Arabic_FineTuningAraBERT_AugV5_k5_task5_organization_fold0

MayBashendy/Arabic_FineTuningAraBERT_AugV5_k5_task5_organization_fold0

Arabic_FineTuningAraBERT_AugV5_k5_task5_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. --

Downloads · 30 days

19% of all-time downloads

All-time downloads

Public

Parameters

135M

541 MB on disk

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.safetensors541 MB · 100%

At a glance

Task: Text Classification
Library: transformers
Model type: bert
Access: Public
Created: Nov 25, 2024
Updated: Nov 25, 2024
SHA: 20a1de8a

Try a prompt

Base models

aubmindlab/bert-base-arabertv02

Model card

From the Hugging Face model README

Arabic_FineTuningAraBERT_AugV5_k5_task5_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: 0.6993
Qwk: 0.7347
Mse: 0.6993
Rmse: 0.8362

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	0.0667	2	2.1177	0.0402	2.1177	1.4552
No log	0.1333	4	0.8728	0.3640	0.8728	0.9342
No log	0.2	6	0.7501	0.4096	0.7501	0.8661
No log	0.2667	8	0.7751	0.3208	0.7751	0.8804
No log	0.3333	10	0.7977	0.3208	0.7977	0.8931
No log	0.4	12	0.8042	0.3657	0.8042	0.8968
No log	0.4667	14	0.7728	0.4096	0.7728	0.8791
No log	0.5333	16	0.7226	0.3511	0.7226	0.8501
No log	0.6	18	0.7659	0.3548	0.7659	0.8752
No log	0.6667	20	0.8416	0.4257	0.8416	0.9174
No log	0.7333	22	0.9516	0.2982	0.9516	0.9755
No log	0.8	24	1.0230	0.1883	1.0230	1.0114
No log	0.8667	26	0.8888	0.4242	0.8888	0.9428
No log	0.9333	28	0.9629	0.5729	0.9629	0.9813
No log	1.0	30	0.9223	0.5354	0.9223	0.9603
No log	1.0667	32	0.8128	0.5511	0.8128	0.9016
No log	1.1333	34	0.6906	0.7027	0.6906	0.8310
No log	1.2	36	0.5956	0.5033	0.5956	0.7717
No log	1.2667	38	0.5713	0.5410	0.5713	0.7558
No log	1.3333	40	0.5619	0.5189	0.5619	0.7496
No log	1.4	42	0.5726	0.5033	0.5726	0.7567
No log	1.4667	44	0.6299	0.4984	0.6299	0.7937
No log	1.5333	46	0.6960	0.4792	0.6960	0.8343
No log	1.6	48	0.7717	0.4834	0.7717	0.8785
No log	1.6667	50	0.7537	0.4403	0.7537	0.8682
No log	1.7333	52	0.7346	0.4403	0.7346	0.8571
No log	1.8	54	0.7063	0.4403	0.7063	0.8404
No log	1.8667	56	0.6644	0.4403	0.6644	0.8151
No log	1.9333	58	0.6399	0.4403	0.6399	0.7999
No log	2.0	60	0.6283	0.3962	0.6283	0.7927
No log	2.0667	62	0.6503	0.3511	0.6503	0.8064
No log	2.1333	64	0.7064	0.4516	0.7064	0.8405
No log	2.2	66	0.7319	0.5511	0.7319	0.8555
No log	2.2667	68	0.6551	0.6247	0.6551	0.8094
No log	2.3333	70	0.5548	0.5692	0.5548	0.7449
No log	2.4	72	0.5045	0.6375	0.5045	0.7103
No log	2.4667	74	0.4833	0.6375	0.4833	0.6952
No log	2.5333	76	0.4603	0.7721	0.4603	0.6784
