ArabicNewSplits6_WithDuplicationsForScore5_FineTuningAraBERT_run3_AugV5_k5_task2_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: 0.9475
• Qwk: 0.4310
• Mse: 0.9475
• Rmse: 0.9734

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	4.1597	-0.0116	4.1597	2.0395
No log	0.1333	4	2.5080	0.0358	2.5080	1.5837
No log	0.2	6	1.2416	0.0864	1.2416	1.1143
No log	0.2667	8	0.9489	-0.0046	0.9489	0.9741
No log	0.3333	10	0.7799	0.0359	0.7799	0.8831
No log	0.4	12	0.8802	0.0086	0.8802	0.9382
No log	0.4667	14	0.8336	0.0763	0.8336	0.9130
No log	0.5333	16	0.7976	0.1308	0.7976	0.8931
No log	0.6	18	0.7446	0.2024	0.7446	0.8629
No log	0.6667	20	0.7042	0.2103	0.7042	0.8392
No log	0.7333	22	0.6787	0.3235	0.6787	0.8238
No log	0.8	24	0.6741	0.2980	0.6741	0.8211
No log	0.8667	26	0.6767	0.2690	0.6767	0.8226
No log	0.9333	28	0.6517	0.3123	0.6517	0.8073
No log	1.0	30	0.6625	0.2705	0.6625	0.8139
No log	1.0667	32	0.6409	0.4105	0.6409	0.8006
No log	1.1333	34	0.6027	0.4332	0.6027	0.7763
No log	1.2	36	0.6123	0.4715	0.6123	0.7825
No log	1.2667	38	0.6779	0.4864	0.6779	0.8234
No log	1.3333	40	0.6342	0.5050	0.6342	0.7964
No log	1.4	42	0.6569	0.4112	0.6569	0.8105
No log	1.4667	44	0.6491	0.5061	0.6491	0.8056
No log	1.5333	46	0.6763	0.5323	0.6763	0.8224
No log	1.6	48	0.7094	0.5315	0.7094	0.8423
No log	1.6667	50	0.6930	0.5229	0.6930	0.8325
No log	1.7333	52	1.0749	0.3387	1.0749	1.0368
No log	1.8	54	0.9787	0.3800	0.9787	0.9893
No log	1.8667	56	0.7230	0.4869	0.7230	0.8503
No log	1.9333	58	0.9999	0.5099	0.9999	0.9999
No log	2.0	60	1.1302	0.3971	1.1302	1.0631
No log	2.0667	62	0.8802	0.5027	0.8802	0.9382
No log	2.1333	64	0.8607	0.5145	0.8607	0.9277
No log	2.2	66	0.8359	0.5322	0.8359	0.9143
No log	2.2667	68	0.9635	0.5365	0.9635	0.9816
No log	2.3333	70	1.0217	0.4957	1.0217	1.0108
No log	2.4	72	0.9469	0.4820	0.9469	0.9731
No log	2.4667	74	0.9690	0.5250	0.9690	0.9844
No log	2.5333	76	1.0663	0.4857	1.0663	1.0326
No log	2.6	78	1.0205	0.4947	1.0205	1.0102
No log	2.6667	80	0.9439	0.4438	0.9439	0.9716
No log	2.7333	82	0.9455	0.4875	0.9455	0.9724
No log	2.8	84	0.9604	0.4696	0.9604	0.9800
No log	2.8667	86	1.1668	0.4533	1.1668	1.0802
No log	2.9333	88	1.0385	0.4789	1.0385	1.0191
No log	3.0	90	0.8093	0.5069	0.8093	0.8996
No log	3.0667	92	0.7671	0.4773	0.7671	0.8759
No log	3.1333	94	0.6894	0.4383	0.6894	0.8303
No log	3.2	96	0.6820	0.4675	0.6820	0.8258
No log	3.2667	98	0.6876	0.4937	0.6876	0.8292
No log	3.3333	100	0.7417	0.4863	0.7417	0.8612
No log	3.4	102	0.9646	0.4968	0.9646	0.9821
No log	3.4667	104	0.9332	0.4965	0.9332	0.9660
No log	3.5333	106	0.8792	0.4499	0.8792	0.9376
No log	3.6	108	0.9572	0.4668	0.9572	0.9783
No log	3.6667	110	1.2718	0.4548	1.2718	1.1277
No log	3.7333	112	1.4120	0.4437	1.4120	1.1883
No log	3.8	114	1.1778	0.4440	1.1778	1.0852
No log	3.8667	116	0.9454	0.4431	0.9454	0.9723
No log	3.9333	118	0.8944	0.4629	0.8944	0.9457
No log	4.0	120	0.8626	0.4449	0.8626	0.9288
No log	4.0667	122	0.8298	0.4188	0.8298	0.9110
No log	4.1333	124	0.7509	0.4514	0.7509	0.8665
No log	4.2	126	0.7220	0.4537	0.7220	0.8497
No log	4.2667	128	0.7333	0.4564	0.7333	0.8563
No log	4.3333	130	0.7786	0.4834	0.7786	0.8824
No log	4.4	132	0.7789	0.4836	0.7789	0.8825
No log	4.4667	134	0.8399	0.4685	0.8399	0.9165
No log	4.5333	136	0.8316	0.4654	0.8316	0.9119
No log	4.6	138	0.7795	0.4734	0.7795	0.8829
No log	4.6667	140	0.8336	0.5170	0.8336	0.9130
No log	4.7333	142	0.8708	0.5103	0.8708	0.9332
No log	4.8	144	0.8636	0.4622	0.8636	0.9293
No log	4.8667	146	0.8812	0.4681	0.8812	0.9387
No log	4.9333	148	0.9719	0.5387	0.9719	0.9858
