ArabicNewSplits5_FineTuningAraBERT_run1_AugV5_k6_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: 1.1471
• Qwk: 0.6029
• Mse: 1.1471
• Rmse: 1.0710

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	0.0645	2	2.2334	0.0125	2.2334	1.4944
No log	0.1290	4	1.5584	0.1609	1.5584	1.2483
No log	0.1935	6	1.6352	0.0670	1.6352	1.2787
No log	0.2581	8	1.7407	-0.0404	1.7407	1.3193
No log	0.3226	10	1.5462	0.0532	1.5462	1.2435
No log	0.3871	12	1.4302	0.1719	1.4302	1.1959
No log	0.4516	14	1.3707	0.2153	1.3707	1.1708
No log	0.5161	16	1.3340	0.2447	1.3340	1.1550
No log	0.5806	18	1.2779	0.1588	1.2779	1.1304
No log	0.6452	20	1.2723	0.1707	1.2723	1.1280
No log	0.7097	22	1.2491	0.2186	1.2491	1.1176
No log	0.7742	24	1.2462	0.2173	1.2462	1.1163
No log	0.8387	26	1.2715	0.2562	1.2715	1.1276
No log	0.9032	28	1.2218	0.2704	1.2218	1.1053
No log	0.9677	30	1.2510	0.2598	1.2510	1.1185
No log	1.0323	32	1.3500	0.2352	1.3500	1.1619
No log	1.0968	34	1.2441	0.3611	1.2441	1.1154
No log	1.1613	36	1.2062	0.3705	1.2062	1.0983
No log	1.2258	38	1.1855	0.3585	1.1855	1.0888
No log	1.2903	40	1.1460	0.3898	1.1460	1.0705
No log	1.3548	42	1.1562	0.3284	1.1562	1.0753
No log	1.4194	44	1.1475	0.3464	1.1475	1.0712
No log	1.4839	46	1.1429	0.3322	1.1429	1.0690
No log	1.5484	48	1.1316	0.3441	1.1316	1.0638
No log	1.6129	50	1.1081	0.4258	1.1081	1.0527
No log	1.6774	52	1.1056	0.4230	1.1056	1.0515
No log	1.7419	54	1.0607	0.4645	1.0607	1.0299
No log	1.8065	56	1.0475	0.4771	1.0475	1.0235
No log	1.8710	58	1.0420	0.4790	1.0420	1.0208
No log	1.9355	60	0.9967	0.5127	0.9967	0.9984
No log	2.0	62	1.0006	0.4736	1.0006	1.0003
No log	2.0645	64	0.9816	0.4949	0.9816	0.9907
No log	2.1290	66	0.9993	0.4726	0.9993	0.9996
No log	2.1935	68	0.9944	0.4744	0.9944	0.9972
No log	2.2581	70	0.9217	0.5139	0.9217	0.9601
No log	2.3226	72	1.0314	0.5414	1.0314	1.0156
No log	2.3871	74	1.0989	0.5473	1.0989	1.0483
No log	2.4516	76	0.9858	0.5406	0.9858	0.9929
No log	2.5161	78	0.8848	0.5867	0.8848	0.9406
No log	2.5806	80	0.8793	0.5880	0.8793	0.9377
No log	2.6452	82	0.8878	0.5574	0.8878	0.9422
No log	2.7097	84	0.8768	0.5749	0.8768	0.9364
No log	2.7742	86	0.8693	0.5551	0.8693	0.9324
No log	2.8387	88	0.9163	0.5578	0.9163	0.9572
No log	2.9032	90	0.8826	0.5659	0.8826	0.9395
No log	2.9677	92	0.9199	0.5743	0.9199	0.9591
No log	3.0323	94	1.0811	0.5577	1.0811	1.0398
No log	3.0968	96	1.2590	0.5903	1.2590	1.1221
No log	3.1613	98	1.1422	0.5722	1.1422	1.0688
No log	3.2258	100	0.9292	0.5674	0.9292	0.9640
