ArabicNewSplits8_FineTuningAraBERT_noAug_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: 0.8245
• Qwk: 0.5349
• Mse: 0.8245
• Rmse: 0.9080

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: 100

Training results

Training Loss	Epoch	Step	Validation Loss	Qwk	Mse	Rmse
No log	0.6667	2	3.2701	-0.0272	3.2701	1.8083
No log	1.3333	4	2.0230	0.0007	2.0230	1.4223
No log	2.0	6	1.0951	0.1104	1.0951	1.0465
No log	2.6667	8	1.0161	0.1628	1.0161	1.0080
No log	3.3333	10	1.0953	0.1021	1.0953	1.0466
No log	4.0	12	1.1892	0.1021	1.1892	1.0905
No log	4.6667	14	1.0553	0.1776	1.0553	1.0273
No log	5.3333	16	0.9292	0.2898	0.9292	0.9640
No log	6.0	18	0.7888	0.3714	0.7888	0.8882
No log	6.6667	20	0.7374	0.3963	0.7374	0.8587
No log	7.3333	22	0.7826	0.3813	0.7826	0.8847
No log	8.0	24	0.8569	0.4116	0.8569	0.9257
No log	8.6667	26	0.9253	0.5013	0.9253	0.9620
No log	9.3333	28	0.7979	0.5106	0.7979	0.8933
No log	10.0	30	0.7661	0.4928	0.7661	0.8753
No log	10.6667	32	0.8839	0.5284	0.8839	0.9401
No log	11.3333	34	0.8728	0.4542	0.8728	0.9342
No log	12.0	36	0.8213	0.4778	0.8213	0.9063
No log	12.6667	38	0.6915	0.5226	0.6915	0.8316
No log	13.3333	40	0.6675	0.5472	0.6675	0.8170
No log	14.0	42	0.6399	0.5100	0.6399	0.8000
No log	14.6667	44	0.6780	0.5783	0.6780	0.8234
No log	15.3333	46	0.6829	0.5861	0.6829	0.8264
No log	16.0	48	0.6859	0.5177	0.6859	0.8282
No log	16.6667	50	0.7491	0.5374	0.7491	0.8655
No log	17.3333	52	0.7679	0.5159	0.7679	0.8763
No log	18.0	54	0.7048	0.4740	0.7048	0.8395
No log	18.6667	56	0.6557	0.5296	0.6557	0.8097
No log	19.3333	58	0.6780	0.5760	0.6780	0.8234
No log	20.0	60	0.6692	0.5760	0.6692	0.8181
No log	20.6667	62	0.6269	0.5304	0.6269	0.7918
No log	21.3333	64	0.6342	0.5522	0.6342	0.7964
No log	22.0	66	0.7431	0.6271	0.7431	0.8620
No log	22.6667	68	0.7428	0.6271	0.7428	0.8619
No log	23.3333	70	0.6956	0.5706	0.6956	0.8340
No log	24.0	72	0.6998	0.5707	0.6998	0.8365
No log	24.6667	74	0.6652	0.5458	0.6652	0.8156
No log	25.3333	76	0.6259	0.5055	0.6259	0.7911
No log	26.0	78	0.6424	0.5304	0.6424	0.8015
No log	26.6667	80	0.8166	0.6271	0.8166	0.9037
No log	27.3333	82	0.9483	0.5556	0.9483	0.9738
No log	28.0	84	0.7602	0.6240	0.7602	0.8719
No log	28.6667	86	0.6924	0.5761	0.6924	0.8321
No log	29.3333	88	0.6957	0.5708	0.6957	0.8341
No log	30.0	90	0.7267	0.5758	0.7267	0.8525
No log	30.6667	92	0.8249	0.5546	0.8249	0.9082
No log	31.3333	94	0.9042	0.5498	0.9042	0.9509
No log	32.0	96	0.8384	0.5549	0.8384	0.9156
No log	32.6667	98	0.6593	0.5632	0.6593	0.8120
No log	33.3333	100	0.6320	0.5647	0.6320	0.7950
No log	34.0	102	0.6310	0.5488	0.6310	0.7944
No log	34.6667	104	0.6450	0.5712	0.6450	0.8031
No log	35.3333	106	0.8915	0.5318	0.8915	0.9442
No log	36.0	108	1.2787	0.3787	1.2787	1.1308
No log	36.6667	110	1.3123	0.3184	1.3123	1.1456
No log	37.3333	112	1.1050	0.3462	1.1050	1.0512
No log	38.0	114	0.8975	0.4934	0.8975	0.9474
No log	38.6667	116	0.6823	0.5737	0.6823	0.8260
No log	39.3333	118	0.6255	0.5775	0.6255	0.7909
No log	40.0	120	0.6292	0.5474	0.6292	0.7932
No log	40.6667	122	0.6513	0.5578	0.6513	0.8070
No log	41.3333	124	0.8106	0.5700	0.8106	0.9003
No log	42.0	126	1.0063	0.5181	1.0063	1.0031
No log	42.6667	128	1.0040	0.5338	1.0040	1.0020
No log	43.3333	130	0.8358	0.5524	0.8358	0.9142
No log	44.0	132	0.7352	0.5071	0.7352	0.8575
No log	44.6667	134	0.7255	0.5543	0.7255	0.8518
No log	45.3333	136	0.6951	0.5708	0.6951	0.8337
No log	46.0	138	0.7018	0.5625	0.7018	0.8377
No log	46.6667	140	0.7045	0.5457	0.7045	0.8394
No log	47.3333	142	0.7349	0.5457	0.7349	0.8573
No log	48.0	144	0.7991	0.5210	0.7991	0.8939
No log	48.6667	146	0.7839	0.5210	0.7839	0.8854
