Arabic_FineTuningAraBERT_AugV0_k5_task2_organization_fold1

MayBashendy/Arabic_FineTuningAraBERT_AugV0_k5_task2_organization_fold1

Arabic_FineTuningAraBERT_AugV0_k5_task2_organization_fold1 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 19, 2024
Updated: Nov 19, 2024
SHA: 47050074

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Base models

aubmindlab/bert-base-arabertv02

Model card

From the Hugging Face model README

Arabic_FineTuningAraBERT_AugV0_k5_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: 0.5346
Qwk: 0.4762
Mse: 0.5346
Rmse: 0.7312

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	0.0625	2	5.4166	0.0	5.4166	2.3274
No log	0.125	4	2.5049	0.0351	2.5049	1.5827
No log	0.1875	6	1.5041	-0.0213	1.5041	1.2264
No log	0.25	8	0.7758	0.2609	0.7758	0.8808
No log	0.3125	10	0.4933	0.2800	0.4933	0.7024
No log	0.375	12	0.4944	0.125	0.4944	0.7031
No log	0.4375	14	0.4863	0.125	0.4863	0.6973
No log	0.5	16	0.4900	0.4444	0.4900	0.7000
No log	0.5625	18	0.6735	0.4	0.6735	0.8207
No log	0.625	20	0.7644	0.3143	0.7644	0.8743
No log	0.6875	22	0.5577	0.4375	0.5577	0.7468
No log	0.75	24	0.4905	0.4375	0.4905	0.7004
No log	0.8125	26	0.5815	0.4923	0.5815	0.7626
No log	0.875	28	0.5538	0.5946	0.5538	0.7442
No log	0.9375	30	0.6760	0.5714	0.6760	0.8222
No log	1.0	32	0.7098	0.5412	0.7098	0.8425
No log	1.0625	34	0.6816	0.5385	0.6816	0.8256
No log	1.125	36	0.5670	0.5263	0.5670	0.7530
No log	1.1875	38	0.4522	0.6301	0.4522	0.6724
No log	1.25	40	0.6126	0.3333	0.6126	0.7827
No log	1.3125	42	0.6748	0.2373	0.6748	0.8215
No log	1.375	44	0.5712	0.3529	0.5712	0.7558
No log	1.4375	46	0.4842	0.3226	0.4842	0.6959
No log	1.5	48	0.5778	0.3824	0.5778	0.7601
No log	1.5625	50	0.7330	0.4179	0.7330	0.8561
No log	1.625	52	0.6933	0.4545	0.6933	0.8327
No log	1.6875	54	0.5763	0.2857	0.5763	0.7591
No log	1.75	56	0.5852	0.2857	0.5852	0.7650
No log	1.8125	58	0.5831	0.2857	0.5831	0.7636
No log	1.875	60	0.6184	0.2857	0.6184	0.7864
No log	1.9375	62	0.7157	0.4658	0.7157	0.8460
No log	2.0	64	0.7613	0.5	0.7613	0.8725
No log	2.0625	66	0.6182	0.5185	0.6182	0.7863
No log	2.125	68	0.5336	0.3855	0.5336	0.7305
No log	2.1875	70	0.5219	0.5000	0.5219	0.7224
No log	2.25	72	0.5577	0.5263	0.5577	0.7468
No log	2.3125	74	0.5510	0.5263	0.5510	0.7423
No log	2.375	76	0.5186	0.5263	0.5186	0.7201
No log	2.4375	78	0.5515	0.4507	0.5515	0.7426
No log	2.5	80	0.6062	0.4545	0.6062	0.7786
No log	2.5625	82	0.5508	0.4545	0.5508	0.7422
No log	2.625	84	0.5112	0.4923	0.5112	0.7150
No log	2.6875	86	0.4703	0.5970	0.4703	0.6858
No log	2.75	88	0.4903	0.5714	0.4903	0.7002
No log	2.8125	90	0.5394	0.5185	0.5394	0.7345