No log	2.6	78	0.4509	0.6439	0.4509	0.6715
No log	2.6667	80	0.4439	0.6707	0.4439	0.6663
No log	2.7333	82	0.4413	0.7458	0.4413	0.6643
No log	2.8	84	0.4420	0.7632	0.4420	0.6648
No log	2.8667	86	0.4468	0.6694	0.4468	0.6684
No log	2.9333	88	0.4477	0.7165	0.4477	0.6691
No log	3.0	90	0.5384	0.7691	0.5384	0.7338
No log	3.0667	92	0.7320	0.6901	0.7320	0.8556
No log	3.1333	94	0.8247	0.6407	0.8247	0.9082
No log	3.2	96	0.7852	0.6901	0.7852	0.8861
No log	3.2667	98	0.6185	0.7430	0.6185	0.7865
No log	3.3333	100	0.4791	0.7176	0.4791	0.6921
No log	3.4	102	0.4487	0.7176	0.4487	0.6698
No log	3.4667	104	0.4543	0.6659	0.4543	0.6740
No log	3.5333	106	0.4951	0.7351	0.4951	0.7037
No log	3.6	108	0.5772	0.7556	0.5772	0.7598
No log	3.6667	110	0.6486	0.7556	0.6486	0.8054
No log	3.7333	112	0.6859	0.6934	0.6859	0.8282
No log	3.8	114	0.7572	0.6675	0.7572	0.8702
No log	3.8667	116	0.7774	0.6675	0.7774	0.8817
No log	3.9333	118	0.7279	0.6934	0.7279	0.8532
No log	4.0	120	0.6572	0.7190	0.6572	0.8107
No log	4.0667	122	0.6263	0.6977	0.6263	0.7914
No log	4.1333	124	0.6016	0.6977	0.6016	0.7757
No log	4.2	126	0.6174	0.7351	0.6174	0.7857
No log	4.2667	128	0.6310	0.7347	0.6310	0.7943
No log	4.3333	130	0.6560	0.7347	0.6560	0.8099
No log	4.4	132	0.6791	0.7347	0.6791	0.8241
No log	4.4667	134	0.7392	0.7347	0.7392	0.8598
No log	4.5333	136	0.7089	0.7347	0.7089	0.8419
No log	4.6	138	0.6203	0.7566	0.6203	0.7876
No log	4.6667	140	0.5356	0.7588	0.5356	0.7318
No log	4.7333	142	0.5039	0.7267	0.5039	0.7099
No log	4.8	144	0.4822	0.6854	0.4822	0.6944
No log	4.8667	146	0.4757	0.7098	0.4757	0.6897
No log	4.9333	148	0.4833	0.6854	0.4833	0.6952
No log	5.0	150	0.5275	0.7495	0.5275	0.7263
No log	5.0667	152	0.6204	0.7566	0.6204	0.7876
No log	5.1333	154	0.6958	0.7556	0.6958	0.8342
No log	5.2	156	0.7398	0.7536	0.7398	0.8601
No log	5.2667	158	0.7223	0.7536	0.7223	0.8499
No log	5.3333	160	0.6656	0.7347	0.6656	0.8159
No log	5.4	162	0.6122	0.7347	0.6122	0.7824
No log	5.4667	164	0.6110	0.7347	0.6110	0.7817
No log	5.5333	166	0.6555	0.7347	0.6555	0.8096
No log	5.6	168	0.6878	0.7347	0.6878	0.8294
No log	5.6667	170	0.7082	0.7347	0.7082	0.8415
No log	5.7333	172	0.7100	0.7347	0.7100	0.8426
No log	5.8	174	0.6678	0.7347	0.6678	0.8172
No log	5.8667	176	0.6909	0.7347	0.6909	0.8312
No log	5.9333	178	0.7635	0.6584	0.7635	0.8738
No log	6.0	180	0.8472	0.6584	0.8472	0.9204
No log	6.0667	182	0.8899	0.6230	0.8899	0.9434
No log	6.1333	184	0.8708	0.6230	0.8708	0.9332
No log	6.2	186	0.7835	0.7347	0.7835	0.8851
No log	6.2667	188	0.6693	0.7351	0.6693	0.8181
No log	6.3333	190	0.5965	0.7351	0.5965	0.7723
