ArabicNewSplits6_WithDuplicationsForScore5_FineTuningAraBERT_run3_AugV5_k5_task3_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: 0.9277
• Qwk: 0.2258
• Mse: 0.9277
• Rmse: 0.9632

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	0.0741	2	3.4327	-0.0138	3.4327	1.8527
No log	0.1481	4	1.8032	-0.0070	1.8032	1.3428
No log	0.2222	6	1.0100	0.0588	1.0100	1.0050
No log	0.2963	8	0.7966	0.2621	0.7966	0.8925
No log	0.3704	10	0.5547	0.0569	0.5547	0.7448
No log	0.4444	12	0.6676	0.0	0.6676	0.8171
No log	0.5185	14	0.6720	-0.0732	0.6720	0.8197
No log	0.5926	16	0.5899	0.0	0.5899	0.7680
No log	0.6667	18	0.7101	0.1304	0.7101	0.8426
No log	0.7407	20	0.8264	0.1111	0.8264	0.9091
No log	0.8148	22	0.6553	0.1913	0.6553	0.8095
No log	0.8889	24	0.5689	0.0	0.5689	0.7542
No log	0.9630	26	0.5986	0.0	0.5986	0.7737
No log	1.0370	28	0.5950	0.0	0.5950	0.7714
No log	1.1111	30	0.5897	-0.0081	0.5897	0.7679
No log	1.1852	32	0.6479	0.1905	0.6479	0.8049
No log	1.2593	34	0.6805	0.0899	0.6805	0.8249
No log	1.3333	36	0.6265	0.1895	0.6265	0.7915
No log	1.4074	38	0.6300	-0.0233	0.6300	0.7937
No log	1.4815	40	0.6714	-0.0794	0.6714	0.8194
No log	1.5556	42	0.6276	0.1667	0.6276	0.7922
No log	1.6296	44	0.9783	0.0578	0.9783	0.9891
No log	1.7037	46	1.2270	0.0843	1.2270	1.1077
No log	1.7778	48	1.0209	0.1111	1.0209	1.0104
No log	1.8519	50	0.6878	0.1398	0.6878	0.8294
No log	1.9259	52	0.5983	0.1407	0.5983	0.7735
No log	2.0	54	0.8161	0.0769	0.8161	0.9034
No log	2.0741	56	0.9257	0.0769	0.9257	0.9621
No log	2.1481	58	0.8293	0.0222	0.8293	0.9107
No log	2.2222	60	0.6871	0.0	0.6871	0.8289
No log	2.2963	62	0.5869	-0.0159	0.5869	0.7661
No log	2.3704	64	0.6065	-0.0963	0.6065	0.7788
No log	2.4444	66	0.6771	0.1813	0.6771	0.8229
No log	2.5185	68	0.6802	0.1429	0.6802	0.8247
No log	2.5926	70	0.6055	-0.0963	0.6055	0.7781
No log	2.6667	72	0.6138	-0.0963	0.6138	0.7834
No log	2.7407	74	0.7214	0.0	0.7214	0.8493
No log	2.8148	76	0.8104	0.1556	0.8104	0.9002
No log	2.8889	78	0.6460	0.0071	0.6460	0.8037
No log	2.9630	80	0.6301	-0.0219	0.6301	0.7938
No log	3.0370	82	0.6749	0.1329	0.6749	0.8215
No log	3.1111	84	0.6551	0.1667	0.6551	0.8094
No log	3.1852	86	0.6262	0.0811	0.6262	0.7913
No log	3.2593	88	0.6553	0.1429	0.6553	0.8095
No log	3.3333	90	0.7509	0.1475	0.7509	0.8666
No log	3.4074	92	0.8701	0.1154	0.8701	0.9328
No log	3.4815	94	0.7217	0.2332	0.7217	0.8495
No log	3.5556	96	0.7035	0.1732	0.7035	0.8387
No log	3.6296	98	0.8124	0.1443	0.8124	0.9013
No log	3.7037	100	0.6816	0.1381	0.6816	0.8256
No log	3.7778	102	0.6060	0.1220	0.6060	0.7784
No log	3.8519	104	0.5623	0.4083	0.5623	0.7499
No log	3.9259	106	0.6486	0.1568	0.6486	0.8054
No log	4.0	108	0.7744	0.1515	0.7744	0.8800
No log	4.0741	110	0.7345	0.0968	0.7345	0.8570
No log	4.1481	112	0.6640	0.2558	0.6640	0.8149
No log	4.2222	114	0.7327	0.1209	0.7327	0.8560
No log	4.2963	116	0.8606	0.1481	0.8606	0.9277
No log	4.3704	118	0.8474	0.1456	0.8474	0.9206
No log	4.4444	120	0.8145	0.0918	0.8145	0.9025
No log	4.5185	122	0.7610	0.0	0.7610	0.8724
No log	4.5926	124	0.7834	0.1304	0.7834	0.8851
No log	4.6667	126	0.8012	0.2157	0.8012	0.8951
No log	4.7407	128	0.8592	0.1610	0.8592	0.9269
No log	4.8148	130	0.9131	0.2348	0.9131	0.9556
No log	4.8889	132	0.9230	0.1644	0.9230	0.9607
