bert_baseline_prompt_adherence_task4_fold3

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: 0.3007
• Qwk: 0.7134
• Mse: 0.3007

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	1.1652	0.0	1.1652
No log	0.0597	4	0.8846	0.0	0.8846
No log	0.0896	6	0.8201	0.0410	0.8201
No log	0.1194	8	0.7309	0.3544	0.7309
No log	0.1493	10	0.7578	0.3105	0.7578
No log	0.1791	12	0.7143	0.3280	0.7143
No log	0.2090	14	0.6343	0.3423	0.6343
No log	0.2388	16	0.5999	0.3575	0.5999
No log	0.2687	18	0.5471	0.3610	0.5471
No log	0.2985	20	0.5081	0.3822	0.5081
No log	0.3284	22	0.4839	0.3950	0.4839
No log	0.3582	24	0.4767	0.4624	0.4767
No log	0.3881	26	0.4623	0.4753	0.4623
No log	0.4179	28	0.4515	0.5443	0.4515
No log	0.4478	30	0.4418	0.5861	0.4418
No log	0.4776	32	0.4497	0.6372	0.4497
No log	0.5075	34	0.4684	0.6804	0.4684
No log	0.5373	36	0.4103	0.5638	0.4103
No log	0.5672	38	0.4692	0.4278	0.4692
No log	0.5970	40	0.4385	0.4702	0.4385
No log	0.6269	42	0.4057	0.6059	0.4057
No log	0.6567	44	0.4075	0.6238	0.4075
No log	0.6866	46	0.4234	0.6279	0.4234
No log	0.7164	48	0.4115	0.6273	0.4115
No log	0.7463	50	0.4058	0.6275	0.4058
No log	0.7761	52	0.4300	0.5914	0.4300
No log	0.8060	54	0.4332	0.6025	0.4332
No log	0.8358	56	0.4235	0.6677	0.4235
No log	0.8657	58	0.4115	0.7315	0.4115
No log	0.8955	60	0.4135	0.7072	0.4135
No log	0.9254	62	0.3817	0.6369	0.3817
No log	0.9552	64	0.3606	0.5386	0.3606
No log	0.9851	66	0.3687	0.4897	0.3687
No log	1.0149	68	0.3556	0.5853	0.3556
No log	1.0448	70	0.5049	0.7415	0.5049
No log	1.0746	72	0.6769	0.7072	0.6769
No log	1.1045	74	0.6039	0.7261	0.6039
No log	1.1343	76	0.4060	0.7198	0.4060
No log	1.1642	78	0.3443	0.6533	0.3443
No log	1.1940	80	0.3495	0.5565	0.3495
No log	1.2239	82	0.3811	0.5224	0.3811
No log	1.2537	84	0.3542	0.5846	0.3542
No log	1.2836	86	0.4255	0.7504	0.4255
No log	1.3134	88	0.6892	0.7008	0.6892
No log	1.3433	90	0.8083	0.6679	0.8083
No log	1.3731	92	0.6980	0.7011	0.6980
No log	1.4030	94	0.4612	0.7265	0.4612
No log	1.4328	96	0.3490	0.5371	0.3490
No log	1.4627	98	0.5146	0.3705	0.5146
No log	1.4925	100	0.5892	0.3434	0.5892
No log	1.5224	102	0.4912	0.3726	0.4912
No log	1.5522	104	0.3555	0.5078	0.3555
No log	1.5821	106	0.3535	0.6587	0.3535
No log	1.6119	108	0.4582	0.7396	0.4582
No log	1.6418	110	0.4804	0.7252	0.4804
No log	1.6716	112	0.4264	0.7211	0.4264
No log	1.7015	114	0.3477	0.6178	0.3477
No log	1.7313	116	0.3480	0.5050	0.3480
No log	1.7612	118	0.3673	0.4892	0.3673
No log	1.7910	120	0.3600	0.4946	0.3600
No log	1.8209	122	0.3388	0.5381	0.3388
No log	1.8507	124	0.3300	0.6645	0.3300
No log	1.8806	126	0.3572	0.7312	0.3572
No log	1.9104	128	0.3822	0.7526	0.3822
No log	1.9403	130	0.4252	0.7575	0.4252
No log	1.9701	132	0.4264	0.7640	0.4264
No log	2.0	134	0.3658	0.7410	0.3658
No log	2.0299	136	0.3297	0.7094	0.3297
No log	2.0597	138	0.3264	0.7102	0.3264
No log	2.0896	140	0.3522	0.7487	0.3522
No log	2.1194	142	0.3914	0.7552	0.3914
No log	2.1493	144	0.4335	0.7680	0.4335
No log	2.1791	146	0.4439	0.7586	0.4439
No log	2.2090	148	0.3692	0.7491	0.3692
No log	2.2388	150	0.3258	0.6501	0.3258
No log	2.2687	152	0.3523	0.6000	0.3523
No log	2.2985	154	0.3407	0.6159	0.3407
No log	2.3284	156	0.3342	0.6202	0.3342
No log	2.3582	158	0.3294	0.7100	0.3294
No log	2.3881	160	0.3491	0.7501	0.3491
No log	2.4179	162	0.3731	0.7590	0.3731
No log	2.4478	164	0.3408	0.7523	0.3408
No log	2.4776	166	0.3112	0.6943	0.3112
