Arabic_FineTuningAraBERT_AugV5_k4_task3_organization_fold0

MayBashendy/Arabic_FineTuningAraBERT_AugV5_k4_task3_organization_fold0

Arabic_FineTuningAraBERT_AugV5_k4_task3_organization_fold0 is a text classification model from MayBashendy. Use it when you need a label for a piece of text. It is set up for transformers.

should probably proofread and complete it, then remove this comment. --

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At a glance

Task: Text Classification
Library: transformers
Model type: bert
Access: Public
Created: Nov 25, 2024
Updated: Nov 25, 2024
SHA: e761c84f

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Base models

aubmindlab/bert-base-arabertv02

Model card

From the Hugging Face model README

Arabic_FineTuningAraBERT_AugV5_k4_task3_organization_fold0

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: 1.1975
Qwk: -0.2375
Mse: 1.1975
Rmse: 1.0943

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	0.08	2	4.6299	-0.0034	4.6299	2.1517
No log	0.16	4	2.8190	-0.0577	2.8190	1.6790
No log	0.24	6	1.2810	0.2870	1.2810	1.1318
No log	0.32	8	1.2064	0.1852	1.2064	1.0984
No log	0.4	10	1.3418	0.0873	1.3418	1.1584
No log	0.48	12	1.4324	0.0873	1.4324	1.1968
No log	0.56	14	1.4271	0.0873	1.4271	1.1946
No log	0.64	16	1.2683	0.0788	1.2683	1.1262
No log	0.72	18	1.2650	0.0788	1.2650	1.1247
No log	0.8	20	1.2037	0.0788	1.2037	1.0971
No log	0.88	22	1.2983	0.0833	1.2983	1.1394
No log	0.96	24	1.3221	0.0873	1.3221	1.1498
No log	1.04	26	1.1991	0.0833	1.1991	1.0951
No log	1.12	28	1.0703	0.0737	1.0703	1.0345
No log	1.2	30	0.9290	0.2029	0.9290	0.9638
No log	1.28	32	1.0283	0.1987	1.0283	1.0140
No log	1.3600	34	1.1382	-0.0421	1.1382	1.0669
No log	1.44	36	1.0924	-0.0732	1.0924	1.0452
No log	1.52	38	1.0098	0.2143	1.0098	1.0049
No log	1.6	40	1.0563	0.0530	1.0563	1.0278
No log	1.6800	42	1.1795	0.0737	1.1795	1.0861
No log	1.76	44	1.1959	0.0737	1.1959	1.0936
No log	1.8400	46	1.1819	0.0788	1.1819	1.0872
No log	1.92	48	1.1432	-0.0421	1.1432	1.0692
No log	2.0	50	1.1489	-0.0421	1.1489	1.0719
No log	2.08	52	1.2008	-0.0565	1.2008	1.0958
No log	2.16	54	1.1576	-0.0565	1.1576	1.0759
No log	2.24	56	1.0946	-0.0732	1.0946	1.0462
No log	2.32	58	1.1192	-0.0732	1.1192	1.0579
No log	2.4	60	1.1440	-0.0732	1.1440	1.0696
No log	2.48	62	1.1855	-0.0732	1.1855	1.0888
No log	2.56	64	1.0275	0.0320	1.0275	1.0137
No log	2.64	66	0.9542	0.0	0.9542	0.9769
No log	2.7200	68	0.9395	0.0	0.9395	0.9693
No log	2.8	70	0.9143	0.0	0.9143	0.9562
No log	2.88	72	0.8535	0.2143	0.8535	0.9239
No log	2.96	74	0.8774	0.384	0.8774	0.9367
No log	3.04	76	0.8699	0.2143	0.8699	0.9327
No log	3.12	78	0.8539	0.0	0.8539	0.9241
No log	3.2	80	0.8294	0.0	0.8294	0.9107
No log	3.2800	82	0.8159	0.0	0.8159	0.9033
No log	3.36	84	0.8802	0.2143	0.8802	0.9382
No log	3.44	86	1.1040	-0.0732	1.1040	1.0507
No log	3.52	88	1.1471	-0.0565	1.1471	1.0710
No log	3.6	90	0.9672	0.1987	0.9672	0.9835
No log	3.68	92	0.8477	0.2143	0.8477	0.9207
No log	3.76	94	0.8363	0.2143	0.8363	0.9145
No log	3.84	96	0.8445	0.2143	0.8445	0.9190
No log	3.92	98	0.8871	0.3636	0.8871	0.9419
No log	4.0	100	0.9312	0.3231	0.9312	0.9650
No log	4.08	102	0.9101	0.3231	0.9101	0.9540
No log	4.16	104	0.9171	0.1295	0.9171	0.9577
No log	4.24	106	0.9626	0.3231	0.9626	0.9811
No log	4.32	108	1.0551	0.1538	1.0551	1.0272
No log	4.4	110	1.2065	-0.0809	1.2065	1.0984
