Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
1.6784	0.04	50	1.2099	0.5995	0.2253	0.3879	0.2247
1.0203	0.08	100	0.7696	0.7533	0.4285	0.5258	0.4563
0.7322	0.12	150	0.6271	0.8152	0.6305	0.6720	0.6056
0.6119	0.16	200	0.5934	0.8270	0.6673	0.7649	0.6662
0.6203	0.2	250	0.5759	0.8281	0.6618	0.7352	0.6566
0.5874	0.24	300	0.5446	0.8373	0.7351	0.7633	0.7256
0.5507	0.28	350	0.5371	0.8394	0.7481	0.7580	0.7435
0.5615	0.33	400	0.5272	0.8469	0.7377	0.7961	0.7241
0.5371	0.37	450	0.5193	0.8431	0.7413	0.7828	0.7299
0.5267	0.41	500	0.5124	0.8490	0.7446	0.7714	0.7321
0.4971	0.45	550	0.5105	0.8509	0.7503	0.8071	0.7192
0.5399	0.49	600	0.5149	0.8473	0.7402	0.7849	0.7291
0.5229	0.53	650	0.5190	0.8447	0.7504	0.7753	0.7421
0.5077	0.57	700	0.5096	0.8487	0.7528	0.7764	0.7413
0.5073	0.61	750	0.4946	0.8511	0.7487	0.8055	0.7279
0.4823	0.65	800	0.5105	0.8506	0.7509	0.7918	0.7292
0.483	0.69	850	0.4887	0.8542	0.7653	0.7936	0.7502
0.55	0.73	900	0.4865	0.8556	0.7599	0.8010	0.7425
0.5406	0.77	950	0.4875	0.8533	0.7515	0.8018	0.7255
0.5078	0.81	1000	0.5075	0.8564	0.7528	0.8134	0.7227
0.4965	0.85	1050	0.4789	0.8560	0.7655	0.7995	0.7405
0.4676	0.89	1100	0.4806	0.8555	0.7468	0.7989	0.7244
0.4786	0.93	1150	0.4822	0.8572	0.7587	0.7762	0.7504
0.4928	0.98	1200	0.4743	0.8569	0.7553	0.8009	0.7404
0.472	1.02	1250	0.4917	0.8581	0.7511	0.8075	0.7278
0.395	1.06	1300	0.4929	0.8573	0.7657	0.7937	0.7516
0.3735	1.1	1350	0.4844	0.8558	0.7687	0.7685	0.7693
0.3974	1.14	1400	0.5005	0.8504	0.7631	0.7556	0.7732
0.4197	1.18	1450	0.5044	0.8557	0.7475	0.8096	0.7265
0.4149	1.22	1500	0.4914	0.8560	0.7556	0.8009	0.7431
0.4937	1.26	1550	0.4684	0.8583	0.7697	0.7847	0.7596
0.344	1.3	1600	0.5126	0.8570	0.7606	0.8084	0.7369
0.4399	1.34	1650	0.4856	0.8545	0.7608	0.7947	0.7490
0.4176	1.38	1700	0.4851	0.8578	0.7648	0.8018	0.7419
0.4301	1.42	1750	0.4725	0.8579	0.7673	0.7811	0.7611
0.4161	1.46	1800	0.4794	0.8587	0.7712	0.7954	0.7583
0.3632	1.5	1850	0.4835	0.8579	0.7716	0.8036	0.7543
0.4328	1.54	1900	0.4748	0.8574	0.7744	0.7958	0.7606
0.4026	1.59	1950	0.4733	0.8571	0.7726	0.7925	0.7591
0.3792	1.63	2000	0.4826	0.8593	0.7715	0.7912	0.7576
0.4087	1.67	2050	0.4732	0.8594	0.7704	0.7954	0.7525
0.3953	1.71	2100	0.4721	0.8592	0.7724	0.7869	0.7634
0.403	1.75	2150	0.4714	0.8629	0.7737	0.8055	0.7552
0.3987	1.79	2200	0.4657	0.8617	0.7729	0.7929	0.7583
0.3891	1.83	2250	0.4694	0.8609	0.7720	0.7877	0.7664
0.4266	1.87	2300	0.4716	0.8603	0.7696	0.7953	0.7625
0.3784	1.91	2350	0.4658	0.8609	0.7735	0.7968	0.7606
0.4108	1.95	2400	0.4571	0.8611	0.7746	0.8005	0.7585
0.4227	1.99	2450	0.4575	0.8634	0.7812	0.8047	0.7643
0.2896	2.03	2500	0.4835	0.8637	0.7801	0.7916	0.7730
0.3539	2.07	2550	0.4741	0.8626	0.7787	0.7974	0.7664
0.3657	2.11	2600	0.4799	0.8579	0.7737	0.7964	0.7592
0.3407	2.15	2650	0.4765	0.8604	0.7681	0.7963	0.7524
0.317	2.2	2700	0.4817	0.8583	0.7729	0.7797	0.7705
0.3166	2.24	2750	0.4886	0.8589	0.7653	0.7917	0.7553
0.3078	2.28	2800	0.4927	0.8574	0.7709	0.7888	0.7607
0.3366	2.32	2850	0.4948	0.8600	0.7735	0.7907	0.7609
0.2863	2.36	2900	0.4994	0.8578	0.7699	0.7784	0.7668
0.255	2.4	2950	0.5017	0.8601	0.7696	0.7862	0.7575
0.3379	2.44	3000	0.4824	0.8591	0.7715	0.7787	0.7671
0.2751	2.48	3050	0.4944	0.8616	0.7745	0.7965	0.7587
0.2902	2.52	3100	0.4865	0.8596	0.7751	0.7863	0.7675
0.2917	2.56	3150	0.4875	0.8608	0.7748	0.7864	0.7656
0.3014	2.6	3200	0.4872	0.8614	0.7756	0.7886	0.7663
0.3269	2.64	3250	0.4905	0.8598	0.7763	0.7884	0.7669
0.3245	2.68	3300	0.4898	0.8625	0.7778	0.7971	0.7627
0.2951	2.72	3350	0.4864	0.8599	0.7771	0.7885	0.7686
0.2888	2.76	3400	0.4906	0.8623	0.7758	0.7969	0.7609
0.3037	2.8	3450	0.4863	0.8609	0.7751	0.7939	0.7630
0.2855	2.85	3500	0.4881	0.8621	0.7773	0.7935	0.7661
0.297	2.89	3550	0.4880	0.8620	0.7786	0.7927	0.7687
0.2753	2.93	3600	0.4887	0.8615	0.7772	0.7902	0.7679
0.2922	2.97	3650	0.4876	0.8610	0.7770	0.7883	0.7691

Framework versions

Transformers 4.38.2
Pytorch 2.1.2
Datasets 2.1.0
Tokenizers 0.15.2

waelChafei/bertuned

TTC4900Model

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

waelChafei/
bertuned