No log	2.875	92	0.5901	0.5610	0.5901	0.7682
No log	2.9375	94	0.6723	0.4667	0.6723	0.8199
No log	3.0	96	0.5853	0.5610	0.5853	0.7650
No log	3.0625	98	0.4652	0.5833	0.4652	0.6821
No log	3.125	100	0.4552	0.4179	0.4552	0.6747
No log	3.1875	102	0.4639	0.3438	0.4639	0.6811
No log	3.25	104	0.4307	0.3333	0.4307	0.6563
No log	3.3125	106	0.3963	0.4828	0.3963	0.6295
No log	3.375	108	0.4475	0.5217	0.4475	0.6690
No log	3.4375	110	0.5755	0.5352	0.5755	0.7586
No log	3.5	112	0.7003	0.5	0.7003	0.8369
No log	3.5625	114	0.7191	0.5	0.7191	0.8480
No log	3.625	116	0.6710	0.56	0.6710	0.8191
No log	3.6875	118	0.5742	0.5063	0.5742	0.7578
No log	3.75	120	0.5119	0.5714	0.5119	0.7155
No log	3.8125	122	0.5224	0.5618	0.5224	0.7227
No log	3.875	124	0.5361	0.5000	0.5361	0.7322
No log	3.9375	126	0.5704	0.5500	0.5704	0.7552
No log	4.0	128	0.6063	0.56	0.6063	0.7787
No log	4.0625	130	0.5946	0.56	0.5946	0.7711
No log	4.125	132	0.5748	0.56	0.5748	0.7582
No log	4.1875	134	0.5537	0.5063	0.5537	0.7441
No log	4.25	136	0.5431	0.3200	0.5431	0.7369
No log	4.3125	138	0.5395	0.3200	0.5395	0.7345
No log	4.375	140	0.5331	0.3200	0.5331	0.7301
No log	4.4375	142	0.5383	0.3684	0.5383	0.7337
No log	4.5	144	0.5621	0.3662	0.5621	0.7498
No log	4.5625	146	0.6018	0.475	0.6018	0.7757
No log	4.625	148	0.6055	0.48	0.6055	0.7781
No log	4.6875	150	0.5942	0.5135	0.5942	0.7709
No log	4.75	152	0.5597	0.5	0.5597	0.7481
No log	4.8125	154	0.5537	0.3662	0.5537	0.7441
No log	4.875	156	0.5479	0.3662	0.5479	0.7402
No log	4.9375	158	0.5442	0.3684	0.5442	0.7377
No log	5.0	160	0.5334	0.3684	0.5334	0.7303
No log	5.0625	162	0.5175	0.3636	0.5175	0.7194
No log	5.125	164	0.5167	0.5161	0.5167	0.7188
No log	5.1875	166	0.5354	0.5217	0.5354	0.7317
No log	5.25	168	0.5350	0.5217	0.5350	0.7314
No log	5.3125	170	0.5526	0.5217	0.5526	0.7434
No log	5.375	172	0.5813	0.5217	0.5813	0.7625
No log	5.4375	174	0.6695	0.4658	0.6695	0.8182
No log	5.5	176	0.7075	0.4658	0.7075	0.8411
No log	5.5625	178	0.6396	0.5217	0.6396	0.7998
No log	5.625	180	0.5524	0.5075	0.5524	0.7433
No log	5.6875	182	0.5372	0.3684	0.5372	0.7329
No log	5.75	184	0.5397	0.3200	0.5397	0.7347
No log	5.8125	186	0.5319	0.4324	0.5319	0.7293
No log	5.875	188	0.5167	0.3200	0.5167	0.7188
No log	5.9375	190	0.5004	0.3636	0.5004	0.7074
No log	6.0	192	0.4985	0.5075	0.4985	0.7060
No log	6.0625	194	0.5123	0.5075	0.5123	0.7157
No log	6.125	196	0.5223	0.5161	0.5223	0.7227
No log	6.1875	198	0.5205	0.5075	0.5205	0.7214
No log	6.25	200	0.5261	0.4935	0.5261	0.7254
No log	6.3125	202	0.5326	0.4935	0.5326	0.7298
No log	6.375	204	0.5493	0.4935	0.5493	0.7412
No log	6.4375	206	0.5546	0.5610	0.5546	0.7447
No log	6.5	208	0.5672	0.5610	0.5672	0.7531