No log	5.0	150	1.0049	0.5131	1.0049	1.0025
No log	5.0667	152	1.0445	0.5004	1.0445	1.0220
No log	5.1333	154	0.9861	0.5018	0.9861	0.9930
No log	5.2	156	0.8861	0.5018	0.8861	0.9413
No log	5.2667	158	0.8027	0.4263	0.8027	0.8959
No log	5.3333	160	0.8338	0.4339	0.8338	0.9131
No log	5.4	162	0.8629	0.4319	0.8629	0.9289
No log	5.4667	164	0.8843	0.4318	0.8843	0.9404
No log	5.5333	166	0.9130	0.4420	0.9130	0.9555
No log	5.6	168	0.9818	0.4684	0.9818	0.9909
No log	5.6667	170	1.0623	0.4832	1.0623	1.0307
No log	5.7333	172	1.1084	0.4700	1.1084	1.0528
No log	5.8	174	1.0742	0.4609	1.0742	1.0364
No log	5.8667	176	1.0266	0.4145	1.0266	1.0132
No log	5.9333	178	1.0083	0.4138	1.0083	1.0042
No log	6.0	180	0.9823	0.4286	0.9823	0.9911
No log	6.0667	182	0.9468	0.4135	0.9468	0.9730
No log	6.1333	184	0.9801	0.4585	0.9801	0.9900
No log	6.2	186	0.9983	0.4849	0.9983	0.9992
No log	6.2667	188	0.9302	0.4547	0.9302	0.9644
No log	6.3333	190	0.9258	0.4424	0.9258	0.9622
No log	6.4	192	0.9326	0.4730	0.9326	0.9657
No log	6.4667	194	0.9002	0.4371	0.9002	0.9488
No log	6.5333	196	0.9308	0.4416	0.9308	0.9648
No log	6.6	198	0.9909	0.4846	0.9909	0.9954
No log	6.6667	200	0.9711	0.4726	0.9711	0.9854
No log	6.7333	202	0.9365	0.4422	0.9365	0.9677
No log	6.8	204	0.9650	0.4450	0.9650	0.9823
No log	6.8667	206	0.9674	0.4467	0.9674	0.9836
No log	6.9333	208	0.9407	0.4399	0.9407	0.9699
No log	7.0	210	0.9493	0.4313	0.9493	0.9743
No log	7.0667	212	0.9673	0.4489	0.9673	0.9835
No log	7.1333	214	1.0339	0.4631	1.0339	1.0168
No log	7.2	216	1.0583	0.4704	1.0583	1.0287
No log	7.2667	218	1.0481	0.4786	1.0481	1.0238
No log	7.3333	220	1.0095	0.4487	1.0095	1.0047
No log	7.4	222	1.0123	0.4777	1.0123	1.0061
No log	7.4667	224	0.9783	0.4833	0.9783	0.9891
No log	7.5333	226	0.9280	0.4758	0.9280	0.9633
No log	7.6	228	0.9025	0.4692	0.9025	0.9500
No log	7.6667	230	0.8961	0.4719	0.8961	0.9466
No log	7.7333	232	0.8872	0.4617	0.8872	0.9419
No log	7.8	234	0.9038	0.4707	0.9038	0.9507
No log	7.8667	236	0.9328	0.5009	0.9328	0.9658
No log	7.9333	238	0.9336	0.4930	0.9336	0.9662
No log	8.0	240	0.9031	0.4557	0.9031	0.9503
No log	8.0667	242	0.8810	0.4379	0.8810	0.9386
No log	8.1333	244	0.8739	0.4441	0.8739	0.9348
No log	8.2	246	0.8873	0.4380	0.8873	0.9420
No log	8.2667	248	0.8892	0.4379	0.8892	0.9430
No log	8.3333	250	0.8890	0.4379	0.8890	0.9429
No log	8.4	252	0.8879	0.4379	0.8879	0.9423
No log	8.4667	254	0.8790	0.4725	0.8790	0.9376
No log	8.5333	256	0.8835	0.4689	0.8835	0.9399
No log	8.6	258	0.8969	0.4671	0.8969	0.9470
No log	8.6667	260	0.9197	0.4524	0.9197	0.9590
No log	8.7333	262	0.9386	0.4491	0.9386	0.9688
No log	8.8	264	0.9445	0.4375	0.9445	0.9719
No log	8.8667	266	0.9383	0.4429	0.9383	0.9686
No log	8.9333	268	0.9414	0.4311	0.9414	0.9703
No log	9.0	270	0.9547	0.4436	0.9547	0.9771
No log	9.0667	272	0.9633	0.4629	0.9633	0.9815
No log	9.1333	274	0.9641	0.4629	0.9641	0.9819
No log	9.2	276	0.9675	0.4629	0.9675	0.9836
No log	9.2667	278	0.9591	0.4573	0.9591	0.9793
No log	9.3333	280	0.9528	0.4518	0.9528	0.9761
No log	9.4	282	0.9506	0.4458	0.9506	0.9750
No log	9.4667	284	0.9572	0.4573	0.9572	0.9784
No log	9.5333	286	0.9589	0.4511	0.9589	0.9792
No log	9.6	288	0.9630	0.4555	0.9630	0.9813
No log	9.6667	290	0.9668	0.4555	0.9668	0.9832
No log	9.7333	292	0.9652	0.4555	0.9652	0.9824
No log	9.8	294	0.9593	0.4573	0.9593	0.9794
No log	9.8667	296	0.9533	0.4458	0.9533	0.9764
No log	9.9333	298	0.9490	0.4424	0.9490	0.9742
No log	10.0	300	0.9475	0.4310	0.9475	0.9734

Framework versions

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