Arabic_FineTuningAraBERT_run2_AugV5_k2_task1_organization_fold1

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: 0.6184
• Qwk: 0.6769
• Mse: 0.6184
• Rmse: 0.7864

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	0.0645	2	3.0954	0.0397	3.0954	1.7594
No log	0.1290	4	2.2926	0.125	2.2926	1.5141
No log	0.1935	6	2.0117	0.1026	2.0117	1.4184
No log	0.2581	8	1.6250	0.0	1.6250	1.2748
No log	0.3226	10	1.3080	0.0	1.3080	1.1437
No log	0.3871	12	1.2601	0.0	1.2601	1.1225
No log	0.4516	14	1.2575	0.0	1.2575	1.1214
No log	0.5161	16	1.1534	0.0	1.1534	1.0740
No log	0.5806	18	1.0539	0.0	1.0539	1.0266
No log	0.6452	20	1.0060	0.0841	1.0060	1.0030
No log	0.7097	22	1.0244	0.0	1.0244	1.0121
No log	0.7742	24	1.1019	0.0	1.1019	1.0497
No log	0.8387	26	1.1311	0.0	1.1311	1.0635
No log	0.9032	28	1.1078	0.0	1.1078	1.0525
No log	0.9677	30	1.1050	0.0	1.1050	1.0512
No log	1.0323	32	1.0923	0.0	1.0923	1.0452
No log	1.0968	34	1.1006	0.0841	1.1006	1.0491
No log	1.1613	36	1.1557	0.0	1.1557	1.0750
No log	1.2258	38	1.1416	0.0	1.1416	1.0685
No log	1.2903	40	1.0933	0.0	1.0933	1.0456
No log	1.3548	42	1.0280	0.0	1.0280	1.0139
No log	1.4194	44	1.0050	0.0	1.0050	1.0025
No log	1.4839	46	1.0047	0.0	1.0047	1.0024
No log	1.5484	48	0.9900	0.1706	0.9900	0.9950
No log	1.6129	50	0.9606	0.2829	0.9606	0.9801
No log	1.6774	52	0.9424	0.2613	0.9424	0.9708
No log	1.7419	54	0.9491	0.2613	0.9491	0.9742
No log	1.8065	56	0.9417	0.3571	0.9417	0.9704
No log	1.8710	58	0.9257	0.3834	0.9257	0.9621
No log	1.9355	60	0.9068	0.3834	0.9068	0.9523
No log	2.0	62	0.8609	0.4842	0.8609	0.9279
No log	2.0645	64	0.7932	0.4199	0.7932	0.8906
No log	2.1290	66	0.7497	0.4199	0.7497	0.8658
No log	2.1935	68	0.7228	0.3708	0.7228	0.8502
No log	2.2581	70	0.7059	0.4	0.7059	0.8402
No log	2.3226	72	0.7068	0.3488	0.7068	0.8407
No log	2.3871	74	0.7337	0.3488	0.7337	0.8566
No log	2.4516	76	0.7535	0.2959	0.7535	0.8681
No log	2.5161	78	0.7536	0.2959	0.7536	0.8681
No log	2.5806	80	0.7318	0.2959	0.7318	0.8554
No log	2.6452	82	0.6737	0.3488	0.6737	0.8208
No log	2.7097	84	0.6550	0.3708	0.6550	0.8093
No log	2.7742	86	0.6505	0.3708	0.6505	0.8066
No log	2.8387	88	0.6498	0.3708	0.6498	0.8061
No log	2.9032	90	0.6325	0.4199	0.6325	0.7953
No log	2.9677	92	0.6273	0.5882	0.6273	0.7920
No log	3.0323	94	0.6184	0.5882	0.6184	0.7864
No log	3.0968	96	0.5901	0.5882	0.5901	0.7682
No log	3.1613	98	0.5801	0.5882	0.5801	0.7617
No log	3.2258	100	0.5668	0.5767	0.5668	0.7528
No log	3.2903	102	0.5807	0.4717	0.5807	0.7620
