Training Loss	Epoch	Step	Validation Loss	Qwk	Mse	Rmse
No log	0.1667	2	4.9275	-0.0722	4.9275	2.2198
No log	0.3333	4	2.8519	0.1317	2.8519	1.6888
No log	0.5	6	1.7547	0.1727	1.7547	1.3246
No log	0.6667	8	1.6261	0.1830	1.6261	1.2752
No log	0.8333	10	1.1467	0.2656	1.1467	1.0709
No log	1.0	12	1.0904	0.3187	1.0904	1.0442
No log	1.1667	14	1.4339	0.0827	1.4339	1.1975
No log	1.3333	16	1.8849	-0.1332	1.8849	1.3729
No log	1.5	18	1.7453	-0.0598	1.7453	1.3211
No log	1.6667	20	1.3953	0.0369	1.3953	1.1812
No log	1.8333	22	1.2226	0.3103	1.2226	1.1057
No log	2.0	24	1.1824	0.2780	1.1824	1.0874
No log	2.1667	26	1.2120	0.1953	1.2120	1.1009
No log	2.3333	28	1.2569	0.1033	1.2569	1.1211
No log	2.5	30	1.2963	0.0436	1.2963	1.1386
No log	2.6667	32	1.2526	0.0559	1.2526	1.1192
No log	2.8333	34	1.1094	0.2794	1.1094	1.0533
No log	3.0	36	0.9655	0.4457	0.9655	0.9826
No log	3.1667	38	0.9148	0.4457	0.9148	0.9565
No log	3.3333	40	0.8363	0.4416	0.8363	0.9145
No log	3.5	42	0.7541	0.4867	0.7541	0.8684
No log	3.6667	44	0.7004	0.5057	0.7004	0.8369
No log	3.8333	46	0.6601	0.5853	0.6601	0.8125
No log	4.0	48	0.7234	0.6139	0.7234	0.8505
No log	4.1667	50	0.7494	0.6406	0.7494	0.8657
No log	4.3333	52	0.6789	0.6406	0.6789	0.8239
No log	4.5	54	0.7091	0.6378	0.7091	0.8421
No log	4.6667	56	0.7010	0.6601	0.7010	0.8373
No log	4.8333	58	0.6893	0.6777	0.6893	0.8302
No log	5.0	60	0.7383	0.6625	0.7383	0.8592
No log	5.1667	62	0.7668	0.6721	0.7668	0.8757
No log	5.3333	64	0.7527	0.6521	0.7527	0.8676
No log	5.5	66	0.6497	0.7332	0.6497	0.8060
No log	5.6667	68	0.5885	0.7466	0.5885	0.7671
No log	5.8333	70	0.5828	0.7466	0.5828	0.7634
No log	6.0	72	0.5990	0.7305	0.5990	0.7740
No log	6.1667	74	0.6409	0.6977	0.6409	0.8006
No log	6.3333	76	0.6871	0.7229	0.6871	0.8289
No log	6.5	78	0.7240	0.7014	0.7240	0.8509
No log	6.6667	80	0.7588	0.7014	0.7588	0.8711
No log	6.8333	82	0.7013	0.6957	0.7013	0.8374
No log	7.0	84	0.6660	0.6650	0.6660	0.8161
No log	7.1667	86	0.6914	0.6650	0.6914	0.8315
No log	7.3333	88	0.7450	0.6400	0.7450	0.8631
No log	7.5	90	0.7370	0.6639	0.7370	0.8585
No log	7.6667	92	0.7143	0.6993	0.7143	0.8452
No log	7.8333	94	0.6874	0.6650	0.6874	0.8291
No log	8.0	96	0.6639	0.6650	0.6639	0.8148
No log	8.1667	98	0.6708	0.6650	0.6708	0.8190
No log	8.3333	100	0.6817	0.6650	0.6817	0.8256
No log	8.5	102	0.6925	0.6650	0.6925	0.8322
No log	8.6667	104	0.6876	0.6650	0.6876	0.8292
No log	8.8333	106	0.6938	0.6993	0.6938	0.8330
No log	9.0	108	0.6932	0.6993	0.6932	0.8326
No log	9.1667	110	0.6832	0.6650	0.6832	0.8266
No log	9.3333	112	0.6770	0.6650	0.6770	0.8228
No log	9.5	114	0.6753	0.6650	0.6753	0.8218
No log	9.6667	116	0.6821	0.6993	0.6821	0.8259
No log	9.8333	118	0.6892	0.6739	0.6892	0.8302
No log	10.0	120	0.6913	0.6739	0.6913	0.8315

Framework versions

Transformers 4.44.2
Pytorch 2.4.0+cu118
Datasets 2.21.0
Tokenizers 0.19.1

MayBashendy/ArabicNewSplits2_FineTuningAraBERT_run1_AugV5_k2_task1_organization

ArabicNewSplits2_FineTuningAraBERT_run1_AugV5_k2_task1_organization

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

MayBashendy/
ArabicNewSplits2_FineTuningAraBERT_run1_AugV5_k2_task1_organization