ArabicNewSplits8_FineTuningAraBERT_noAug_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: 0.6463
• Qwk: 0.6613
• Mse: 0.6463
• Rmse: 0.8039

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: 100

Training results

Training Loss	Epoch	Step	Validation Loss	Qwk	Mse	Rmse
No log	0.5	2	3.3581	0.1137	3.3581	1.8325
No log	1.0	4	2.0055	0.0748	2.0055	1.4161
No log	1.5	6	1.3760	0.0798	1.3760	1.1730
No log	2.0	8	1.1656	0.2867	1.1656	1.0796
No log	2.5	10	1.1435	0.2540	1.1435	1.0694
No log	3.0	12	1.0264	0.3141	1.0264	1.0131
No log	3.5	14	0.9219	0.4206	0.9219	0.9601
No log	4.0	16	0.8868	0.5547	0.8868	0.9417
No log	4.5	18	0.7939	0.6148	0.7939	0.8910
No log	5.0	20	0.8761	0.6348	0.8761	0.9360
No log	5.5	22	0.7890	0.6149	0.7890	0.8883
No log	6.0	24	0.7899	0.6238	0.7899	0.8887
No log	6.5	26	0.6968	0.6753	0.6968	0.8347
No log	7.0	28	0.7605	0.6348	0.7605	0.8720
No log	7.5	30	0.7046	0.6835	0.7046	0.8394
No log	8.0	32	0.6788	0.6136	0.6788	0.8239
No log	8.5	34	0.6823	0.5957	0.6823	0.8260
No log	9.0	36	0.7147	0.6644	0.7147	0.8454
No log	9.5	38	0.6626	0.6836	0.6626	0.8140
No log	10.0	40	0.6834	0.6477	0.6834	0.8267
No log	10.5	42	0.6527	0.6585	0.6527	0.8079
No log	11.0	44	0.8448	0.6713	0.8448	0.9191
No log	11.5	46	0.9311	0.6439	0.9311	0.9649
No log	12.0	48	0.6772	0.7294	0.6772	0.8229
No log	12.5	50	0.7484	0.6294	0.7484	0.8651
No log	13.0	52	0.7141	0.6162	0.7141	0.8451
No log	13.5	54	0.6410	0.6605	0.6410	0.8006
No log	14.0	56	0.6670	0.6553	0.6670	0.8167
No log	14.5	58	0.6506	0.6512	0.6506	0.8066
No log	15.0	60	0.7036	0.6572	0.7036	0.8388
No log	15.5	62	0.6330	0.6543	0.6330	0.7956
No log	16.0	64	0.7001	0.7128	0.7001	0.8367
No log	16.5	66	0.6719	0.7428	0.6719	0.8197
No log	17.0	68	0.5864	0.6627	0.5864	0.7658
No log	17.5	70	0.5719	0.6745	0.5719	0.7562
No log	18.0	72	0.6067	0.7230	0.6067	0.7789
No log	18.5	74	0.6293	0.7149	0.6293	0.7933
No log	19.0	76	0.5870	0.7113	0.5870	0.7661
No log	19.5	78	0.6339	0.6995	0.6339	0.7962
No log	20.0	80	0.6256	0.6860	0.6256	0.7909
No log	20.5	82	0.6599	0.7005	0.6599	0.8124
No log	21.0	84	0.7115	0.7121	0.7115	0.8435
No log	21.5	86	0.6271	0.6917	0.6271	0.7919
No log	22.0	88	0.5960	0.7209	0.5960	0.7720
No log	22.5	90	0.5473	0.6605	0.5473	0.7398
No log	23.0	92	0.6255	0.6737	0.6255	0.7909
No log	23.5	94	0.9046	0.6359	0.9046	0.9511
No log	24.0	96	1.0702	0.5869	1.0702	1.0345
No log	24.5	98	0.8596	0.6329	0.8596	0.9271
No log	25.0	100	0.6164	0.6903	0.6164	0.7851
No log	25.5	102	0.5722	0.6847	0.5722	0.7565
No log	26.0	104	0.5886	0.6805	0.5886	0.7672
No log	26.5	106	0.5793	0.6728	0.5793	0.7611
No log	27.0	108	0.5719	0.7053	0.5719	0.7562
No log	27.5	110	0.5880	0.6939	0.5880	0.7668
No log	28.0	112	0.6004	0.6877	0.6004	0.7749
No log	28.5	114	0.5866	0.6943	0.5866	0.7659
No log	29.0	116	0.6032	0.6977	0.6032	0.7767
No log	29.5	118	0.6240	0.6900	0.6240	0.7900
No log	30.0	120	0.6846	0.6646	0.6846	0.8274
No log	30.5	122	0.7123	0.6845	0.7123	0.8440
No log	31.0	124	0.6228	0.6813	0.6228	0.7892
No log	31.5	126	0.6008	0.6984	0.6008	0.7751
No log	32.0	128	0.6471	0.7009	0.6471	0.8044
