bert_baseline_prompt_adherence_task3_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: 0.3672
• Qwk: 0.6476
• Mse: 0.3673

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	0.9615	0.1429	0.9616
No log	0.0615	4	0.7862	0.0038	0.7858
No log	0.0923	6	0.6844	0.0	0.6838
No log	0.1231	8	0.6747	0.0	0.6741
No log	0.1538	10	0.6542	0.0	0.6535
No log	0.1846	12	0.6353	0.0	0.6346
No log	0.2154	14	0.6257	0.0	0.6251
No log	0.2462	16	0.6083	0.0	0.6077
No log	0.2769	18	0.5683	0.0	0.5677
No log	0.3077	20	0.5631	0.0087	0.5626
No log	0.3385	22	0.5316	0.0587	0.5312
No log	0.3692	24	0.5169	0.0454	0.5164
No log	0.4	26	0.6864	0.0277	0.6859
No log	0.4308	28	0.7257	0.1009	0.7252
No log	0.4615	30	0.5620	0.4027	0.5615
No log	0.4923	32	0.4296	0.4319	0.4292
No log	0.5231	34	0.4145	0.3748	0.4142
No log	0.5538	36	0.4076	0.4540	0.4073
No log	0.5846	38	0.4092	0.4943	0.4091
No log	0.6154	40	0.4155	0.5085	0.4154
No log	0.6462	42	0.3900	0.4752	0.3899
No log	0.6769	44	0.3908	0.4653	0.3907
No log	0.7077	46	0.3797	0.5278	0.3797
No log	0.7385	48	0.4396	0.5822	0.4395
No log	0.7692	50	0.5112	0.5465	0.5110
No log	0.8	52	0.4901	0.5905	0.4898
No log	0.8308	54	0.4233	0.5483	0.4230
No log	0.8615	56	0.3703	0.5119	0.3701
No log	0.8923	58	0.3680	0.4891	0.3679
No log	0.9231	60	0.3758	0.4994	0.3758
No log	0.9538	62	0.3686	0.5173	0.3687
No log	0.9846	64	0.3553	0.5850	0.3554
No log	1.0154	66	0.3982	0.6446	0.3982
No log	1.0462	68	0.4363	0.6294	0.4363
No log	1.0769	70	0.4614	0.6294	0.4614
No log	1.1077	72	0.3792	0.6388	0.3794
No log	1.1385	74	0.3585	0.5345	0.3588
No log	1.1692	76	0.3653	0.4926	0.3656
No log	1.2	78	0.3399	0.5941	0.3401
No log	1.2308	80	0.3858	0.6290	0.3858
No log	1.2615	82	0.3975	0.6239	0.3974
No log	1.2923	84	0.3774	0.6024	0.3773
No log	1.3231	86	0.3559	0.5760	0.3559
No log	1.3538	88	0.3482	0.5222	0.3483
No log	1.3846	90	0.3434	0.5102	0.3434
No log	1.4154	92	0.3413	0.5185	0.3413
No log	1.4462	94	0.3582	0.5777	0.3580
No log	1.4769	96	0.4007	0.6123	0.4005
No log	1.5077	98	0.4155	0.6218	0.4152
No log	1.5385	100	0.3631	0.6169	0.3631
No log	1.5692	102	0.3270	0.5561	0.3272
No log	1.6	104	0.3283	0.5718	0.3285
No log	1.6308	106	0.3685	0.6305	0.3685
No log	1.6615	108	0.4489	0.6318	0.4488
No log	1.6923	110	0.4564	0.6312	0.4563
No log	1.7231	112	0.3829	0.6407	0.3829
No log	1.7538	114	0.3263	0.5923	0.3265
No log	1.7846	116	0.3309	0.5543	0.3312
No log	1.8154	118	0.3249	0.5825	0.3250
No log	1.8462	120	0.3435	0.6119	0.3435
No log	1.8769	122	0.4346	0.6258	0.4345
No log	1.9077	124	0.5205	0.6379	0.5201
No log	1.9385	126	0.5314	0.6348	0.5311
No log	1.9692	128	0.4719	0.6443	0.4717
No log	2.0	130	0.3841	0.6266	0.3840
No log	2.0308	132	0.3337	0.5746	0.3337
No log	2.0615	134	0.3699	0.4733	0.3700
No log	2.0923	136	0.3926	0.4274	0.3928
No log	2.1231	138	0.3637	0.4600	0.3639
No log	2.1538	140	0.3353	0.5317	0.3354
No log	2.1846	142	0.3592	0.5948	0.3591
No log	2.2154	144	0.3889	0.6171	0.3888
No log	2.2462	146	0.3890	0.6239	0.3889
No log	2.2769	148	0.3593	0.6240	0.3593
No log	2.3077	150	0.3409	0.6086	0.3410
No log	2.3385	152	0.3386	0.5812	0.3387
No log	2.3692	154	0.3416	0.5988	0.3417
No log	2.4	156	0.3500	0.6069	0.3500
No log	2.4308	158	0.3473	0.5999	0.3474
No log	2.4615	160	0.3635	0.6239	0.3635
No log	2.4923	162	0.3797	0.6424	0.3796
