ArabicNewSplits6_FineTuningAraBERT_run2_AugV5_k8_task5_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: 0.9763
• Qwk: 0.6480
• Mse: 0.9763
• Rmse: 0.9881

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	2.3362	-0.0013	2.3362	1.5285
No log	0.125	4	1.6741	0.1343	1.6741	1.2939
No log	0.1875	6	1.6120	0.0250	1.6120	1.2696
No log	0.25	8	1.7419	0.0504	1.7419	1.3198
No log	0.3125	10	1.5192	0.1697	1.5192	1.2326
No log	0.375	12	1.3138	0.1682	1.3138	1.1462
No log	0.4375	14	1.2804	0.1841	1.2804	1.1316
No log	0.5	16	1.2734	0.1920	1.2734	1.1285
No log	0.5625	18	1.2671	0.2078	1.2671	1.1256
No log	0.625	20	1.2547	0.2281	1.2547	1.1201
No log	0.6875	22	1.2592	0.2264	1.2592	1.1222
No log	0.75	24	1.2542	0.2883	1.2542	1.1199
No log	0.8125	26	1.3124	0.2898	1.3124	1.1456
No log	0.875	28	1.3609	0.3377	1.3609	1.1666
No log	0.9375	30	1.3700	0.2926	1.3700	1.1705
No log	1.0	32	1.3525	0.2281	1.3525	1.1630
No log	1.0625	34	1.3229	0.1951	1.3229	1.1502
No log	1.125	36	1.2647	0.2476	1.2647	1.1246
No log	1.1875	38	1.1668	0.2869	1.1668	1.0802
No log	1.25	40	1.1276	0.3422	1.1276	1.0619
No log	1.3125	42	1.1670	0.3491	1.1670	1.0803
No log	1.375	44	1.1424	0.4131	1.1424	1.0688
No log	1.4375	46	1.1031	0.4184	1.1031	1.0503
No log	1.5	48	1.0553	0.3759	1.0553	1.0273
No log	1.5625	50	1.0832	0.3602	1.0832	1.0408
No log	1.625	52	1.2415	0.4128	1.2415	1.1142
No log	1.6875	54	1.3717	0.4178	1.3717	1.1712
No log	1.75	56	1.3789	0.3923	1.3789	1.1743
No log	1.8125	58	1.2713	0.4576	1.2713	1.1275
No log	1.875	60	1.1086	0.5085	1.1086	1.0529
No log	1.9375	62	1.0306	0.5337	1.0306	1.0152
No log	2.0	64	0.9817	0.4881	0.9817	0.9908
No log	2.0625	66	0.9498	0.5053	0.9498	0.9746
No log	2.125	68	0.9693	0.5008	0.9693	0.9845
No log	2.1875	70	0.9890	0.4983	0.9890	0.9945
No log	2.25	72	1.0509	0.5095	1.0509	1.0251
No log	2.3125	74	1.1621	0.5161	1.1621	1.0780
No log	2.375	76	1.2414	0.5129	1.2414	1.1142
No log	2.4375	78	1.1899	0.4973	1.1899	1.0908
No log	2.5	80	1.0775	0.5633	1.0775	1.0380
No log	2.5625	82	1.1033	0.5185	1.1033	1.0504
No log	2.625	84	1.1893	0.5170	1.1893	1.0906
No log	2.6875	86	1.2443	0.5167	1.2443	1.1155
No log	2.75	88	1.2468	0.5068	1.2468	1.1166
No log	2.8125	90	1.1763	0.5112	1.1763	1.0846
No log	2.875	92	1.0471	0.5769	1.0471	1.0233
No log	2.9375	94	1.0099	0.6036	1.0099	1.0049
No log	3.0	96	1.0935	0.6172	1.0935	1.0457
No log	3.0625	98	1.1317	0.5756	1.1317	1.0638
No log	3.125	100	1.1033	0.6017	1.1033	1.0504
No log	3.1875	102	1.0504	0.6125	1.0504	1.0249
No log	3.25	104	1.0353	0.5982	1.0353	1.0175