No log	32.5	130	0.6593	0.7102	0.6593	0.8119
No log	33.0	132	0.5897	0.7122	0.5897	0.7679
No log	33.5	134	0.5778	0.7029	0.5778	0.7601
No log	34.0	136	0.5763	0.7089	0.5763	0.7592
No log	34.5	138	0.5809	0.6977	0.5809	0.7622
No log	35.0	140	0.5866	0.6863	0.5866	0.7659
No log	35.5	142	0.5925	0.6587	0.5925	0.7697
No log	36.0	144	0.5900	0.6873	0.5900	0.7681
No log	36.5	146	0.6181	0.6644	0.6181	0.7862
No log	37.0	148	0.6533	0.6708	0.6533	0.8083
No log	37.5	150	0.6263	0.6728	0.6263	0.7914
No log	38.0	152	0.5848	0.6947	0.5848	0.7647
No log	38.5	154	0.5737	0.7229	0.5737	0.7574
No log	39.0	156	0.5791	0.7300	0.5791	0.7610
No log	39.5	158	0.6346	0.7359	0.6346	0.7966
No log	40.0	160	0.6498	0.7057	0.6498	0.8061
No log	40.5	162	0.6150	0.6718	0.6150	0.7842
No log	41.0	164	0.5969	0.6626	0.5969	0.7726
No log	41.5	166	0.6199	0.6444	0.6199	0.7873
No log	42.0	168	0.6155	0.7016	0.6155	0.7845
No log	42.5	170	0.6535	0.6297	0.6535	0.8084
No log	43.0	172	0.8596	0.6330	0.8596	0.9271
No log	43.5	174	0.9150	0.6256	0.9150	0.9566
No log	44.0	176	0.8357	0.6476	0.8357	0.9142
No log	44.5	178	0.6816	0.6913	0.6816	0.8256
No log	45.0	180	0.5742	0.7082	0.5742	0.7578
No log	45.5	182	0.5626	0.7015	0.5626	0.7500
No log	46.0	184	0.5905	0.6873	0.5905	0.7685
No log	46.5	186	0.6383	0.7054	0.6383	0.7990
No log	47.0	188	0.6477	0.7120	0.6477	0.8048
No log	47.5	190	0.6913	0.6824	0.6913	0.8314
No log	48.0	192	0.6985	0.6677	0.6985	0.8357
No log	48.5	194	0.6664	0.6556	0.6664	0.8164
No log	49.0	196	0.6341	0.6643	0.6341	0.7963
No log	49.5	198	0.6096	0.6599	0.6096	0.7808
No log	50.0	200	0.5828	0.7148	0.5828	0.7634
No log	50.5	202	0.5793	0.6904	0.5793	0.7611
No log	51.0	204	0.5884	0.7066	0.5884	0.7671
No log	51.5	206	0.5947	0.6954	0.5947	0.7712
No log	52.0	208	0.5942	0.6869	0.5942	0.7708
No log	52.5	210	0.5948	0.6840	0.5948	0.7713
No log	53.0	212	0.6178	0.6306	0.6178	0.7860
No log	53.5	214	0.6390	0.6355	0.6390	0.7994
No log	54.0	216	0.6345	0.6574	0.6345	0.7966
No log	54.5	218	0.6298	0.6616	0.6298	0.7936
No log	55.0	220	0.6437	0.6528	0.6437	0.8023
No log	55.5	222	0.6287	0.6852	0.6287	0.7929
No log	56.0	224	0.6034	0.6617	0.6034	0.7768
No log	56.5	226	0.5983	0.6759	0.5983	0.7735
No log	57.0	228	0.6057	0.6954	0.6057	0.7783
No log	57.5	230	0.6553	0.7012	0.6553	0.8095
No log	58.0	232	0.7629	0.7035	0.7629	0.8735
No log	58.5	234	0.8221	0.6862	0.8221	0.9067
No log	59.0	236	0.7871	0.7035	0.7871	0.8872
No log	59.5	238	0.6983	0.6969	0.6983	0.8356
No log	60.0	240	0.6503	0.6980	0.6503	0.8064
No log	60.5	242	0.6812	0.6614	0.6812	0.8254
No log	61.0	244	0.7588	0.6566	0.7588	0.8711
No log	61.5	246	0.7822	0.6578	0.7822	0.8844
No log	62.0	248	0.6999	0.6562	0.6999	0.8366
No log	62.5	250	0.6100	0.6785	0.6100	0.7810
No log	63.0	252	0.5991	0.6331	0.5991	0.7740
No log	63.5	254	0.6230	0.6349	0.6230	0.7893
No log	64.0	256	0.6304	0.6318	0.6304	0.7939
No log	64.5	258	0.6178	0.6308	0.6178	0.7860
No log	65.0	260	0.6425	0.6518	0.6425	0.8016
No log	65.5	262	0.7050	0.6462	0.7050	0.8396
No log	66.0	264	0.7521	0.6528	0.7521	0.8673
No log	66.5	266	0.7961	0.6409	0.7961	0.8922
