bert_baseline_prompt_adherence_task3_fold1

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: 0.3261
• Qwk: 0.7419
• Mse: 0.3261

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	0.0308	2	0.9807	0.1780	0.9807
No log	0.0615	4	0.8190	0.0	0.8190
No log	0.0923	6	0.7346	0.0	0.7346
No log	0.1231	8	0.7097	0.0	0.7097
No log	0.1538	10	0.7013	0.0	0.7013
No log	0.1846	12	0.6926	0.0	0.6926
No log	0.2154	14	0.6150	0.2050	0.6150
No log	0.2462	16	0.5746	0.2776	0.5746
No log	0.2769	18	0.5175	0.4580	0.5175
No log	0.3077	20	0.5071	0.5008	0.5071
No log	0.3385	22	0.4892	0.5513	0.4892
No log	0.3692	24	0.4671	0.5600	0.4671
No log	0.4	26	0.4385	0.5743	0.4385
No log	0.4308	28	0.4164	0.5687	0.4164
No log	0.4615	30	0.4113	0.6369	0.4113
No log	0.4923	32	0.4986	0.6548	0.4986
No log	0.5231	34	0.5170	0.6308	0.5170
No log	0.5538	36	0.4885	0.5581	0.4885
No log	0.5846	38	0.4618	0.5734	0.4618
No log	0.6154	40	0.4343	0.3746	0.4343
No log	0.6462	42	0.4788	0.3393	0.4788
No log	0.6769	44	0.4827	0.3710	0.4827
No log	0.7077	46	0.3803	0.5139	0.3803
No log	0.7385	48	0.3696	0.6756	0.3696
No log	0.7692	50	0.3869	0.6732	0.3869
No log	0.8	52	0.3724	0.6508	0.3724
No log	0.8308	54	0.3556	0.6402	0.3556
No log	0.8615	56	0.3590	0.5721	0.3590
No log	0.8923	58	0.3473	0.5751	0.3473
No log	0.9231	60	0.3341	0.6211	0.3341
No log	0.9538	62	0.3796	0.6945	0.3796
No log	0.9846	64	0.4263	0.7143	0.4263
No log	1.0154	66	0.4252	0.7207	0.4252
No log	1.0462	68	0.4305	0.7265	0.4305
No log	1.0769	70	0.3484	0.7072	0.3484
No log	1.1077	72	0.3248	0.6605	0.3248
No log	1.1385	74	0.3408	0.6993	0.3408
No log	1.1692	76	0.3358	0.6859	0.3358
No log	1.2	78	0.3628	0.7167	0.3628
No log	1.2308	80	0.3367	0.7063	0.3367
No log	1.2615	82	0.3377	0.7016	0.3377
No log	1.2923	84	0.3682	0.7021	0.3682
No log	1.3231	86	0.3592	0.6835	0.3592
No log	1.3538	88	0.3456	0.6733	0.3456
No log	1.3846	90	0.3377	0.6864	0.3377
No log	1.4154	92	0.3212	0.6771	0.3212
No log	1.4462	94	0.3114	0.6704	0.3114
No log	1.4769	96	0.3247	0.6922	0.3247
No log	1.5077	98	0.3329	0.7037	0.3329
No log	1.5385	100	0.3875	0.7406	0.3875
No log	1.5692	102	0.3673	0.7270	0.3673
No log	1.6	104	0.3376	0.7079	0.3376
No log	1.6308	106	0.3260	0.6641	0.3260
No log	1.6615	108	0.3205	0.6688	0.3205
No log	1.6923	110	0.3265	0.7115	0.3265
No log	1.7231	112	0.4055	0.7452	0.4055
No log	1.7538	114	0.4056	0.7501	0.4056
No log	1.7846	116	0.3271	0.7345	0.3271
No log	1.8154	118	0.2897	0.6549	0.2897
No log	1.8462	120	0.2970	0.5891	0.2970
No log	1.8769	122	0.3028	0.6598	0.3028
No log	1.9077	124	0.3424	0.7042	0.3424
No log	1.9385	126	0.3600	0.7182	0.3600
No log	1.9692	128	0.3537	0.7192	0.3537
No log	2.0	130	0.3151	0.7111	0.3151
No log	2.0308	132	0.2889	0.6887	0.2889
No log	2.0615	134	0.2812	0.6636	0.2812
No log	2.0923	136	0.2804	0.6723	0.2804
No log	2.1231	138	0.2997	0.7178	0.2997
No log	2.1538	140	0.3040	0.7180	0.3040
No log	2.1846	142	0.2868	0.6978	0.2868
No log	2.2154	144	0.3064	0.7133	0.3064
No log	2.2462	146	0.3242	0.7393	0.3242
No log	2.2769	148	0.3634	0.7441	0.3634
No log	2.3077	150	0.3306	0.7538	0.3306
No log	2.3385	152	0.2919	0.6979	0.2919
No log	2.3692	154	0.2832	0.6896	0.2832
No log	2.4	156	0.2814	0.6919	0.2814
No log	2.4308	158	0.3092	0.7323	0.3092
No log	2.4615	160	0.3124	0.7312	0.3124
