ArabicNewSplits6_FineTuningAraBERT_run3_AugV5_k6_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: 0.8738
• Qwk: 0.6149
• Mse: 0.8738
• Rmse: 0.9348

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	0.0606	2	5.0683	-0.0452	5.0683	2.2513
No log	0.1212	4	3.5363	0.0656	3.5363	1.8805
No log	0.1818	6	2.0716	0.1347	2.0716	1.4393
No log	0.2424	8	1.5391	-0.0147	1.5391	1.2406
No log	0.3030	10	1.4212	0.0656	1.4212	1.1922
No log	0.3636	12	1.3287	0.1710	1.3287	1.1527
No log	0.4242	14	1.4597	0.0932	1.4597	1.2082
No log	0.4848	16	1.4749	0.0251	1.4749	1.2144
No log	0.5455	18	1.4457	0.0749	1.4457	1.2024
No log	0.6061	20	1.6383	0.0491	1.6383	1.2800
No log	0.6667	22	1.7472	0.0636	1.7472	1.3218
No log	0.7273	24	1.4426	0.1014	1.4426	1.2011
No log	0.7879	26	1.0782	0.3815	1.0782	1.0384
No log	0.8485	28	1.0073	0.3883	1.0073	1.0036
No log	0.9091	30	0.9779	0.3788	0.9779	0.9889
No log	0.9697	32	0.9371	0.4032	0.9371	0.9680
No log	1.0303	34	0.9316	0.4760	0.9316	0.9652
No log	1.0909	36	0.9444	0.4919	0.9444	0.9718
No log	1.1515	38	1.2499	0.3019	1.2499	1.1180
No log	1.2121	40	1.2528	0.3161	1.2528	1.1193
No log	1.2727	42	1.4347	0.3027	1.4347	1.1978
No log	1.3333	44	1.2378	0.3237	1.2378	1.1126
No log	1.3939	46	0.9303	0.4785	0.9303	0.9645
No log	1.4545	48	0.9553	0.4537	0.9553	0.9774
No log	1.5152	50	1.0996	0.4313	1.0996	1.0486
No log	1.5758	52	0.9382	0.5124	0.9382	0.9686
No log	1.6364	54	0.7624	0.6324	0.7624	0.8732
No log	1.6970	56	0.7582	0.6124	0.7582	0.8707
No log	1.7576	58	0.7332	0.6835	0.7332	0.8563
No log	1.8182	60	0.7222	0.6728	0.7222	0.8498
No log	1.8788	62	0.7210	0.6747	0.7210	0.8491
No log	1.9394	64	0.7487	0.625	0.7487	0.8653
No log	2.0	66	0.9366	0.6137	0.9366	0.9678
No log	2.0606	68	1.0211	0.5802	1.0211	1.0105
No log	2.1212	70	0.9342	0.6266	0.9342	0.9665
No log	2.1818	72	0.9266	0.6059	0.9266	0.9626
No log	2.2424	74	0.9925	0.5955	0.9925	0.9962
No log	2.3030	76	0.8049	0.5839	0.8049	0.8972
No log	2.3636	78	0.7406	0.6273	0.7406	0.8606
No log	2.4242	80	0.7763	0.5606	0.7763	0.8811
No log	2.4848	82	0.7725	0.5747	0.7725	0.8789
No log	2.5455	84	0.8009	0.5730	0.8009	0.8949
No log	2.6061	86	0.7663	0.5794	0.7663	0.8754
No log	2.6667	88	0.7698	0.5634	0.7698	0.8774
No log	2.7273	90	0.7548	0.5854	0.7548	0.8688
No log	2.7879	92	0.7736	0.6741	0.7736	0.8795
No log	2.8485	94	0.8624	0.6224	0.8624	0.9286
No log	2.9091	96	0.9042	0.6176	0.9042	0.9509
No log	2.9697	98	0.7302	0.6770	0.7302	0.8545
No log	3.0303	100	0.7136	0.7155	0.7136	0.8447
No log	3.0909	102	0.7459	0.6817	0.7459	0.8637
No log	3.1515	104	0.8909	0.6231	0.8909	0.9439
No log	3.2121	106	1.2649	0.4784	1.2649	1.1247
