ArabicNewSplits5_FineTuningAraBERT_run2_AugV5_k5_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: 0.6639
• Qwk: 0.7474
• Mse: 0.6639
• Rmse: 0.8148

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	0.0769	2	2.2608	0.0485	2.2608	1.5036
No log	0.1538	4	1.4335	0.2507	1.4335	1.1973
No log	0.2308	6	1.2690	0.2429	1.2689	1.1265
No log	0.3077	8	1.2687	0.2251	1.2687	1.1264
No log	0.3846	10	1.2867	0.2307	1.2867	1.1343
No log	0.4615	12	1.2820	0.1848	1.2820	1.1323
No log	0.5385	14	1.2574	0.1428	1.2574	1.1213
No log	0.6154	16	1.2763	0.2799	1.2763	1.1297
No log	0.6923	18	1.2837	0.3610	1.2837	1.1330
No log	0.7692	20	1.2626	0.3508	1.2626	1.1237
No log	0.8462	22	1.1855	0.2931	1.1855	1.0888
No log	0.9231	24	1.1454	0.1635	1.1454	1.0702
No log	1.0	26	1.1317	0.1456	1.1317	1.0638
No log	1.0769	28	1.1012	0.2348	1.1012	1.0494
No log	1.1538	30	1.0901	0.3076	1.0901	1.0441
No log	1.2308	32	1.0958	0.3512	1.0958	1.0468
No log	1.3077	34	1.0593	0.4088	1.0593	1.0292
No log	1.3846	36	1.0245	0.4636	1.0245	1.0122
No log	1.4615	38	1.0038	0.4857	1.0038	1.0019
No log	1.5385	40	0.9697	0.4975	0.9697	0.9847
No log	1.6154	42	0.9087	0.5522	0.9087	0.9533
No log	1.6923	44	0.8595	0.5750	0.8595	0.9271
No log	1.7692	46	0.8307	0.6491	0.8307	0.9114
No log	1.8462	48	0.8435	0.6454	0.8435	0.9184
No log	1.9231	50	0.7918	0.6196	0.7918	0.8898
No log	2.0	52	0.8185	0.6240	0.8185	0.9047
No log	2.0769	54	1.0778	0.5418	1.0778	1.0382
No log	2.1538	56	1.1652	0.5008	1.1652	1.0795
No log	2.2308	58	1.0609	0.5498	1.0609	1.0300
No log	2.3077	60	0.8682	0.5980	0.8682	0.9318
No log	2.3846	62	0.7980	0.6313	0.7980	0.8933
No log	2.4615	64	0.7805	0.6421	0.7805	0.8834
No log	2.5385	66	0.8246	0.6001	0.8246	0.9081
No log	2.6154	68	0.9405	0.5715	0.9405	0.9698
No log	2.6923	70	1.1673	0.4634	1.1673	1.0804
No log	2.7692	72	1.2357	0.4342	1.2357	1.1116
No log	2.8462	74	0.9793	0.5717	0.9793	0.9896
No log	2.9231	76	0.7294	0.6606	0.7294	0.8540
No log	3.0	78	0.7914	0.6385	0.7914	0.8896
No log	3.0769	80	0.9623	0.4955	0.9623	0.9810
No log	3.1538	82	0.9735	0.4684	0.9735	0.9866
No log	3.2308	84	0.8693	0.5316	0.8693	0.9323
No log	3.3077	86	0.8047	0.6054	0.8047	0.8971
No log	3.3846	88	0.8229	0.5669	0.8229	0.9071
No log	3.4615	90	0.8680	0.5852	0.8680	0.9316
No log	3.5385	92	0.9616	0.5684	0.9616	0.9806
No log	3.6154	94	1.0041	0.5601	1.0041	1.0021
No log	3.6923	96	0.9057	0.6146	0.9057	0.9517
No log	3.7692	98	0.7453	0.6940	0.7453	0.8633
No log	3.8462	100	0.6919	0.7164	0.6919	0.8318
No log	3.9231	102	0.6839	0.7257	0.6839	0.8270
No log	4.0	104	0.7049	0.7146	0.7049	0.8396
No log	4.0769	106	0.8325	0.7375	0.8325	0.9124
No log	4.1538	108	0.9124	0.7223	0.9124	0.9552
No log	4.2308	110	0.8172	0.7225	0.8172	0.9040
No log	4.3077	112	0.7328	0.6957	0.7328	0.8560
No log	4.3846	114	0.6657	0.7033	0.6657	0.8159
No log	4.4615	116	0.6671	0.7178	0.6671	0.8167
No log	4.5385	118	0.6630	0.7148	0.6630	0.8142
No log	4.6154	120	0.6739	0.7025	0.6739	0.8209
No log	4.6923	122	0.7576	0.7317	0.7576	0.8704
No log	4.7692	124	0.9851	0.6427	0.9851	0.9925
No log	4.8462	126	1.1482	0.5852	1.1482	1.0715
No log	4.9231	128	1.1245	0.5725	1.1245	1.0604