No log	6.5625	210	0.5774	0.4444	0.5774	0.7599
No log	6.625	212	0.5948	0.5618	0.5948	0.7712
No log	6.6875	214	0.6195	0.5055	0.6195	0.7871
No log	6.75	216	0.6590	0.4255	0.6590	0.8118
No log	6.8125	218	0.6449	0.4878	0.6449	0.8031
No log	6.875	220	0.6103	0.4935	0.6103	0.7812
No log	6.9375	222	0.5808	0.4935	0.5808	0.7621
No log	7.0	224	0.5328	0.5075	0.5328	0.7299
No log	7.0625	226	0.5042	0.3636	0.5042	0.7101
No log	7.125	228	0.4976	0.3636	0.4976	0.7054
No log	7.1875	230	0.4927	0.3607	0.4927	0.7019
No log	7.25	232	0.4917	0.3607	0.4917	0.7012
No log	7.3125	234	0.4978	0.5161	0.4978	0.7056
No log	7.375	236	0.5040	0.5161	0.5040	0.7099
No log	7.4375	238	0.5162	0.5161	0.5162	0.7185
No log	7.5	240	0.5327	0.4762	0.5327	0.7299
No log	7.5625	242	0.5346	0.4762	0.5346	0.7311
No log	7.625	244	0.5338	0.4762	0.5338	0.7306
No log	7.6875	246	0.5305	0.5075	0.5305	0.7284
No log	7.75	248	0.5290	0.5	0.5290	0.7273
No log	7.8125	250	0.5438	0.3684	0.5438	0.7374
No log	7.875	252	0.5543	0.3704	0.5543	0.7445
No log	7.9375	254	0.5550	0.3704	0.5550	0.7450
No log	8.0	256	0.5529	0.4935	0.5529	0.7436
No log	8.0625	258	0.5586	0.4615	0.5586	0.7474
No log	8.125	260	0.5595	0.4658	0.5595	0.7480
No log	8.1875	262	0.5561	0.48	0.5561	0.7457
No log	8.25	264	0.5503	0.4706	0.5503	0.7418
No log	8.3125	266	0.5495	0.4706	0.5495	0.7413
No log	8.375	268	0.5457	0.4706	0.5457	0.7387
No log	8.4375	270	0.5386	0.4706	0.5386	0.7339
No log	8.5	272	0.5308	0.5075	0.5308	0.7286
No log	8.5625	274	0.5243	0.5	0.5243	0.7241
No log	8.625	276	0.5227	0.3662	0.5227	0.7230
No log	8.6875	278	0.5228	0.3662	0.5228	0.7230
No log	8.75	280	0.5199	0.3662	0.5199	0.7211
No log	8.8125	282	0.5163	0.3662	0.5163	0.7185
No log	8.875	284	0.5157	0.5161	0.5157	0.7181
No log	8.9375	286	0.5175	0.4762	0.5175	0.7194
No log	9.0	288	0.5187	0.4762	0.5187	0.7202
No log	9.0625	290	0.5189	0.4762	0.5189	0.7204
No log	9.125	292	0.5181	0.4762	0.5181	0.7198
No log	9.1875	294	0.5177	0.5161	0.5177	0.7195
No log	9.25	296	0.5176	0.3636	0.5176	0.7194
No log	9.3125	298	0.5188	0.3636	0.5188	0.7203
No log	9.375	300	0.5204	0.3636	0.5204	0.7214
No log	9.4375	302	0.5217	0.3636	0.5217	0.7223
No log	9.5	304	0.5227	0.3636	0.5227	0.7230
No log	9.5625	306	0.5251	0.4762	0.5251	0.7247
No log	9.625	308	0.5279	0.4762	0.5279	0.7266
No log	9.6875	310	0.5302	0.4762	0.5302	0.7282
No log	9.75	312	0.5319	0.4762	0.5319	0.7293
No log	9.8125	314	0.5328	0.4762	0.5328	0.7300
No log	9.875	316	0.5338	0.4762	0.5338	0.7306
No log	9.9375	318	0.5343	0.4762	0.5343	0.7310
No log	10.0	320	0.5346	0.4762	0.5346	0.7312

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 19, 2024
Updated: Nov 19, 2024