	70	0.5651	0.3548	0.5651	0.7517
No log	2.25	72	0.5880	0.2707	0.5880	0.7668
No log	2.3125	74	0.7195	0.1304	0.7195	0.8482
No log	2.375	76	0.7730	0.2072	0.7730	0.8792
No log	2.4375	78	0.7711	0.2793	0.7711	0.8781
No log	2.5	80	1.2529	0.1399	1.2529	1.1193
No log	2.5625	82	1.0086	0.2062	1.0086	1.0043
No log	2.625	84	0.8052	0.2542	0.8052	0.8973
No log	2.6875	86	0.7443	0.1610	0.7443	0.8627
No log	2.75	88	0.6711	0.2513	0.6711	0.8192
No log	2.8125	90	0.6815	0.3237	0.6815	0.8255
No log	2.875	92	1.0606	0.1777	1.0606	1.0299
No log	2.9375	94	0.8255	0.2327	0.8255	0.9086
No log	3.0	96	0.6480	0.4404	0.6480	0.8050
No log	3.0625	98	0.6098	0.3161	0.6098	0.7809
No log	3.125	100	0.6272	0.3258	0.6272	0.7919
No log	3.1875	102	0.6735	0.3398	0.6735	0.8207
No log	3.25	104	0.6921	0.3365	0.6921	0.8319
No log	3.3125	106	0.8168	0.2126	0.8168	0.9037
No log	3.375	108	0.7756	0.3016	0.7756	0.8807
No log	3.4375	110	0.8457	0.2558	0.8457	0.9196
No log	3.5	112	0.9226	0.3114	0.9226	0.9605
No log	3.5625	114	0.7673	0.3722	0.7673	0.8760
No log	3.625	116	0.8138	0.2681	0.8138	0.9021
No log	3.6875	118	0.8882	0.2199	0.8882	0.9425
No log	3.75	120	0.7122	0.3818	0.7122	0.8439
No log	3.8125	122	0.6586	0.3892	0.6586	0.8116
No log	3.875	124	0.6792	0.2965	0.6792	0.8242
No log	3.9375	126	0.6590	0.3498	0.6590	0.8118
No log	4.0	128	0.7028	0.2621	0.7028	0.8384
No log	4.0625	130	0.6505	0.3267	0.6505	0.8065
No log	4.125	132	0.6289	0.2653	0.6289	0.7930
No log	4.1875	134	0.6367	0.3398	0.6367	0.7979
No log	4.25	136	0.9549	0.2060	0.9549	0.9772
No log	4.3125	138	0.7974	0.3422	0.7974	0.8929
No log	4.375	140	0.5904	0.4	0.5904	0.7684
No log	4.4375	142	0.6038	0.3061	0.6038	0.7771
No log	4.5	144	0.7556	0.3422	0.7556	0.8693
No log	4.5625	146	0.7169	0.3722	0.7169	0.8467
No log	4.625	148	0.5845	0.3769	0.5845	0.7645
No log	4.6875	150	0.6077	0.2990	0.6077	0.7796
No log	4.75	152	0.5609	0.4400	0.5609	0.7490
No log	4.8125	154	0.8169	0.3362	0.8169	0.9038
No log	4.875	156	0.8180	0.3633	0.8180	0.9044
No log	4.9375	158	0.5740	0.4346	0.5740	0.7576
No log	5.0	160	0.6008	0.2965	0.6008	0.7751
No log	5.0625	162	0.7114	0.3091	0.7114	0.8435
No log	5.125	164	0.5819	0.3267	0.5819	0.7628
No log	5.1875	166	0.5582	0.3862	0.5582	0.7472
No log	5.25	168	0.6242	0.3645	0.6242	0.7901
No log	5.3125	170	0.6837	0.3704	0.6837	0.8269
No log	5.375	172	0.6743	0.3365	0.6743	0.8212
No log	5.4375	174	0.6823	0.3365	0.6823	0.8260
No log	5.5	176	0.8697	0.2741	0.8697	0.9326
No log	5.5625	178	1.1383	0.1742	1.1383	1.0669
No log	5.625	180	0.9596	0.2768	0.9596	0.9796
No log	5.6875	182	0.7101	0.3301	0.7101	0.8426
No log	5.75	184	0.6751	0.3208	0.6751	0.8216
No log	5.8125	186	0.7056	0.3398	0.7056	0.8400
No log	5.875	188	0.7138	0.3303	0.7138	0.8448
No log	5.9375	190	0.6863	0.3427	0.6863	0.8284
No log	6.0	192	0.5857	0.4167	0.5857	0.7653
No log	6.0625	194	0.5784	0.3617	0.5784	0.7605
No log	6.125	196	0.5846	0.3862	0.5846	0.7646
