ArabicNewSplits4_FineTuningAraBERT_run2_AugV5_k7_task5_organization

MayBashendy/ArabicNewSplits4_FineTuningAraBERT_run2_AugV5_k7_task5_organization

ArabicNewSplits4_FineTuningAraBERT_run2_AugV5_k7_task5_organization 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: Dec 9, 2024
Updated: Dec 9, 2024
SHA: fe022e13

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Base models

aubmindlab/bert-base-arabertv02

Model card

From the Hugging Face model README

ArabicNewSplits4_FineTuningAraBERT_run2_AugV5_k7_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: 0.8440
Qwk: 0.6538
Mse: 0.8440
Rmse: 0.9187

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	0.0833	2	2.2801	0.0110	2.2801	1.5100
No log	0.1667	4	1.5576	0.1536	1.5576	1.2481
No log	0.25	6	1.4824	0.2143	1.4824	1.2176
No log	0.3333	8	1.6686	0.1771	1.6686	1.2917
No log	0.4167	10	1.8535	0.3225	1.8535	1.3614
No log	0.5	12	1.7993	0.2666	1.7993	1.3414
No log	0.5833	14	1.5314	0.2306	1.5314	1.2375
No log	0.6667	16	1.4093	0.0894	1.4093	1.1871
No log	0.75	18	1.4111	0.0645	1.4111	1.1879
No log	0.8333	20	1.4582	0.1100	1.4582	1.2076
No log	0.9167	22	1.5348	0.1640	1.5348	1.2389
No log	1.0	24	1.5607	0.1666	1.5607	1.2493
No log	1.0833	26	1.4991	0.1544	1.4991	1.2244
No log	1.1667	28	1.4834	0.2415	1.4834	1.2179
No log	1.25	30	1.5743	0.3694	1.5743	1.2547
No log	1.3333	32	1.6827	0.3806	1.6827	1.2972
No log	1.4167	34	1.6007	0.3697	1.6007	1.2652
No log	1.5	36	1.5247	0.3629	1.5247	1.2348
No log	1.5833	38	1.4770	0.3717	1.4770	1.2153
No log	1.6667	40	1.4601	0.3821	1.4601	1.2083
No log	1.75	42	1.4040	0.3927	1.4040	1.1849
No log	1.8333	44	1.3342	0.4129	1.3342	1.1551
No log	1.9167	46	1.4093	0.4039	1.4093	1.1872
No log	2.0	48	1.5169	0.4041	1.5169	1.2316
No log	2.0833	50	1.4422	0.4341	1.4422	1.2009
No log	2.1667	52	1.3798	0.4614	1.3798	1.1747
No log	2.25	54	1.4296	0.4562	1.4296	1.1957
No log	2.3333	56	1.7065	0.4242	1.7065	1.3063
No log	2.4167	58	1.9867	0.3870	1.9867	1.4095
No log	2.5	60	1.9045	0.4067	1.9045	1.3800
No log	2.5833	62	1.6496	0.4181	1.6496	1.2843
No log	2.6667	64	1.2948	0.4956	1.2948	1.1379
No log	2.75	66	1.1587	0.4611	1.1587	1.0764
No log	2.8333	68	1.1417	0.4958	1.1417	1.0685
No log	2.9167	70	1.1759	0.5056	1.1759	1.0844
No log	3.0	72	1.4146	0.5088	1.4146	1.1894
No log	3.0833	74	1.6077	0.4557	1.6077	1.2680
No log	3.1667	76	1.4586	0.4872	1.4586	1.2077
No log	3.25	78	1.2365	0.5166	1.2365	1.1120
No log	3.3333	80	1.0568	0.4921	1.0568	1.0280
No log	3.4167	82	1.0049	0.5104	1.0049	1.0025
No log	3.5	84	1.1509	0.5331	1.1509	1.0728
No log	3.5833	86	1.4415	0.5414	1.4415	1.2006
No log	3.6667	88	1.5532	0.5154	1.5532	1.2463
No log	3.75	90	1.3505	0.5408	1.3505	1.1621
No log	3.8333	92	1.0277	0.5635	1.0277	1.0138
No log	3.9167	94	0.8973	0.6225	0.8973	0.9473
No log	4.0	96	0.8354	0.6431	0.8354	0.9140
No log	4.0833	98	0.8635	0.6295	0.8635	0.9292
No log	4.1667	100	1.0863	0.5956	1.0863	1.0423
No log	4.25	102	1.2670	0.5616	1.2670	1.1256
No log	4.3333	104	1.1645	0.5828	1.1645	1.0791
No log	4.4167	106	0.9873	0.6122	0.9873	0.9936
No log	4.5	108	0.9100	0.6567	0.9100	0.9539
