Training Loss	Epoch	Step	Validation Loss	Accuracy	Brier Loss	Nll	F1 Micro	F1 Macro	Ece	Aurc
No log	1.0	7	1.8736	0.105	1.0144	8.6059	0.1050	0.0844	0.3169	0.8967
No log	2.0	14	1.2559	0.155	0.8899	7.1587	0.155	0.1259	0.2459	0.7824
No log	3.0	21	1.0441	0.33	0.8123	5.3633	0.33	0.2575	0.2995	0.5173
No log	4.0	28	0.9169	0.525	0.6852	3.4671	0.525	0.4253	0.3387	0.2892
No log	5.0	35	0.8589	0.615	0.6269	3.1119	0.615	0.5500	0.3683	0.2124
No log	6.0	42	0.7954	0.675	0.5756	2.2578	0.675	0.5752	0.3626	0.1550
No log	7.0	49	0.7664	0.685	0.5143	1.8811	0.685	0.6073	0.3254	0.1390
No log	8.0	56	0.7305	0.76	0.4895	1.5449	0.76	0.6768	0.3695	0.1016
No log	9.0	63	0.7056	0.765	0.4721	1.3575	0.765	0.6991	0.3828	0.0927
No log	10.0	70	0.6961	0.77	0.4380	1.2662	0.7700	0.7509	0.3549	0.0803
No log	11.0	77	0.6772	0.81	0.4508	1.3169	0.81	0.7915	0.4175	0.0629
No log	12.0	84	0.6766	0.785	0.4491	1.2979	0.785	0.7650	0.3839	0.0800
No log	13.0	91	0.6754	0.785	0.4382	1.2395	0.785	0.7794	0.3609	0.0689
No log	14.0	98	0.6768	0.8	0.4472	1.2218	0.8000	0.7837	0.3910	0.0640
No log	15.0	105	0.6793	0.81	0.4663	1.2698	0.81	0.7856	0.4293	0.0672
No log	16.0	112	0.6784	0.795	0.4726	1.3043	0.795	0.7728	0.4232	0.0669
No log	17.0	119	0.6638	0.805	0.4372	1.2746	0.805	0.7747	0.3956	0.0677
No log	18.0	126	0.6588	0.8	0.4297	1.4466	0.8000	0.7762	0.3866	0.0686
No log	19.0	133	0.6588	0.81	0.4588	1.2093	0.81	0.7912	0.4029	0.0702
No log	20.0	140	0.6587	0.81	0.4534	1.0697	0.81	0.7980	0.4197	0.0641
No log	21.0	147	0.6527	0.815	0.4529	1.1527	0.815	0.7942	0.4196	0.0598
No log	22.0	154	0.6608	0.78	0.4559	1.2039	0.78	0.7581	0.3612	0.0725
No log	23.0	161	0.6558	0.8	0.4547	1.0687	0.8000	0.7644	0.3964	0.0584
No log	24.0	168	0.6584	0.8	0.4491	1.2869	0.8000	0.7735	0.3810	0.0687
No log	25.0	175	0.6493	0.805	0.4497	0.9981	0.805	0.7887	0.4162	0.0570
No log	26.0	182	0.6425	0.795	0.4424	1.1317	0.795	0.7790	0.3974	0.0596
No log	27.0	189	0.6518	0.8	0.4552	0.9743	0.8000	0.7715	0.4122	0.0592
No log	28.0	196	0.6526	0.805	0.4630	1.1343	0.805	0.7941	0.4171	0.0672
No log	29.0	203	0.6515	0.8	0.4531	1.0062	0.8000	0.7681	0.3970	0.0566
No log	30.0	210	0.6459	0.795	0.4534	1.0893	0.795	0.7853	0.3972	0.0600
No log	31.0	217	0.6423	0.81	0.4483	0.9035	0.81	0.7927	0.4297	0.0536
No log	32.0	224	0.6454	0.8	0.4517	1.1025	0.8000	0.7688	0.3923	0.0599
No log	33.0	231	0.6417	0.805	0.4476	0.9658	0.805	0.7767	0.4136	0.0563
No log	34.0	238	0.6399	0.815	0.4462	0.8565	0.815	0.7940	0.4234	0.0550