No log	3.2903	102	0.9301	0.5231	0.9301	0.9644
No log	3.3548	104	0.9360	0.5273	0.9360	0.9675
No log	3.4194	106	0.9165	0.5307	0.9165	0.9573
No log	3.4839	108	0.8596	0.6182	0.8596	0.9271
No log	3.5484	110	0.9178	0.5869	0.9178	0.9580
No log	3.6129	112	1.0745	0.5661	1.0745	1.0366
No log	3.6774	114	1.1160	0.5537	1.1160	1.0564
No log	3.7419	116	0.9777	0.5958	0.9777	0.9888
No log	3.8065	118	0.9842	0.5958	0.9842	0.9921
No log	3.8710	120	0.9814	0.5908	0.9814	0.9906
No log	3.9355	122	0.9502	0.5910	0.9502	0.9748
No log	4.0	124	0.9922	0.5410	0.9922	0.9961
No log	4.0645	126	1.1897	0.5398	1.1897	1.0907
No log	4.1290	128	1.4879	0.5005	1.4879	1.2198
No log	4.1935	130	1.5213	0.5055	1.5213	1.2334
No log	4.2581	132	1.3857	0.4941	1.3857	1.1772
No log	4.3226	134	1.1543	0.5311	1.1543	1.0744
No log	4.3871	136	1.0215	0.5497	1.0215	1.0107
No log	4.4516	138	1.0062	0.5644	1.0062	1.0031
No log	4.5161	140	1.1347	0.5433	1.1347	1.0652
No log	4.5806	142	1.2579	0.5154	1.2579	1.1216
No log	4.6452	144	1.1518	0.5239	1.1518	1.0732
No log	4.7097	146	0.9974	0.5606	0.9974	0.9987
No log	4.7742	148	0.9134	0.5896	0.9134	0.9557
No log	4.8387	150	0.8897	0.6083	0.8897	0.9432
No log	4.9032	152	0.9118	0.5805	0.9118	0.9549
No log	4.9677	154	0.9857	0.5584	0.9857	0.9928
No log	5.0323	156	1.0994	0.5428	1.0994	1.0485
No log	5.0968	158	1.0864	0.5393	1.0864	1.0423
No log	5.1613	160	0.9631	0.5903	0.9631	0.9814
No log	5.2258	162	0.9170	0.6188	0.9170	0.9576
No log	5.2903	164	0.8726	0.6475	0.8726	0.9341
No log	5.3548	166	0.8494	0.6440	0.8494	0.9216
No log	5.4194	168	0.8282	0.6499	0.8282	0.9101
No log	5.4839	170	0.8200	0.6499	0.8200	0.9056
No log	5.5484	172	0.8640	0.6426	0.8640	0.9295
No log	5.6129	174	0.9953	0.5542	0.9953	0.9976
No log	5.6774	176	1.0772	0.5597	1.0772	1.0379
No log	5.7419	178	1.1785	0.5563	1.1785	1.0856
No log	5.8065	180	1.2245	0.5586	1.2245	1.1066
No log	5.8710	182	1.1323	0.5667	1.1323	1.0641
No log	5.9355	184	1.0676	0.5414	1.0676	1.0333
No log	6.0	186	0.9629	0.6208	0.9629	0.9813
No log	6.0645	188	0.9492	0.6208	0.9492	0.9743
No log	6.1290	190	1.0006	0.5709	1.0006	1.0003
No log	6.1935	192	1.0589	0.5584	1.0589	1.0290
No log	6.2581	194	1.1102	0.5593	1.1102	1.0537
No log	6.3226	196	1.1627	0.5808	1.1627	1.0783
No log	6.3871	198	1.1402	0.5745	1.1402	1.0678
No log	6.4516	200	1.0545	0.5667	1.0545	1.0269
No log	6.5161	202	0.9246	0.6299	0.9246	0.9616
No log	6.5806	204	0.8868	0.6416	0.8868	0.9417
No log	6.6452	206	0.9257	0.6335	0.9257	0.9622