No log	4.5833	110	0.8662	0.6509	0.8662	0.9307
No log	4.6667	112	0.9046	0.6409	0.9046	0.9511
No log	4.75	114	0.9202	0.6428	0.9202	0.9593
No log	4.8333	116	0.8822	0.6550	0.8822	0.9393
No log	4.9167	118	0.9475	0.6252	0.9475	0.9734
No log	5.0	120	1.0359	0.6047	1.0359	1.0178
No log	5.0833	122	0.9872	0.6072	0.9872	0.9936
No log	5.1667	124	0.9260	0.6400	0.9260	0.9623
No log	5.25	126	0.9507	0.6236	0.9507	0.9751
No log	5.3333	128	1.0273	0.6351	1.0273	1.0136
No log	5.4167	130	1.0669	0.6153	1.0669	1.0329
No log	5.5	132	1.0070	0.6452	1.0070	1.0035
No log	5.5833	134	0.9257	0.6246	0.9257	0.9621
No log	5.6667	136	0.8463	0.6501	0.8463	0.9200
No log	5.75	138	0.7726	0.6642	0.7726	0.8790
No log	5.8333	140	0.7824	0.6825	0.7824	0.8845
No log	5.9167	142	0.8229	0.6644	0.8229	0.9071
No log	6.0	144	0.8901	0.6561	0.8901	0.9434
No log	6.0833	146	0.9494	0.6449	0.9494	0.9744
No log	6.1667	148	0.9519	0.6542	0.9519	0.9757
No log	6.25	150	0.8608	0.6569	0.8608	0.9278
No log	6.3333	152	0.8401	0.6832	0.8401	0.9166
No log	6.4167	154	0.8826	0.6583	0.8826	0.9395
No log	6.5	156	0.9828	0.6674	0.9828	0.9913
No log	6.5833	158	0.9888	0.6422	0.9888	0.9944
No log	6.6667	160	0.9957	0.6385	0.9957	0.9979
No log	6.75	162	0.9818	0.6401	0.9818	0.9909
No log	6.8333	164	0.9077	0.6396	0.9077	0.9527
No log	6.9167	166	0.8052	0.6378	0.8052	0.8974
No log	7.0	168	0.6977	0.7409	0.6977	0.8353
No log	7.0833	170	0.6561	0.7534	0.6561	0.8100
No log	7.1667	172	0.6571	0.7509	0.6571	0.8106
No log	7.25	174	0.7071	0.7443	0.7071	0.8409
No log	7.3333	176	0.8073	0.6569	0.8073	0.8985
No log	7.4167	178	0.9736	0.6561	0.9736	0.9867
No log	7.5	180	1.1918	0.6208	1.1918	1.0917
No log	7.5833	182	1.2868	0.6161	1.2868	1.1344
No log	7.6667	184	1.2482	0.6157	1.2482	1.1172
No log	7.75	186	1.1275	0.6280	1.1275	1.0619
No log	7.8333	188	0.9881	0.6444	0.9881	0.9940
No log	7.9167	190	0.8658	0.6623	0.8658	0.9305
No log	8.0	192	0.8192	0.6663	0.8192	0.9051
No log	8.0833	194	0.8227	0.6465	0.8227	0.9070
No log	8.1667	196	0.8633	0.6344	0.8633	0.9291
No log	8.25	198	0.8921	0.6406	0.8921	0.9445
No log	8.3333	200	0.8922	0.6406	0.8922	0.9446
No log	8.4167	202	0.8721	0.6406	0.8721	0.9338
No log	8.5	204	0.8391	0.6637	0.8391	0.9161
No log	8.5833	206	0.8371	0.6637	0.8371	0.9149
No log	8.6667	208	0.8575	0.6499	0.8575	0.9260
No log	8.75	210	0.8766	0.6499	0.8766	0.9363
No log	8.8333	212	0.8781	0.6499	0.8781	0.9371
No log	8.9167	214	0.8695	0.6583	0.8695	0.9325
No log	9.0	216	0.8729	0.6583	0.8729	0.9343
No log	9.0833	218	0.8677	0.6697	0.8677	0.9315
No log	9.1667	220	0.8625	0.6639	0.8625	0.9287
No log	9.25	222	0.8716	0.6697	0.8716	0.9336
No log	9.3333	224	0.8746	0.6697	0.8746	0.9352
No log	9.4167	226	0.8616	0.6697	0.8616	0.9283
No log	9.5	228	0.8468	0.6622	0.8468	0.9202
No log	9.5833	230	0.8397	0.6538	0.8397	0.9164
No log	9.6667	232	0.8301	0.6538	0.8301	0.9111
No log	9.75	234	0.8304	0.6538	0.8304	0.9113
No log	9.8333	236	0.8363	0.6538	0.8363	0.9145
No log	9.9167	238	0.8420	0.6538	0.8420	0.9176
No log	10.0	240	0.8440	0.6538	0.8440	0.9187

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: Dec 9, 2024
Updated: Dec 9, 2024