Arabic_FineTuningAraBERT_AugV0_k4_task2_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: 0.6578
• Qwk: 0.2683
• Mse: 0.6578
• Rmse: 0.8111

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	0.0714	2	3.3270	-0.0167	3.3270	1.8240
No log	0.1429	4	1.5796	0.0792	1.5796	1.2568
No log	0.2143	6	0.6012	0.1600	0.6012	0.7754
No log	0.2857	8	0.7403	0.0870	0.7403	0.8604
No log	0.3571	10	0.8431	0.0	0.8431	0.9182
No log	0.4286	12	0.7596	0.0870	0.7596	0.8715
No log	0.5	14	0.6973	-0.0800	0.6973	0.8350
No log	0.5714	16	0.6680	-0.1176	0.6680	0.8173
No log	0.6429	18	0.6402	-0.1176	0.6402	0.8001
No log	0.7143	20	0.6401	0.0	0.6401	0.8001
No log	0.7857	22	0.6894	0.1702	0.6894	0.8303
No log	0.8571	24	0.6530	-0.0408	0.6530	0.8081
No log	0.9286	26	0.6586	0.0769	0.6586	0.8116
No log	1.0	28	0.6782	0.0377	0.6782	0.8235
No log	1.0714	30	0.7022	-0.1111	0.7022	0.8380
No log	1.1429	32	0.7166	0.1000	0.7166	0.8465
No log	1.2143	34	0.7430	0.3158	0.7430	0.8620
No log	1.2857	36	0.7776	0.2817	0.7776	0.8818
No log	1.3571	38	0.7186	0.3226	0.7186	0.8477
No log	1.4286	40	0.6710	0.1818	0.6710	0.8191
No log	1.5	42	0.6582	0.1356	0.6582	0.8113
No log	1.5714	44	0.6373	0.1356	0.6373	0.7983
No log	1.6429	46	0.6490	0.2353	0.6490	0.8056
No log	1.7143	48	0.6936	0.1600	0.6936	0.8328
No log	1.7857	50	0.6359	0.1600	0.6359	0.7974
No log	1.8571	52	0.5820	0.2800	0.5820	0.7629
No log	1.9286	54	0.5722	0.2800	0.5722	0.7565
No log	2.0	56	0.5934	0.1176	0.5934	0.7703
No log	2.0714	58	0.6491	0.0769	0.6491	0.8056
No log	2.1429	60	0.6219	0.0769	0.6219	0.7886
No log	2.2143	62	0.6338	0.2258	0.6338	0.7961
No log	2.2857	64	0.7060	0.25	0.7060	0.8402
No log	2.3571	66	0.6707	0.25	0.6707	0.8190
No log	2.4286	68	0.6506	0.2609	0.6506	0.8066
No log	2.5	70	0.6567	0.4156	0.6567	0.8104
No log	2.5714	72	0.6423	0.2941	0.6423	0.8015
No log	2.6429	74	0.6548	0.4	0.6548	0.8092
No log	2.7143	76	0.6824	0.2857	0.6824	0.8261
No log	2.7857	78	0.6953	0.3023	0.6953	0.8338
No log	2.8571	80	0.7223	0.2963	0.7223	0.8499
No log	2.9286	82	0.6910	0.3023	0.6910	0.8312
No log	3.0	84	0.6670	0.3636	0.6670	0.8167
No log	3.0714	86	0.6631	0.3284	0.6631	0.8143
No log	3.1429	88	0.6426	0.3284	0.6426	0.8016
No log	3.2143	90	0.5976	0.3636	0.5976	0.7731
No log	3.2857	92	0.6017	0.125	0.6017	0.7757
No log	3.3571	94	0.6463	0.1509	0.6463	0.8039
No log	3.4286	96	0.5751	-0.0408	0.5751	0.7584
No log	3.5	98	0.5511	0.1111	0.5511	0.7424
No log	3.5714	100	0.5712	0.2258	0.5712	0.7558
No log	3.6429	102	0.5849	0.2258	0.5849	0.7648
No log	3.7143	104	0.5903	0.0400	0.5903	0.7683
No log	3.7857	106	0.6033	0.0400	0.6033	0.7767
No log	3.8571	108	0.6112	0.0625	0.6112	0.7818
No log	3.9286	110	0.6441	0.3014	0.6441	0.8025
No log	4.0	112	0.6996	0.2963	0.6996	0.8364
No log	4.0714	114	0.6853	0.3077	0.6853	0.8278
No log	4.1429	116	0.7185	0.3415	0.7185	0.8477
No log	4.2143	118	0.7827	0.3514	0.7827	0.8847
No log	4.2857	120	0.7519	0.3704	0.7519	0.8671
No log	4.3571	122	0.7181	0.3182	0.7181	0.8474
No log	4.4286	124	0.7180	0.2857	0.7180	0.8474
No log	4.5	126	0.6928	0.3133	0.6928	0.8324
No log	4.5714	128	0.6773	0.4156	0.6773	0.8230
No log	4.6429	130	0.6983	0.3514	0.6983	0.8357
No log	4.7143	132	0.6846	0.3514	0.6846	0.8274
No log	4.7857	134	0.6298	0.3014	0.6298	0.7936
No log	4.8571	136	0.6207	0.2895	0.6207	0.7878
No log	4.9286	138	0.6234	0.3077	0.6234	0.7896
