bert_baseline_prompt_adherence_task6_fold0

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: 0.3214
• Qwk: 0.7303
• Mse: 0.3214

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	0.0294	2	1.9024	0.0	1.9024
No log	0.0588	4	1.6433	-0.0376	1.6433
No log	0.0882	6	1.4580	-0.0106	1.4580
No log	0.1176	8	1.1646	0.0061	1.1646
No log	0.1471	10	0.9673	0.0061	0.9673
No log	0.1765	12	0.8529	0.0061	0.8529
No log	0.2059	14	0.8166	0.1658	0.8166
No log	0.2353	16	0.8014	0.0430	0.8014
No log	0.2647	18	0.7507	0.2430	0.7507
No log	0.2941	20	0.6900	0.3980	0.6900
No log	0.3235	22	0.6517	0.4566	0.6517
No log	0.3529	24	0.6213	0.4542	0.6213
No log	0.3824	26	0.5886	0.3707	0.5886
No log	0.4118	28	0.5738	0.3586	0.5738
No log	0.4412	30	0.5467	0.4152	0.5467
No log	0.4706	32	0.5428	0.3809	0.5428
No log	0.5	34	0.4846	0.4818	0.4846
No log	0.5294	36	0.4315	0.4939	0.4315
No log	0.5588	38	0.4162	0.5244	0.4162
No log	0.5882	40	0.3789	0.5985	0.3789
No log	0.6176	42	0.3613	0.5956	0.3613
No log	0.6471	44	0.3505	0.5933	0.3505
No log	0.6765	46	0.3581	0.6419	0.3581
No log	0.7059	48	0.3340	0.6165	0.3340
No log	0.7353	50	0.3323	0.6190	0.3323
No log	0.7647	52	0.3927	0.7193	0.3927
No log	0.7941	54	0.4713	0.7380	0.4713
No log	0.8235	56	0.3768	0.6750	0.3768
No log	0.8529	58	0.3531	0.5832	0.3531
No log	0.8824	60	0.4043	0.5390	0.4043
No log	0.9118	62	0.3447	0.5850	0.3447
No log	0.9412	64	0.3618	0.6575	0.3618
No log	0.9706	66	0.3572	0.6539	0.3572
No log	1.0	68	0.3949	0.6765	0.3949
No log	1.0294	70	0.3686	0.6660	0.3686
No log	1.0588	72	0.3326	0.6180	0.3326
No log	1.0882	74	0.3520	0.5823	0.3520
No log	1.1176	76	0.3303	0.6063	0.3303
No log	1.1471	78	0.3475	0.6601	0.3475
No log	1.1765	80	0.3729	0.6752	0.3729
No log	1.2059	82	0.3223	0.6533	0.3223
No log	1.2353	84	0.3665	0.5588	0.3665
No log	1.2647	86	0.3824	0.5485	0.3824
No log	1.2941	88	0.3093	0.6230	0.3093
No log	1.3235	90	0.3160	0.6514	0.3160
No log	1.3529	92	0.3212	0.6588	0.3212
No log	1.3824	94	0.3075	0.6459	0.3075
No log	1.4118	96	0.3146	0.6141	0.3146
No log	1.4412	98	0.3140	0.6051	0.3140
No log	1.4706	100	0.2968	0.6409	0.2968
No log	1.5	102	0.3146	0.6665	0.3146
No log	1.5294	104	0.3225	0.6744	0.3225
No log	1.5588	106	0.2963	0.6660	0.2963
No log	1.5882	108	0.3015	0.6202	0.3015
No log	1.6176	110	0.3128	0.6101	0.3128
No log	1.6471	112	0.2930	0.6835	0.2930
No log	1.6765	114	0.3211	0.7509	0.3211
No log	1.7059	116	0.3024	0.7304	0.3024
No log	1.7353	118	0.2830	0.6659	0.2830
No log	1.7647	120	0.2853	0.6455	0.2853
No log	1.7941	122	0.2959	0.7087	0.2959
No log	1.8235	124	0.3210	0.7212	0.3210
No log	1.8529	126	0.3687	0.7455	0.3687
No log	1.8824	128	0.3281	0.7077	0.3281
No log	1.9118	130	0.2932	0.6235	0.2932
No log	1.9412	132	0.3188	0.5858	0.3188
No log	1.9706	134	0.3395	0.5668	0.3395
No log	2.0	136	0.3031	0.5998	0.3031
No log	2.0294	138	0.2965	0.6165	0.2965
No log	2.0588	140	0.2870	0.6407	0.2870
No log	2.0882	142	0.2971	0.6951	0.2971
No log	2.1176	144	0.3088	0.7183	0.3088
No log	2.1471	146	0.2953	0.6786	0.2953
No log	2.1765	148	0.3026	0.6304	0.3026
No log	2.2059	150	0.2990	0.6499	0.2990
No log	2.2353	152	0.3100	0.6986	0.3100
No log	2.2647	154	0.3029	0.6558	0.3029
No log	2.2941	156	0.3094	0.6451	0.3094
No log	2.3235	158	0.3189	0.6789	0.3189
No log	2.3529	160	0.3296	0.7205	0.3296
No log	2.3824	162	0.3857	0.7668	0.3857
No log	2.4118	164	0.3847	0.7738	0.3847
No log	2.4412	166	0.3288	0.7196	0.3288
No log	2.4706	168	0.3127	0.6857	0.3127
