ArabicNewSplits7_usingWellWrittenEssays_FineTuningAraBERT_run2_AugV5_k1_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: 0.7404
• Qwk: 0.3238
• Mse: 0.7404
• Rmse: 0.8605

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	2.6632	-0.1213	2.6632	1.6319
No log	1.3333	4	1.3882	0.1265	1.3882	1.1782
No log	2.0	6	1.1319	-0.0970	1.1319	1.0639
No log	2.6667	8	1.0927	-0.0810	1.0927	1.0453
No log	3.3333	10	0.9247	0.0058	0.9247	0.9616
No log	4.0	12	0.8601	0.0236	0.8601	0.9274
No log	4.6667	14	0.8247	0.0393	0.8247	0.9081
No log	5.3333	16	0.7599	0.0	0.7599	0.8717
No log	6.0	18	0.7561	0.0481	0.7561	0.8696
No log	6.6667	20	0.7398	0.0937	0.7398	0.8601
No log	7.3333	22	0.6974	0.0889	0.6974	0.8351
No log	8.0	24	0.7067	0.0840	0.7067	0.8407
No log	8.6667	26	0.7288	0.1139	0.7288	0.8537
No log	9.3333	28	0.7213	0.0327	0.7213	0.8493
No log	10.0	30	0.6967	0.0393	0.6967	0.8347
No log	10.6667	32	0.6970	0.0846	0.6970	0.8349
No log	11.3333	34	0.6807	0.1327	0.6807	0.8251
No log	12.0	36	0.6864	0.2783	0.6864	0.8285
No log	12.6667	38	0.7758	0.1341	0.7758	0.8808
No log	13.3333	40	1.0549	0.1650	1.0549	1.0271
No log	14.0	42	1.0926	0.1753	1.0926	1.0453
No log	14.6667	44	0.9507	0.1323	0.9507	0.9750
No log	15.3333	46	0.9933	0.2153	0.9933	0.9966
No log	16.0	48	1.0836	0.1926	1.0836	1.0410
No log	16.6667	50	1.1782	0.1077	1.1782	1.0854
No log	17.3333	52	1.0397	0.1339	1.0397	1.0196
No log	18.0	54	0.8137	0.2715	0.8137	0.9021
No log	18.6667	56	0.7808	0.3541	0.7808	0.8836
No log	19.3333	58	0.7654	0.3622	0.7654	0.8749
No log	20.0	60	0.9714	0.2239	0.9714	0.9856
No log	20.6667	62	1.0619	0.2507	1.0619	1.0305
No log	21.3333	64	1.0113	0.1856	1.0113	1.0056
No log	22.0	66	0.8359	0.2662	0.8359	0.9143
No log	22.6667	68	0.7538	0.2414	0.7538	0.8682
No log	23.3333	70	0.7411	0.2237	0.7411	0.8609
No log	24.0	72	0.8121	0.2096	0.8121	0.9012
No log	24.6667	74	0.9212	0.2253	0.9212	0.9598
No log	25.3333	76	0.9368	0.3586	0.9368	0.9679
No log	26.0	78	0.8852	0.3344	0.8852	0.9409
No log	26.6667	80	0.8121	0.3261	0.8121	0.9012
No log	27.3333	82	0.8265	0.3918	0.8265	0.9091
No log	28.0	84	0.8877	0.3234	0.8877	0.9422
No log	28.6667	86	0.8820	0.3099	0.8820	0.9392
No log	29.3333	88	0.8031	0.3196	0.8031	0.8962
No log	30.0	90	0.8070	0.3127	0.8070	0.8983
No log	30.6667	92	0.9023	0.2967	0.9023	0.9499
No log	31.3333	94	0.9381	0.2692	0.9381	0.9686
No log	32.0	96	0.8218	0.2967	0.8218	0.9066
No log	32.6667	98	0.6896	0.2099	0.6896	0.8304
No log	33.3333	100	0.6649	0.2317	0.6649	0.8154
No log	34.0	102	0.6654	0.2476	0.6654	0.8157
No log	34.6667	104	0.7198	0.3840	0.7198	0.8484
No log	35.3333	106	0.7595	0.4020	0.7595	0.8715
No log	36.0	108	0.7477	0.3498	0.7477	0.8647
No log	36.6667	110	0.7214	0.3572	0.7214	0.8494
No log	37.3333	112	0.7180	0.2379	0.7180	0.8474
No log	38.0	114	0.7629	0.1972	0.7629	0.8735
No log	38.6667	116	0.7824	0.1972	0.7824	0.8845
No log	39.3333	118	0.7750	0.1972	0.7750	0.8804
No log	40.0	120	0.7531	0.2652	0.7531	0.8678
No log	40.6667	122	0.7773	0.2171	0.7773	0.8817
No log	41.3333	124	0.8507	0.2692	0.8507	0.9223
No log	42.0	126	0.9124	0.3234	0.9124	0.9552
No log	42.6667	128	0.8637	0.2967	0.8637	0.9293
No log	43.3333	130	0.8389	0.2967	0.8389	0.9159
No log	44.0	132	0.7617	0.2498	0.7617	0.8727
No log	44.6667	134	0.7038	0.3341	0.7038	0.8390
No log	45.3333	136	0.6932	0.2981	0.6932	0.8326
No log	46.0	138	0.6988	0.3894	0.6988	0.8359
No log	46.6667	140	0.7067	0.3894	0.7067	0.8406
No log	47.3333	142	0.7387	0.3399	0.7387	0.8595
No log	48.0	144	0.7523	0.3590	0.7523	0.8673
No log	48.6667	146	0.7570	0.3590	0.7570	0.8701
No log	49.3333	148	0.8021	0.3940	0.8021	0.8956