No log	5.0	140	0.6270	0.3333	0.6270	0.7919
No log	5.0714	142	0.6339	0.3736	0.6339	0.7962
No log	5.1429	144	0.6255	0.3704	0.6255	0.7909
No log	5.2143	146	0.6131	0.2192	0.6131	0.7830
No log	5.2857	148	0.6338	0.3377	0.6338	0.7961
No log	5.3571	150	0.7014	0.3294	0.7014	0.8375
No log	5.4286	152	0.6928	0.3846	0.6928	0.8323
No log	5.5	154	0.6982	0.3846	0.6982	0.8356
No log	5.5714	156	0.6254	0.3200	0.6254	0.7908
No log	5.6429	158	0.6262	0.4146	0.6262	0.7913
No log	5.7143	160	0.6606	0.3014	0.6606	0.8128
No log	5.7857	162	0.6319	0.3514	0.6319	0.7950
No log	5.8571	164	0.5744	0.3294	0.5744	0.7579
No log	5.9286	166	0.5796	0.4304	0.5796	0.7613
No log	6.0	168	0.5825	0.4000	0.5825	0.7632
No log	6.0714	170	0.5753	0.4000	0.5753	0.7585
No log	6.1429	172	0.5588	0.3662	0.5588	0.7475
No log	6.2143	174	0.5572	0.24	0.5572	0.7465
No log	6.2857	176	0.5740	0.4507	0.5740	0.7576
No log	6.3571	178	0.6019	0.4474	0.6019	0.7758
No log	6.4286	180	0.6160	0.4474	0.6160	0.7849
No log	6.5	182	0.6171	0.4167	0.6171	0.7856
No log	6.5714	184	0.6392	0.4	0.6392	0.7995
No log	6.6429	186	0.6977	0.3226	0.6977	0.8353
No log	6.7143	188	0.7495	0.3596	0.7495	0.8657
No log	6.7857	190	0.7369	0.4130	0.7369	0.8584
No log	6.8571	192	0.7241	0.3368	0.7241	0.8509
No log	6.9286	194	0.7524	0.4	0.7524	0.8674
No log	7.0	196	0.7877	0.4	0.7877	0.8875
No log	7.0714	198	0.7917	0.4	0.7917	0.8898
No log	7.1429	200	0.7937	0.3368	0.7937	0.8909
No log	7.2143	202	0.8037	0.3125	0.8037	0.8965
No log	7.2857	204	0.7941	0.2653	0.7941	0.8911
No log	7.3571	206	0.7814	0.2500	0.7814	0.8839
No log	7.4286	208	0.7588	0.1750	0.7588	0.8711
No log	7.5	210	0.7264	0.2921	0.7264	0.8523
No log	7.5714	212	0.7299	0.3544	0.7299	0.8543
No log	7.6429	214	0.7446	0.3077	0.7446	0.8629
No log	7.7143	216	0.7406	0.3077	0.7406	0.8606
No log	7.7857	218	0.7207	0.3544	0.7207	0.8489
No log	7.8571	220	0.7022	0.2921	0.7022	0.8380
No log	7.9286	222	0.7035	0.2785	0.7035	0.8388
No log	8.0	224	0.7137	0.3415	0.7137	0.8448
No log	8.0714	226	0.7313	0.2597	0.7313	0.8551
No log	8.1429	228	0.7212	0.2597	0.7212	0.8492
No log	8.2143	230	0.6920	0.2963	0.6920	0.8319
No log	8.2857	232	0.6653	0.2857	0.6653	0.8157
No log	8.3571	234	0.6638	0.3544	0.6638	0.8148
No log	8.4286	236	0.6660	0.3544	0.6660	0.8161
No log	8.5	238	0.6562	0.3544	0.6562	0.8100
No log	8.5714	240	0.6436	0.4000	0.6436	0.8023
No log	8.6429	242	0.6405	0.2683	0.6405	0.8003
No log	8.7143	244	0.6387	0.3704	0.6387	0.7992
No log	8.7857	246	0.6409	0.4000	0.6409	0.8006
No log	8.8571	248	0.6442	0.4000	0.6442	0.8026
No log	8.9286	250	0.6462	0.3704	0.6462	0.8039
No log	9.0	252	0.6472	0.2683	0.6472	0.8045
No log	9.0714	254	0.6491	0.2683	0.6491	0.8056
No log	9.1429	256	0.6496	0.2683	0.6496	0.8060
No log	9.2143	258	0.6528	0.2683	0.6528	0.8079
No log	9.2857	260	0.6559	0.2921	0.6559	0.8099
No log	9.3571	262	0.6587	0.2921	0.6587	0.8116
No log	9.4286	264	0.6609	0.2921	0.6609	0.8130
No log	9.5	266	0.6619	0.2921	0.6619	0.8136
No log	9.5714	268	0.6623	0.2921	0.6623	0.8138
No log	9.6429	270	0.6617	0.2921	0.6617	0.8134
No log	9.7143	272	0.6603	0.2921	0.6603	0.8126
No log	9.7857	274	0.6591	0.2921	0.6591	0.8118
No log	9.8571	276	0.6582	0.2921	0.6582	0.8113
No log	9.9286	278	0.6579	0.2921	0.6579	0.8111
No log	10.0	280	0.6578	0.2683	0.6578	0.8111

Framework versions

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