No log	3.2727	108	1.4394	0.4300	1.4394	1.1998
No log	3.3333	110	1.2596	0.5073	1.2596	1.1223
No log	3.3939	112	0.9966	0.5798	0.9966	0.9983
No log	3.4545	114	0.9537	0.6058	0.9537	0.9766
No log	3.5152	116	1.1709	0.5444	1.1709	1.0821
No log	3.5758	118	1.4982	0.4929	1.4982	1.2240
No log	3.6364	120	1.4927	0.4883	1.4927	1.2218
No log	3.6970	122	1.2037	0.5157	1.2037	1.0971
No log	3.7576	124	1.0027	0.6069	1.0027	1.0014
No log	3.8182	126	0.8629	0.6531	0.8629	0.9289
No log	3.8788	128	0.8824	0.6489	0.8824	0.9394
No log	3.9394	130	0.9713	0.6045	0.9713	0.9855
No log	4.0	132	0.9979	0.5830	0.9979	0.9990
No log	4.0606	134	0.9657	0.5892	0.9657	0.9827
No log	4.1212	136	1.0492	0.5530	1.0492	1.0243
No log	4.1818	138	1.1095	0.5461	1.1095	1.0533
No log	4.2424	140	1.3599	0.5053	1.3599	1.1661
No log	4.3030	142	1.3912	0.4728	1.3912	1.1795
No log	4.3636	144	1.1845	0.5238	1.1845	1.0884
No log	4.4242	146	1.0118	0.5520	1.0118	1.0059
No log	4.4848	148	1.0391	0.5272	1.0391	1.0194
No log	4.5455	150	1.0703	0.5367	1.0703	1.0346
No log	4.6061	152	0.9821	0.5739	0.9821	0.9910
No log	4.6667	154	0.9698	0.5834	0.9698	0.9848
No log	4.7273	156	1.0287	0.5803	1.0287	1.0142
No log	4.7879	158	0.9209	0.6276	0.9209	0.9596
No log	4.8485	160	0.8224	0.6719	0.8224	0.9069
No log	4.9091	162	0.8237	0.6907	0.8237	0.9076
No log	4.9697	164	0.7965	0.6699	0.7965	0.8925
No log	5.0303	166	0.8676	0.6683	0.8676	0.9314
No log	5.0909	168	0.8910	0.6617	0.8910	0.9439
No log	5.1515	170	0.8622	0.6493	0.8622	0.9285
No log	5.2121	172	0.8204	0.6703	0.8204	0.9058
No log	5.2727	174	0.7770	0.6944	0.7770	0.8815
No log	5.3333	176	0.7200	0.7162	0.7200	0.8485
No log	5.3939	178	0.6995	0.7043	0.6995	0.8364
No log	5.4545	180	0.7136	0.6940	0.7136	0.8447
No log	5.5152	182	0.7883	0.6666	0.7883	0.8879
No log	5.5758	184	0.8106	0.6618	0.8106	0.9004
No log	5.6364	186	0.7944	0.6477	0.7944	0.8913
No log	5.6970	188	0.7387	0.6661	0.7387	0.8595
No log	5.7576	190	0.7143	0.7077	0.7143	0.8452
No log	5.8182	192	0.7117	0.7041	0.7117	0.8436
No log	5.8788	194	0.6859	0.7148	0.6859	0.8282
No log	5.9394	196	0.7099	0.7080	0.7099	0.8425
No log	6.0	198	0.8168	0.6803	0.8168	0.9037
No log	6.0606	200	0.8903	0.6346	0.8903	0.9436
No log	6.1212	202	0.8384	0.6669	0.8384	0.9156
No log	6.1818	204	0.7466	0.7035	0.7466	0.8641
No log	6.2424	206	0.7319	0.7095	0.7319	0.8555
No log	6.3030	208	0.8026	0.6739	0.8026	0.8959
No log	6.3636	210	0.8479	0.6589	0.8479	0.9208
No log	6.4242	212	0.8456	0.6733	0.8456	0.9195
No log	6.4848	214	0.8421	0.6733	0.8421	0.9176
No log	6.5455	216	0.7836	0.6664	0.7836	0.8852
No log	6.6061	218	0.7345	0.6781	0.7345	0.8570
No log	6.6667	220	0.7111	0.7087	0.7111	0.8433