No log	5.0	130	0.9532	0.6538	0.9532	0.9763
No log	5.0769	132	0.7661	0.7102	0.7661	0.8753
No log	5.1538	134	0.6833	0.6938	0.6833	0.8266
No log	5.2308	136	0.6461	0.7208	0.6461	0.8038
No log	5.3077	138	0.6390	0.7190	0.6390	0.7994
No log	5.3846	140	0.6474	0.7217	0.6474	0.8046
No log	5.4615	142	0.6945	0.7224	0.6945	0.8334
No log	5.5385	144	0.7849	0.7266	0.7849	0.8859
No log	5.6154	146	0.8939	0.6878	0.8939	0.9455
No log	5.6923	148	0.8688	0.6878	0.8688	0.9321
No log	5.7692	150	0.7810	0.7133	0.7810	0.8838
No log	5.8462	152	0.6909	0.7286	0.6909	0.8312
No log	5.9231	154	0.6374	0.7257	0.6374	0.7984
No log	6.0	156	0.6599	0.6783	0.6599	0.8123
No log	6.0769	158	0.6757	0.6662	0.6757	0.8220
No log	6.1538	160	0.6563	0.6717	0.6563	0.8101
No log	6.2308	162	0.6402	0.7223	0.6402	0.8001
No log	6.3077	164	0.6497	0.7529	0.6497	0.8060
No log	6.3846	166	0.7231	0.7215	0.7231	0.8504
No log	6.4615	168	0.8282	0.7154	0.8282	0.9101
No log	6.5385	170	0.8806	0.7113	0.8806	0.9384
No log	6.6154	172	0.8868	0.7036	0.8868	0.9417
No log	6.6923	174	0.8236	0.7150	0.8236	0.9075
No log	6.7692	176	0.7439	0.7288	0.7439	0.8625
No log	6.8462	178	0.6678	0.7195	0.6678	0.8172
No log	6.9231	180	0.6448	0.7270	0.6448	0.8030
No log	7.0	182	0.6470	0.7270	0.6470	0.8044
No log	7.0769	184	0.6677	0.7171	0.6677	0.8171
No log	7.1538	186	0.7070	0.7146	0.7070	0.8408
No log	7.2308	188	0.7242	0.7266	0.7242	0.8510
No log	7.3077	190	0.7075	0.7309	0.7075	0.8411
No log	7.3846	192	0.6694	0.7155	0.6694	0.8182
No log	7.4615	194	0.6435	0.7141	0.6435	0.8022
No log	7.5385	196	0.6236	0.7525	0.6236	0.7897
No log	7.6154	198	0.6251	0.7462	0.6251	0.7906
No log	7.6923	200	0.6366	0.7141	0.6366	0.7979
No log	7.7692	202	0.6703	0.7256	0.6703	0.8187
No log	7.8462	204	0.7242	0.7266	0.7242	0.8510
No log	7.9231	206	0.7536	0.7344	0.7536	0.8681
No log	8.0	208	0.7883	0.7302	0.7883	0.8879
No log	8.0769	210	0.8235	0.7261	0.8235	0.9075
No log	8.1538	212	0.8141	0.7207	0.8141	0.9023
No log	8.2308	214	0.7972	0.7281	0.7972	0.8929
No log	8.3077	216	0.7602	0.7419	0.7602	0.8719
No log	8.3846	218	0.7269	0.7294	0.7269	0.8526
No log	8.4615	220	0.6908	0.7431	0.6908	0.8311
No log	8.5385	222	0.6686	0.7355	0.6686	0.8177
No log	8.6154	224	0.6657	0.7355	0.6657	0.8159
No log	8.6923	226	0.6737	0.7355	0.6737	0.8208
No log	8.7692	228	0.6779	0.7491	0.6779	0.8233
No log	8.8462	230	0.6798	0.7361	0.6798	0.8245
No log	8.9231	232	0.6778	0.7339	0.6778	0.8233
No log	9.0	234	0.6760	0.7339	0.6760	0.8222
No log	9.0769	236	0.6753	0.7339	0.6753	0.8218
No log	9.1538	238	0.6726	0.7339	0.6726	0.8201
No log	9.2308	240	0.6749	0.7339	0.6749	0.8215
No log	9.3077	242	0.6745	0.7339	0.6745	0.8213
No log	9.3846	244	0.6725	0.7339	0.6725	0.8201
No log	9.4615	246	0.6705	0.7339	0.6705	0.8188
No log	9.5385	248	0.6657	0.7474	0.6657	0.8159
No log	9.6154	250	0.6631	0.7474	0.6631	0.8143
No log	9.6923	252	0.6612	0.7474	0.6612	0.8131
No log	9.7692	254	0.6615	0.7474	0.6615	0.8134
No log	9.8462	256	0.6619	0.7474	0.6619	0.8136
No log	9.9231	258	0.6630	0.7474	0.6630	0.8143
No log	10.0	260	0.6639	0.7474	0.6639	0.8148

Framework versions

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