bert_baseline_prompt_adherence_task3_fold2

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: 0.3865
• Qwk: 0.6205
• Mse: 0.3868

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	0.9209	0.0721	0.9218
No log	0.0615	4	0.7058	0.0	0.7068
No log	0.0923	6	0.6332	0.0	0.6344
No log	0.1231	8	0.6461	0.0	0.6473
No log	0.1538	10	0.6356	0.0	0.6368
No log	0.1846	12	0.5833	0.0	0.5844
No log	0.2154	14	0.5584	0.0	0.5595
No log	0.2462	16	0.5636	0.0	0.5645
No log	0.2769	18	0.5578	0.0	0.5588
No log	0.3077	20	0.5330	0.0090	0.5340
No log	0.3385	22	0.4862	0.0297	0.4871
No log	0.3692	24	0.4627	0.1885	0.4635
No log	0.4	26	0.4589	0.4569	0.4597
No log	0.4308	28	0.4252	0.5118	0.4259
No log	0.4615	30	0.4208	0.5424	0.4214
No log	0.4923	32	0.4120	0.4962	0.4126
No log	0.5231	34	0.4650	0.3983	0.4657
No log	0.5538	36	0.6042	0.2581	0.6049
No log	0.5846	38	0.5797	0.2927	0.5804
No log	0.6154	40	0.4671	0.3941	0.4677
No log	0.6462	42	0.4642	0.4488	0.4647
No log	0.6769	44	0.4843	0.5479	0.4848
No log	0.7077	46	0.4777	0.6022	0.4781
No log	0.7385	48	0.4644	0.5947	0.4648
No log	0.7692	50	0.3865	0.5476	0.3870
No log	0.8	52	0.3739	0.5548	0.3743
No log	0.8308	54	0.4036	0.6030	0.4040
No log	0.8615	56	0.4922	0.6210	0.4926
No log	0.8923	58	0.5134	0.6215	0.5138
No log	0.9231	60	0.4476	0.6219	0.4479
No log	0.9538	62	0.4020	0.6279	0.4023
No log	0.9846	64	0.3963	0.6294	0.3966
No log	1.0154	66	0.3739	0.6026	0.3742
No log	1.0462	68	0.3901	0.6210	0.3903
No log	1.0769	70	0.3873	0.6134	0.3875
No log	1.1077	72	0.4214	0.6277	0.4215
No log	1.1385	74	0.4557	0.6312	0.4558
No log	1.1692	76	0.4140	0.6287	0.4141
No log	1.2	78	0.3723	0.5992	0.3725
No log	1.2308	80	0.3738	0.5884	0.3740
No log	1.2615	82	0.3897	0.6109	0.3898
No log	1.2923	84	0.4131	0.6202	0.4132
No log	1.3231	86	0.4389	0.6198	0.4391
No log	1.3538	88	0.4140	0.6212	0.4142
No log	1.3846	90	0.3720	0.6116	0.3723
No log	1.4154	92	0.3373	0.5762	0.3376
No log	1.4462	94	0.3269	0.5504	0.3273
No log	1.4769	96	0.3340	0.6284	0.3344
No log	1.5077	98	0.3765	0.6424	0.3769
No log	1.5385	100	0.4626	0.6258	0.4631
No log	1.5692	102	0.4455	0.6303	0.4461
No log	1.6	104	0.3552	0.6401	0.3558
No log	1.6308	106	0.3091	0.5522	0.3097
No log	1.6615	108	0.3105	0.5415	0.3111
No log	1.6923	110	0.3240	0.6195	0.3247
No log	1.7231	112	0.3762	0.6409	0.3770
No log	1.7538	114	0.4521	0.6156	0.4529
No log	1.7846	116	0.4163	0.6405	0.4170
No log	1.8154	118	0.3626	0.6411	0.3633
No log	1.8462	120	0.3529	0.6359	0.3536
No log	1.8769	122	0.3726	0.6447	0.3734
No log	1.9077	124	0.3840	0.6250	0.3847
No log	1.9385	126	0.3554	0.6208	0.3562
No log	1.9692	128	0.3276	0.5576	0.3285
No log	2.0	130	0.3269	0.5270	0.3278
No log	2.0308	132	0.3320	0.5808	0.3328
No log	2.0615	134	0.3699	0.6345	0.3706
No log	2.0923	136	0.3914	0.6391	0.3919
No log	2.1231	138	0.3926	0.6470	0.3932
No log	2.1538	140	0.3570	0.6304	0.3574
