Arabic_FineTuningAraBERT_AugV5_k2_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: 0.6073
• Qwk: 0.4490
• Mse: 0.6073
• Rmse: 0.7793

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	2.9490	0.0	2.9490	1.7173
No log	0.1538	4	1.0182	0.0	1.0182	1.0091
No log	0.2308	6	0.5614	0.1923	0.5614	0.7493
No log	0.3077	8	0.5505	0.3333	0.5505	0.7419
No log	0.3846	10	0.8157	0.1563	0.8157	0.9032
No log	0.4615	12	1.2634	0.0548	1.2634	1.1240
No log	0.5385	14	1.2180	0.0	1.2180	1.1036
No log	0.6154	16	1.2773	0.0548	1.2773	1.1302
No log	0.6923	18	0.9583	0.0	0.9583	0.9789
No log	0.7692	20	0.7891	0.1905	0.7891	0.8883
No log	0.8462	22	0.6350	0.2258	0.6350	0.7969
No log	0.9231	24	0.5472	0.3774	0.5472	0.7397
No log	1.0	26	0.5534	0.3774	0.5534	0.7439
No log	1.0769	28	0.8524	0.0548	0.8524	0.9232
No log	1.1538	30	1.4893	-0.0690	1.4893	1.2204
No log	1.2308	32	1.2087	0.0548	1.2087	1.0994
No log	1.3077	34	1.0141	0.0	1.0141	1.0070
No log	1.3846	36	0.8205	0.1972	0.8205	0.9058
No log	1.4615	38	0.5866	0.3607	0.5866	0.7659
No log	1.5385	40	0.5295	0.1724	0.5295	0.7276
No log	1.6154	42	0.5504	0.2909	0.5504	0.7419
No log	1.6923	44	0.6433	0.1000	0.6433	0.8020
No log	1.7692	46	0.8197	0.1563	0.8197	0.9054
No log	1.8462	48	0.8808	0.1667	0.8808	0.9385
No log	1.9231	50	0.7920	0.1667	0.7920	0.8899
No log	2.0	52	0.6053	0.4	0.6053	0.7780
No log	2.0769	54	0.4358	0.4407	0.4358	0.6602
No log	2.1538	56	0.4216	0.4407	0.4216	0.6493
No log	2.2308	58	0.4277	0.4407	0.4277	0.6540
No log	2.3077	60	0.4186	0.4407	0.4186	0.6470
No log	2.3846	62	0.5070	0.4179	0.5070	0.7120
No log	2.4615	64	0.4386	0.4545	0.4386	0.6622
No log	2.5385	66	0.3335	0.6316	0.3335	0.5775
No log	2.6154	68	0.3407	0.6316	0.3407	0.5837
No log	2.6923	70	0.3750	0.4828	0.3750	0.6124
No log	2.7692	72	0.4242	0.4407	0.4242	0.6513
No log	2.8462	74	0.5271	0.4935	0.5271	0.7261
No log	2.9231	76	0.4888	0.4935	0.4888	0.6992
No log	3.0	78	0.3899	0.5217	0.3899	0.6244
No log	3.0769	80	0.3440	0.6667	0.3440	0.5865
No log	3.1538	82	0.3190	0.6494	0.3190	0.5648
No log	3.2308	84	0.3266	0.6494	0.3266	0.5715
No log	3.3077	86	0.3506	0.6582	0.3506	0.5921
No log	3.3846	88	0.5609	0.4545	0.5609	0.7489
No log	3.4615	90	0.7536	0.4466	0.7536	0.8681
No log	3.5385	92	0.7737	0.4466	0.7737	0.8796
No log	3.6154	94	0.6454	0.5143	0.6454	0.8033
No log	3.6923	96	0.5354	0.5161	0.5354	0.7317
No log	3.7692	98	0.4671	0.5116	0.4671	0.6834
No log	3.8462	100	0.4484	0.6024	0.4484	0.6696
No log	3.9231	102	0.4732	0.5385	0.4732	0.6879
No log	4.0	104	0.5530	0.4474	0.5530	0.7437
No log	4.0769	106	0.6267	0.5185	0.6267	0.7917
No log	4.1538	108	0.6186	0.5185	0.6186	0.7865
No log	4.2308	110	0.5704	0.4474	0.5704	0.7553
No log	4.3077	112	0.5407	0.4474	0.5407	0.7353
No log	4.3846	114	0.5360	0.5185	0.5360	0.7321
No log	4.4615	116	0.5769	0.5116	0.5769	0.7596
No log	4.5385	118	0.6265	0.5185	0.6265	0.7915
No log	4.6154	120	0.5782	0.5185	0.5782	0.7604
No log	4.6923	122	0.5396	0.5227	0.5396	0.7345
No log	4.7692	124	0.5212	0.5227	0.5212	0.7220
No log	4.8462	126	0.4975	0.5435	0.4975	0.7053
No log	4.9231	128	0.4920	0.5435	0.4920	0.7014
No log	5.0	130	0.4746	0.6966	0.4746	0.6889