No log	3.3548	104	0.6117	0.4563	0.6117	0.7821
No log	3.4194	106	0.6239	0.4563	0.6239	0.7899
No log	3.4839	108	0.6653	0.3978	0.6653	0.8157
No log	3.5484	110	0.6298	0.4138	0.6298	0.7936
No log	3.6129	112	0.5572	0.5161	0.5572	0.7465
No log	3.6774	114	0.5320	0.6016	0.5320	0.7294
No log	3.7419	116	0.5707	0.5370	0.5707	0.7555
No log	3.8065	118	0.5859	0.5370	0.5859	0.7654
No log	3.8710	120	0.5648	0.6486	0.5648	0.7515
No log	3.9355	122	0.6348	0.5882	0.6348	0.7968
No log	4.0	124	0.7331	0.6471	0.7331	0.8562
No log	4.0645	126	0.7342	0.6111	0.7342	0.8568
No log	4.1290	128	0.6880	0.6224	0.6880	0.8294
No log	4.1935	130	0.6281	0.5116	0.6281	0.7925
No log	4.2581	132	0.6224	0.6263	0.6224	0.7889
No log	4.3226	134	0.6356	0.6263	0.6356	0.7972
No log	4.3871	136	0.6229	0.6164	0.6229	0.7892
No log	4.4516	138	0.6088	0.6267	0.6088	0.7803
No log	4.5161	140	0.6040	0.6617	0.6040	0.7772
No log	4.5806	142	0.6091	0.6617	0.6091	0.7805
No log	4.6452	144	0.5863	0.6617	0.5863	0.7657
No log	4.7097	146	0.5682	0.6624	0.5682	0.7538
No log	4.7742	148	0.5586	0.6624	0.5586	0.7474
No log	4.8387	150	0.5598	0.7129	0.5598	0.7482
No log	4.9032	152	0.5728	0.6797	0.5728	0.7569
No log	4.9677	154	0.5720	0.6441	0.5720	0.7563
No log	5.0323	156	0.5731	0.6535	0.5731	0.7570
No log	5.0968	158	0.5978	0.6624	0.5978	0.7732
No log	5.1613	160	0.6389	0.6667	0.6389	0.7993
No log	5.2258	162	0.6835	0.5828	0.6835	0.8267
No log	5.2903	164	0.7011	0.5828	0.7011	0.8373
No log	5.3548	166	0.6771	0.5911	0.6771	0.8229
No log	5.4194	168	0.6446	0.5882	0.6446	0.8029
No log	5.4839	170	0.6524	0.5765	0.6524	0.8077
No log	5.5484	172	0.6605	0.6164	0.6605	0.8127
No log	5.6129	174	0.6627	0.6164	0.6627	0.8141
No log	5.6774	176	0.6731	0.6267	0.6731	0.8205
No log	5.7419	178	0.6727	0.6557	0.6727	0.8202
No log	5.8065	180	0.6510	0.6557	0.6510	0.8068
No log	5.8710	182	0.6214	0.6522	0.6214	0.7883
No log	5.9355	184	0.5911	0.6522	0.5911	0.7688
No log	6.0	186	0.5762	0.6522	0.5762	0.7591
No log	6.0645	188	0.5651	0.6879	0.5651	0.7518
No log	6.1290	190	0.5274	0.6733	0.5274	0.7262
No log	6.1935	192	0.4827	0.7336	0.4827	0.6948
No log	6.2581	194	0.4672	0.7034	0.4672	0.6835
No log	6.3226	196	0.4796	0.72	0.4796	0.6925
No log	6.3871	198	0.4497	0.72	0.4497	0.6706
No log	6.4516	200	0.4274	0.7266	0.4274	0.6537
No log	6.5161	202	0.4796	0.6624	0.4796	0.6925
No log	6.5806	204	0.5517	0.7129	0.5517	0.7428
No log	6.6452	206	0.5682	0.7129	0.5682	0.7538
No log	6.7097	208	0.5669	0.6624	0.5669	0.7529
