ArabicNewSplits7_usingWellWrittenEssays_FineTuningAraBERT_run1_AugV5_k1_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: 0.8198
• Qwk: 0.3837
• Mse: 0.8198
• Rmse: 0.9054

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	8.9796	-0.0037	8.9796	2.9966
No log	1.3333	4	5.8199	0.0281	5.8199	2.4124
No log	2.0	6	3.3361	0.0173	3.3361	1.8265
No log	2.6667	8	2.0996	0.1892	2.0996	1.4490
No log	3.3333	10	1.4196	0.1394	1.4196	1.1915
No log	4.0	12	0.9964	0.3007	0.9964	0.9982
No log	4.6667	14	0.9374	0.3280	0.9374	0.9682
No log	5.3333	16	1.0161	0.3421	1.0161	1.0080
No log	6.0	18	1.2001	0.3021	1.2001	1.0955
No log	6.6667	20	1.3631	0.1900	1.3631	1.1675
No log	7.3333	22	2.1209	0.1763	2.1209	1.4563
No log	8.0	24	2.0626	0.1961	2.0626	1.4362
No log	8.6667	26	1.2964	0.1501	1.2964	1.1386
No log	9.3333	28	1.0116	0.3772	1.0116	1.0058
No log	10.0	30	0.9880	0.4186	0.9880	0.9940
No log	10.6667	32	1.1597	0.4012	1.1597	1.0769
No log	11.3333	34	1.1854	0.3957	1.1854	1.0888
No log	12.0	36	1.0054	0.4258	1.0054	1.0027
No log	12.6667	38	1.0089	0.3834	1.0089	1.0044
No log	13.3333	40	1.1008	0.4458	1.1008	1.0492
No log	14.0	42	1.0049	0.3718	1.0049	1.0024
No log	14.6667	44	0.9209	0.3485	0.9209	0.9596
No log	15.3333	46	1.0022	0.3067	1.0022	1.0011
No log	16.0	48	0.9570	0.2057	0.9570	0.9783
No log	16.6667	50	0.9841	0.4424	0.9841	0.9920
No log	17.3333	52	1.1034	0.4641	1.1034	1.0504
No log	18.0	54	0.9986	0.4767	0.9986	0.9993
No log	18.6667	56	0.9746	0.2114	0.9746	0.9872
No log	19.3333	58	1.0163	0.2288	1.0163	1.0081
No log	20.0	60	0.9305	0.2746	0.9305	0.9646
No log	20.6667	62	0.8636	0.3257	0.8636	0.9293
No log	21.3333	64	0.8777	0.3986	0.8777	0.9369
No log	22.0	66	0.8609	0.3952	0.8609	0.9278
No log	22.6667	68	0.8964	0.4249	0.8964	0.9468
No log	23.3333	70	0.8749	0.4242	0.8749	0.9354
No log	24.0	72	0.8674	0.4215	0.8674	0.9313
No log	24.6667	74	0.9325	0.4880	0.9325	0.9657
No log	25.3333	76	0.9361	0.4775	0.9361	0.9675
No log	26.0	78	0.8957	0.4	0.8957	0.9464
No log	26.6667	80	0.8952	0.4321	0.8952	0.9461
No log	27.3333	82	0.8843	0.4093	0.8843	0.9404
No log	28.0	84	0.8758	0.4321	0.8758	0.9358
No log	28.6667	86	0.9259	0.3272	0.9259	0.9622
No log	29.3333	88	0.9038	0.3151	0.9038	0.9507
No log	30.0	90	0.8649	0.4069	0.8649	0.9300
No log	30.6667	92	0.8813	0.4087	0.8813	0.9388
No log	31.3333	94	0.8921	0.4238	0.8921	0.9445
No log	32.0	96	0.8744	0.4221	0.8744	0.9351
No log	32.6667	98	0.8597	0.3656	0.8597	0.9272
No log	33.3333	100	0.8574	0.3011	0.8574	0.9260
No log	34.0	102	0.8613	0.2619	0.8613	0.9281
No log	34.6667	104	0.8902	0.3795	0.8902	0.9435
No log	35.3333	106	1.0775	0.4808	1.0775	1.0380
No log	36.0	108	1.0725	0.4917	1.0725	1.0356
No log	36.6667	110	0.9323	0.4118	0.9323	0.9656
No log	37.3333	112	0.9009	0.3517	0.9009	0.9492
No log	38.0	114	0.9209	0.3008	0.9209	0.9596
No log	38.6667	116	0.9539	0.2600	0.9539	0.9767
No log	39.3333	118	0.9192	0.3008	0.9192	0.9587
No log	40.0	120	0.8954	0.3517	0.8954	0.9462
No log	40.6667	122	0.9339	0.3986	0.9339	0.9664
No log	41.3333	124	0.9799	0.4265	0.9799	0.9899
No log	42.0	126	0.9379	0.4221	0.9379	0.9685
No log	42.6667	128	0.8803	0.3517	0.8803	0.9382
No log	43.3333	130	0.8751	0.3117	0.8751	0.9355
No log	44.0	132	0.8911	0.2391	0.8911	0.9440
No log	44.6667	134	0.8972	0.2492	0.8972	0.9472
No log	45.3333	136	0.8711	0.2692	0.8711	0.9333
No log	46.0	138	0.8594	0.3236	0.8594	0.9270
No log	46.6667	140	0.8634	0.3854	0.8634	0.9292
No log	47.3333	142	0.8579	0.3816	0.8579	0.9262
No log	48.0	144	0.8524	0.3915	0.8524	0.9233
No log	48.6667	146	0.8531	0.3636	0.8531	0.9237
No log	49.3333	148	0.8551	0.2692	0.8551	0.9247
