ArabicNewSplits6_WithDuplicationsForScore5_FineTuningAraBERT_run1_AugV5_k4_task1_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: 0.8864
• Qwk: 0.6749
• Mse: 0.8864
• Rmse: 0.9415

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	0.0769	2	5.3256	-0.0152	5.3256	2.3077
No log	0.1538	4	3.7031	0.0524	3.7031	1.9243
No log	0.2308	6	2.0420	0.1920	2.0420	1.4290
No log	0.3077	8	1.4072	0.0539	1.4072	1.1863
No log	0.3846	10	1.8217	-0.1087	1.8217	1.3497
No log	0.4615	12	1.5132	-0.0228	1.5132	1.2301
No log	0.5385	14	1.4137	0.0437	1.4137	1.1890
No log	0.6154	16	1.4096	0.0945	1.4096	1.1873
No log	0.6923	18	1.2999	0.0782	1.2999	1.1401
No log	0.7692	20	1.2532	0.1527	1.2532	1.1195
No log	0.8462	22	1.2446	0.1770	1.2446	1.1156
No log	0.9231	24	1.2400	0.2146	1.2400	1.1136
No log	1.0	26	1.2788	0.1811	1.2788	1.1309
No log	1.0769	28	1.2797	0.1206	1.2797	1.1312
No log	1.1538	30	1.1555	0.3164	1.1555	1.0750
No log	1.2308	32	1.0719	0.3399	1.0719	1.0353
No log	1.3077	34	1.0651	0.3603	1.0651	1.0321
No log	1.3846	36	1.1738	0.2638	1.1738	1.0834
No log	1.4615	38	1.2611	0.1855	1.2611	1.1230
No log	1.5385	40	1.1684	0.2765	1.1684	1.0809
No log	1.6154	42	1.0673	0.3942	1.0673	1.0331
No log	1.6923	44	1.0046	0.3966	1.0046	1.0023
No log	1.7692	46	0.9375	0.4411	0.9375	0.9682
No log	1.8462	48	0.8624	0.4742	0.8624	0.9287
No log	1.9231	50	0.8131	0.4912	0.8131	0.9017
No log	2.0	52	0.7808	0.5147	0.7808	0.8836
No log	2.0769	54	0.7338	0.5562	0.7338	0.8566
No log	2.1538	56	0.7091	0.5562	0.7091	0.8421
No log	2.2308	58	0.7541	0.5265	0.7541	0.8684
No log	2.3077	60	0.8186	0.5244	0.8186	0.9048
No log	2.3846	62	0.8460	0.5571	0.8460	0.9198
No log	2.4615	64	0.7494	0.5931	0.7494	0.8657
No log	2.5385	66	0.6926	0.6295	0.6926	0.8322
No log	2.6154	68	0.6524	0.6304	0.6524	0.8077
No log	2.6923	70	0.6364	0.6312	0.6364	0.7977
No log	2.7692	72	0.6472	0.6293	0.6472	0.8045
No log	2.8462	74	0.6508	0.6602	0.6508	0.8067
No log	2.9231	76	0.7551	0.6129	0.7551	0.8689
No log	3.0	78	0.8104	0.6240	0.8104	0.9002
No log	3.0769	80	0.7775	0.6358	0.7775	0.8818
No log	3.1538	82	0.6973	0.6952	0.6973	0.8350
No log	3.2308	84	0.6891	0.6793	0.6891	0.8301
No log	3.3077	86	0.7850	0.6216	0.7850	0.8860
No log	3.3846	88	0.8072	0.6470	0.8072	0.8984
No log	3.4615	90	0.8024	0.6527	0.8024	0.8957
No log	3.5385	92	0.7266	0.6679	0.7266	0.8524
No log	3.6154	94	0.7241	0.6698	0.7241	0.8510
No log	3.6923	96	0.7923	0.6773	0.7923	0.8901
No log	3.7692	98	0.8340	0.6681	0.8340	0.9132
No log	3.8462	100	0.8589	0.6546	0.8589	0.9268
No log	3.9231	102	0.7610	0.6993	0.7610	0.8723
No log	4.0	104	0.6438	0.7129	0.6438	0.8024
No log	4.0769	106	0.6209	0.7121	0.6209	0.7879
No log	4.1538	108	0.6357	0.6875	0.6357	0.7973
No log	4.2308	110	0.6444	0.6919	0.6444	0.8027
No log	4.3077	112	0.6409	0.6685	0.6409	0.8006
No log	4.3846	114	0.6604	0.6671	0.6604	0.8126
No log	4.4615	116	0.6956	0.6796	0.6956	0.8340
No log	4.5385	118	0.6810	0.6881	0.6810	0.8252
No log	4.6154	120	0.7213	0.6974	0.7213	0.8493
No log	4.6923	122	0.8382	0.6985	0.8382	0.9155
No log	4.7692	124	1.0832	0.6494	1.0832	1.0408
No log	4.8462	126	1.2266	0.6074	1.2266	1.1075
No log	4.9231	128	1.2247	0.6074	1.2247	1.1066