No log	2.5	170	0.3142	0.6321	0.3142
No log	2.5294	172	0.2971	0.6805	0.2971
No log	2.5588	174	0.2919	0.6809	0.2919
No log	2.5882	176	0.2883	0.6832	0.2883
No log	2.6176	178	0.2908	0.7045	0.2908
No log	2.6471	180	0.3183	0.7436	0.3183
No log	2.6765	182	0.3840	0.7915	0.3840
No log	2.7059	184	0.4421	0.8013	0.4421
No log	2.7353	186	0.4693	0.8022	0.4693
No log	2.7647	188	0.3933	0.7893	0.3933
No log	2.7941	190	0.3167	0.7355	0.3167
No log	2.8235	192	0.3053	0.6908	0.3053
No log	2.8529	194	0.3028	0.6759	0.3028
No log	2.8824	196	0.2999	0.6618	0.2999
No log	2.9118	198	0.2966	0.6730	0.2966
No log	2.9412	200	0.3041	0.6986	0.3041
No log	2.9706	202	0.3492	0.7601	0.3492
No log	3.0	204	0.3807	0.7895	0.3807
No log	3.0294	206	0.3448	0.7616	0.3448
No log	3.0588	208	0.2938	0.7110	0.2938
No log	3.0882	210	0.2832	0.6748	0.2832
No log	3.1176	212	0.2984	0.6126	0.2984
No log	3.1471	214	0.3016	0.6126	0.3016
No log	3.1765	216	0.2831	0.6494	0.2831
No log	3.2059	218	0.2895	0.7158	0.2895
No log	3.2353	220	0.3130	0.7480	0.3130
No log	3.2647	222	0.3255	0.7594	0.3255
No log	3.2941	224	0.3160	0.7489	0.3160
No log	3.3235	226	0.3049	0.7209	0.3049
No log	3.3529	228	0.2995	0.7190	0.2995
No log	3.3824	230	0.3001	0.7290	0.3001
No log	3.4118	232	0.3108	0.7388	0.3108
No log	3.4412	234	0.3102	0.7363	0.3102
No log	3.4706	236	0.3025	0.7162	0.3025
No log	3.5	238	0.2998	0.7035	0.2998
No log	3.5294	240	0.3007	0.7119	0.3007
No log	3.5588	242	0.3111	0.7343	0.3111
No log	3.5882	244	0.3146	0.7327	0.3146
No log	3.6176	246	0.2978	0.6769	0.2978
No log	3.6471	248	0.3000	0.6276	0.3000
No log	3.6765	250	0.3051	0.6143	0.3051
No log	3.7059	252	0.3019	0.6351	0.3019
No log	3.7353	254	0.3106	0.7052	0.3106
No log	3.7647	256	0.3545	0.7642	0.3545
No log	3.7941	258	0.3953	0.7867	0.3953
No log	3.8235	260	0.3837	0.7747	0.3837
No log	3.8529	262	0.3480	0.7461	0.3480
No log	3.8824	264	0.3239	0.7146	0.3239
No log	3.9118	266	0.3220	0.6736	0.3220
No log	3.9412	268	0.3211	0.6705	0.3211
No log	3.9706	270	0.3251	0.7223	0.3251
No log	4.0	272	0.3272	0.7300	0.3272
No log	4.0294	274	0.3318	0.7415	0.3318
No log	4.0588	276	0.3398	0.7610	0.3398
No log	4.0882	278	0.3381	0.7626	0.3381
No log	4.1176	280	0.3233	0.7381	0.3233
No log	4.1471	282	0.3073	0.7105	0.3073
No log	4.1765	284	0.3043	0.6954	0.3043
No log	4.2059	286	0.3047	0.6717	0.3047
No log	4.2353	288	0.3047	0.6814	0.3047
No log	4.2647	290	0.3073	0.7041	0.3073
No log	4.2941	292	0.3091	0.7089	0.3091
No log	4.3235	294	0.3070	0.7084	0.3070
No log	4.3529	296	0.3104	0.7163	0.3104
No log	4.3824	298	0.3123	0.7197	0.3123
No log	4.4118	300	0.3140	0.7269	0.3140
No log	4.4412	302	0.3164	0.7296	0.3164
No log	4.4706	304	0.3152	0.7273	0.3152
No log	4.5	306	0.3091	0.7130	0.3091
No log	4.5294	308	0.3050	0.7072	0.3050
No log	4.5588	310	0.3048	0.7058	0.3048
No log	4.5882	312	0.3085	0.7116	0.3085
No log	4.6176	314	0.3132	0.7236	0.3132
No log	4.6471	316	0.3216	0.7357	0.3216
No log	4.6765	318	0.3286	0.7448	0.3286
No log	4.7059	320	0.3381	0.7533	0.3381
No log	4.7353	322	0.3398	0.7547	0.3398
No log	4.7647	324	0.3416	0.7532	0.3416
No log	4.7941	326	0.3410	0.7532	0.3410
No log	4.8235	328	0.3387	0.7493	0.3387
No log	4.8529	330	0.3357	0.7492	0.3357
No log	4.8824	332	0.3319	0.7451	0.3319
No log	4.9118	334	0.3279	0.7365	0.3279
No log	4.9412	336	0.3242	0.7330	0.3242
No log	4.9706	338	0.3222	0.7336	0.3222
No log	5.0	340	0.3214	0.7303	0.3214

Framework versions

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