bert_baseline_prompt_adherence_task6_fold4

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: 0.3140
• Qwk: 0.7355
• Mse: 0.3140

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	1.7731	0.0	1.7731
No log	0.0588	4	1.5249	-0.0355	1.5249
No log	0.0882	6	1.3394	0.0063	1.3394
No log	0.1176	8	1.0928	0.0063	1.0928
No log	0.1471	10	0.9324	0.0	0.9324
No log	0.1765	12	0.8722	0.0	0.8722
No log	0.2059	14	0.8033	0.0496	0.8033
No log	0.2353	16	0.7505	0.2215	0.7505
No log	0.2647	18	0.7181	0.2184	0.7181
No log	0.2941	20	0.6872	0.4284	0.6872
No log	0.3235	22	0.7688	0.3774	0.7688
No log	0.3529	24	0.5964	0.3975	0.5964
No log	0.3824	26	0.6008	0.2741	0.6008
No log	0.4118	28	0.5457	0.3797	0.5457
No log	0.4412	30	0.5244	0.4100	0.5244
No log	0.4706	32	0.5016	0.4511	0.5016
No log	0.5	34	0.5591	0.4587	0.5591
No log	0.5294	36	0.5077	0.4939	0.5077
No log	0.5588	38	0.4706	0.4977	0.4706
No log	0.5882	40	0.4432	0.4991	0.4432
No log	0.6176	42	0.4155	0.5372	0.4155
No log	0.6471	44	0.4768	0.6194	0.4768
No log	0.6765	46	0.5242	0.6172	0.5242
No log	0.7059	48	0.4671	0.6175	0.4671
No log	0.7353	50	0.3960	0.6193	0.3960
No log	0.7647	52	0.4175	0.5536	0.4175
No log	0.7941	54	0.3733	0.6438	0.3733
No log	0.8235	56	0.4495	0.6714	0.4495
No log	0.8529	58	0.4330	0.6759	0.4330
No log	0.8824	60	0.3958	0.6733	0.3958
No log	0.9118	62	0.3887	0.6597	0.3887
No log	0.9412	64	0.3779	0.6713	0.3779
No log	0.9706	66	0.3633	0.6598	0.3633
No log	1.0	68	0.3660	0.6661	0.3660
No log	1.0294	70	0.3679	0.6801	0.3679
No log	1.0588	72	0.4033	0.6939	0.4033
No log	1.0882	74	0.3593	0.6694	0.3593
No log	1.1176	76	0.3401	0.6566	0.3401
No log	1.1471	78	0.4047	0.7308	0.4047
No log	1.1765	80	0.3792	0.7128	0.3792
No log	1.2059	82	0.3576	0.6205	0.3576
No log	1.2353	84	0.3725	0.5982	0.3725
No log	1.2647	86	0.3609	0.6493	0.3609
No log	1.2941	88	0.3487	0.6491	0.3487
No log	1.3235	90	0.3444	0.6190	0.3444
No log	1.3529	92	0.3382	0.6528	0.3382
No log	1.3824	94	0.4003	0.6808	0.4003
No log	1.4118	96	0.3485	0.6639	0.3485
No log	1.4412	98	0.3436	0.5977	0.3436
No log	1.4706	100	0.3353	0.6044	0.3353
No log	1.5	102	0.3425	0.6683	0.3425
No log	1.5294	104	0.3614	0.6788	0.3614
No log	1.5588	106	0.3180	0.6736	0.3180
No log	1.5882	108	0.3011	0.6451	0.3011
No log	1.6176	110	0.3116	0.6776	0.3116
No log	1.6471	112	0.3225	0.6770	0.3225
No log	1.6765	114	0.3064	0.6724	0.3064
No log	1.7059	116	0.2963	0.6510	0.2963
No log	1.7353	118	0.3046	0.6722	0.3046
No log	1.7647	120	0.4046	0.7168	0.4046
No log	1.7941	122	0.4861	0.7029	0.4861
No log	1.8235	124	0.3696	0.7054	0.3696
No log	1.8529	126	0.3163	0.6432	0.3163
No log	1.8824	128	0.3631	0.5751	0.3631
No log	1.9118	130	0.3209	0.6215	0.3209
No log	1.9412	132	0.3080	0.6676	0.3080
No log	1.9706	134	0.3557	0.7102	0.3557
No log	2.0	136	0.4403	0.7214	0.4403
No log	2.0294	138	0.4122	0.7260	0.4122
No log	2.0588	140	0.3123	0.6990	0.3123
No log	2.0882	142	0.3288	0.5868	0.3288
No log	2.1176	144	0.4142	0.5123	0.4142
No log	2.1471	146	0.3557	0.5771	0.3557
No log	2.1765	148	0.2977	0.6870	0.2977
No log	2.2059	150	0.3840	0.7335	0.3840
No log	2.2353	152	0.3987	0.7550	0.3987
No log	2.2647	154	0.3107	0.7115	0.3107
No log	2.2941	156	0.3032	0.6222	0.3032
No log	2.3235	158	0.3221	0.5907	0.3221
No log	2.3529	160	0.2993	0.6363	0.2993
No log	2.3824	162	0.2911	0.6587	0.2911
No log	2.4118	164	0.2982	0.6949	0.2982
No log	2.4412	166	0.3440	0.7431	0.3440
No log	2.4706	168	0.3482	0.7596	0.3482
