bert_baseline_prompt_adherence_task4_fold2

This model is a fine-tuned version of google-bert/bert-base-cased on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.3619
• Qwk: 0.6718
• Mse: 0.3642

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: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Qwk	Mse
No log	0.0299	2	1.6150	0.0	1.6151
No log	0.0597	4	1.1131	0.0	1.1127
No log	0.0896	6	0.9923	0.0	0.9917
No log	0.1194	8	0.8764	0.0931	0.8757
No log	0.1493	10	0.7878	0.3258	0.7870
No log	0.1791	12	0.7017	0.3282	0.7009
No log	0.2090	14	0.6637	0.3119	0.6629
No log	0.2388	16	0.6324	0.3554	0.6317
No log	0.2687	18	0.7643	0.2593	0.7637
No log	0.2985	20	0.6080	0.3281	0.6076
No log	0.3284	22	0.5178	0.3875	0.5177
No log	0.3582	24	0.5524	0.3591	0.5525
No log	0.3881	26	0.5475	0.3552	0.5478
No log	0.4179	28	0.4919	0.3781	0.4925
No log	0.4478	30	0.5056	0.3505	0.5060
No log	0.4776	32	0.5090	0.3430	0.5097
No log	0.5075	34	0.4966	0.4605	0.4976
No log	0.5373	36	0.5050	0.5425	0.5062
No log	0.5672	38	0.5247	0.6176	0.5262
No log	0.5970	40	0.5400	0.6151	0.5417
No log	0.6269	42	0.5638	0.5715	0.5656
No log	0.6567	44	0.5227	0.5910	0.5246
No log	0.6866	46	0.5162	0.6358	0.5182
No log	0.7164	48	0.5014	0.6362	0.5034
No log	0.7463	50	0.4957	0.6499	0.4976
No log	0.7761	52	0.4510	0.6120	0.4528
No log	0.8060	54	0.4435	0.4895	0.4450
No log	0.8358	56	0.4428	0.4449	0.4440
No log	0.8657	58	0.4246	0.5098	0.4260
No log	0.8955	60	0.4176	0.5447	0.4191
No log	0.9254	62	0.4144	0.5936	0.4160
No log	0.9552	64	0.4111	0.6017	0.4127
No log	0.9851	66	0.4215	0.5073	0.4229
No log	1.0149	68	0.4799	0.3889	0.4809
No log	1.0448	70	0.4582	0.4065	0.4593
No log	1.0746	72	0.3961	0.5408	0.3976
No log	1.1045	74	0.3860	0.5622	0.3876
No log	1.1343	76	0.3850	0.5397	0.3865
No log	1.1642	78	0.3971	0.4816	0.3985
No log	1.1940	80	0.4177	0.4745	0.4191
No log	1.2239	82	0.4110	0.5098	0.4126
No log	1.2537	84	0.3889	0.5834	0.3906
No log	1.2836	86	0.3825	0.6343	0.3843
No log	1.3134	88	0.3983	0.6735	0.4000
No log	1.3433	90	0.3892	0.6564	0.3910
No log	1.3731	92	0.4124	0.5726	0.4143
No log	1.4030	94	0.4329	0.5433	0.4347
No log	1.4328	96	0.3962	0.5530	0.3982
No log	1.4627	98	0.3875	0.5613	0.3895
No log	1.4925	100	0.3712	0.6099	0.3733
No log	1.5224	102	0.3695	0.6647	0.3719
No log	1.5522	104	0.3651	0.6477	0.3675
No log	1.5821	106	0.3638	0.6590	0.3662
No log	1.6119	108	0.3697	0.6664	0.3723
No log	1.6418	110	0.3732	0.6626	0.3759
No log	1.6716	112	0.3828	0.6856	0.3856
No log	1.7015	114	0.4137	0.7194	0.4164
No log	1.7313	116	0.3987	0.7078	0.4015
No log	1.7612	118	0.3763	0.6479	0.3790
No log	1.7910	120	0.4326	0.5145	0.4345
No log	1.8209	122	0.4430	0.4898	0.4446
No log	1.8507	124	0.3836	0.5850	0.3858
No log	1.8806	126	0.3662	0.6777	0.3690
No log	1.9104	128	0.3657	0.6847	0.3686
No log	1.9403	130	0.3716	0.6916	0.3745
No log	1.9701	132	0.3571	0.6809	0.3597
No log	2.0	134	0.3441	0.6243	0.3461
No log	2.0299	136	0.3643	0.5408	0.3658
No log	2.0597	138	0.3673	0.5518	0.3688
No log	2.0896	140	0.3785	0.5621	0.3801
No log	2.1194	142	0.3667	0.5927	0.3684
No log	2.1493	144	0.3548	0.6597	0.3568
No log	2.1791	146	0.3561	0.6778	0.3583
No log	2.2090	148	0.3534	0.6716	0.3554
No log	2.2388	150	0.3540	0.6743	0.3560
No log	2.2687	152	0.3537	0.6544	0.3555
No log	2.2985	154	0.3533	0.6431	0.3550
No log	2.3284	156	0.3628	0.6787	0.3651
No log	2.3582	158	0.3772	0.6896	0.3799
No log	2.3881	160	0.3757	0.6716	0.3785
No log	2.4179	162	0.3721	0.6471	0.3745
