ArabicNewSplits5_FineTuningAraBERT_run3_AugV5_k5_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: 0.7102
• Qwk: 0.7097
• Mse: 0.7102
• Rmse: 0.8427

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	0.0588	2	5.1822	-0.0251	5.1822	2.2764
No log	0.1176	4	3.1591	0.0524	3.1591	1.7774
No log	0.1765	6	2.0759	0.0695	2.0759	1.4408
No log	0.2353	8	1.8010	0.1199	1.8010	1.3420
No log	0.2941	10	1.7486	0.1250	1.7486	1.3223
No log	0.3529	12	1.7730	0.1175	1.7730	1.3315
No log	0.4118	14	1.8075	0.1225	1.8075	1.3444
No log	0.4706	16	1.6255	0.1578	1.6255	1.2749
No log	0.5294	18	2.2048	0.1696	2.2048	1.4849
No log	0.5882	20	3.0429	0.0862	3.0429	1.7444
No log	0.6471	22	3.2549	0.0563	3.2549	1.8041
No log	0.7059	24	2.6552	0.1544	2.6552	1.6295
No log	0.7647	26	1.6848	0.3401	1.6848	1.2980
No log	0.8235	28	1.4255	0.3771	1.4255	1.1940
No log	0.8824	30	1.4641	0.3947	1.4641	1.2100
No log	0.9412	32	1.3568	0.3967	1.3568	1.1648
No log	1.0	34	1.4360	0.4346	1.4360	1.1983
No log	1.0588	36	1.3649	0.4369	1.3649	1.1683
No log	1.1176	38	1.0667	0.5305	1.0667	1.0328
No log	1.1765	40	0.9976	0.5557	0.9976	0.9988
No log	1.2353	42	1.1933	0.4811	1.1933	1.0924
No log	1.2941	44	1.1406	0.5382	1.1406	1.0680
No log	1.3529	46	1.1043	0.5514	1.1043	1.0509
No log	1.4118	48	1.1315	0.5662	1.1315	1.0637
No log	1.4706	50	1.1321	0.5490	1.1321	1.0640
No log	1.5294	52	1.3522	0.4373	1.3522	1.1629
No log	1.5882	54	1.3685	0.4791	1.3685	1.1698
No log	1.6471	56	1.5389	0.4401	1.5389	1.2405
No log	1.7059	58	1.4686	0.4579	1.4686	1.2118
No log	1.7647	60	1.0390	0.5714	1.0390	1.0193
No log	1.8235	62	0.7499	0.6575	0.7499	0.8660
No log	1.8824	64	0.6767	0.6838	0.6767	0.8226
No log	1.9412	66	0.7356	0.6566	0.7356	0.8577
No log	2.0	68	1.0686	0.5712	1.0686	1.0337
No log	2.0588	70	1.6078	0.4160	1.6078	1.2680
No log	2.1176	72	1.6984	0.3688	1.6984	1.3032
No log	2.1765	74	1.4138	0.5003	1.4138	1.1890
No log	2.2353	76	0.9886	0.6286	0.9886	0.9943
No log	2.2941	78	0.7441	0.6865	0.7441	0.8626
No log	2.3529	80	0.6918	0.6987	0.6918	0.8318
No log	2.4118	82	0.7043	0.6770	0.7043	0.8392
No log	2.4706	84	0.7191	0.6828	0.7191	0.8480
No log	2.5294	86	0.8365	0.6796	0.8365	0.9146
No log	2.5882	88	0.8275	0.6785	0.8275	0.9097
No log	2.6471	90	0.7850	0.6799	0.7850	0.8860
No log	2.7059	92	0.6591	0.7294	0.6591	0.8119
No log	2.7647	94	0.6236	0.7195	0.6236	0.7897
No log	2.8235	96	0.6442	0.7300	0.6442	0.8026
No log	2.8824	98	0.7117	0.6799	0.7117	0.8436
No log	2.9412	100	0.8596	0.6696	0.8596	0.9272
No log	3.0	102	0.8714	0.6732	0.8714	0.9335
No log	3.0588	104	0.8954	0.6643	0.8954	0.9462
No log	3.1176	106	0.7460	0.6962	0.7460	0.8637
No log	3.1765	108	0.6993	0.7137	0.6993	0.8362
No log	3.2353	110	0.6623	0.7036	0.6623	0.8138
