ArabicNewSplits5_FineTuningAraBERT_run3_AugV5_k3_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: 1.0708
• Qwk: 0.1093
• Mse: 1.0708
• Rmse: 1.0348

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	0.1	2	3.2878	-0.0149	3.2878	1.8132
No log	0.2	4	1.8902	-0.0370	1.8902	1.3748
No log	0.3	6	1.0319	0.0038	1.0319	1.0158
No log	0.4	8	1.0480	0.0388	1.0480	1.0237
No log	0.5	10	1.1456	0.0431	1.1456	1.0703
No log	0.6	12	0.6004	0.1304	0.6004	0.7748
No log	0.7	14	0.6181	0.0	0.6181	0.7862
No log	0.8	16	0.6137	0.0	0.6137	0.7834
No log	0.9	18	0.7388	0.0707	0.7388	0.8596
No log	1.0	20	1.0461	0.0	1.0461	1.0228
No log	1.1	22	1.3516	0.0	1.3516	1.1626
No log	1.2	24	1.2739	0.0	1.2739	1.1287
No log	1.3	26	0.8751	0.0476	0.8751	0.9355
No log	1.4	28	0.7237	0.0601	0.7237	0.8507
No log	1.5	30	0.6729	0.2099	0.6729	0.8203
No log	1.6	32	0.7069	0.0968	0.7069	0.8408
No log	1.7	34	0.6834	0.1724	0.6834	0.8267
No log	1.8	36	0.6111	0.1895	0.6111	0.7817
No log	1.9	38	0.7008	0.2184	0.7008	0.8372
No log	2.0	40	0.7227	0.2169	0.7227	0.8501
No log	2.1	42	0.6286	0.2381	0.6286	0.7929
No log	2.2	44	0.6399	0.2688	0.6399	0.7999
No log	2.3	46	0.6517	0.2410	0.6517	0.8073
No log	2.4	48	0.6287	0.25	0.6287	0.7929
No log	2.5	50	0.5765	0.1282	0.5765	0.7593
No log	2.6	52	0.6209	0.2222	0.6209	0.7880
No log	2.7	54	0.6342	0.2289	0.6342	0.7964
No log	2.8	56	0.7866	0.1781	0.7866	0.8869
No log	2.9	58	0.8902	0.1289	0.8902	0.9435
No log	3.0	60	0.6763	0.1801	0.6763	0.8224
No log	3.1	62	0.7791	0.0291	0.7791	0.8827
No log	3.2	64	0.6272	0.3086	0.6272	0.7920
No log	3.3	66	0.7177	0.1600	0.7177	0.8472
No log	3.4	68	0.8819	0.1092	0.8819	0.9391
No log	3.5	70	0.6337	0.2179	0.6337	0.7961
No log	3.6	72	0.6189	0.2360	0.6189	0.7867
No log	3.7	74	0.6313	0.3073	0.6313	0.7946
No log	3.8	76	0.6966	0.2637	0.6966	0.8346
No log	3.9	78	0.7760	0.1111	0.7760	0.8809
No log	4.0	80	0.8120	0.1597	0.8120	0.9011
No log	4.1	82	0.7225	0.3303	0.7225	0.8500
No log	4.2	84	0.7806	0.2632	0.7806	0.8835
No log	4.3	86	0.7244	0.2072	0.7244	0.8511
No log	4.4	88	0.8595	0.136	0.8595	0.9271
No log	4.5	90	1.1196	0.0996	1.1196	1.0581
No log	4.6	92	1.1626	0.0476	1.1626	1.0783
No log	4.7	94	0.9250	0.0817	0.9250	0.9618
No log	4.8	96	0.6996	0.3462	0.6996	0.8364
No log	4.9	98	0.6809	0.2986	0.6809	0.8252
No log	5.0	100	0.8504	0.1366	0.8504	0.9222
No log	5.1	102	0.9230	0.1093	0.9230	0.9608
No log	5.2	104	0.8397	0.1636	0.8397	0.9164
No log	5.3	106	0.9505	0.1093	0.9505	0.9749
No log	5.4	108	1.1871	0.0463	1.1871	1.0895
No log	5.5	110	1.2093	0.0463	1.2093	1.0997
No log	5.6	112	1.0830	0.0861	1.0830	1.0407
No log	5.7	114	0.9017	0.0744	0.9017	0.9496
No log	5.8	116	0.8029	0.2000	0.8029	0.8960
No log	5.9	118	0.7584	0.3462	0.7584	0.8709
No log	6.0	120	0.8623	0.1055	0.8623	0.9286
No log	6.1	122	0.9597	0.1093	0.9597	0.9797
No log	6.2	124	1.1174	0.0038	1.1174	1.0571
No log	6.3	126	1.0540	0.1145	1.0540	1.0266
No log	6.4	128	1.0005	0.1093	1.0005	1.0002
No log	6.5	130	0.9612	0.1093	0.9612	0.9804
No log	6.6	132	0.8723	0.1718	0.8723	0.9340
No log	6.7	134	0.7915	0.1855	0.7915	0.8896
No log	6.8	136	0.8060	0.1855	0.8060	0.8978
No log	6.9	138	0.9583	0.1074	0.9583	0.9789
No log	7.0	140	1.1859	-0.0185	1.1859	1.0890
No log	7.1	142	1.2029	0.0463	1.2029	1.0968
No log	7.2	144	1.2088	0.0463	1.2088	1.0995
No log	7.3	146	1.0782	0.1417	1.0782	1.0384
No log	7.4	148	0.8899	0.1579	0.8899	0.9433
No log	7.5	150	0.8291	0.2442	0.8291	0.9106
No log	7.6	152	0.8539	0.2287	0.8539	0.9241
No log	7.7	154	0.9033	0.1588	0.9033	0.9504
No log	7.8	156	1.0050	0.1074	1.0050	1.0025
No log	7.9	158	1.0246	0.1074	1.0246	1.0122
No log	8.0	160	1.0879	0.1751	1.0879	1.0430
No log	8.1	162	1.0555	0.1093	1.0555	1.0274
No log	8.2	164	0.9919	0.1020	0.9919	0.9959
No log	8.3	166	1.0079	0.1333	1.0079	1.0039
No log	8.4	168	1.0327	0.1040	1.0327	1.0162
No log	8.5	170	1.0400	0.1040	1.0400	1.0198
No log	8.6	172	0.9967	0.1333	0.9967	0.9983
No log	8.7	174	0.9519	0.1333	0.9519	0.9757
No log	8.8	176	0.9581	0.1333	0.9581	0.9788
No log	8.9	178	0.9880	0.1333	0.9880	0.9940
No log	9.0	180	0.9936	0.1333	0.9936	0.9968
No log	9.1	182	0.9504	0.1333	0.9504	0.9749
No log	9.2	184	0.9123	0.1333	0.9123	0.9551
No log	9.3	186	0.9032	0.1319	0.9032	0.9504
No log	9.4	188	0.9028	0.1319	0.9028	0.9501
No log	9.5	190	0.9245	0.1333	0.9245	0.9615
No log	9.6	192	0.9643	0.1333	0.9643	0.9820
No log	9.7	194	1.0086	0.1333	1.0086	1.0043
No log	9.8	196	1.0476	0.1074	1.0476	1.0235
No log	9.9	198	1.0653	0.1093	1.0653	1.0321
No log	10.0	200	1.0708	0.1093	1.0708	1.0348

Framework versions

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