No log	6.4	192	0.5673	0.7351	0.5673	0.7532
No log	6.4667	194	0.5572	0.7588	0.5572	0.7464
No log	6.5333	196	0.5681	0.7588	0.5681	0.7537
No log	6.6	198	0.5794	0.7267	0.5794	0.7612
No log	6.6667	200	0.6058	0.7267	0.6058	0.7783
No log	6.7333	202	0.6140	0.7267	0.6140	0.7836
No log	6.8	204	0.5987	0.7267	0.5987	0.7738
No log	6.8667	206	0.6030	0.7267	0.6030	0.7765
No log	6.9333	208	0.6191	0.7267	0.6191	0.7868
No log	7.0	210	0.6582	0.7269	0.6582	0.8113
No log	7.0667	212	0.7250	0.7566	0.7250	0.8515
No log	7.1333	214	0.7778	0.6230	0.7778	0.8819
No log	7.2	216	0.8343	0.6230	0.8343	0.9134
No log	7.2667	218	0.8661	0.6230	0.8661	0.9306
No log	7.3333	220	0.8493	0.6230	0.8493	0.9216
No log	7.4	222	0.7897	0.6230	0.7897	0.8887
No log	7.4667	224	0.7253	0.7347	0.7253	0.8516
No log	7.5333	226	0.6975	0.7347	0.6975	0.8351
No log	7.6	228	0.7012	0.7347	0.7012	0.8374
No log	7.6667	230	0.7368	0.7347	0.7368	0.8584
No log	7.7333	232	0.7596	0.6584	0.7596	0.8715
No log	7.8	234	0.7595	0.6584	0.7595	0.8715
No log	7.8667	236	0.7628	0.6584	0.7628	0.8734
No log	7.9333	238	0.7373	0.7347	0.7373	0.8587
No log	8.0	240	0.7022	0.7347	0.7022	0.8380
No log	8.0667	242	0.6777	0.7566	0.6777	0.8232
No log	8.1333	244	0.6526	0.7566	0.6526	0.8079
No log	8.2	246	0.6476	0.7566	0.6476	0.8047
No log	8.2667	248	0.6596	0.7347	0.6596	0.8122
No log	8.3333	250	0.6802	0.7347	0.6802	0.8247
No log	8.4	252	0.6958	0.7347	0.6958	0.8341
No log	8.4667	254	0.7152	0.7347	0.7152	0.8457
No log	8.5333	256	0.7309	0.7347	0.7309	0.8549
No log	8.6	258	0.7434	0.7347	0.7434	0.8622
No log	8.6667	260	0.7391	0.7347	0.7391	0.8597
No log	8.7333	262	0.7382	0.7347	0.7382	0.8592
No log	8.8	264	0.7546	0.7347	0.7546	0.8687
No log	8.8667	266	0.7638	0.7347	0.7638	0.8739
No log	8.9333	268	0.7598	0.7347	0.7598	0.8717
No log	9.0	270	0.7399	0.7347	0.7399	0.8602
No log	9.0667	272	0.7196	0.7347	0.7196	0.8483
No log	9.1333	274	0.7000	0.7347	0.7000	0.8366
No log	9.2	276	0.6879	0.7347	0.6879	0.8294
No log	9.2667	278	0.6840	0.7347	0.6840	0.8271
No log	9.3333	280	0.6828	0.7347	0.6828	0.8263
No log	9.4	282	0.6785	0.7347	0.6785	0.8237
No log	9.4667	284	0.6781	0.7347	0.6781	0.8235
No log	9.5333	286	0.6800	0.7347	0.6800	0.8246
No log	9.6	288	0.6842	0.7347	0.6842	0.8271
No log	9.6667	290	0.6896	0.7347	0.6896	0.8304
No log	9.7333	292	0.6953	0.7347	0.6953	0.8338
No log	9.8	294	0.6966	0.7347	0.6966	0.8346
No log	9.8667	296	0.6977	0.7347	0.6977	0.8353
No log	9.9333	298	0.6991	0.7347	0.6991	0.8361
No log	10.0	300	0.6993	0.7347	0.6993	0.8362

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