No log	2.5075	168	0.3135	0.7184	0.3135
No log	2.5373	170	0.3134	0.7015	0.3134
No log	2.5672	172	0.3262	0.7419	0.3262
No log	2.5970	174	0.3347	0.7282	0.3347
No log	2.6269	176	0.3192	0.6942	0.3192
No log	2.6567	178	0.3078	0.6348	0.3078
No log	2.6866	180	0.3097	0.6600	0.3097
No log	2.7164	182	0.3294	0.6841	0.3294
No log	2.7463	184	0.3479	0.7260	0.3479
No log	2.7761	186	0.3401	0.7118	0.3401
No log	2.8060	188	0.3360	0.7117	0.3360
No log	2.8358	190	0.3056	0.6730	0.3056
No log	2.8657	192	0.2965	0.6508	0.2965
No log	2.8955	194	0.2960	0.6731	0.2960
No log	2.9254	196	0.3068	0.7254	0.3068
No log	2.9552	198	0.3087	0.7405	0.3087
No log	2.9851	200	0.3304	0.7504	0.3304
No log	3.0149	202	0.3751	0.7815	0.3751
No log	3.0448	204	0.3574	0.7730	0.3574
No log	3.0746	206	0.3088	0.7355	0.3088
No log	3.1045	208	0.2871	0.6991	0.2871
No log	3.1343	210	0.2886	0.6702	0.2886
No log	3.1642	212	0.2844	0.7040	0.2844
No log	3.1940	214	0.3033	0.7327	0.3033
No log	3.2239	216	0.3049	0.7362	0.3049
No log	3.2537	218	0.2916	0.6614	0.2916
No log	3.2836	220	0.2944	0.6488	0.2944
No log	3.3134	222	0.2985	0.6593	0.2985
No log	3.3433	224	0.2998	0.6534	0.2998
No log	3.3731	226	0.3006	0.6674	0.3006
No log	3.4030	228	0.3110	0.7123	0.3110
No log	3.4328	230	0.3410	0.7500	0.3410
No log	3.4627	232	0.3420	0.7495	0.3420
No log	3.4925	234	0.3212	0.7474	0.3212
No log	3.5224	236	0.3012	0.7157	0.3012
No log	3.5522	238	0.2985	0.7168	0.2985
No log	3.5821	240	0.3101	0.7502	0.3101
No log	3.6119	242	0.3348	0.7567	0.3348
No log	3.6418	244	0.3399	0.7589	0.3399
No log	3.6716	246	0.3245	0.7547	0.3245
No log	3.7015	248	0.3113	0.7515	0.3113
No log	3.7313	250	0.2960	0.7236	0.2960
No log	3.7612	252	0.2962	0.7293	0.2962
No log	3.7910	254	0.3069	0.7442	0.3069
No log	3.8209	256	0.3069	0.7433	0.3069
No log	3.8507	258	0.2979	0.7457	0.2979
No log	3.8806	260	0.2953	0.7366	0.2953
No log	3.9104	262	0.2937	0.7168	0.2937
No log	3.9403	264	0.2930	0.6800	0.2930
No log	3.9701	266	0.2948	0.6522	0.2948
No log	4.0	268	0.2976	0.6603	0.2976
No log	4.0299	270	0.3080	0.7057	0.3080
No log	4.0597	272	0.3385	0.7483	0.3385
No log	4.0896	274	0.3662	0.7436	0.3662
No log	4.1194	276	0.3628	0.7465	0.3628
No log	4.1493	278	0.3366	0.7420	0.3366
No log	4.1791	280	0.3211	0.7371	0.3211
No log	4.2090	282	0.3076	0.7307	0.3076
No log	4.2388	284	0.3029	0.6986	0.3029
No log	4.2687	286	0.3028	0.6533	0.3028
No log	4.2985	288	0.3025	0.6613	0.3025
No log	4.3284	290	0.3052	0.7293	0.3052
No log	4.3582	292	0.3108	0.7444	0.3108
No log	4.3881	294	0.3108	0.7444	0.3108
No log	4.4179	296	0.3085	0.7431	0.3085
No log	4.4478	298	0.3061	0.7384	0.3061
No log	4.4776	300	0.3071	0.7357	0.3071
No log	4.5075	302	0.3097	0.7392	0.3097
No log	4.5373	304	0.3115	0.7464	0.3115
No log	4.5672	306	0.3114	0.7477	0.3114
No log	4.5970	308	0.3072	0.7332	0.3072
No log	4.6269	310	0.3050	0.7310	0.3050
No log	4.6567	312	0.3040	0.7358	0.3040
No log	4.6866	314	0.3036	0.7311	0.3036
No log	4.7164	316	0.3050	0.7392	0.3050
No log	4.7463	318	0.3053	0.7440	0.3053
No log	4.7761	320	0.3055	0.7440	0.3055
No log	4.8060	322	0.3037	0.7311	0.3037
No log	4.8358	324	0.3023	0.7286	0.3023
No log	4.8657	326	0.3017	0.7284	0.3017
No log	4.8955	328	0.3009	0.7134	0.3009
No log	4.9254	330	0.3007	0.7134	0.3007
No log	4.9552	332	0.3006	0.7134	0.3006
No log	4.9851	334	0.3007	0.7134	0.3007

Framework versions

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