No log	3.2941	112	0.6507	0.7184	0.6507	0.8067
No log	3.3529	114	0.6654	0.7227	0.6654	0.8157
No log	3.4118	116	0.7884	0.6598	0.7884	0.8879
No log	3.4706	118	0.8385	0.6487	0.8385	0.9157
No log	3.5294	120	0.7171	0.7154	0.7171	0.8468
No log	3.5882	122	0.6843	0.7324	0.6843	0.8272
No log	3.6471	124	0.7357	0.7066	0.7357	0.8577
No log	3.7059	126	0.7076	0.7254	0.7076	0.8412
No log	3.7647	128	0.7244	0.7014	0.7244	0.8511
No log	3.8235	130	0.7728	0.6947	0.7728	0.8791
No log	3.8824	132	0.8038	0.6795	0.8038	0.8966
No log	3.9412	134	0.7385	0.6964	0.7385	0.8594
No log	4.0	136	0.6743	0.7357	0.6743	0.8212
No log	4.0588	138	0.6827	0.7234	0.6827	0.8263
No log	4.1176	140	0.7600	0.6715	0.7600	0.8718
No log	4.1765	142	0.7378	0.6919	0.7378	0.8590
No log	4.2353	144	0.6914	0.7180	0.6914	0.8315
No log	4.2941	146	0.6533	0.7272	0.6533	0.8083
No log	4.3529	148	0.6683	0.7214	0.6683	0.8175
No log	4.4118	150	0.6596	0.7229	0.6596	0.8122
No log	4.4706	152	0.6848	0.7250	0.6848	0.8275
No log	4.5294	154	0.6861	0.7222	0.6861	0.8283
No log	4.5882	156	0.6850	0.7352	0.6850	0.8276
No log	4.6471	158	0.7019	0.7101	0.7019	0.8378
No log	4.7059	160	0.6992	0.7111	0.6992	0.8362
No log	4.7647	162	0.6874	0.7205	0.6874	0.8291
No log	4.8235	164	0.6903	0.7326	0.6903	0.8309
No log	4.8824	166	0.6933	0.7193	0.6933	0.8327
No log	4.9412	168	0.7114	0.6842	0.7114	0.8434
No log	5.0	170	0.7167	0.6779	0.7167	0.8466
No log	5.0588	172	0.7072	0.6663	0.7072	0.8410
No log	5.1176	174	0.6851	0.7158	0.6851	0.8277
No log	5.1765	176	0.6878	0.7118	0.6878	0.8294
No log	5.2353	178	0.6981	0.7069	0.6981	0.8355
No log	5.2941	180	0.7111	0.7170	0.7111	0.8433
No log	5.3529	182	0.7345	0.7168	0.7345	0.8571
No log	5.4118	184	0.7246	0.7273	0.7246	0.8512
No log	5.4706	186	0.7279	0.7215	0.7279	0.8532
No log	5.5294	188	0.7421	0.7017	0.7421	0.8614
No log	5.5882	190	0.7271	0.7195	0.7271	0.8527
No log	5.6471	192	0.7396	0.7097	0.7396	0.8600
No log	5.7059	194	0.7566	0.6784	0.7566	0.8698
No log	5.7647	196	0.7326	0.7041	0.7326	0.8559
No log	5.8235	198	0.7218	0.7020	0.7218	0.8496
No log	5.8824	200	0.7367	0.7093	0.7367	0.8583
No log	5.9412	202	0.8015	0.6576	0.8015	0.8953
No log	6.0	204	0.8355	0.6381	0.8355	0.9140
No log	6.0588	206	0.7892	0.6641	0.7892	0.8884
No log	6.1176	208	0.7340	0.7028	0.7340	0.8568
No log	6.1765	210	0.7135	0.7072	0.7135	0.8447
No log	6.2353	212	0.7119	0.6923	0.7119	0.8437
No log	6.2941	214	0.7149	0.7109	0.7149	0.8455
No log	6.3529	216	0.7576	0.6533	0.7576	0.8704
No log	6.4118	218	0.8698	0.6312	0.8698	0.9326
No log	6.4706	220	0.9664	0.6210	0.9664	0.9830
No log	6.5294	222	0.9070	0.6160	0.9070	0.9524
No log	6.5882	224	0.7883	0.6540	0.7883	0.8879
No log	6.6471	226	0.7197	0.7024	0.7197	0.8483