No log	2.5231	164	0.3800	0.6418	0.3800
No log	2.5538	166	0.3826	0.6463	0.3827
No log	2.5846	168	0.3477	0.6192	0.3479
No log	2.6154	170	0.3348	0.5882	0.3350
No log	2.6462	172	0.3317	0.5717	0.3318
No log	2.6769	174	0.3416	0.5885	0.3416
No log	2.7077	176	0.3816	0.5900	0.3815
No log	2.7385	178	0.4602	0.6362	0.4601
No log	2.7692	180	0.4794	0.6460	0.4793
No log	2.8	182	0.4356	0.6327	0.4354
No log	2.8308	184	0.3822	0.6207	0.3822
No log	2.8615	186	0.3481	0.6257	0.3482
No log	2.8923	188	0.3499	0.6358	0.3500
No log	2.9231	190	0.3737	0.6458	0.3739
No log	2.9538	192	0.3877	0.6515	0.3879
No log	2.9846	194	0.4120	0.6824	0.4121
No log	3.0154	196	0.4185	0.6528	0.4186
No log	3.0462	198	0.4191	0.6368	0.4191
No log	3.0769	200	0.3750	0.6447	0.3751
No log	3.1077	202	0.3520	0.6394	0.3521
No log	3.1385	204	0.3416	0.6069	0.3417
No log	3.1692	206	0.3451	0.6084	0.3451
No log	3.2	208	0.3505	0.6130	0.3505
No log	3.2308	210	0.3410	0.5970	0.3411
No log	3.2615	212	0.3320	0.5733	0.3321
No log	3.2923	214	0.3347	0.5757	0.3348
No log	3.3231	216	0.3565	0.6142	0.3565
No log	3.3538	218	0.3948	0.6357	0.3948
No log	3.3846	220	0.4004	0.6454	0.4004
No log	3.4154	222	0.3671	0.6277	0.3672
No log	3.4462	224	0.3385	0.5896	0.3387
No log	3.4769	226	0.3378	0.5551	0.3380
No log	3.5077	228	0.3388	0.5810	0.3391
No log	3.5385	230	0.3547	0.6271	0.3549
No log	3.5692	232	0.3822	0.6452	0.3823
No log	3.6	234	0.3794	0.6401	0.3795
No log	3.6308	236	0.3584	0.6388	0.3585
No log	3.6615	238	0.3366	0.6063	0.3368
No log	3.6923	240	0.3337	0.6033	0.3339
No log	3.7231	242	0.3443	0.6309	0.3445
No log	3.7538	244	0.3600	0.6476	0.3601
No log	3.7846	246	0.3946	0.6493	0.3946
No log	3.8154	248	0.4118	0.6646	0.4118
No log	3.8462	250	0.3983	0.6572	0.3984
No log	3.8769	252	0.3868	0.6631	0.3869
No log	3.9077	254	0.3689	0.6476	0.3691
No log	3.9385	256	0.3520	0.6317	0.3522
No log	3.9692	258	0.3393	0.6187	0.3395
No log	4.0	260	0.3356	0.6003	0.3358
No log	4.0308	262	0.3386	0.6112	0.3387
No log	4.0615	264	0.3491	0.6257	0.3493
No log	4.0923	266	0.3547	0.6302	0.3549
No log	4.1231	268	0.3524	0.6297	0.3526
No log	4.1538	270	0.3537	0.6318	0.3539
No log	4.1846	272	0.3603	0.6392	0.3605
No log	4.2154	274	0.3647	0.6437	0.3648
No log	4.2462	276	0.3737	0.6531	0.3739
No log	4.2769	278	0.3842	0.6557	0.3843
No log	4.3077	280	0.3792	0.6516	0.3793
No log	4.3385	282	0.3619	0.6430	0.3620
No log	4.3692	284	0.3506	0.6277	0.3507
No log	4.4	286	0.3455	0.6196	0.3456
No log	4.4308	288	0.3404	0.6090	0.3406
No log	4.4615	290	0.3431	0.6208	0.3432
No log	4.4923	292	0.3528	0.6328	0.3530
No log	4.5231	294	0.3631	0.6357	0.3632
No log	4.5538	296	0.3687	0.6398	0.3688
No log	4.5846	298	0.3757	0.6438	0.3758
No log	4.6154	300	0.3844	0.6506	0.3845
No log	4.6462	302	0.3922	0.6574	0.3923
No log	4.6769	304	0.3932	0.6448	0.3933
No log	4.7077	306	0.3882	0.6454	0.3883
No log	4.7385	308	0.3828	0.6449	0.3829
No log	4.7692	310	0.3753	0.6439	0.3754
No log	4.8	312	0.3721	0.6439	0.3722
No log	4.8308	314	0.3707	0.6418	0.3708
No log	4.8615	316	0.3706	0.6418	0.3707
No log	4.8923	318	0.3696	0.6439	0.3697
No log	4.9231	320	0.3689	0.6439	0.3691
No log	4.9538	322	0.3679	0.6476	0.3680
No log	4.9846	324	0.3672	0.6476	0.3673

Framework versions

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