No log	2.4923	162	0.2931	0.6999	0.2931
No log	2.5231	164	0.2997	0.7057	0.2997
No log	2.5538	166	0.2948	0.6755	0.2948
No log	2.5846	168	0.2973	0.6602	0.2973
No log	2.6154	170	0.3109	0.6931	0.3109
No log	2.6462	172	0.3195	0.7091	0.3195
No log	2.6769	174	0.3614	0.7301	0.3614
No log	2.7077	176	0.3865	0.7458	0.3865
No log	2.7385	178	0.3807	0.7437	0.3807
No log	2.7692	180	0.3296	0.7136	0.3296
No log	2.8	182	0.3040	0.6771	0.3040
No log	2.8308	184	0.3004	0.6553	0.3004
No log	2.8615	186	0.3005	0.6671	0.3005
No log	2.8923	188	0.3144	0.7023	0.3144
No log	2.9231	190	0.3337	0.7186	0.3337
No log	2.9538	192	0.3574	0.7361	0.3574
No log	2.9846	194	0.3635	0.7393	0.3635
No log	3.0154	196	0.3718	0.7456	0.3718
No log	3.0462	198	0.3520	0.7369	0.3520
No log	3.0769	200	0.3182	0.7152	0.3182
No log	3.1077	202	0.2977	0.6968	0.2977
No log	3.1385	204	0.3083	0.7107	0.3083
No log	3.1692	206	0.3088	0.7154	0.3088
No log	3.2	208	0.3043	0.7046	0.3043
No log	3.2308	210	0.3116	0.7165	0.3116
No log	3.2615	212	0.3249	0.7280	0.3249
No log	3.2923	214	0.3299	0.7237	0.3299
No log	3.3231	216	0.3162	0.7211	0.3162
No log	3.3538	218	0.3099	0.7051	0.3099
No log	3.3846	220	0.3210	0.7122	0.3210
No log	3.4154	222	0.3211	0.7014	0.3211
No log	3.4462	224	0.3307	0.7150	0.3307
No log	3.4769	226	0.3494	0.7385	0.3494
No log	3.5077	228	0.3586	0.7349	0.3586
No log	3.5385	230	0.3637	0.7372	0.3637
No log	3.5692	232	0.3602	0.7341	0.3602
No log	3.6	234	0.3325	0.7104	0.3325
No log	3.6308	236	0.3106	0.6508	0.3106
No log	3.6615	238	0.3102	0.6331	0.3102
No log	3.6923	240	0.3122	0.6795	0.3122
No log	3.7231	242	0.3664	0.7351	0.3664
No log	3.7538	244	0.4637	0.7692	0.4637
No log	3.7846	246	0.4890	0.7653	0.4890
No log	3.8154	248	0.4399	0.7707	0.4399
No log	3.8462	250	0.3669	0.7570	0.3669
No log	3.8769	252	0.3203	0.7198	0.3203
No log	3.9077	254	0.3120	0.7160	0.3120
No log	3.9385	256	0.3250	0.7464	0.3250
No log	3.9692	258	0.3259	0.7473	0.3259
No log	4.0	260	0.3151	0.7323	0.3151
No log	4.0308	262	0.3094	0.7229	0.3094
No log	4.0615	264	0.3087	0.7171	0.3087
No log	4.0923	266	0.3251	0.7373	0.3251
No log	4.1231	268	0.3589	0.7566	0.3589
No log	4.1538	270	0.3822	0.7659	0.3822
No log	4.1846	272	0.3732	0.7540	0.3732
No log	4.2154	274	0.3398	0.7494	0.3398
No log	4.2462	276	0.3140	0.7166	0.3140
No log	4.2769	278	0.3087	0.6987	0.3087
No log	4.3077	280	0.3153	0.7117	0.3153
No log	4.3385	282	0.3321	0.7500	0.3321
No log	4.3692	284	0.3502	0.7553	0.3502
No log	4.4	286	0.3540	0.7564	0.3540
No log	4.4308	288	0.3416	0.7550	0.3416
No log	4.4615	290	0.3188	0.7331	0.3188
No log	4.4923	292	0.3005	0.6814	0.3005
No log	4.5231	294	0.2955	0.6704	0.2955
No log	4.5538	296	0.2953	0.6723	0.2953
No log	4.5846	298	0.2986	0.6795	0.2986
No log	4.6154	300	0.3092	0.7144	0.3092
No log	4.6462	302	0.3261	0.7374	0.3261
No log	4.6769	304	0.3347	0.7471	0.3347
No log	4.7077	306	0.3362	0.7471	0.3362
No log	4.7385	308	0.3357	0.7471	0.3357
No log	4.7692	310	0.3384	0.7490	0.3384
No log	4.8	312	0.3362	0.7490	0.3362
No log	4.8308	314	0.3300	0.7449	0.3300
No log	4.8615	316	0.3257	0.7419	0.3257
No log	4.8923	318	0.3250	0.7419	0.3250
No log	4.9231	320	0.3240	0.7419	0.3240
No log	4.9538	322	0.3250	0.7419	0.3250
No log	4.9846	324	0.3261	0.7419	0.3261

Framework versions

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