No log	6.7059	228	0.7400	0.7145	0.7400	0.8602
No log	6.7647	230	0.7653	0.7209	0.7653	0.8748
No log	6.8235	232	0.7330	0.7187	0.7330	0.8562
No log	6.8824	234	0.6963	0.6915	0.6963	0.8344
No log	6.9412	236	0.7030	0.7117	0.7030	0.8385
No log	7.0	238	0.7267	0.7168	0.7267	0.8525
No log	7.0588	240	0.7443	0.6997	0.7443	0.8627
No log	7.1176	242	0.7277	0.7034	0.7277	0.8530
No log	7.1765	244	0.6878	0.7125	0.6878	0.8293
No log	7.2353	246	0.6665	0.7345	0.6665	0.8164
No log	7.2941	248	0.6778	0.6876	0.6778	0.8233
No log	7.3529	250	0.6814	0.7002	0.6814	0.8255
No log	7.4118	252	0.6717	0.6960	0.6717	0.8196
No log	7.4706	254	0.6668	0.7300	0.6668	0.8166
No log	7.5294	256	0.6726	0.7424	0.6726	0.8201
No log	7.5882	258	0.6781	0.7185	0.6781	0.8235
No log	7.6471	260	0.6837	0.6972	0.6837	0.8269
No log	7.7059	262	0.6801	0.7114	0.6801	0.8247
No log	7.7647	264	0.6643	0.7227	0.6643	0.8151
No log	7.8235	266	0.6604	0.7071	0.6604	0.8127
No log	7.8824	268	0.6615	0.7151	0.6615	0.8133
No log	7.9412	270	0.6601	0.7026	0.6601	0.8125
No log	8.0	272	0.6595	0.7026	0.6595	0.8121
No log	8.0588	274	0.6610	0.7026	0.6610	0.8130
No log	8.1176	276	0.6611	0.7244	0.6611	0.8131
No log	8.1765	278	0.6633	0.7357	0.6633	0.8144
No log	8.2353	280	0.6650	0.7206	0.6650	0.8155
No log	8.2941	282	0.6703	0.7185	0.6703	0.8187
No log	8.3529	284	0.6762	0.7257	0.6762	0.8223
No log	8.4118	286	0.6807	0.7127	0.6807	0.8251
No log	8.4706	288	0.6872	0.7070	0.6872	0.8290
No log	8.5294	290	0.6927	0.7080	0.6927	0.8323
No log	8.5882	292	0.6946	0.7037	0.6946	0.8334
No log	8.6471	294	0.6956	0.7037	0.6956	0.8340
No log	8.7059	296	0.6979	0.7007	0.6979	0.8354
No log	8.7647	298	0.6958	0.7037	0.6958	0.8342
No log	8.8235	300	0.6963	0.7080	0.6963	0.8344
No log	8.8824	302	0.6950	0.6825	0.6950	0.8337
No log	8.9412	304	0.6950	0.7012	0.6950	0.8337
No log	9.0	306	0.6967	0.7012	0.6967	0.8347
No log	9.0588	308	0.7011	0.6814	0.7011	0.8373
No log	9.1176	310	0.7078	0.6957	0.7078	0.8413
No log	9.1765	312	0.7163	0.7157	0.7163	0.8463
No log	9.2353	314	0.7177	0.7157	0.7177	0.8472
No log	9.2941	316	0.7159	0.7157	0.7159	0.8461
No log	9.3529	318	0.7146	0.7097	0.7146	0.8454
No log	9.4118	320	0.7120	0.7097	0.7120	0.8438
No log	9.4706	322	0.7128	0.7097	0.7128	0.8443
No log	9.5294	324	0.7129	0.7097	0.7129	0.8443
No log	9.5882	326	0.7128	0.7097	0.7128	0.8443
No log	9.6471	328	0.7118	0.7097	0.7118	0.8437
No log	9.7059	330	0.7111	0.7097	0.7111	0.8433
No log	9.7647	332	0.7118	0.7097	0.7118	0.8437
No log	9.8235	334	0.7116	0.7097	0.7116	0.8436
No log	9.8824	336	0.7111	0.7097	0.7111	0.8433
No log	9.9412	338	0.7106	0.7097	0.7106	0.8430
No log	10.0	340	0.7102	0.7097	0.7102	0.8427

Framework versions

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