No log	6.7742	210	0.5765	0.6522	0.5765	0.7592
No log	6.8387	212	0.6114	0.6708	0.6114	0.7819
No log	6.9032	214	0.6342	0.6708	0.6342	0.7964
No log	6.9677	216	0.6472	0.6708	0.6472	0.8045
No log	7.0323	218	0.6363	0.6522	0.6363	0.7977
No log	7.0968	220	0.6102	0.6522	0.6102	0.7811
No log	7.1613	222	0.5915	0.6522	0.5915	0.7691
No log	7.2258	224	0.5831	0.6879	0.5831	0.7636
No log	7.2903	226	0.5771	0.6879	0.5771	0.7597
No log	7.3548	228	0.5819	0.6522	0.5819	0.7629
No log	7.4194	230	0.5975	0.6522	0.5975	0.7730
No log	7.4839	232	0.6304	0.6606	0.6304	0.7940
No log	7.5484	234	0.6712	0.6789	0.6712	0.8193
No log	7.6129	236	0.6837	0.6789	0.6837	0.8268
No log	7.6774	238	0.6580	0.6789	0.6580	0.8112
No log	7.7419	240	0.6248	0.6426	0.6248	0.7904
No log	7.8065	242	0.6025	0.6522	0.6025	0.7762
No log	7.8710	244	0.5963	0.6769	0.5963	0.7722
No log	7.9355	246	0.5962	0.6769	0.5962	0.7722
No log	8.0	248	0.5963	0.6769	0.5963	0.7722
No log	8.0645	250	0.5963	0.6769	0.5963	0.7722
No log	8.1290	252	0.6029	0.6769	0.6029	0.7764
No log	8.1935	254	0.6090	0.6667	0.6090	0.7804
No log	8.2581	256	0.6111	0.6667	0.6111	0.7817
No log	8.3226	258	0.6049	0.6667	0.6049	0.7778
No log	8.3871	260	0.6020	0.6667	0.6020	0.7759
No log	8.4516	262	0.6038	0.6667	0.6038	0.7770
No log	8.5161	264	0.6099	0.6667	0.6099	0.7809
No log	8.5806	266	0.6157	0.6667	0.6157	0.7847
No log	8.6452	268	0.6227	0.6667	0.6227	0.7891
No log	8.7097	270	0.6279	0.6667	0.6279	0.7924
No log	8.7742	272	0.6303	0.6667	0.6303	0.7939
No log	8.8387	274	0.6326	0.6667	0.6326	0.7954
No log	8.9032	276	0.6350	0.6667	0.6350	0.7969
No log	8.9677	278	0.6351	0.6667	0.6351	0.7969
No log	9.0323	280	0.6341	0.6667	0.6341	0.7963
No log	9.0968	282	0.6323	0.6667	0.6323	0.7952
No log	9.1613	284	0.6288	0.6667	0.6288	0.7930
No log	9.2258	286	0.6257	0.6667	0.6257	0.7910
No log	9.2903	288	0.6253	0.6426	0.6253	0.7908
No log	9.3548	290	0.6252	0.6426	0.6252	0.7907
No log	9.4194	292	0.6246	0.6426	0.6246	0.7903
No log	9.4839	294	0.6228	0.6426	0.6228	0.7892
No log	9.5484	296	0.6209	0.6667	0.6209	0.7880
No log	9.6129	298	0.6199	0.6667	0.6199	0.7873
No log	9.6774	300	0.6194	0.6667	0.6194	0.7870
No log	9.7419	302	0.6185	0.6769	0.6185	0.7865
No log	9.8065	304	0.6182	0.6769	0.6182	0.7863
No log	9.8710	306	0.6182	0.6769	0.6182	0.7862
No log	9.9355	308	0.6182	0.6769	0.6182	0.7862
No log	10.0	310	0.6184	0.6769	0.6184	0.7864

Framework versions

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