ArabicNewSplits7_usingWellWrittenEssays_FineTuningAraBERT_run1_AugV5_k1_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: 0.8883
• Qwk: 0.0748
• Mse: 0.8883
• Rmse: 0.9425

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	4.0603	0.0110	4.0603	2.0150
No log	1.3333	4	2.1472	0.0284	2.1472	1.4653
No log	2.0	6	1.4839	-0.0040	1.4839	1.2182
No log	2.6667	8	1.1869	0.0298	1.1869	1.0894
No log	3.3333	10	1.0274	0.0762	1.0274	1.0136
No log	4.0	12	1.1640	-0.0221	1.1640	1.0789
No log	4.6667	14	0.9834	0.0431	0.9834	0.9917
No log	5.3333	16	0.7947	-0.0766	0.7947	0.8915
No log	6.0	18	0.7654	-0.1233	0.7654	0.8748
No log	6.6667	20	0.8176	-0.0351	0.8176	0.9042
No log	7.3333	22	0.9802	-0.0218	0.9802	0.9901
No log	8.0	24	1.2653	-0.0435	1.2653	1.1249
No log	8.6667	26	1.2545	-0.0423	1.2545	1.1201
No log	9.3333	28	0.8924	0.0316	0.8924	0.9447
No log	10.0	30	0.7711	-0.0778	0.7711	0.8781
No log	10.6667	32	0.7180	-0.0695	0.7180	0.8473
No log	11.3333	34	0.7361	-0.0739	0.7361	0.8580
No log	12.0	36	1.0098	-0.0504	1.0098	1.0049
No log	12.6667	38	0.9370	0.0476	0.9370	0.9680
No log	13.3333	40	0.7508	-0.0612	0.7508	0.8665
No log	14.0	42	0.8013	0.1425	0.8013	0.8951
No log	14.6667	44	0.8533	-0.0295	0.8533	0.9237
No log	15.3333	46	0.9449	-0.0158	0.9449	0.9721
No log	16.0	48	0.9416	-0.0241	0.9416	0.9703
No log	16.6667	50	0.8232	0.1550	0.8232	0.9073
No log	17.3333	52	0.8372	0.1673	0.8372	0.9150
No log	18.0	54	0.7877	0.1029	0.7877	0.8875
No log	18.6667	56	0.8330	0.0191	0.8330	0.9127
No log	19.3333	58	1.1875	0.0753	1.1875	1.0897
No log	20.0	60	1.1749	0.0107	1.1749	1.0839
No log	20.6667	62	0.8759	0.0549	0.8759	0.9359
No log	21.3333	64	0.7620	-0.1774	0.7620	0.8729
No log	22.0	66	0.7760	-0.2221	0.7760	0.8809
No log	22.6667	68	0.8303	-0.0240	0.8303	0.9112
No log	23.3333	70	1.0994	-0.0138	1.0994	1.0485
No log	24.0	72	1.2158	-0.1196	1.2158	1.1026
No log	24.6667	74	1.0655	0.1025	1.0655	1.0322
No log	25.3333	76	0.8706	-0.0557	0.8706	0.9330
No log	26.0	78	0.8796	-0.0320	0.8796	0.9379
No log	26.6667	80	0.8715	-0.0320	0.8715	0.9336
No log	27.3333	82	0.9093	0.0226	0.9093	0.9536
No log	28.0	84	0.9388	0.0999	0.9388	0.9689
No log	28.6667	86	0.9121	0.0159	0.9121	0.9550
No log	29.3333	88	0.8656	-0.1168	0.8656	0.9304
No log	30.0	90	0.8718	-0.0976	0.8718	0.9337
No log	30.6667	92	0.8670	-0.2008	0.8670	0.9311
No log	31.3333	94	0.9281	-0.0287	0.9281	0.9634
No log	32.0	96	1.1318	-0.0854	1.1318	1.0639
