ArabicNewSplits8_FineTuningAraBERT_noAug_task7_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: 0.6075
• Qwk: 0.5101
• Mse: 0.6075
• Rmse: 0.7794

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	2.1474	0.0339	2.1474	1.4654
No log	1.3333	4	1.3213	0.0723	1.3213	1.1495
No log	2.0	6	0.6446	0.1622	0.6446	0.8028
No log	2.6667	8	0.8130	0.2940	0.8130	0.9017
No log	3.3333	10	1.0316	0.2027	1.0316	1.0157
No log	4.0	12	0.8163	0.3321	0.8163	0.9035
No log	4.6667	14	0.5551	0.5315	0.5551	0.7451
No log	5.3333	16	0.5100	0.5123	0.5100	0.7141
No log	6.0	18	0.5523	0.5025	0.5523	0.7432
No log	6.6667	20	0.5506	0.4589	0.5506	0.7420
No log	7.3333	22	0.5711	0.4759	0.5711	0.7557
No log	8.0	24	0.5892	0.4492	0.5892	0.7676
No log	8.6667	26	0.5732	0.4292	0.5732	0.7571
No log	9.3333	28	0.6004	0.4185	0.6004	0.7749
No log	10.0	30	0.6516	0.3661	0.6516	0.8072
No log	10.6667	32	0.6818	0.3765	0.6818	0.8257
No log	11.3333	34	0.6758	0.3988	0.6758	0.8221
No log	12.0	36	0.6504	0.3905	0.6504	0.8065
No log	12.6667	38	0.5567	0.4414	0.5567	0.7462
No log	13.3333	40	0.5557	0.4669	0.5557	0.7454
No log	14.0	42	0.5239	0.5430	0.5239	0.7238
No log	14.6667	44	0.7165	0.4218	0.7165	0.8465
No log	15.3333	46	0.6867	0.4343	0.6867	0.8287
No log	16.0	48	0.5641	0.4725	0.5641	0.7511
No log	16.6667	50	0.5551	0.5205	0.5551	0.7450
No log	17.3333	52	0.5751	0.5035	0.5751	0.7583
No log	18.0	54	0.6803	0.4549	0.6803	0.8248
No log	18.6667	56	0.6782	0.5051	0.6782	0.8235
No log	19.3333	58	0.5668	0.4929	0.5668	0.7528
No log	20.0	60	0.5338	0.4315	0.5338	0.7306
No log	20.6667	62	0.5276	0.4640	0.5276	0.7264
No log	21.3333	64	0.5527	0.4722	0.5527	0.7435
No log	22.0	66	0.6596	0.5376	0.6596	0.8122
No log	22.6667	68	0.7277	0.4822	0.7277	0.8531
No log	23.3333	70	0.5849	0.5272	0.5849	0.7648
No log	24.0	72	0.5113	0.5053	0.5113	0.7151
No log	24.6667	74	0.5041	0.5223	0.5041	0.7100
No log	25.3333	76	0.5902	0.4664	0.5902	0.7682
No log	26.0	78	0.7216	0.5015	0.7216	0.8495
No log	26.6667	80	0.8025	0.4086	0.8025	0.8958
No log	27.3333	82	0.7171	0.4218	0.7171	0.8468
No log	28.0	84	0.5938	0.5055	0.5938	0.7706
No log	28.6667	86	0.5747	0.4748	0.5747	0.7581
No log	29.3333	88	0.6186	0.4123	0.6186	0.7865
No log	30.0	90	0.7446	0.4676	0.7446	0.8629
No log	30.6667	92	0.8161	0.4241	0.8161	0.9034
No log	31.3333	94	0.8996	0.3973	0.8996	0.9485
No log	32.0	96	0.7428	0.4369	0.7428	0.8619
No log	32.6667	98	0.6311	0.4400	0.6311	0.7944
No log	33.3333	100	0.6400	0.4848	0.6400	0.8000
No log	34.0	102	0.7560	0.3974	0.7560	0.8695
No log	34.6667	104	0.9413	0.3497	0.9413	0.9702
No log	35.3333	106	0.9029	0.4086	0.9029	0.9502
No log	36.0	108	0.7306	0.4360	0.7306	0.8548
No log	36.6667	110	0.6129	0.4282	0.6129	0.7829
No log	37.3333	112	0.6088	0.4249	0.6088	0.7803
No log	38.0	114	0.7047	0.4360	0.7047	0.8394
No log	38.6667	116	0.8933	0.3611	0.8933	0.9451
No log	39.3333	118	0.9288	0.3568	0.9288	0.9638
No log	40.0	120	0.8323	0.3761	0.8323	0.9123
No log	40.6667	122	0.6955	0.4009	0.6955	0.8340
No log	41.3333	124	0.6258	0.4705	0.6258	0.7911
No log	42.0	126	0.5640	0.4905	0.5640	0.7510
No log	42.6667	128	0.5791	0.4281	0.5791	0.7610
No log	43.3333	130	0.6355	0.4606	0.6355	0.7972
No log	44.0	132	0.7685	0.4066	0.7685	0.8766
No log	44.6667	134	0.9025	0.2998	0.9025	0.9500
No log	45.3333	136	0.9050	0.2861	0.9050	0.9513
No log	46.0	138	0.8015	0.3321	0.8015	0.8953
No log	46.6667	140	0.7314	0.3671	0.7314	0.8552
No log	47.3333	142	0.7086	0.4331	0.7086	0.8418
No log	48.0	144	0.6768	0.4747	0.6768	0.8227
No log	48.6667	146	0.6122	0.4409	0.6122	0.7824
No log	49.3333	148	0.5908	0.4241	0.5908	0.7686