No log	49.3333	148	0.7769	0.5100	0.7769	0.8814
No log	50.0	150	0.7198	0.5254	0.7198	0.8484
No log	50.6667	152	0.7114	0.5424	0.7114	0.8434
No log	51.3333	154	0.7177	0.5430	0.7177	0.8472
No log	52.0	156	0.7458	0.5071	0.7458	0.8636
No log	52.6667	158	0.8203	0.5308	0.8203	0.9057
No log	53.3333	160	0.8864	0.5521	0.8864	0.9415
No log	54.0	162	0.8570	0.5652	0.8570	0.9258
No log	54.6667	164	0.7892	0.5281	0.7892	0.8884
No log	55.3333	166	0.7416	0.5041	0.7416	0.8612
No log	56.0	168	0.7590	0.5057	0.7590	0.8712
No log	56.6667	170	0.8131	0.5100	0.8131	0.9017
No log	57.3333	172	0.8186	0.5087	0.8186	0.9047
No log	58.0	174	0.8255	0.5004	0.8255	0.9086
No log	58.6667	176	0.7683	0.5182	0.7683	0.8765
No log	59.3333	178	0.7228	0.5845	0.7228	0.8502
No log	60.0	180	0.7169	0.5682	0.7169	0.8467
No log	60.6667	182	0.7477	0.5264	0.7477	0.8647
No log	61.3333	184	0.7659	0.5284	0.7659	0.8751
No log	62.0	186	0.7907	0.5300	0.7907	0.8892
No log	62.6667	188	0.7748	0.5300	0.7748	0.8802
No log	63.3333	190	0.7277	0.5435	0.7277	0.8530
No log	64.0	192	0.6938	0.5682	0.6938	0.8330
No log	64.6667	194	0.7109	0.5537	0.7109	0.8432
No log	65.3333	196	0.7568	0.4872	0.7568	0.8699
No log	66.0	198	0.8124	0.5328	0.8124	0.9013
No log	66.6667	200	0.8411	0.5328	0.8411	0.9171
No log	67.3333	202	0.8467	0.5622	0.8467	0.9201
No log	68.0	204	0.8666	0.5465	0.8666	0.9309
No log	68.6667	206	0.8513	0.5355	0.8513	0.9227
No log	69.3333	208	0.8169	0.5300	0.8169	0.9038
No log	70.0	210	0.7615	0.5216	0.7615	0.8726
No log	70.6667	212	0.7481	0.5216	0.7481	0.8649
No log	71.3333	214	0.7541	0.5216	0.7541	0.8684
No log	72.0	216	0.7755	0.5135	0.7755	0.8806
No log	72.6667	218	0.8363	0.5503	0.8363	0.9145
No log	73.3333	220	0.8890	0.5474	0.8890	0.9429
No log	74.0	222	0.9038	0.5216	0.9038	0.9507
No log	74.6667	224	0.9102	0.5216	0.9102	0.9540
No log	75.3333	226	0.8665	0.5276	0.8665	0.9309
No log	76.0	228	0.8022	0.4470	0.8022	0.8956
No log	76.6667	230	0.7517	0.4638	0.7517	0.8670
No log	77.3333	232	0.7167	0.4711	0.7167	0.8466
No log	78.0	234	0.7063	0.4711	0.7063	0.8404
No log	78.6667	236	0.7091	0.4897	0.7091	0.8421
No log	79.3333	238	0.7258	0.5041	0.7258	0.8519
No log	80.0	240	0.7583	0.5041	0.7583	0.8708
No log	80.6667	242	0.7985	0.4973	0.7985	0.8936
No log	81.3333	244	0.8054	0.4973	0.8054	0.8974
No log	82.0	246	0.7897	0.4973	0.7897	0.8886
No log	82.6667	248	0.7746	0.4973	0.7746	0.8801
No log	83.3333	250	0.7633	0.4959	0.7633	0.8736
No log	84.0	252	0.7711	0.5182	0.7711	0.8781
No log	84.6667	254	0.7830	0.5182	0.7830	0.8849
No log	85.3333	256	0.8057	0.5488	0.8057	0.8976
No log	86.0	258	0.8166	0.5488	0.8166	0.9037
No log	86.6667	260	0.8115	0.5488	0.8115	0.9008
No log	87.3333	262	0.7979	0.5381	0.7979	0.8932
No log	88.0	264	0.7697	0.5361	0.7697	0.8773
No log	88.6667	266	0.7499	0.5164	0.7499	0.8659
No log	89.3333	268	0.7414	0.5164	0.7414	0.8611
No log	90.0	270	0.7299	0.5599	0.7299	0.8544
No log	90.6667	272	0.7249	0.5599	0.7249	0.8514
No log	91.3333	274	0.7292	0.5599	0.7292	0.8539
No log	92.0	276	0.7410	0.5517	0.7410	0.8608
No log	92.6667	278	0.7620	0.5381	0.7620	0.8729
No log	93.3333	280	0.7856	0.5381	0.7856	0.8863
No log	94.0	282	0.8121	0.5230	0.8121	0.9012
No log	94.6667	284	0.8328	0.5374	0.8328	0.9126
No log	95.3333	286	0.8423	0.5374	0.8423	0.9178
No log	96.0	288	0.8483	0.5374	0.8483	0.9211
No log	96.6667	290	0.8486	0.5374	0.8486	0.9212
No log	97.3333	292	0.8443	0.5374	0.8443	0.9189
No log	98.0	294	0.8379	0.5374	0.8379	0.9154
No log	98.6667	296	0.8309	0.5374	0.8309	0.9115
No log	99.3333	298	0.8267	0.5374	0.8267	0.9092
No log	100.0	300	0.8245	0.5349	0.8245	0.9080

Framework versions

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