No log	32.6667	98	1.2491	-0.1468	1.2491	1.1176
No log	33.3333	100	1.1257	0.0260	1.1257	1.0610
No log	34.0	102	0.9173	0.0123	0.9173	0.9578
No log	34.6667	104	0.8712	-0.1270	0.8712	0.9334
No log	35.3333	106	0.8665	-0.1270	0.8665	0.9308
No log	36.0	108	0.8389	-0.0831	0.8389	0.9159
No log	36.6667	110	0.8248	-0.0204	0.8248	0.9082
No log	37.3333	112	0.9110	0.0476	0.9110	0.9545
No log	38.0	114	0.9910	0.0711	0.9910	0.9955
No log	38.6667	116	0.9673	0.1196	0.9673	0.9835
No log	39.3333	118	0.9096	0.0071	0.9096	0.9537
No log	40.0	120	0.8532	-0.0264	0.8532	0.9237
No log	40.6667	122	0.8476	-0.0264	0.8476	0.9206
No log	41.3333	124	0.8644	-0.0264	0.8644	0.9298
No log	42.0	126	0.9068	-0.0309	0.9068	0.9523
No log	42.6667	128	0.9612	0.0490	0.9612	0.9804
No log	43.3333	130	1.0316	0.0755	1.0316	1.0157
No log	44.0	132	1.0521	0.0287	1.0521	1.0257
No log	44.6667	134	0.9475	0.0826	0.9475	0.9734
No log	45.3333	136	0.8609	-0.0309	0.8609	0.9279
No log	46.0	138	0.8310	-0.0675	0.8310	0.9116
No log	46.6667	140	0.8334	-0.0690	0.8334	0.9129
No log	47.3333	142	0.8629	-0.0287	0.8629	0.9289
No log	48.0	144	0.8955	0.0549	0.8955	0.9463
No log	48.6667	146	0.9272	0.0017	0.9272	0.9629
No log	49.3333	148	0.9277	0.0017	0.9277	0.9632
No log	50.0	150	0.9052	0.0525	0.9052	0.9514
No log	50.6667	152	0.8678	0.0600	0.8678	0.9316
No log	51.3333	154	0.8459	0.0159	0.8459	0.9197
No log	52.0	156	0.8196	-0.0264	0.8196	0.9053
No log	52.6667	158	0.8112	-0.1236	0.8112	0.9007
No log	53.3333	160	0.8115	-0.1236	0.8115	0.9008
No log	54.0	162	0.8339	-0.0264	0.8339	0.9132
No log	54.6667	164	0.8580	0.0159	0.8580	0.9263
No log	55.3333	166	0.8917	0.0588	0.8917	0.9443
No log	56.0	168	0.9153	0.0549	0.9153	0.9567
No log	56.6667	170	0.9171	0.0118	0.9171	0.9577
No log	57.3333	172	0.8815	-0.0658	0.8815	0.9389
No log	58.0	174	0.8684	-0.0599	0.8684	0.9319
No log	58.6667	176	0.8524	-0.0086	0.8524	0.9233
No log	59.3333	178	0.8350	-0.0612	0.8350	0.9138
No log	60.0	180	0.8366	-0.0718	0.8366	0.9147
No log	60.6667	182	0.8666	0.0476	0.8666	0.9309
No log	61.3333	184	0.9070	0.0748	0.9070	0.9523
No log	62.0	186	0.9200	0.0748	0.9200	0.9592
No log	62.6667	188	0.8982	0.0748	0.8982	0.9478
No log	63.3333	190	0.8715	0.0867	0.8715	0.9336
No log	64.0	192	0.8546	-0.0287	0.8546	0.9245
No log	64.6667	194	0.8372	-0.0287	0.8372	0.9150
No log	65.3333	196	0.8318	-0.0264	0.8318	0.9120
No log	66.0	198	0.8415	-0.0287	0.8415	0.9173
No log	66.6667	200	0.8614	-0.0287	0.8614	0.9281