No log	50.0	150	0.7996	0.4329	0.7996	0.8942
No log	50.6667	152	0.7466	0.3590	0.7466	0.8640
No log	51.3333	154	0.6695	0.3788	0.6695	0.8182
No log	52.0	156	0.6423	0.3070	0.6423	0.8015
No log	52.6667	158	0.6455	0.3336	0.6455	0.8034
No log	53.3333	160	0.6411	0.3070	0.6411	0.8007
No log	54.0	162	0.6462	0.3599	0.6462	0.8039
No log	54.6667	164	0.6690	0.3524	0.6690	0.8179
No log	55.3333	166	0.6858	0.3267	0.6858	0.8281
No log	56.0	168	0.7004	0.3545	0.7004	0.8369
No log	56.6667	170	0.7119	0.3545	0.7119	0.8437
No log	57.3333	172	0.7268	0.3060	0.7268	0.8525
No log	58.0	174	0.7169	0.3127	0.7169	0.8467
No log	58.6667	176	0.6937	0.3498	0.6937	0.8329
No log	59.3333	178	0.6644	0.3524	0.6644	0.8151
No log	60.0	180	0.6653	0.3170	0.6653	0.8157
No log	60.6667	182	0.6667	0.3481	0.6667	0.8165
No log	61.3333	184	0.6775	0.3860	0.6775	0.8231
No log	62.0	186	0.6774	0.3806	0.6774	0.8230
No log	62.6667	188	0.6643	0.2652	0.6643	0.8150
No log	63.3333	190	0.6663	0.3280	0.6663	0.8163
No log	64.0	192	0.6705	0.3280	0.6705	0.8188
No log	64.6667	194	0.6854	0.2973	0.6854	0.8279
No log	65.3333	196	0.6973	0.3524	0.6973	0.8350
No log	66.0	198	0.7181	0.3840	0.7181	0.8474
No log	66.6667	200	0.7369	0.3425	0.7369	0.8584
No log	67.3333	202	0.7561	0.3060	0.7561	0.8695
No log	68.0	204	0.7591	0.2754	0.7591	0.8712
No log	68.6667	206	0.7362	0.3060	0.7362	0.8580
No log	69.3333	208	0.7107	0.2558	0.7107	0.8430
No log	70.0	210	0.7025	0.3267	0.7025	0.8382
No log	70.6667	212	0.6982	0.3267	0.6982	0.8356
No log	71.3333	214	0.7089	0.3267	0.7089	0.8420
No log	72.0	216	0.7317	0.3545	0.7317	0.8554
No log	72.6667	218	0.7634	0.2754	0.7634	0.8737
No log	73.3333	220	0.8069	0.3169	0.8069	0.8983
No log	74.0	222	0.8195	0.3675	0.8195	0.9053
No log	74.6667	224	0.8127	0.3564	0.8127	0.9015
No log	75.3333	226	0.8149	0.3564	0.8149	0.9027
No log	76.0	228	0.7888	0.3032	0.7888	0.8881
No log	76.6667	230	0.7572	0.3518	0.7572	0.8702
No log	77.3333	232	0.7508	0.3518	0.7508	0.8665
No log	78.0	234	0.7350	0.3312	0.7350	0.8573
No log	78.6667	236	0.7308	0.3312	0.7308	0.8549
No log	79.3333	238	0.7419	0.3594	0.7419	0.8613
No log	80.0	240	0.7610	0.3518	0.7610	0.8724
No log	80.6667	242	0.7882	0.3302	0.7882	0.8878
No log	81.3333	244	0.8140	0.3564	0.8140	0.9022
No log	82.0	246	0.8316	0.3819	0.8316	0.9119
No log	82.6667	248	0.8344	0.3819	0.8344	0.9135
No log	83.3333	250	0.8211	0.3819	0.8211	0.9062
No log	84.0	252	0.7963	0.3564	0.7963	0.8924
No log	84.6667	254	0.7777	0.3302	0.7777	0.8819
No log	85.3333	256	0.7631	0.3444	0.7631	0.8736
No log	86.0	258	0.7530	0.3444	0.7530	0.8678
No log	86.6667	260	0.7475	0.3444	0.7475	0.8646
No log	87.3333	262	0.7487	0.3444	0.7487	0.8652
No log	88.0	264	0.7545	0.3032	0.7545	0.8686
No log	88.6667	266	0.7650	0.3032	0.7650	0.8747
No log	89.3333	268	0.7701	0.3032	0.7701	0.8776
No log	90.0	270	0.7715	0.3032	0.7715	0.8783
No log	90.6667	272	0.7700	0.3032	0.7700	0.8775
No log	91.3333	274	0.7710	0.3032	0.7710	0.8781
No log	92.0	276	0.7701	0.3032	0.7701	0.8775
No log	92.6667	278	0.7653	0.3032	0.7653	0.8748
No log	93.3333	280	0.7617	0.3032	0.7617	0.8727
No log	94.0	282	0.7548	0.3444	0.7548	0.8688
No log	94.6667	284	0.7498	0.3167	0.7498	0.8659
No log	95.3333	286	0.7451	0.3238	0.7451	0.8632
No log	96.0	288	0.7421	0.3238	0.7421	0.8615
No log	96.6667	290	0.7399	0.3238	0.7399	0.8602
No log	97.3333	292	0.7388	0.3238	0.7388	0.8595
No log	98.0	294	0.7384	0.3238	0.7384	0.8593
No log	98.6667	296	0.7393	0.3238	0.7393	0.8598
No log	99.3333	298	0.7400	0.3238	0.7400	0.8603
No log	100.0	300	0.7404	0.3238	0.7404	0.8605

Framework versions

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