No log	4.48	112	1.2999	-0.0645	1.2999	1.1401
No log	4.5600	114	1.3993	-0.0645	1.3993	1.1829
No log	4.64	116	1.3760	-0.0645	1.3760	1.1730
No log	4.72	118	1.2322	-0.0809	1.2322	1.1101
No log	4.8	120	1.1092	0.0272	1.1092	1.0532
No log	4.88	122	1.1002	0.0272	1.1002	1.0489
No log	4.96	124	1.1456	0.0272	1.1456	1.0703
No log	5.04	126	1.3237	-0.0645	1.3237	1.1505
No log	5.12	128	1.2705	-0.0645	1.2705	1.1272
No log	5.2	130	1.0929	0.0435	1.0929	1.0454
No log	5.28	132	1.0678	0.0320	1.0678	1.0333
No log	5.36	134	1.1337	0.0435	1.1337	1.0648
No log	5.44	136	1.0999	0.0320	1.0999	1.0488
No log	5.52	138	1.0237	0.0320	1.0237	1.0118
No log	5.6	140	1.0149	0.0320	1.0149	1.0074
No log	5.68	142	1.0536	0.0320	1.0536	1.0264
No log	5.76	144	1.1730	0.0435	1.1730	1.0831
No log	5.84	146	1.2612	-0.0732	1.2612	1.1230
No log	5.92	148	1.3168	-0.0732	1.3168	1.1475
No log	6.0	150	1.2701	-0.2384	1.2701	1.1270
No log	6.08	152	1.3025	-0.2375	1.3025	1.1413
No log	6.16	154	1.2760	-0.1065	1.2760	1.1296
No log	6.24	156	1.2807	-0.1065	1.2807	1.1317
No log	6.32	158	1.3331	-0.1065	1.3331	1.1546
No log	6.4	160	1.4417	0.0410	1.4417	1.2007
No log	6.48	162	1.5828	0.0410	1.5828	1.2581
No log	6.5600	164	1.6016	0.0410	1.6016	1.2655
No log	6.64	166	1.6733	0.0410	1.6733	1.2936
No log	6.72	168	1.6667	0.0410	1.6667	1.2910
No log	6.8	170	1.5033	0.0410	1.5033	1.2261
No log	6.88	172	1.3823	0.0330	1.3823	1.1757
No log	6.96	174	1.2780	0.1538	1.2780	1.1305
No log	7.04	176	1.1893	0.1316	1.1893	1.0905
No log	7.12	178	1.1873	0.0149	1.1873	1.0896
No log	7.2	180	1.2640	0.0272	1.2640	1.1243
No log	7.28	182	1.3310	-0.0809	1.3310	1.1537
No log	7.36	184	1.2932	-0.0732	1.2932	1.1372
No log	7.44	186	1.2558	-0.2384	1.2558	1.1206
No log	7.52	188	1.1725	0.0149	1.1725	1.0828
No log	7.6	190	1.1119	0.0149	1.1119	1.0545
No log	7.68	192	1.0927	0.0149	1.0927	1.0453
No log	7.76	194	1.1083	0.0149	1.1083	1.0528
No log	7.84	196	1.1735	0.0272	1.1735	1.0833
No log	7.92	198	1.2644	-0.2384	1.2644	1.1244
No log	8.0	200	1.3790	-0.0732	1.3790	1.1743
No log	8.08	202	1.4414	-0.0565	1.4414	1.2006
No log	8.16	204	1.4324	-0.0732	1.4324	1.1968
No log	8.24	206	1.4515	-0.0565	1.4515	1.2048
No log	8.32	208	1.4075	-0.0732	1.4075	1.1864
No log	8.4	210	1.3814	-0.0732	1.3814	1.1753
No log	8.48	212	1.3075	-0.2375	1.3075	1.1435
No log	8.56	214	1.2362	-0.2375	1.2362	1.1119
No log	8.64	216	1.1800	0.0272	1.1800	1.0863
No log	8.72	218	1.1314	0.0149	1.1314	1.0637
No log	8.8	220	1.0773	0.0149	1.0773	1.0379
No log	8.88	222	1.0475	0.0149	1.0475	1.0235
No log	8.96	224	1.0364	0.0149	1.0364	1.0181
No log	9.04	226	1.0471	0.0149	1.0471	1.0233
No log	9.12	228	1.0754	0.0149	1.0754	1.0370
No log	9.2	230	1.1052	0.0149	1.1052	1.0513
No log	9.28	232	1.1253	0.0149	1.1253	1.0608
No log	9.36	234	1.1432	0.0149	1.1432	1.0692
No log	9.44	236	1.1660	0.0149	1.1660	1.0798
No log	9.52	238	1.1851	-0.2375	1.1851	1.0886
No log	9.6	240	1.1974	-0.2375	1.1974	1.0943
No log	9.68	242	1.1972	-0.2375	1.1972	1.0942
No log	9.76	244	1.1961	-0.2375	1.1961	1.0936
No log	9.84	246	1.1964	-0.2375	1.1964	1.0938
No log	9.92	248	1.1980	-0.2375	1.1980	1.0945
No log	10.0	250	1.1975	-0.2375	1.1975	1.0943

Framework versions

Transformers 4.44.2
Pytorch 2.4.0+cu118
Datasets 2.21.0
Tokenizers 0.19.1

Task: Text Classification
Library: transformers
Type: bert
Created: Nov 25, 2024
Updated: Nov 25, 2024