No log	67.0	268	0.7699	0.6229	0.7699	0.8774
No log	67.5	270	0.7201	0.6615	0.7201	0.8486
No log	68.0	272	0.6868	0.6624	0.6868	0.8287
No log	68.5	274	0.6894	0.6866	0.6894	0.8303
No log	69.0	276	0.6740	0.6859	0.6740	0.8210
No log	69.5	278	0.6934	0.7009	0.6934	0.8327
No log	70.0	280	0.7377	0.6918	0.7377	0.8589
No log	70.5	282	0.8186	0.6932	0.8186	0.9047
No log	71.0	284	0.8520	0.6616	0.8520	0.9231
No log	71.5	286	0.8425	0.6787	0.8425	0.9179
No log	72.0	288	0.8296	0.6752	0.8296	0.9108
No log	72.5	290	0.8317	0.6752	0.8317	0.9120
No log	73.0	292	0.7906	0.6783	0.7906	0.8891
No log	73.5	294	0.7214	0.6817	0.7214	0.8494
No log	74.0	296	0.6418	0.6841	0.6418	0.8011
No log	74.5	298	0.5965	0.6870	0.5965	0.7723
No log	75.0	300	0.5861	0.6661	0.5861	0.7656
No log	75.5	302	0.5891	0.6717	0.5891	0.7676
No log	76.0	304	0.5929	0.6684	0.5929	0.7700
No log	76.5	306	0.6044	0.6799	0.6044	0.7774
No log	77.0	308	0.6289	0.6544	0.6289	0.7930
No log	77.5	310	0.6611	0.6297	0.6611	0.8131
No log	78.0	312	0.6802	0.6430	0.6802	0.8247
No log	78.5	314	0.6912	0.6430	0.6912	0.8314
No log	79.0	316	0.6992	0.6504	0.6992	0.8362
No log	79.5	318	0.6764	0.6535	0.6764	0.8224
No log	80.0	320	0.6451	0.6520	0.6451	0.8032
No log	80.5	322	0.6157	0.6686	0.6157	0.7847
No log	81.0	324	0.5882	0.6997	0.5882	0.7669
No log	81.5	326	0.5782	0.6953	0.5782	0.7604
No log	82.0	328	0.5714	0.6996	0.5714	0.7559
No log	82.5	330	0.5705	0.6996	0.5705	0.7553
No log	83.0	332	0.5742	0.6919	0.5742	0.7577
No log	83.5	334	0.5815	0.6782	0.5815	0.7626
No log	84.0	336	0.5952	0.6988	0.5952	0.7715
No log	84.5	338	0.6073	0.6792	0.6073	0.7793
No log	85.0	340	0.6210	0.6633	0.6210	0.7881
No log	85.5	342	0.6309	0.6633	0.6309	0.7943
No log	86.0	344	0.6359	0.6633	0.6359	0.7974
No log	86.5	346	0.6389	0.6613	0.6389	0.7993
No log	87.0	348	0.6377	0.6524	0.6377	0.7986
No log	87.5	350	0.6307	0.6524	0.6307	0.7942
No log	88.0	352	0.6199	0.6544	0.6199	0.7873
No log	88.5	354	0.6158	0.6544	0.6158	0.7848
No log	89.0	356	0.6140	0.6653	0.6140	0.7836
No log	89.5	358	0.6127	0.6653	0.6127	0.7827
No log	90.0	360	0.6108	0.6632	0.6108	0.7815
No log	90.5	362	0.6086	0.6708	0.6086	0.7801
No log	91.0	364	0.6099	0.6708	0.6099	0.7810
No log	91.5	366	0.6104	0.6815	0.6104	0.7813
No log	92.0	368	0.6136	0.6792	0.6136	0.7834
No log	92.5	370	0.6213	0.6633	0.6213	0.7882
No log	93.0	372	0.6332	0.6633	0.6332	0.7957
No log	93.5	374	0.6441	0.6739	0.6441	0.8025
No log	94.0	376	0.6581	0.6769	0.6581	0.8112
No log	94.5	378	0.6651	0.6748	0.6651	0.8155
No log	95.0	380	0.6669	0.6606	0.6669	0.8166
No log	95.5	382	0.6630	0.6748	0.6630	0.8142
No log	96.0	384	0.6604	0.6748	0.6604	0.8127
No log	96.5	386	0.6557	0.6769	0.6557	0.8098
No log	97.0	388	0.6520	0.6769	0.6520	0.8074
No log	97.5	390	0.6495	0.6790	0.6495	0.8059
No log	98.0	392	0.6485	0.6790	0.6485	0.8053
No log	98.5	394	0.6483	0.6718	0.6483	0.8052
No log	99.0	396	0.6474	0.6718	0.6474	0.8046
No log	99.5	398	0.6466	0.6613	0.6466	0.8041
No log	100.0	400	0.6463	0.6613	0.6463	0.8039

Framework versions

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