No log	6.7273	222	0.7191	0.6705	0.7191	0.8480
No log	6.7879	224	0.8058	0.6639	0.8058	0.8977
No log	6.8485	226	0.9589	0.6049	0.9589	0.9792
No log	6.9091	228	0.9848	0.5950	0.9848	0.9924
No log	6.9697	230	0.9018	0.6265	0.9018	0.9497
No log	7.0303	232	0.7802	0.6968	0.7802	0.8833
No log	7.0909	234	0.7358	0.7188	0.7358	0.8578
No log	7.1515	236	0.7584	0.7072	0.7584	0.8709
No log	7.2121	238	0.8194	0.6524	0.8194	0.9052
No log	7.2727	240	0.9178	0.5991	0.9178	0.9580
No log	7.3333	242	0.9195	0.5991	0.9195	0.9589
No log	7.3939	244	0.8763	0.6405	0.8763	0.9361
No log	7.4545	246	0.7857	0.6961	0.7857	0.8864
No log	7.5152	248	0.7304	0.6964	0.7304	0.8547
No log	7.5758	250	0.7220	0.6964	0.7220	0.8497
No log	7.6364	252	0.7448	0.6964	0.7448	0.8630
No log	7.6970	254	0.7648	0.6956	0.7648	0.8745
No log	7.7576	256	0.8218	0.6724	0.8218	0.9066
No log	7.8182	258	0.8562	0.6465	0.8562	0.9253
No log	7.8788	260	0.8191	0.6742	0.8191	0.9050
No log	7.9394	262	0.7567	0.6931	0.7567	0.8699
No log	8.0	264	0.7137	0.6784	0.7137	0.8448
No log	8.0606	266	0.6974	0.7128	0.6974	0.8351
No log	8.1212	268	0.6944	0.7174	0.6944	0.8333
No log	8.1818	270	0.7004	0.7192	0.7004	0.8369
No log	8.2424	272	0.7199	0.6906	0.7199	0.8485
No log	8.3030	274	0.7636	0.6891	0.7636	0.8738
No log	8.3636	276	0.8111	0.6589	0.8111	0.9006
No log	8.4242	278	0.8572	0.6465	0.8572	0.9258
No log	8.4848	280	0.8745	0.6465	0.8745	0.9351
No log	8.5455	282	0.8709	0.6465	0.8709	0.9332
No log	8.6061	284	0.8409	0.6399	0.8409	0.9170
No log	8.6667	286	0.8116	0.6638	0.8116	0.9009
No log	8.7273	288	0.7934	0.6618	0.7934	0.8907
No log	8.7879	290	0.7907	0.6618	0.7907	0.8892
No log	8.8485	292	0.7985	0.6618	0.7985	0.8936
No log	8.9091	294	0.8124	0.6704	0.8124	0.9013
No log	8.9697	296	0.8351	0.6384	0.8351	0.9139
No log	9.0303	298	0.8635	0.6354	0.8635	0.9292
No log	9.0909	300	0.8681	0.6176	0.8681	0.9317
No log	9.1515	302	0.8561	0.6354	0.8561	0.9253
No log	9.2121	304	0.8375	0.6354	0.8375	0.9152
No log	9.2727	306	0.8079	0.6566	0.8079	0.8988
No log	9.3333	308	0.7923	0.6730	0.7923	0.8901
No log	9.3939	310	0.7841	0.6730	0.7841	0.8855
No log	9.4545	312	0.7827	0.6730	0.7827	0.8847
No log	9.5152	314	0.7928	0.6750	0.7928	0.8904
No log	9.5758	316	0.8117	0.6467	0.8117	0.9010
No log	9.6364	318	0.8244	0.6444	0.8244	0.9079
No log	9.6970	320	0.8359	0.6444	0.8359	0.9143
No log	9.7576	322	0.8497	0.6257	0.8497	0.9218
No log	9.8182	324	0.8618	0.6324	0.8618	0.9284
No log	9.8788	326	0.8693	0.6149	0.8693	0.9323
No log	9.9394	328	0.8734	0.6149	0.8734	0.9346
No log	10.0	330	0.8738	0.6149	0.8738	0.9348

Framework versions

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