No log	3.3125	106	1.0304	0.6076	1.0304	1.0151
No log	3.375	108	0.9050	0.6397	0.9050	0.9513
No log	3.4375	110	0.8312	0.5762	0.8312	0.9117
No log	3.5	112	0.8206	0.6020	0.8206	0.9059
No log	3.5625	114	0.8737	0.6140	0.8737	0.9347
No log	3.625	116	0.9318	0.6440	0.9318	0.9653
No log	3.6875	118	0.9293	0.6445	0.9293	0.9640
No log	3.75	120	0.9602	0.6500	0.9602	0.9799
No log	3.8125	122	0.9962	0.6184	0.9962	0.9981
No log	3.875	124	0.9308	0.6494	0.9308	0.9648
No log	3.9375	126	0.9495	0.6114	0.9495	0.9744
No log	4.0	128	1.0779	0.6107	1.0779	1.0382
No log	4.0625	130	1.3482	0.5446	1.3482	1.1611
No log	4.125	132	1.4804	0.5184	1.4804	1.2167
No log	4.1875	134	1.4225	0.5448	1.4225	1.1927
No log	4.25	136	1.1963	0.5735	1.1963	1.0937
No log	4.3125	138	0.9890	0.6387	0.9890	0.9945
No log	4.375	140	0.9017	0.6543	0.9017	0.9496
No log	4.4375	142	0.9075	0.6457	0.9075	0.9526
No log	4.5	144	0.9157	0.6724	0.9157	0.9569
No log	4.5625	146	0.9595	0.6308	0.9595	0.9795
No log	4.625	148	0.9674	0.6463	0.9674	0.9836
No log	4.6875	150	0.9293	0.6451	0.9293	0.9640
No log	4.75	152	0.8533	0.6576	0.8533	0.9237
No log	4.8125	154	0.7894	0.6470	0.7894	0.8885
No log	4.875	156	0.7726	0.6537	0.7726	0.8790
No log	4.9375	158	0.8188	0.6571	0.8188	0.9049
No log	5.0	160	0.9471	0.6594	0.9471	0.9732
No log	5.0625	162	1.0439	0.6389	1.0439	1.0217
No log	5.125	164	1.1172	0.6020	1.1172	1.0570
No log	5.1875	166	1.2086	0.5957	1.2086	1.0993
No log	5.25	168	1.1551	0.5968	1.1551	1.0748
No log	5.3125	170	1.0179	0.6563	1.0179	1.0089
No log	5.375	172	0.9283	0.6670	0.9283	0.9635
No log	5.4375	174	0.9245	0.6670	0.9245	0.9615
No log	5.5	176	0.9987	0.6337	0.9987	0.9994
No log	5.5625	178	1.0782	0.5968	1.0782	1.0384
No log	5.625	180	1.1121	0.5882	1.1121	1.0546
No log	5.6875	182	1.0713	0.6010	1.0713	1.0350
No log	5.75	184	0.9730	0.6565	0.9730	0.9864
No log	5.8125	186	0.8515	0.6582	0.8515	0.9227
No log	5.875	188	0.7757	0.6664	0.7757	0.8808
No log	5.9375	190	0.7728	0.6879	0.7728	0.8791
No log	6.0	192	0.8131	0.6809	0.8131	0.9017
No log	6.0625	194	0.9130	0.6625	0.9130	0.9555
No log	6.125	196	1.0750	0.6122	1.0750	1.0368
No log	6.1875	198	1.3164	0.5715	1.3164	1.1474
No log	6.25	200	1.4902	0.5670	1.4902	1.2207
No log	6.3125	202	1.4686	0.5670	1.4686	1.2119
No log	6.375	204	1.3289	0.5715	1.3289	1.1528
No log	6.4375	206	1.1564	0.5765	1.1564	1.0753
No log	6.5	208	1.0171	0.6585	1.0171	1.0085
No log	6.5625	210	0.9591	0.6562	0.9591	0.9793
No log	6.625	212	0.9705	0.6551	0.9705	0.9852
No log	6.6875	214	1.0292	0.6168	1.0292	1.0145