No log	50.0	150	0.8479	0.3733	0.8479	0.9208
No log	50.6667	152	0.8447	0.3517	0.8447	0.9191
No log	51.3333	154	0.8460	0.3952	0.8460	0.9198
No log	52.0	156	0.8413	0.3952	0.8413	0.9172
No log	52.6667	158	0.8366	0.3816	0.8366	0.9146
No log	53.3333	160	0.8372	0.3680	0.8372	0.9150
No log	54.0	162	0.8513	0.2812	0.8513	0.9226
No log	54.6667	164	0.8769	0.2618	0.8769	0.9364
No log	55.3333	166	0.8775	0.2214	0.8775	0.9368
No log	56.0	168	0.8517	0.3280	0.8517	0.9229
No log	56.6667	170	0.8485	0.3540	0.8485	0.9211
No log	57.3333	172	0.8525	0.3540	0.8525	0.9233
No log	58.0	174	0.8496	0.3540	0.8496	0.9217
No log	58.6667	176	0.8523	0.3540	0.8523	0.9232
No log	59.3333	178	0.8759	0.2596	0.8759	0.9359
No log	60.0	180	0.9304	0.2480	0.9304	0.9646
No log	60.6667	182	0.9467	0.3048	0.9467	0.9730
No log	61.3333	184	0.9193	0.2744	0.9193	0.9588
No log	62.0	186	0.8798	0.2865	0.8798	0.9380
No log	62.6667	188	0.8554	0.3446	0.8554	0.9249
No log	63.3333	190	0.8462	0.3933	0.8462	0.9199
No log	64.0	192	0.8461	0.3636	0.8461	0.9198
No log	64.6667	194	0.8631	0.2541	0.8631	0.9291
No log	65.3333	196	0.8829	0.2239	0.8829	0.9396
No log	66.0	198	0.8822	0.2239	0.8822	0.9392
No log	66.6667	200	0.8570	0.2667	0.8570	0.9258
No log	67.3333	202	0.8509	0.2667	0.8509	0.9224
No log	68.0	204	0.8576	0.2667	0.8576	0.9261
No log	68.6667	206	0.8439	0.3117	0.8439	0.9186
No log	69.3333	208	0.8215	0.3540	0.8215	0.9063
No log	70.0	210	0.8161	0.4450	0.8161	0.9034
No log	70.6667	212	0.8212	0.4221	0.8212	0.9062
No log	71.3333	214	0.8285	0.4221	0.8285	0.9102
No log	72.0	216	0.8194	0.4221	0.8194	0.9052
No log	72.6667	218	0.8089	0.4477	0.8089	0.8994
No log	73.3333	220	0.8053	0.4083	0.8053	0.8974
No log	74.0	222	0.8074	0.4138	0.8074	0.8985
No log	74.6667	224	0.8137	0.3837	0.8137	0.9021
No log	75.3333	226	0.8211	0.3837	0.8211	0.9062
No log	76.0	228	0.8196	0.3837	0.8196	0.9053
No log	76.6667	230	0.8179	0.3837	0.8179	0.9044
No log	77.3333	232	0.8226	0.3414	0.8226	0.9069
No log	78.0	234	0.8258	0.3414	0.8258	0.9087
No log	78.6667	236	0.8268	0.3414	0.8268	0.9093
No log	79.3333	238	0.8282	0.3200	0.8282	0.9101
No log	80.0	240	0.8328	0.3816	0.8328	0.9126
No log	80.6667	242	0.8301	0.3816	0.8301	0.9111
No log	81.3333	244	0.8263	0.3797	0.8263	0.9090
No log	82.0	246	0.8245	0.3616	0.8245	0.9080
No log	82.6667	248	0.8234	0.3797	0.8234	0.9074
No log	83.3333	250	0.8220	0.3837	0.8220	0.9066
No log	84.0	252	0.8256	0.3837	0.8256	0.9086
No log	84.6667	254	0.8299	0.3837	0.8299	0.9110
No log	85.3333	256	0.8311	0.3837	0.8311	0.9117
No log	86.0	258	0.8289	0.3837	0.8289	0.9104
No log	86.6667	260	0.8245	0.3837	0.8245	0.9080
No log	87.3333	262	0.8227	0.3837	0.8227	0.9070
No log	88.0	264	0.8245	0.3200	0.8245	0.9080
No log	88.6667	266	0.8267	0.3517	0.8267	0.9092
No log	89.3333	268	0.8283	0.3816	0.8283	0.9101
No log	90.0	270	0.8271	0.3816	0.8271	0.9095
No log	90.6667	272	0.8259	0.3816	0.8259	0.9088
No log	91.3333	274	0.8240	0.3816	0.8240	0.9078
No log	92.0	276	0.8217	0.3797	0.8217	0.9064
No log	92.6667	278	0.8203	0.3837	0.8203	0.9057
No log	93.3333	280	0.8197	0.3837	0.8197	0.9054
No log	94.0	282	0.8199	0.3837	0.8199	0.9055
No log	94.6667	284	0.8204	0.3837	0.8204	0.9058
No log	95.3333	286	0.8211	0.3837	0.8211	0.9062
No log	96.0	288	0.8208	0.3837	0.8208	0.9060
No log	96.6667	290	0.8200	0.3837	0.8200	0.9055
No log	97.3333	292	0.8196	0.3837	0.8196	0.9053
No log	98.0	294	0.8195	0.3837	0.8195	0.9053
No log	98.6667	296	0.8197	0.3837	0.8197	0.9054
No log	99.3333	298	0.8198	0.3837	0.8198	0.9054
No log	100.0	300	0.8198	0.3837	0.8198	0.9054

Framework versions

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