bert_baseline_prompt_adherence_task4_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: 0.3584
• Qwk: 0.7661
• Mse: 0.3584

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	1.2443	0.0	1.2443
No log	0.0597	4	0.9707	0.0	0.9707
No log	0.0896	6	0.8255	0.3275	0.8255
No log	0.1194	8	0.7870	0.3717	0.7870
No log	0.1493	10	0.7604	0.3805	0.7604
No log	0.1791	12	0.7414	0.3322	0.7414
No log	0.2090	14	0.7169	0.3568	0.7169
No log	0.2388	16	0.6759	0.3554	0.6759
No log	0.2687	18	0.6392	0.3504	0.6392
No log	0.2985	20	0.6005	0.3656	0.6005
No log	0.3284	22	0.5749	0.3572	0.5749
No log	0.3582	24	0.6085	0.3548	0.6085
No log	0.3881	26	0.5712	0.3867	0.5712
No log	0.4179	28	0.4782	0.4192	0.4782
No log	0.4478	30	0.4704	0.3709	0.4704
No log	0.4776	32	0.4817	0.3659	0.4817
No log	0.5075	34	0.4440	0.4181	0.4440
No log	0.5373	36	0.4484	0.4808	0.4484
No log	0.5672	38	0.4278	0.6458	0.4278
No log	0.5970	40	0.4117	0.5914	0.4117
No log	0.6269	42	0.4057	0.5708	0.4057
No log	0.6567	44	0.3990	0.6590	0.3990
No log	0.6866	46	0.3990	0.6750	0.3990
No log	0.7164	48	0.3870	0.6519	0.3870
No log	0.7463	50	0.3799	0.6386	0.3799
No log	0.7761	52	0.3939	0.7013	0.3939
No log	0.8060	54	0.5031	0.7409	0.5031
No log	0.8358	56	0.6553	0.7154	0.6553
No log	0.8657	58	0.8023	0.6679	0.8023
No log	0.8955	60	0.6686	0.7089	0.6686
No log	0.9254	62	0.4643	0.6871	0.4643
No log	0.9552	64	0.3993	0.5443	0.3993
No log	0.9851	66	0.4001	0.4857	0.4001
No log	1.0149	68	0.3614	0.5379	0.3614
No log	1.0448	70	0.3637	0.6897	0.3637
No log	1.0746	72	0.3844	0.7311	0.3844
No log	1.1045	74	0.3574	0.6973	0.3574
No log	1.1343	76	0.3401	0.6778	0.3401
No log	1.1642	78	0.3395	0.6981	0.3395
No log	1.1940	80	0.3617	0.7317	0.3617
No log	1.2239	82	0.3786	0.7466	0.3786
No log	1.2537	84	0.3423	0.7234	0.3423
No log	1.2836	86	0.3218	0.6556	0.3218
No log	1.3134	88	0.3278	0.6166	0.3278
No log	1.3433	90	0.3505	0.5513	0.3505
No log	1.3731	92	0.3330	0.5929	0.3330
No log	1.4030	94	0.3197	0.6819	0.3197
No log	1.4328	96	0.3346	0.7089	0.3346
No log	1.4627	98	0.3389	0.7312	0.3389
No log	1.4925	100	0.3203	0.7106	0.3203
No log	1.5224	102	0.3314	0.7252	0.3314
No log	1.5522	104	0.3731	0.7459	0.3731
No log	1.5821	106	0.3357	0.7275	0.3357
No log	1.6119	108	0.3198	0.6921	0.3198
No log	1.6418	110	0.3098	0.6386	0.3098
No log	1.6716	112	0.3157	0.6932	0.3157
No log	1.7015	114	0.3673	0.7532	0.3673
No log	1.7313	116	0.3748	0.7573	0.3748
No log	1.7612	118	0.3899	0.7593	0.3899
No log	1.7910	120	0.3975	0.7575	0.3975
No log	1.8209	122	0.3556	0.7447	0.3556
No log	1.8507	124	0.3253	0.6647	0.3253
No log	1.8806	126	0.3533	0.5111	0.3533
No log	1.9104	128	0.3439	0.5285	0.3439
No log	1.9403	130	0.3254	0.6668	0.3254
No log	1.9701	132	0.3701	0.7315	0.3701
No log	2.0	134	0.4611	0.7495	0.4611
No log	2.0299	136	0.5215	0.7473	0.5215
No log	2.0597	138	0.4775	0.7629	0.4775
No log	2.0896	140	0.3735	0.7431	0.3735
No log	2.1194	142	0.3063	0.7134	0.3063
No log	2.1493	144	0.2971	0.6687	0.2971
No log	2.1791	146	0.2961	0.6860	0.2961
No log	2.2090	148	0.3076	0.7257	0.3076
No log	2.2388	150	0.3181	0.7335	0.3181
No log	2.2687	152	0.3115	0.7324	0.3115
No log	2.2985	154	0.3106	0.7336	0.3106
No log	2.3284	156	0.3062	0.7246	0.3062
No log	2.3582	158	0.2957	0.7093	0.2957
No log	2.3881	160	0.2906	0.6976	0.2906
No log	2.4179	162	0.2893	0.6849	0.2893
No log	2.4478	164	0.2949	0.7037	0.2949
No log	2.4776	166	0.3165	0.7460	0.3165