No log	6.75	216	1.0796	0.5961	1.0796	1.0391
No log	6.8125	218	1.1060	0.5677	1.1060	1.0517
No log	6.875	220	1.1358	0.5654	1.1358	1.0658
No log	6.9375	222	1.1697	0.5679	1.1697	1.0815
No log	7.0	224	1.1910	0.5630	1.1910	1.0913
No log	7.0625	226	1.1808	0.5588	1.1808	1.0867
No log	7.125	228	1.1010	0.6039	1.1010	1.0493
No log	7.1875	230	1.0527	0.6177	1.0527	1.0260
No log	7.25	232	1.0226	0.6191	1.0226	1.0112
No log	7.3125	234	1.0302	0.6191	1.0302	1.0150
No log	7.375	236	1.0906	0.6044	1.0906	1.0443
No log	7.4375	238	1.1149	0.5973	1.1149	1.0559
No log	7.5	240	1.1457	0.6066	1.1457	1.0704
No log	7.5625	242	1.1529	0.5935	1.1529	1.0737
No log	7.625	244	1.1907	0.5520	1.1907	1.0912
No log	7.6875	246	1.1924	0.5520	1.1924	1.0920
No log	7.75	248	1.1514	0.5441	1.1514	1.0730
No log	7.8125	250	1.0853	0.5949	1.0853	1.0418
No log	7.875	252	1.0210	0.6324	1.0210	1.0104
No log	7.9375	254	0.9989	0.6461	0.9989	0.9994
No log	8.0	256	1.0068	0.6446	1.0068	1.0034
No log	8.0625	258	1.0402	0.6261	1.0402	1.0199
No log	8.125	260	1.0602	0.6185	1.0602	1.0296
No log	8.1875	262	1.0819	0.6055	1.0819	1.0401
No log	8.25	264	1.1015	0.6042	1.1015	1.0495
No log	8.3125	266	1.0865	0.6172	1.0865	1.0423
No log	8.375	268	1.0434	0.6233	1.0434	1.0215
No log	8.4375	270	0.9971	0.6418	0.9971	0.9985
No log	8.5	272	0.9796	0.6529	0.9796	0.9898
No log	8.5625	274	0.9577	0.6653	0.9577	0.9786
No log	8.625	276	0.9558	0.6653	0.9558	0.9777
No log	8.6875	278	0.9618	0.6583	0.9618	0.9807
No log	8.75	280	0.9681	0.6461	0.9681	0.9839
No log	8.8125	282	0.9793	0.6602	0.9793	0.9896
No log	8.875	284	0.9972	0.6585	0.9972	0.9986
No log	8.9375	286	1.0060	0.6503	1.0060	1.0030
No log	9.0	288	1.0058	0.6503	1.0058	1.0029
No log	9.0625	290	1.0105	0.6503	1.0105	1.0053
No log	9.125	292	1.0164	0.6503	1.0164	1.0081
No log	9.1875	294	1.0291	0.6385	1.0291	1.0145
No log	9.25	296	1.0323	0.6372	1.0323	1.0160
No log	9.3125	298	1.0211	0.6372	1.0211	1.0105
No log	9.375	300	1.0028	0.6465	1.0028	1.0014
No log	9.4375	302	0.9892	0.6480	0.9892	0.9946
No log	9.5	304	0.9879	0.6480	0.9879	0.9939
No log	9.5625	306	0.9807	0.6602	0.9807	0.9903
No log	9.625	308	0.9759	0.6602	0.9759	0.9879
No log	9.6875	310	0.9767	0.6602	0.9767	0.9883
No log	9.75	312	0.9773	0.6602	0.9773	0.9886
No log	9.8125	314	0.9765	0.6480	0.9765	0.9882
No log	9.875	316	0.9758	0.6480	0.9758	0.9878
No log	9.9375	318	0.9760	0.6480	0.9760	0.9879
No log	10.0	320	0.9763	0.6480	0.9763	0.9881

Framework versions

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