No log	2.5	170	0.2934	0.6929	0.2934
No log	2.5294	172	0.3095	0.6149	0.3095
No log	2.5588	174	0.3005	0.6227	0.3005
No log	2.5882	176	0.2882	0.6912	0.2882
No log	2.6176	178	0.3117	0.7172	0.3117
No log	2.6471	180	0.3361	0.7213	0.3361
No log	2.6765	182	0.3066	0.6892	0.3066
No log	2.7059	184	0.2959	0.6777	0.2959
No log	2.7353	186	0.2988	0.6323	0.2988
No log	2.7647	188	0.2937	0.6654	0.2937
No log	2.7941	190	0.3078	0.6989	0.3078
No log	2.8235	192	0.3538	0.7279	0.3538
No log	2.8529	194	0.3596	0.7439	0.3596
No log	2.8824	196	0.3188	0.7230	0.3188
No log	2.9118	198	0.2966	0.6588	0.2966
No log	2.9412	200	0.3129	0.625	0.3129
No log	2.9706	202	0.2986	0.6571	0.2986
No log	3.0	204	0.3074	0.7078	0.3074
No log	3.0294	206	0.3579	0.7419	0.3579
No log	3.0588	208	0.3908	0.7443	0.3908
No log	3.0882	210	0.3664	0.7492	0.3664
No log	3.1176	212	0.3036	0.7114	0.3036
No log	3.1471	214	0.3011	0.6291	0.3011
No log	3.1765	216	0.3126	0.6087	0.3126
No log	3.2059	218	0.2970	0.6413	0.2970
No log	3.2353	220	0.3062	0.7192	0.3062
No log	3.2647	222	0.3390	0.7308	0.3390
No log	3.2941	224	0.3515	0.7299	0.3515
No log	3.3235	226	0.3199	0.7283	0.3199
No log	3.3529	228	0.2997	0.7073	0.2997
No log	3.3824	230	0.2946	0.6991	0.2946
No log	3.4118	232	0.3023	0.7173	0.3023
No log	3.4412	234	0.3074	0.7180	0.3074
No log	3.4706	236	0.3019	0.7045	0.3019
No log	3.5	238	0.2905	0.6931	0.2905
No log	3.5294	240	0.2957	0.7056	0.2957
No log	3.5588	242	0.2920	0.7135	0.2920
No log	3.5882	244	0.2826	0.6959	0.2826
No log	3.6176	246	0.2840	0.6513	0.2840
No log	3.6471	248	0.2867	0.6470	0.2867
No log	3.6765	250	0.2838	0.6926	0.2838
No log	3.7059	252	0.3129	0.7375	0.3129
No log	3.7353	254	0.3778	0.7924	0.3778
No log	3.7647	256	0.3806	0.7984	0.3806
No log	3.7941	258	0.3375	0.7697	0.3375
No log	3.8235	260	0.3166	0.7362	0.3166
No log	3.8529	262	0.3073	0.7274	0.3073
No log	3.8824	264	0.2995	0.7215	0.2995
No log	3.9118	266	0.2894	0.7029	0.2894
No log	3.9412	268	0.2851	0.6823	0.2851
No log	3.9706	270	0.2883	0.7121	0.2883
No log	4.0	272	0.3028	0.7266	0.3028
No log	4.0294	274	0.3086	0.7235	0.3086
No log	4.0588	276	0.3139	0.7331	0.3139
No log	4.0882	278	0.2997	0.7202	0.2997
No log	4.1176	280	0.2916	0.7012	0.2916
No log	4.1471	282	0.2878	0.6852	0.2878
No log	4.1765	284	0.2851	0.6679	0.2851
No log	4.2059	286	0.2852	0.6684	0.2852
No log	4.2353	288	0.2875	0.6871	0.2875
No log	4.2647	290	0.2872	0.6868	0.2872
No log	4.2941	292	0.2893	0.6988	0.2893
No log	4.3235	294	0.2893	0.6995	0.2893
No log	4.3529	296	0.2971	0.7215	0.2971
No log	4.3824	298	0.3064	0.7294	0.3064
No log	4.4118	300	0.3035	0.7303	0.3035
No log	4.4412	302	0.3049	0.7285	0.3049
No log	4.4706	304	0.3111	0.7348	0.3111
No log	4.5	306	0.3044	0.7264	0.3044
No log	4.5294	308	0.3038	0.7280	0.3038
No log	4.5588	310	0.3029	0.7242	0.3029
No log	4.5882	312	0.2988	0.7206	0.2988
No log	4.6176	314	0.2982	0.7202	0.2982
No log	4.6471	316	0.3030	0.7271	0.3030
No log	4.6765	318	0.3070	0.7312	0.3070
No log	4.7059	320	0.3086	0.7359	0.3086
No log	4.7353	322	0.3153	0.7364	0.3153
No log	4.7647	324	0.3182	0.7403	0.3182
No log	4.7941	326	0.3219	0.7432	0.3219
No log	4.8235	328	0.3241	0.7454	0.3241
No log	4.8529	330	0.3228	0.7422	0.3228
No log	4.8824	332	0.3217	0.7422	0.3217
No log	4.9118	334	0.3200	0.7416	0.3200
No log	4.9412	336	0.3172	0.7349	0.3172
No log	4.9706	338	0.3147	0.7355	0.3147
No log	5.0	340	0.3140	0.7355	0.3140

Framework versions

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