No log	2.5075	168	0.3729	0.7651	0.3729
No log	2.5373	170	0.3809	0.7697	0.3809
No log	2.5672	172	0.3709	0.7628	0.3709
No log	2.5970	174	0.3413	0.7589	0.3413
No log	2.6269	176	0.2959	0.7228	0.2959
No log	2.6567	178	0.2837	0.6782	0.2837
No log	2.6866	180	0.2888	0.7069	0.2888
No log	2.7164	182	0.3101	0.7416	0.3101
No log	2.7463	184	0.3048	0.7388	0.3048
No log	2.7761	186	0.3104	0.7408	0.3104
No log	2.8060	188	0.3197	0.7525	0.3197
No log	2.8358	190	0.3004	0.7215	0.3004
No log	2.8657	192	0.2988	0.7148	0.2988
No log	2.8955	194	0.3121	0.7416	0.3121
No log	2.9254	196	0.3250	0.7529	0.3250
No log	2.9552	198	0.3176	0.7560	0.3176
No log	2.9851	200	0.2903	0.7044	0.2903
No log	3.0149	202	0.2847	0.6752	0.2847
No log	3.0448	204	0.2875	0.6945	0.2875
No log	3.0746	206	0.3199	0.7513	0.3199
No log	3.1045	208	0.3502	0.7715	0.3502
No log	3.1343	210	0.3315	0.7667	0.3315
No log	3.1642	212	0.2976	0.7158	0.2976
No log	3.1940	214	0.2918	0.6987	0.2918
No log	3.2239	216	0.2976	0.7149	0.2976
No log	3.2537	218	0.3126	0.7332	0.3126
No log	3.2836	220	0.3172	0.7364	0.3172
No log	3.3134	222	0.3281	0.7466	0.3281
No log	3.3433	224	0.3377	0.7607	0.3377
No log	3.3731	226	0.3158	0.7340	0.3158
No log	3.4030	228	0.2957	0.7081	0.2957
No log	3.4328	230	0.2992	0.7140	0.2992
No log	3.4627	232	0.3063	0.7218	0.3063
No log	3.4925	234	0.3184	0.7298	0.3184
No log	3.5224	236	0.3368	0.7492	0.3368
No log	3.5522	238	0.3361	0.7488	0.3361
No log	3.5821	240	0.3091	0.7341	0.3091
No log	3.6119	242	0.2903	0.7114	0.2903
No log	3.6418	244	0.2887	0.7066	0.2887
No log	3.6716	246	0.2996	0.7274	0.2996
No log	3.7015	248	0.3100	0.7465	0.3100
No log	3.7313	250	0.3222	0.7545	0.3222
No log	3.7612	252	0.3362	0.7657	0.3362
No log	3.7910	254	0.3708	0.7816	0.3708
No log	3.8209	256	0.3823	0.7803	0.3823
No log	3.8507	258	0.3711	0.7799	0.3711
No log	3.8806	260	0.3283	0.7588	0.3283
No log	3.9104	262	0.2906	0.7152	0.2906
No log	3.9403	264	0.2818	0.6789	0.2818
No log	3.9701	266	0.2853	0.6354	0.2853
No log	4.0	268	0.2828	0.6511	0.2828
No log	4.0299	270	0.2831	0.6897	0.2831
No log	4.0597	272	0.2921	0.7002	0.2921
No log	4.0896	274	0.3105	0.7367	0.3105
No log	4.1194	276	0.3293	0.7447	0.3293
No log	4.1493	278	0.3376	0.7589	0.3376
No log	4.1791	280	0.3380	0.7617	0.3380
No log	4.2090	282	0.3289	0.7531	0.3289
No log	4.2388	284	0.3310	0.7580	0.3310
No log	4.2687	286	0.3411	0.7673	0.3411
No log	4.2985	288	0.3570	0.7693	0.3570
No log	4.3284	290	0.3615	0.7713	0.3615
No log	4.3582	292	0.3468	0.7754	0.3468
No log	4.3881	294	0.3233	0.7388	0.3233
No log	4.4179	296	0.3046	0.7277	0.3046
No log	4.4478	298	0.2949	0.7194	0.2949
No log	4.4776	300	0.2899	0.7098	0.2899
No log	4.5075	302	0.2876	0.6944	0.2876
No log	4.5373	304	0.2882	0.6944	0.2882
No log	4.5672	306	0.2910	0.7098	0.2910
No log	4.5970	308	0.2972	0.7173	0.2972
No log	4.6269	310	0.3095	0.7307	0.3095
No log	4.6567	312	0.3256	0.7388	0.3256
No log	4.6866	314	0.3452	0.7578	0.3452
No log	4.7164	316	0.3647	0.7688	0.3647
No log	4.7463	318	0.3846	0.7727	0.3846
No log	4.7761	320	0.3940	0.7746	0.3940
No log	4.8060	322	0.3935	0.7746	0.3935
No log	4.8358	324	0.3867	0.7674	0.3867
No log	4.8657	326	0.3786	0.7635	0.3786
No log	4.8955	328	0.3706	0.7674	0.3706
No log	4.9254	330	0.3649	0.7647	0.3649
No log	4.9552	332	0.3602	0.7661	0.3602
No log	4.9851	334	0.3584	0.7661	0.3584

Framework versions

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