No log	35.0	245	0.6430	0.81	0.4505	1.0491	0.81	0.7855	0.4279	0.0629
No log	36.0	252	0.6440	0.815	0.4481	1.0288	0.815	0.7813	0.4132	0.0539
No log	37.0	259	0.6396	0.82	0.4493	0.9477	0.82	0.8125	0.4266	0.0525
No log	38.0	266	0.6410	0.815	0.4462	1.0462	0.815	0.7971	0.4157	0.0522
No log	39.0	273	0.6360	0.8	0.4399	0.9645	0.8000	0.7779	0.3974	0.0566
No log	40.0	280	0.6376	0.805	0.4412	0.8777	0.805	0.7772	0.4104	0.0544
No log	41.0	287	0.6411	0.795	0.4475	0.9240	0.795	0.7780	0.4062	0.0583
No log	42.0	294	0.6398	0.795	0.4509	0.9279	0.795	0.7650	0.4068	0.0577
No log	43.0	301	0.6430	0.79	0.4567	0.9279	0.79	0.7683	0.4073	0.0590
No log	44.0	308	0.6401	0.8	0.4495	0.9915	0.8000	0.7744	0.4200	0.0565
No log	45.0	315	0.6364	0.795	0.4448	0.9245	0.795	0.7729	0.4115	0.0568
No log	46.0	322	0.6391	0.79	0.4472	1.0060	0.79	0.7633	0.4044	0.0561
No log	47.0	329	0.6376	0.795	0.4470	0.9530	0.795	0.7693	0.3989	0.0578
No log	48.0	336	0.6383	0.8	0.4476	0.9992	0.8000	0.7804	0.4084	0.0579
No log	49.0	343	0.6353	0.8	0.4424	0.8500	0.8000	0.7756	0.4055	0.0546
No log	50.0	350	0.6381	0.795	0.4470	0.9931	0.795	0.7691	0.4170	0.0573
No log	51.0	357	0.6374	0.795	0.4477	0.9729	0.795	0.7630	0.4076	0.0563
No log	52.0	364	0.6377	0.8	0.4481	0.9846	0.8000	0.7759	0.4212	0.0555
No log	53.0	371	0.6378	0.795	0.4485	0.9379	0.795	0.7733	0.4052	0.0565
No log	54.0	378	0.6385	0.79	0.4477	0.9900	0.79	0.7684	0.4165	0.0571
No log	55.0	385	0.6371	0.81	0.4466	0.9178	0.81	0.7867	0.4149	0.0546
No log	56.0	392	0.6373	0.795	0.4460	0.9254	0.795	0.7692	0.4081	0.0568
No log	57.0	399	0.6376	0.79	0.4476	0.9194	0.79	0.7596	0.3996	0.0568
No log	58.0	406	0.6380	0.79	0.4477	0.9259	0.79	0.7619	0.4024	0.0575
No log	59.0	413	0.6377	0.8	0.4474	0.9100	0.8000	0.7806	0.4096	0.0569
No log	60.0	420	0.6378	0.8	0.4481	0.9189	0.8000	0.7806	0.4076	0.0566
No log	61.0	427	0.6378	0.795	0.4478	0.9860	0.795	0.7709	0.3994	0.0566
No log	62.0	434	0.6380	0.795	0.4480	0.9189	0.795	0.7692	0.4070	0.0564
No log	63.0	441	0.6381	0.8	0.4482	0.9195	0.8000	0.7806	0.4047	0.0568
No log	64.0	448	0.6379	0.8	0.4480	0.9223	0.8000	0.7806	0.4224	0.0563
No log	65.0	455	0.6382	0.8	0.4481	0.9196	0.8000	0.7806	0.4113	0.0569
No log	66.0	462	0.6381	0.8	0.4484	0.9200	0.8000	0.7806	0.4308	0.0566
No log	67.0	469	0.6379	0.8	0.4479	0.9198	0.8000	0.7806	0.4186	0.0566
No log	68.0	476	0.6378	0.8	0.4476	0.9167	0.8000	0.7806	0.4166	0.0569
No log	69.0	483	0.6380	0.8	0.4481	0.9179	0.8000	0.7806	0.4254	0.0566