No log	4.9630	134	0.8539	0.2479	0.8539	0.9241
No log	5.0370	136	0.9302	0.2065	0.9302	0.9645
No log	5.1111	138	0.9865	0.2195	0.9865	0.9932
No log	5.1852	140	1.2236	-0.0036	1.2236	1.1061
No log	5.2593	142	1.2317	0.0	1.2317	1.1098
No log	5.3333	144	0.9968	0.1867	0.9968	0.9984
No log	5.4074	146	0.8571	0.2372	0.8571	0.9258
No log	5.4815	148	0.8520	0.1273	0.8520	0.9230
No log	5.5556	150	0.8727	0.2070	0.8727	0.9342
No log	5.6296	152	0.7926	0.2222	0.7926	0.8903
No log	5.7037	154	0.8422	0.3214	0.8422	0.9177
No log	5.7778	156	1.0752	0.1719	1.0752	1.0369
No log	5.8519	158	1.1500	0.1557	1.1500	1.0724
No log	5.9259	160	1.0272	0.1579	1.0272	1.0135
No log	6.0	162	0.8289	0.1379	0.8289	0.9104
No log	6.0741	164	0.7636	0.2300	0.7636	0.8739
No log	6.1481	166	0.6725	0.2941	0.6725	0.8201
No log	6.2222	168	0.6452	0.3407	0.6452	0.8033
No log	6.2963	170	0.6650	0.2990	0.6650	0.8154
No log	6.3704	172	0.7810	0.2661	0.7810	0.8837
No log	6.4444	174	0.9668	0.1475	0.9668	0.9833
No log	6.5185	176	1.1209	0.1235	1.1209	1.0587
No log	6.5926	178	1.0576	0.1475	1.0576	1.0284
No log	6.6667	180	0.9140	0.1933	0.9140	0.9560
No log	6.7407	182	0.9055	0.1933	0.9055	0.9516
No log	6.8148	184	0.9190	0.1605	0.9190	0.9587
No log	6.8889	186	0.9182	0.1867	0.9182	0.9582
No log	6.9630	188	0.9953	0.1597	0.9953	0.9977
No log	7.0370	190	1.0748	0.1621	1.0748	1.0367
No log	7.1111	192	1.0673	0.1621	1.0673	1.0331
No log	7.1852	194	0.9411	0.2203	0.9411	0.9701
No log	7.2593	196	0.9066	0.3214	0.9066	0.9522
No log	7.3333	198	0.9778	0.2188	0.9778	0.9888
No log	7.4074	200	1.0799	0.1886	1.0799	1.0392
No log	7.4815	202	1.0738	0.1886	1.0738	1.0362
No log	7.5556	204	1.1606	0.1608	1.1606	1.0773
No log	7.6296	206	1.1047	0.2174	1.1047	1.0510
No log	7.7037	208	1.0251	0.2180	1.0251	1.0125
No log	7.7778	210	0.9981	0.2180	0.9981	0.9990
No log	7.8519	212	0.9812	0.2180	0.9812	0.9906
No log	7.9259	214	1.0026	0.2548	1.0026	1.0013
No log	8.0	216	1.0404	0.2234	1.0404	1.0200
No log	8.0741	218	1.0466	0.2440	1.0466	1.0230
No log	8.1481	220	1.1114	0.1683	1.1114	1.0542
No log	8.2222	222	1.0756	0.2432	1.0756	1.0371
No log	8.2963	224	0.9831	0.2000	0.9831	0.9915
No log	8.3704	226	0.8634	0.3028	0.8634	0.9292
No log	8.4444	228	0.7966	0.3010	0.7966	0.8925
No log	8.5185	230	0.7944	0.3010	0.7944	0.8913
No log	8.5926	232	0.7872	0.3010	0.7872	0.8873
No log	8.6667	234	0.8069	0.3010	0.8069	0.8983
No log	8.7407	236	0.8735	0.3004	0.8735	0.9346
No log	8.8148	238	0.9924	0.2314	0.9924	0.9962
No log	8.8889	240	1.1300	0.2000	1.1300	1.0630
No log	8.9630	242	1.2167	0.1742	1.2167	1.1030
No log	9.0370	244	1.2420	0.1742	1.2420	1.1145
No log	9.1111	246	1.1916	0.1738	1.1916	1.0916
No log	9.1852	248	1.1207	0.2000	1.1207	1.0586
No log	9.2593	250	1.0352	0.2314	1.0352	1.0174
No log	9.3333	252	0.9582	0.1937	0.9582	0.9789
No log	9.4074	254	0.8966	0.2275	0.8966	0.9469
No log	9.4815	256	0.8806	0.2287	0.8806	0.9384
No log	9.5556	258	0.8706	0.2287	0.8706	0.9330
No log	9.6296	260	0.8711	0.2287	0.8711	0.9333
No log	9.7037	262	0.8832	0.1930	0.8832	0.9398
No log	9.7778	264	0.9009	0.2275	0.9009	0.9492
No log	9.8519	266	0.9142	0.2269	0.9142	0.9561
No log	9.9259	268	0.9227	0.2593	0.9227	0.9606
No log	10.0	270	0.9277	0.2258	0.9277	0.9632

Framework versions

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