ArabicNewSplits5_FineTuningAraBERT_run1_AugV5_k5_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: 0.7706
• Qwk: 0.6953
• Mse: 0.7706
• Rmse: 0.8778

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	2.4109	-0.0671	2.4109	1.5527
No log	0.1538	4	1.6134	0.0913	1.6134	1.2702
No log	0.2308	6	1.4357	0.1638	1.4357	1.1982
No log	0.3077	8	1.5779	0.1892	1.5779	1.2562
No log	0.3846	10	1.4304	0.1794	1.4304	1.1960
No log	0.4615	12	1.2416	0.1968	1.2416	1.1143
No log	0.5385	14	1.2161	0.2129	1.2161	1.1028
No log	0.6154	16	1.2394	0.1924	1.2394	1.1133
No log	0.6923	18	1.2069	0.2156	1.2069	1.0986
No log	0.7692	20	1.1912	0.3177	1.1912	1.0914
No log	0.8462	22	1.1846	0.3346	1.1846	1.0884
No log	0.9231	24	1.1449	0.4265	1.1449	1.0700
No log	1.0	26	1.0625	0.4151	1.0625	1.0308
No log	1.0769	28	1.0022	0.4599	1.0022	1.0011
No log	1.1538	30	0.9546	0.5112	0.9546	0.9770
No log	1.2308	32	1.0224	0.4902	1.0224	1.0111
No log	1.3077	34	1.1357	0.4757	1.1357	1.0657
No log	1.3846	36	0.9487	0.5540	0.9487	0.9740
No log	1.4615	38	0.9067	0.5309	0.9067	0.9522
No log	1.5385	40	0.9700	0.5086	0.9700	0.9849
No log	1.6154	42	0.9565	0.5007	0.9565	0.9780
No log	1.6923	44	0.9000	0.5323	0.9000	0.9487
No log	1.7692	46	0.9139	0.5652	0.9139	0.9560
No log	1.8462	48	1.0357	0.5070	1.0357	1.0177
No log	1.9231	50	1.1509	0.4888	1.1509	1.0728
No log	2.0	52	1.0404	0.4809	1.0404	1.0200
No log	2.0769	54	0.9230	0.5827	0.9230	0.9607
No log	2.1538	56	0.9124	0.5677	0.9124	0.9552
No log	2.2308	58	0.9005	0.5752	0.9005	0.9490
No log	2.3077	60	0.9586	0.5183	0.9586	0.9791
No log	2.3846	62	1.3769	0.4996	1.3769	1.1734
No log	2.4615	64	1.7101	0.3313	1.7101	1.3077
No log	2.5385	66	1.6519	0.3755	1.6519	1.2853
No log	2.6154	68	1.2261	0.4198	1.2261	1.1073
No log	2.6923	70	0.9166	0.5457	0.9166	0.9574
No log	2.7692	72	0.8767	0.6230	0.8767	0.9363
No log	2.8462	74	1.0182	0.5879	1.0182	1.0091
No log	2.9231	76	1.1582	0.5239	1.1582	1.0762
No log	3.0	78	1.0983	0.5565	1.0983	1.0480
No log	3.0769	80	0.9011	0.6226	0.9011	0.9493
No log	3.1538	82	0.8079	0.6715	0.8079	0.8988
No log	3.2308	84	0.7319	0.7088	0.7319	0.8555
No log	3.3077	86	0.7155	0.6983	0.7155	0.8459
No log	3.3846	88	0.7105	0.6594	0.7105	0.8429
No log	3.4615	90	0.7038	0.7006	0.7038	0.8389
No log	3.5385	92	0.7551	0.7286	0.7551	0.8690
No log	3.6154	94	0.9960	0.6166	0.9960	0.9980
No log	3.6923	96	1.0276	0.6174	1.0276	1.0137
No log	3.7692	98	0.8420	0.6687	0.8420	0.9176
No log	3.8462	100	0.7236	0.7295	0.7236	0.8507
No log	3.9231	102	0.7028	0.7086	0.7028	0.8384
No log	4.0	104	0.6905	0.7301	0.6905	0.8309
No log	4.0769	106	0.6973	0.7041	0.6973	0.8351
No log	4.1538	108	0.7096	0.7232	0.7096	0.8424
No log	4.2308	110	0.7860	0.7026	0.7860	0.8865
No log	4.3077	112	0.8212	0.6795	0.8212	0.9062
No log	4.3846	114	0.8827	0.6304	0.8827	0.9395
No log	4.4615	116	0.7835	0.7084	0.7835	0.8851
No log	4.5385	118	0.7488	0.7180	0.7488	0.8653
No log	4.6154	120	0.7925	0.7009	0.7925	0.8902
No log	4.6923	122	0.7968	0.7009	0.7968	0.8926
No log	4.7692	124	0.7734	0.6993	0.7734	0.8794
No log	4.8462	126	0.7699	0.7105	0.7699	0.8775
No log	4.9231	128	0.7315	0.7250	0.7315	0.8553