No log	70.0	490	0.6384	0.795	0.4486	0.9225	0.795	0.7709	0.4158	0.0566
No log	71.0	497	0.6380	0.795	0.4476	0.9211	0.795	0.7709	0.4215	0.0568
0.5133	72.0	504	0.6381	0.795	0.4480	0.9232	0.795	0.7709	0.4151	0.0566
0.5133	73.0	511	0.6380	0.795	0.4479	0.9242	0.795	0.7709	0.4218	0.0564
0.5133	74.0	518	0.6380	0.795	0.4478	0.9231	0.795	0.7709	0.4151	0.0566
0.5133	75.0	525	0.6382	0.795	0.4484	0.9245	0.795	0.7709	0.4156	0.0565
0.5133	76.0	532	0.6382	0.795	0.4481	0.9216	0.795	0.7709	0.4153	0.0567
0.5133	77.0	539	0.6382	0.795	0.4481	0.9231	0.795	0.7709	0.4222	0.0567
0.5133	78.0	546	0.6382	0.795	0.4481	0.9210	0.795	0.7709	0.4220	0.0565
0.5133	79.0	553	0.6382	0.795	0.4480	0.9220	0.795	0.7709	0.4220	0.0565
0.5133	80.0	560	0.6384	0.795	0.4484	0.9220	0.795	0.7709	0.4224	0.0567
0.5133	81.0	567	0.6383	0.795	0.4483	0.9218	0.795	0.7709	0.4224	0.0567
0.5133	82.0	574	0.6382	0.795	0.4480	0.9220	0.795	0.7709	0.4221	0.0568
0.5133	83.0	581	0.6384	0.795	0.4484	0.9240	0.795	0.7709	0.4157	0.0566
0.5133	84.0	588	0.6384	0.795	0.4484	0.9262	0.795	0.7709	0.4224	0.0566
0.5133	85.0	595	0.6382	0.795	0.4481	0.9235	0.795	0.7709	0.4221	0.0566
0.5133	86.0	602	0.6384	0.795	0.4484	0.9236	0.795	0.7709	0.4225	0.0566
0.5133	87.0	609	0.6384	0.795	0.4484	0.9235	0.795	0.7709	0.4225	0.0567
0.5133	88.0	616	0.6384	0.795	0.4483	0.9250	0.795	0.7709	0.4224	0.0566
0.5133	89.0	623	0.6384	0.795	0.4483	0.9244	0.795	0.7709	0.4223	0.0567
0.5133	90.0	630	0.6384	0.795	0.4483	0.9251	0.795	0.7709	0.4224	0.0567
0.5133	91.0	637	0.6384	0.795	0.4484	0.9246	0.795	0.7709	0.4224	0.0567
0.5133	92.0	644	0.6384	0.795	0.4484	0.9256	0.795	0.7709	0.4224	0.0567
0.5133	93.0	651	0.6385	0.795	0.4484	0.9252	0.795	0.7709	0.4224	0.0567
0.5133	94.0	658	0.6384	0.795	0.4484	0.9245	0.795	0.7709	0.4223	0.0565
0.5133	95.0	665	0.6385	0.795	0.4484	0.9254	0.795	0.7709	0.4224	0.0567
0.5133	96.0	672	0.6384	0.795	0.4484	0.9242	0.795	0.7709	0.4225	0.0566
0.5133	97.0	679	0.6384	0.795	0.4484	0.9242	0.795	0.7709	0.4224	0.0567
0.5133	98.0	686	0.6385	0.795	0.4484	0.9249	0.795	0.7709	0.4224	0.0567
0.5133	99.0	693	0.6385	0.795	0.4484	0.9252	0.795	0.7709	0.4224	0.0566
0.5133	100.0	700	0.6385	0.795	0.4484	0.9250	0.795	0.7709	0.4225	0.0567

Framework versions

Transformers 4.26.1
Pytorch 1.13.1.post200
Datasets 2.9.0
Tokenizers 0.13.2

jordyvl/18-tiny_tobacco3482_kd_CEKD_t2.5_a0.5

18-tiny_tobacco3482_kd_CEKD_t2.5_a0.5

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

jordyvl/
18-tiny_tobacco3482_kd_CEKD_t2.5_a0.5