No log	6.1875	198	0.6902	0.3524	0.6902	0.8308
No log	6.25	200	0.6464	0.3462	0.6464	0.8040
No log	6.3125	202	0.6020	0.3878	0.6020	0.7759
No log	6.375	204	0.7070	0.3274	0.7070	0.8409
No log	6.4375	206	0.7262	0.3274	0.7262	0.8522
No log	6.5	208	0.6196	0.3469	0.6196	0.7872
No log	6.5625	210	0.6074	0.3365	0.6074	0.7793
No log	6.625	212	0.6065	0.3704	0.6065	0.7788
No log	6.6875	214	0.6451	0.3684	0.6451	0.8032
No log	6.75	216	0.7708	0.2829	0.7708	0.8779
No log	6.8125	218	0.7706	0.3030	0.7706	0.8778
No log	6.875	220	0.6854	0.3365	0.6854	0.8279
No log	6.9375	222	0.6476	0.3524	0.6476	0.8047
No log	7.0	224	0.6663	0.3271	0.6663	0.8162
No log	7.0625	226	0.7281	0.2208	0.7281	0.8533
No log	7.125	228	0.6680	0.3365	0.6680	0.8173
No log	7.1875	230	0.6043	0.3402	0.6043	0.7774
No log	7.25	232	0.5799	0.3878	0.5799	0.7615
No log	7.3125	234	0.5796	0.3878	0.5796	0.7613
No log	7.375	236	0.6409	0.3433	0.6409	0.8006
No log	7.4375	238	0.7083	0.3028	0.7083	0.8416
No log	7.5	240	0.7747	0.2960	0.7747	0.8801
No log	7.5625	242	0.7826	0.2941	0.7826	0.8846
No log	7.625	244	0.6779	0.3427	0.6779	0.8233
No log	7.6875	246	0.6024	0.3706	0.6024	0.7761
No log	7.75	248	0.5832	0.3978	0.5832	0.7637
No log	7.8125	250	0.5862	0.3978	0.5862	0.7656
No log	7.875	252	0.5859	0.3978	0.5859	0.7655
No log	7.9375	254	0.5759	0.3535	0.5759	0.7589
No log	8.0	256	0.5838	0.3706	0.5838	0.7641
No log	8.0625	258	0.6292	0.3469	0.6292	0.7932
No log	8.125	260	0.6632	0.3704	0.6632	0.8143
No log	8.1875	262	0.7240	0.3333	0.7240	0.8509
No log	8.25	264	0.7062	0.2920	0.7062	0.8404
No log	8.3125	266	0.6478	0.3398	0.6478	0.8048
No log	8.375	268	0.6230	0.3725	0.6230	0.7893
No log	8.4375	270	0.6106	0.36	0.6106	0.7814
No log	8.5	272	0.6156	0.36	0.6156	0.7846
No log	8.5625	274	0.6331	0.3725	0.6331	0.7957
No log	8.625	276	0.6701	0.3365	0.6701	0.8186
No log	8.6875	278	0.6604	0.3645	0.6604	0.8126
No log	8.75	280	0.6276	0.3769	0.6276	0.7922
No log	8.8125	282	0.6141	0.36	0.6141	0.7836
No log	8.875	284	0.6114	0.3398	0.6114	0.7819
No log	8.9375	286	0.6116	0.3398	0.6116	0.7820
No log	9.0	288	0.6184	0.36	0.6184	0.7864
No log	9.0625	290	0.6408	0.3725	0.6408	0.8005
No log	9.125	292	0.6520	0.3684	0.6520	0.8074
No log	9.1875	294	0.6565	0.3645	0.6565	0.8102
No log	9.25	296	0.6437	0.3684	0.6437	0.8023
No log	9.3125	298	0.6287	0.3769	0.6287	0.7929
No log	9.375	300	0.6102	0.3706	0.6102	0.7811
No log	9.4375	302	0.6010	0.3706	0.6010	0.7752
No log	9.5	304	0.6013	0.3706	0.6013	0.7754
No log	9.5625	306	0.5999	0.3706	0.5999	0.7745
No log	9.625	308	0.6014	0.3706	0.6014	0.7755
No log	9.6875	310	0.6018	0.3706	0.6018	0.7758
No log	9.75	312	0.6006	0.3706	0.6006	0.7750
No log	9.8125	314	0.5996	0.3706	0.5996	0.7743
No log	9.875	316	0.5995	0.3706	0.5995	0.7743
No log	9.9375	318	0.5996	0.3706	0.5996	0.7743
No log	10.0	320	0.5997	0.3706	0.5997	0.7744

Framework versions

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