No log	5.0	130	0.6836	0.7292	0.6836	0.8268
No log	5.0769	132	0.6785	0.7025	0.6785	0.8237
No log	5.1538	134	0.6823	0.7134	0.6823	0.8260
No log	5.2308	136	0.6768	0.7006	0.6768	0.8227
No log	5.3077	138	0.6825	0.6907	0.6825	0.8261
No log	5.3846	140	0.6800	0.6907	0.6800	0.8246
No log	5.4615	142	0.6993	0.7284	0.6993	0.8362
No log	5.5385	144	0.7867	0.6973	0.7867	0.8870
No log	5.6154	146	0.9433	0.6194	0.9433	0.9712
No log	5.6923	148	0.9992	0.6214	0.9992	0.9996
No log	5.7692	150	0.8868	0.6354	0.8868	0.9417
No log	5.8462	152	0.7696	0.6956	0.7696	0.8773
No log	5.9231	154	0.7257	0.7158	0.7257	0.8519
No log	6.0	156	0.7370	0.7150	0.7370	0.8585
No log	6.0769	158	0.8360	0.6713	0.8360	0.9143
No log	6.1538	160	0.8873	0.6402	0.8873	0.9420
No log	6.2308	162	0.9168	0.6402	0.9168	0.9575
No log	6.3077	164	0.8332	0.6602	0.8332	0.9128
No log	6.3846	166	0.7603	0.6611	0.7603	0.8719
No log	6.4615	168	0.7417	0.6882	0.7417	0.8612
No log	6.5385	170	0.7152	0.7070	0.7152	0.8457
No log	6.6154	172	0.7019	0.7263	0.7019	0.8378
No log	6.6923	174	0.6956	0.7270	0.6956	0.8340
No log	6.7692	176	0.6798	0.7119	0.6798	0.8245
No log	6.8462	178	0.6880	0.7121	0.6880	0.8295
No log	6.9231	180	0.7352	0.7128	0.7352	0.8574
No log	7.0	182	0.7924	0.6963	0.7924	0.8902
No log	7.0769	184	0.7836	0.6963	0.7836	0.8852
No log	7.1538	186	0.7317	0.7168	0.7317	0.8554
No log	7.2308	188	0.6877	0.7001	0.6877	0.8293
No log	7.3077	190	0.6812	0.7055	0.6812	0.8253
No log	7.3846	192	0.6779	0.7020	0.6779	0.8233
No log	7.4615	194	0.6834	0.6931	0.6834	0.8267
No log	7.5385	196	0.7056	0.7218	0.7056	0.8400
No log	7.6154	198	0.7462	0.7108	0.7462	0.8638
No log	7.6923	200	0.7678	0.6879	0.7678	0.8763
No log	7.7692	202	0.7517	0.6941	0.7517	0.8670
No log	7.8462	204	0.7361	0.7126	0.7361	0.8580
No log	7.9231	206	0.7057	0.7256	0.7057	0.8400
No log	8.0	208	0.7065	0.7294	0.7065	0.8405
No log	8.0769	210	0.7078	0.7142	0.7078	0.8413
No log	8.1538	212	0.7144	0.7120	0.7144	0.8452
No log	8.2308	214	0.7026	0.7142	0.7026	0.8382
No log	8.3077	216	0.6833	0.7035	0.6833	0.8266
No log	8.3846	218	0.6801	0.7018	0.6801	0.8247
No log	8.4615	220	0.6918	0.7217	0.6918	0.8318
No log	8.5385	222	0.7094	0.7146	0.7094	0.8422
No log	8.6154	224	0.7302	0.7126	0.7302	0.8545
No log	8.6923	226	0.7724	0.6990	0.7724	0.8789
No log	8.7692	228	0.7982	0.6956	0.7982	0.8934
No log	8.8462	230	0.8026	0.6877	0.8026	0.8959
No log	8.9231	232	0.8090	0.6835	0.8090	0.8994
No log	9.0	234	0.7907	0.6877	0.7907	0.8892
No log	9.0769	236	0.7669	0.6879	0.7669	0.8758
No log	9.1538	238	0.7489	0.7000	0.7489	0.8654
No log	9.2308	240	0.7390	0.7126	0.7390	0.8597
No log	9.3077	242	0.7389	0.7126	0.7389	0.8596
No log	9.3846	244	0.7483	0.7126	0.7483	0.8650
No log	9.4615	246	0.7655	0.6953	0.7655	0.8750
No log	9.5385	248	0.7768	0.6879	0.7768	0.8814
No log	9.6154	250	0.7773	0.6879	0.7773	0.8817
No log	9.6923	252	0.7776	0.6879	0.7776	0.8818
No log	9.7692	254	0.7767	0.6879	0.7767	0.8813
No log	9.8462	256	0.7738	0.6953	0.7738	0.8797
No log	9.9231	258	0.7720	0.6953	0.7720	0.8787
No log	10.0	260	0.7706	0.6953	0.7706	0.8778

Framework versions

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