No log	2.4478	164	0.3928	0.5908	0.3947
No log	2.4776	166	0.3910	0.5933	0.3928
No log	2.5075	168	0.3730	0.6497	0.3753
No log	2.5373	170	0.3663	0.6622	0.3689
No log	2.5672	172	0.3630	0.6852	0.3658
No log	2.5970	174	0.3529	0.6644	0.3554
No log	2.6269	176	0.3522	0.6532	0.3543
No log	2.6567	178	0.3531	0.6474	0.3552
No log	2.6866	180	0.3544	0.6314	0.3565
No log	2.7164	182	0.3551	0.6349	0.3573
No log	2.7463	184	0.3573	0.6408	0.3595
No log	2.7761	186	0.3585	0.6419	0.3607
No log	2.8060	188	0.3552	0.6452	0.3574
No log	2.8358	190	0.3526	0.6438	0.3548
No log	2.8657	192	0.3496	0.6430	0.3517
No log	2.8955	194	0.3533	0.6347	0.3551
No log	2.9254	196	0.3628	0.6228	0.3645
No log	2.9552	198	0.3575	0.6505	0.3596
No log	2.9851	200	0.3609	0.6649	0.3632
No log	3.0149	202	0.3745	0.6968	0.3773
No log	3.0448	204	0.3948	0.7071	0.3979
No log	3.0746	206	0.4027	0.7042	0.4059
No log	3.1045	208	0.3964	0.7026	0.3994
No log	3.1343	210	0.3705	0.6951	0.3730
No log	3.1642	212	0.3664	0.6148	0.3682
No log	3.1940	214	0.3754	0.5845	0.3770
No log	3.2239	216	0.3698	0.5859	0.3713
No log	3.2537	218	0.3582	0.6089	0.3598
No log	3.2836	220	0.3515	0.6564	0.3534
No log	3.3134	222	0.3522	0.6775	0.3543
No log	3.3433	224	0.3535	0.6820	0.3556
No log	3.3731	226	0.3554	0.6878	0.3576
No log	3.4030	228	0.3605	0.6915	0.3630
No log	3.4328	230	0.3839	0.7020	0.3867
No log	3.4627	232	0.3961	0.7105	0.3990
No log	3.4925	234	0.3751	0.7051	0.3778
No log	3.5224	236	0.3457	0.6892	0.3479
No log	3.5522	238	0.3464	0.6424	0.3479
No log	3.5821	240	0.3583	0.6144	0.3597
No log	3.6119	242	0.3556	0.6319	0.3571
No log	3.6418	244	0.3514	0.6898	0.3534
No log	3.6716	246	0.3516	0.6929	0.3537
No log	3.7015	248	0.3512	0.6900	0.3533
No log	3.7313	250	0.3522	0.6904	0.3543
No log	3.7612	252	0.3510	0.6830	0.3530
No log	3.7910	254	0.3507	0.6780	0.3526
No log	3.8209	256	0.3612	0.6288	0.3626
No log	3.8507	258	0.3904	0.5419	0.3914
No log	3.8806	260	0.3907	0.5404	0.3917
No log	3.9104	262	0.3671	0.5869	0.3683
No log	3.9403	264	0.3493	0.6553	0.3510
No log	3.9701	266	0.3487	0.6782	0.3508
No log	4.0	268	0.3501	0.6847	0.3523
No log	4.0299	270	0.3476	0.6695	0.3497
No log	4.0597	272	0.3472	0.6652	0.3490
No log	4.0896	274	0.3531	0.6503	0.3548
No log	4.1194	276	0.3593	0.6312	0.3610
No log	4.1493	278	0.3624	0.6358	0.3641
No log	4.1791	280	0.3685	0.6320	0.3703
No log	4.2090	282	0.3659	0.6432	0.3678
No log	4.2388	284	0.3634	0.6778	0.3657
No log	4.2687	286	0.3687	0.6865	0.3713
No log	4.2985	288	0.3752	0.6901	0.3780
No log	4.3284	290	0.3746	0.6925	0.3774
No log	4.3582	292	0.3677	0.6883	0.3702
No log	4.3881	294	0.3627	0.6674	0.3649
No log	4.4179	296	0.3664	0.6362	0.3683
No log	4.4478	298	0.3710	0.6230	0.3727
No log	4.4776	300	0.3702	0.6190	0.3719
No log	4.5075	302	0.3687	0.6266	0.3704
No log	4.5373	304	0.3642	0.6383	0.3660
No log	4.5672	306	0.3607	0.6552	0.3626
No log	4.5970	308	0.3603	0.6705	0.3625
No log	4.6269	310	0.3622	0.6824	0.3646
No log	4.6567	312	0.3636	0.6819	0.3660
No log	4.6866	314	0.3626	0.6819	0.3650
No log	4.7164	316	0.3613	0.6799	0.3636
No log	4.7463	318	0.3606	0.6772	0.3629
No log	4.7761	320	0.3605	0.6736	0.3627
No log	4.8060	322	0.3607	0.6665	0.3629
No log	4.8358	324	0.3607	0.6611	0.3629
No log	4.8657	326	0.3609	0.6727	0.3630
No log	4.8955	328	0.3611	0.6736	0.3633
No log	4.9254	330	0.3615	0.6698	0.3638
No log	4.9552	332	0.3618	0.6718	0.3641
No log	4.9851	334	0.3619	0.6718	0.3642

Framework versions

• Transformers 4.42.3
• Pytorch 2.1.2
• Datasets 2.20.0
• Tokenizers 0.19.1