No log	50.0	150	0.6497	0.4589	0.6497	0.8060
No log	50.6667	152	0.7459	0.3980	0.7459	0.8636
No log	51.3333	154	0.8399	0.3844	0.8399	0.9165
No log	52.0	156	0.9210	0.3730	0.9210	0.9597
No log	52.6667	158	0.8614	0.4118	0.8614	0.9281
No log	53.3333	160	0.7090	0.4469	0.7090	0.8420
No log	54.0	162	0.6224	0.4262	0.6224	0.7889
No log	54.6667	164	0.5817	0.4749	0.5817	0.7627
No log	55.3333	166	0.5629	0.4963	0.5629	0.7503
No log	56.0	168	0.5647	0.5250	0.5647	0.7515
No log	56.6667	170	0.5722	0.5196	0.5722	0.7564
No log	57.3333	172	0.6110	0.4436	0.6110	0.7816
No log	58.0	174	0.6854	0.4598	0.6854	0.8279
No log	58.6667	176	0.7666	0.3496	0.7666	0.8756
No log	59.3333	178	0.8282	0.3293	0.8282	0.9100
No log	60.0	180	0.8424	0.3426	0.8424	0.9178
No log	60.6667	182	0.8670	0.3426	0.8670	0.9311
No log	61.3333	184	0.8375	0.3426	0.8375	0.9152
No log	62.0	186	0.7924	0.3415	0.7924	0.8902
No log	62.6667	188	0.7521	0.3935	0.7521	0.8673
No log	63.3333	190	0.7321	0.3980	0.7321	0.8556
No log	64.0	192	0.6943	0.4598	0.6943	0.8333
No log	64.6667	194	0.6372	0.4705	0.6372	0.7982
No log	65.3333	196	0.5764	0.4072	0.5764	0.7592
No log	66.0	198	0.5649	0.4623	0.5649	0.7516
No log	66.6667	200	0.5604	0.4799	0.5604	0.7486
No log	67.3333	202	0.5796	0.4260	0.5796	0.7613
No log	68.0	204	0.6050	0.4357	0.6050	0.7778
No log	68.6667	206	0.6350	0.4367	0.6350	0.7969
No log	69.3333	208	0.6583	0.4367	0.6583	0.8113
No log	70.0	210	0.6856	0.4520	0.6856	0.8280
No log	70.6667	212	0.7125	0.4198	0.7125	0.8441
No log	71.3333	214	0.7093	0.4363	0.7093	0.8422
No log	72.0	216	0.6728	0.4198	0.6728	0.8202
No log	72.6667	218	0.6735	0.4198	0.6735	0.8206
No log	73.3333	220	0.6626	0.4367	0.6626	0.8140
No log	74.0	222	0.6762	0.4198	0.6762	0.8223
No log	74.6667	224	0.6924	0.4198	0.6924	0.8321
No log	75.3333	226	0.6963	0.4198	0.6963	0.8344
No log	76.0	228	0.6720	0.4198	0.6720	0.8198
No log	76.6667	230	0.6603	0.4367	0.6603	0.8126
No log	77.3333	232	0.6394	0.4533	0.6394	0.7996
No log	78.0	234	0.6330	0.4533	0.6330	0.7956
No log	78.6667	236	0.6186	0.4533	0.6186	0.7865
No log	79.3333	238	0.6221	0.4479	0.6221	0.7887
No log	80.0	240	0.6380	0.4222	0.6380	0.7988
No log	80.6667	242	0.6631	0.4896	0.6631	0.8143
No log	81.3333	244	0.6821	0.4896	0.6821	0.8259
No log	82.0	246	0.6991	0.4896	0.6991	0.8361
No log	82.6667	248	0.7052	0.4896	0.7052	0.8398
No log	83.3333	250	0.6773	0.4896	0.6773	0.8230
No log	84.0	252	0.6617	0.4748	0.6617	0.8134
No log	84.6667	254	0.6431	0.4687	0.6431	0.8019
No log	85.3333	256	0.6186	0.4543	0.6186	0.7865
No log	86.0	258	0.5900	0.4688	0.5900	0.7681
No log	86.6667	260	0.5775	0.4629	0.5775	0.7599
No log	87.3333	262	0.5773	0.4678	0.5773	0.7598
No log	88.0	264	0.5884	0.4688	0.5884	0.7671
No log	88.6667	266	0.5977	0.5043	0.5977	0.7731
No log	89.3333	268	0.6007	0.5101	0.6007	0.7751
No log	90.0	270	0.6084	0.4836	0.6084	0.7800
No log	90.6667	272	0.6202	0.4415	0.6202	0.7875
No log	91.3333	274	0.6380	0.4369	0.6380	0.7987
No log	92.0	276	0.6614	0.4748	0.6614	0.8133
No log	92.6667	278	0.6784	0.4896	0.6784	0.8237
No log	93.3333	280	0.6848	0.4896	0.6848	0.8275
No log	94.0	282	0.6794	0.4896	0.6794	0.8243
No log	94.6667	284	0.6719	0.4896	0.6719	0.8197
No log	95.3333	286	0.6606	0.4748	0.6606	0.8128
No log	96.0	288	0.6476	0.4687	0.6476	0.8047
No log	96.6667	290	0.6362	0.4687	0.6362	0.7976
No log	97.3333	292	0.6252	0.4333	0.6252	0.7907
No log	98.0	294	0.6183	0.4586	0.6183	0.7863
No log	98.6667	296	0.6130	0.4845	0.6130	0.7829
No log	99.3333	298	0.6089	0.4676	0.6089	0.7803
No log	100.0	300	0.6075	0.5101	0.6075	0.7794

Framework versions

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