No log	6.7097	208	0.9712	0.5915	0.9712	0.9855
No log	6.7742	210	1.0628	0.5554	1.0628	1.0309
No log	6.8387	212	1.1629	0.5711	1.1629	1.0784
No log	6.9032	214	1.2232	0.5690	1.2232	1.1060
No log	6.9677	216	1.1931	0.5690	1.1931	1.0923
No log	7.0323	218	1.1321	0.5712	1.1321	1.0640
No log	7.0968	220	1.0735	0.5823	1.0735	1.0361
No log	7.1613	222	1.0346	0.5654	1.0346	1.0172
No log	7.2258	224	1.0483	0.5767	1.0483	1.0239
No log	7.2903	226	1.0972	0.5767	1.0972	1.0475
No log	7.3548	228	1.1527	0.5777	1.1527	1.0737
No log	7.4194	230	1.2381	0.6002	1.2381	1.1127
No log	7.4839	232	1.3237	0.5778	1.3237	1.1505
No log	7.5484	234	1.3002	0.5778	1.3002	1.1403
No log	7.6129	236	1.1885	0.5944	1.1885	1.0902
No log	7.6774	238	1.0806	0.5677	1.0806	1.0395
No log	7.7419	240	1.0323	0.5664	1.0323	1.0160
No log	7.8065	242	1.0334	0.5664	1.0334	1.0165
No log	7.8710	244	1.0951	0.5821	1.0951	1.0465
No log	7.9355	246	1.1454	0.5914	1.1454	1.0702
No log	8.0	248	1.2027	0.5641	1.2027	1.0967
No log	8.0645	250	1.2036	0.5641	1.2036	1.0971
No log	8.1290	252	1.1298	0.5799	1.1298	1.0629
No log	8.1935	254	1.0542	0.5821	1.0542	1.0267
No log	8.2581	256	1.0423	0.5656	1.0423	1.0209
No log	8.3226	258	1.0167	0.5767	1.0167	1.0083
No log	8.3871	260	1.0035	0.5790	1.0035	1.0018
No log	8.4516	262	1.0127	0.5790	1.0127	1.0063
No log	8.5161	264	1.0077	0.5733	1.0077	1.0038
No log	8.5806	266	1.0084	0.5923	1.0084	1.0042
No log	8.6452	268	1.0164	0.6020	1.0164	1.0082
No log	8.7097	270	1.0113	0.6020	1.0113	1.0056
No log	8.7742	272	1.0015	0.6020	1.0015	1.0008
No log	8.8387	274	0.9815	0.6154	0.9815	0.9907
No log	8.9032	276	0.9539	0.6339	0.9539	0.9767
No log	8.9677	278	0.9373	0.6245	0.9373	0.9681
No log	9.0323	280	0.9263	0.6228	0.9263	0.9625
No log	9.0968	282	0.9129	0.6373	0.9129	0.9555
No log	9.1613	284	0.9245	0.6326	0.9245	0.9615
No log	9.2258	286	0.9507	0.6200	0.9507	0.9750
No log	9.2903	288	0.9868	0.5903	0.9868	0.9934
No log	9.3548	290	1.0233	0.5722	1.0233	1.0116
No log	9.4194	292	1.0713	0.5844	1.0713	1.0350
No log	9.4839	294	1.1127	0.5937	1.1127	1.0548
No log	9.5484	296	1.1379	0.6119	1.1379	1.0667
No log	9.6129	298	1.1560	0.6062	1.1560	1.0752
No log	9.6774	300	1.1622	0.6062	1.1622	1.0780
No log	9.7419	302	1.1577	0.5973	1.1577	1.0760
No log	9.8065	304	1.1561	0.5973	1.1561	1.0752
No log	9.8710	306	1.1529	0.6029	1.1529	1.0737
No log	9.9355	308	1.1492	0.6029	1.1492	1.0720
No log	10.0	310	1.1471	0.6029	1.1471	1.0710

Framework versions

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