No log	5.0	130	1.1060	0.6339	1.1060	1.0517
No log	5.0769	132	0.8971	0.6910	0.8971	0.9472
No log	5.1538	134	0.8147	0.7056	0.8147	0.9026
No log	5.2308	136	0.8458	0.7020	0.8458	0.9197
No log	5.3077	138	0.8407	0.7030	0.8407	0.9169
No log	5.3846	140	0.8139	0.6934	0.8139	0.9022
No log	5.4615	142	0.7979	0.6832	0.7979	0.8933
No log	5.5385	144	0.7375	0.6852	0.7375	0.8588
No log	5.6154	146	0.6791	0.7130	0.6791	0.8241
No log	5.6923	148	0.6658	0.7145	0.6658	0.8160
No log	5.7692	150	0.6941	0.6835	0.6941	0.8331
No log	5.8462	152	0.7692	0.6545	0.7692	0.8771
No log	5.9231	154	0.8915	0.6487	0.8915	0.9442
No log	6.0	156	1.0503	0.5969	1.0503	1.0249
No log	6.0769	158	1.0742	0.6058	1.0742	1.0364
No log	6.1538	160	0.9756	0.6217	0.9756	0.9877
No log	6.2308	162	0.8025	0.6560	0.8025	0.8958
No log	6.3077	164	0.7230	0.6924	0.7230	0.8503
No log	6.3846	166	0.7357	0.7009	0.7357	0.8577
No log	6.4615	168	0.8122	0.6763	0.8122	0.9012
No log	6.5385	170	0.9291	0.6332	0.9291	0.9639
No log	6.6154	172	1.0103	0.6255	1.0103	1.0052
No log	6.6923	174	1.0561	0.6171	1.0561	1.0277
No log	6.7692	176	0.9870	0.6170	0.9870	0.9935
No log	6.8462	178	0.8768	0.6159	0.8768	0.9364
No log	6.9231	180	0.7808	0.7000	0.7808	0.8836
No log	7.0	182	0.7328	0.7261	0.7328	0.8560
No log	7.0769	184	0.7396	0.7197	0.7396	0.8600
No log	7.1538	186	0.7475	0.7256	0.7475	0.8646
No log	7.2308	188	0.7906	0.7039	0.7906	0.8892
No log	7.3077	190	0.8951	0.6567	0.8951	0.9461
No log	7.3846	192	0.9755	0.6345	0.9755	0.9877
No log	7.4615	194	0.9786	0.6332	0.9786	0.9892
No log	7.5385	196	0.9737	0.6332	0.9737	0.9868
No log	7.6154	198	0.9171	0.6569	0.9171	0.9576
No log	7.6923	200	0.8856	0.6645	0.8856	0.9411
No log	7.7692	202	0.8401	0.6887	0.8401	0.9166
No log	7.8462	204	0.8233	0.6842	0.8233	0.9074
No log	7.9231	206	0.8264	0.6785	0.8264	0.9091
No log	8.0	208	0.8382	0.6954	0.8382	0.9155
No log	8.0769	210	0.8251	0.6865	0.8251	0.9083
No log	8.1538	212	0.7906	0.7013	0.7906	0.8891
No log	8.2308	214	0.7784	0.7049	0.7784	0.8823
No log	8.3077	216	0.7734	0.7240	0.7734	0.8794
No log	8.3846	218	0.7817	0.7217	0.7817	0.8842
No log	8.4615	220	0.7881	0.7102	0.7881	0.8877
No log	8.5385	222	0.8128	0.7015	0.8128	0.9016
No log	8.6154	224	0.8447	0.6740	0.8447	0.9191
No log	8.6923	226	0.8647	0.6636	0.8647	0.9299
No log	8.7692	228	0.8707	0.6477	0.8707	0.9331
No log	8.8462	230	0.8582	0.6491	0.8582	0.9264
No log	8.9231	232	0.8498	0.6780	0.8498	0.9218
No log	9.0	234	0.8575	0.6780	0.8575	0.9260
No log	9.0769	236	0.8663	0.6836	0.8663	0.9307
No log	9.1538	238	0.8750	0.6836	0.8750	0.9354
No log	9.2308	240	0.8826	0.6892	0.8826	0.9395
No log	9.3077	242	0.9022	0.6591	0.9022	0.9498
No log	9.3846	244	0.9101	0.6553	0.9101	0.9540
No log	9.4615	246	0.9151	0.6553	0.9151	0.9566
No log	9.5385	248	0.9156	0.6553	0.9156	0.9569
No log	9.6154	250	0.9121	0.6710	0.9121	0.9550
No log	9.6923	252	0.9065	0.6710	0.9065	0.9521
No log	9.7692	254	0.8998	0.6710	0.8998	0.9486
No log	9.8462	256	0.8927	0.6749	0.8927	0.9448
No log	9.9231	258	0.8877	0.6749	0.8877	0.9422
No log	10.0	260	0.8864	0.6749	0.8864	0.9415

Framework versions

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