No log	67.3333	202	0.8870	-0.0262	0.8870	0.9418
No log	68.0	204	0.9016	-0.0262	0.9016	0.9495
No log	68.6667	206	0.9065	-0.0656	0.9065	0.9521
No log	69.3333	208	0.9068	-0.0656	0.9068	0.9523
No log	70.0	210	0.9173	-0.0283	0.9173	0.9578
No log	70.6667	212	0.9364	0.0470	0.9364	0.9677
No log	71.3333	214	0.9469	0.0831	0.9469	0.9731
No log	72.0	216	0.9236	0.0456	0.9236	0.9611
No log	72.6667	218	0.9100	0.0095	0.9100	0.9540
No log	73.3333	220	0.8851	-0.0699	0.8851	0.9408
No log	74.0	222	0.8684	-0.0699	0.8684	0.9319
No log	74.6667	224	0.8522	-0.0643	0.8522	0.9232
No log	75.3333	226	0.8418	-0.0658	0.8418	0.9175
No log	76.0	228	0.8403	-0.0658	0.8403	0.9167
No log	76.6667	230	0.8380	-0.0704	0.8380	0.9154
No log	77.3333	232	0.8395	-0.0718	0.8395	0.9162
No log	78.0	234	0.8487	-0.0731	0.8487	0.9212
No log	78.6667	236	0.8591	-0.0331	0.8591	0.9269
No log	79.3333	238	0.8839	0.0071	0.8839	0.9402
No log	80.0	240	0.8961	0.1196	0.8961	0.9467
No log	80.6667	242	0.9015	0.1196	0.9015	0.9495
No log	81.3333	244	0.9089	0.0748	0.9089	0.9534
No log	82.0	246	0.9054	0.0748	0.9054	0.9515
No log	82.6667	248	0.8914	0.1196	0.8914	0.9441
No log	83.3333	250	0.8822	0.0826	0.8822	0.9392
No log	84.0	252	0.8742	0.0043	0.8742	0.9350
No log	84.6667	254	0.8655	-0.0351	0.8655	0.9303
No log	85.3333	256	0.8619	-0.0351	0.8619	0.9284
No log	86.0	258	0.8644	-0.0351	0.8644	0.9298
No log	86.6667	260	0.8703	0.0071	0.8703	0.9329
No log	87.3333	262	0.8780	0.0826	0.8780	0.9370
No log	88.0	264	0.8836	0.0748	0.8836	0.9400
No log	88.6667	266	0.8842	0.0748	0.8842	0.9403
No log	89.3333	268	0.8872	0.0748	0.8872	0.9419
No log	90.0	270	0.8952	0.0748	0.8952	0.9461
No log	90.6667	272	0.8991	0.0748	0.8991	0.9482
No log	91.3333	274	0.8962	0.0748	0.8962	0.9467
No log	92.0	276	0.8972	0.0748	0.8972	0.9472
No log	92.6667	278	0.8997	0.0748	0.8997	0.9485
No log	93.3333	280	0.9029	0.0748	0.9029	0.9502
No log	94.0	282	0.9025	0.0748	0.9025	0.9500
No log	94.6667	284	0.9010	0.0748	0.9010	0.9492
No log	95.3333	286	0.9008	0.0748	0.9008	0.9491
No log	96.0	288	0.8989	0.0748	0.8989	0.9481
No log	96.6667	290	0.8976	0.0748	0.8976	0.9474
No log	97.3333	292	0.8955	0.0748	0.8955	0.9463
No log	98.0	294	0.8932	0.0748	0.8932	0.9451
No log	98.6667	296	0.8907	0.0748	0.8907	0.9437
No log	99.3333	298	0.8890	0.0748	0.8890	0.9429
No log	100.0	300	0.8883	0.0748	0.8883	0.9425

Framework versions

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