No log	5.0769	132	0.4939	0.6809	0.4939	0.7028
No log	5.1538	134	0.5308	0.5116	0.5308	0.7286
No log	5.2308	136	0.5700	0.5116	0.5700	0.7550
No log	5.3077	138	0.5638	0.5116	0.5638	0.7509
No log	5.3846	140	0.5607	0.5116	0.5607	0.7488
No log	5.4615	142	0.5695	0.5161	0.5695	0.7546
No log	5.5385	144	0.6313	0.4667	0.6313	0.7945
No log	5.6154	146	0.6907	0.4000	0.6907	0.8311
No log	5.6923	148	0.6219	0.4632	0.6219	0.7886
No log	5.7692	150	0.5302	0.5333	0.5302	0.7282
No log	5.8462	152	0.5294	0.5227	0.5294	0.7276
No log	5.9231	154	0.5552	0.5055	0.5552	0.7451
No log	6.0	156	0.5858	0.4000	0.5858	0.7654
No log	6.0769	158	0.6002	0.4000	0.6002	0.7747
No log	6.1538	160	0.6291	0.4944	0.6291	0.7932
No log	6.2308	162	0.7189	0.5116	0.7189	0.8479
No log	6.3077	164	0.7895	0.4600	0.7895	0.8886
No log	6.3846	166	0.7818	0.4600	0.7818	0.8842
No log	6.4615	168	0.7259	0.4490	0.7259	0.8520
No log	6.5385	170	0.6702	0.5895	0.6702	0.8187
No log	6.6154	172	0.6439	0.5532	0.6439	0.8024
No log	6.6923	174	0.6277	0.5055	0.6277	0.7923
No log	6.7692	176	0.6150	0.5435	0.6150	0.7842
No log	6.8462	178	0.6246	0.5895	0.6246	0.7903
No log	6.9231	180	0.6724	0.4571	0.6724	0.8200
No log	7.0	182	0.7990	0.4643	0.7990	0.8939
No log	7.0769	184	0.9308	0.4545	0.9308	0.9648
No log	7.1538	186	0.9532	0.4545	0.9532	0.9763
No log	7.2308	188	0.8828	0.4444	0.8828	0.9396
No log	7.3077	190	0.7647	0.4571	0.7647	0.8745
No log	7.3846	192	0.6839	0.4490	0.6839	0.8270
No log	7.4615	194	0.6580	0.4490	0.6580	0.8112
No log	7.5385	196	0.6679	0.4490	0.6679	0.8172
No log	7.6154	198	0.7090	0.4571	0.7090	0.8420
No log	7.6923	200	0.7346	0.4571	0.7346	0.8571
No log	7.7692	202	0.7148	0.4571	0.7148	0.8454
No log	7.8462	204	0.6534	0.4490	0.6534	0.8083
No log	7.9231	206	0.5825	0.5055	0.5825	0.7632
No log	8.0	208	0.5404	0.5227	0.5404	0.7351
No log	8.0769	210	0.5383	0.5227	0.5383	0.7337
No log	8.1538	212	0.5539	0.5227	0.5539	0.7442
No log	8.2308	214	0.5908	0.5333	0.5908	0.7687
No log	8.3077	216	0.6262	0.4490	0.6262	0.7913
No log	8.3846	218	0.6595	0.4490	0.6595	0.8121
No log	8.4615	220	0.6616	0.4490	0.6616	0.8134
No log	8.5385	222	0.6653	0.4490	0.6653	0.8157
No log	8.6154	224	0.6513	0.4490	0.6513	0.8070
No log	8.6923	226	0.6296	0.4490	0.6296	0.7935
No log	8.7692	228	0.6232	0.4490	0.6232	0.7894
No log	8.8462	230	0.6189	0.4490	0.6189	0.7867
No log	8.9231	232	0.6248	0.4490	0.6248	0.7905
No log	9.0	234	0.6320	0.4490	0.6320	0.7950
No log	9.0769	236	0.6460	0.4571	0.6460	0.8038
No log	9.1538	238	0.6420	0.4490	0.6420	0.8012
No log	9.2308	240	0.6311	0.4490	0.6311	0.7944
No log	9.3077	242	0.6242	0.4490	0.6242	0.7900
No log	9.3846	244	0.6194	0.4490	0.6194	0.7870
No log	9.4615	246	0.6123	0.4490	0.6123	0.7825
No log	9.5385	248	0.6047	0.4490	0.6047	0.7776
No log	9.6154	250	0.6020	0.4742	0.6020	0.7759
No log	9.6923	252	0.6017	0.4742	0.6017	0.7757
No log	9.7692	254	0.6034	0.4490	0.6034	0.7768
No log	9.8462	256	0.6047	0.4490	0.6047	0.7776
No log	9.9231	258	0.6062	0.4490	0.6062	0.7786
No log	10.0	260	0.6073	0.4490	0.6073	0.7793

Framework versions

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