No log	2.1846	142	0.3445	0.5527	0.3449
No log	2.2154	144	0.3578	0.5157	0.3582
No log	2.2462	146	0.3503	0.5666	0.3506
No log	2.2769	148	0.4131	0.6374	0.4133
No log	2.3077	150	0.5248	0.6554	0.5249
No log	2.3385	152	0.5552	0.6448	0.5553
No log	2.3692	154	0.4859	0.6509	0.4861
No log	2.4	156	0.3954	0.6432	0.3956
No log	2.4308	158	0.3557	0.6127	0.3560
No log	2.4615	160	0.3583	0.6304	0.3585
No log	2.4923	162	0.3558	0.6184	0.3560
No log	2.5231	164	0.3630	0.6348	0.3632
No log	2.5538	166	0.3875	0.6517	0.3877
No log	2.5846	168	0.3741	0.6488	0.3743
No log	2.6154	170	0.3590	0.6356	0.3593
No log	2.6462	172	0.3372	0.5962	0.3375
No log	2.6769	174	0.3386	0.6013	0.3388
No log	2.7077	176	0.3585	0.6326	0.3587
No log	2.7385	178	0.3830	0.6366	0.3832
No log	2.7692	180	0.3715	0.6394	0.3717
No log	2.8	182	0.3562	0.6129	0.3564
No log	2.8308	184	0.3686	0.6059	0.3687
No log	2.8615	186	0.4020	0.6375	0.4021
No log	2.8923	188	0.4058	0.6248	0.4058
No log	2.9231	190	0.3896	0.6170	0.3897
No log	2.9538	192	0.3750	0.6119	0.3752
No log	2.9846	194	0.3567	0.5864	0.3570
No log	3.0154	196	0.3520	0.5827	0.3523
No log	3.0462	198	0.3761	0.6138	0.3763
No log	3.0769	200	0.4113	0.6249	0.4115
No log	3.1077	202	0.4565	0.6324	0.4567
No log	3.1385	204	0.4397	0.6308	0.4398
No log	3.1692	206	0.4039	0.6298	0.4041
No log	3.2	208	0.3731	0.6179	0.3733
No log	3.2308	210	0.3707	0.6174	0.3709
No log	3.2615	212	0.3995	0.6206	0.3996
No log	3.2923	214	0.4179	0.6259	0.4181
No log	3.3231	216	0.4157	0.6315	0.4159
No log	3.3538	218	0.4204	0.6264	0.4205
No log	3.3846	220	0.3934	0.6247	0.3936
No log	3.4154	222	0.3840	0.6296	0.3842
No log	3.4462	224	0.3688	0.6245	0.3690
No log	3.4769	226	0.3566	0.6139	0.3568
No log	3.5077	228	0.3496	0.6088	0.3499
No log	3.5385	230	0.3631	0.6246	0.3633
No log	3.5692	232	0.3979	0.6243	0.3982
No log	3.6	234	0.4009	0.6244	0.4011
No log	3.6308	236	0.3887	0.6232	0.3889
No log	3.6615	238	0.3761	0.6199	0.3764
No log	3.6923	240	0.3744	0.6173	0.3747
No log	3.7231	242	0.3733	0.6157	0.3736
No log	3.7538	244	0.3747	0.6199	0.3749
No log	3.7846	246	0.3837	0.6211	0.3839
No log	3.8154	248	0.3847	0.6274	0.3850
No log	3.8462	250	0.3831	0.6205	0.3834
No log	3.8769	252	0.3816	0.6199	0.3819
No log	3.9077	254	0.3958	0.6242	0.3961
No log	3.9385	256	0.3982	0.6242	0.3985
No log	3.9692	258	0.4001	0.6200	0.4004
No log	4.0	260	0.4020	0.6152	0.4022
No log	4.0308	262	0.4158	0.6227	0.4160
No log	4.0615	264	0.4118	0.6227	0.4121
No log	4.0923	266	0.4022	0.6173	0.4025
No log	4.1231	268	0.4025	0.6184	0.4028
No log	4.1538	270	0.4206	0.6190	0.4208
No log	4.1846	272	0.4420	0.6309	0.4422
No log	4.2154	274	0.4818	0.6453	0.4820
No log	4.2462	276	0.4957	0.6506	0.4959
No log	4.2769	278	0.4752	0.6434	0.4754
No log	4.3077	280	0.4413	0.6298	0.4416
No log	4.3385	282	0.4079	0.6117	0.4082
No log	4.3692	284	0.3895	0.6052	0.3898
No log	4.4	286	0.3731	0.6013	0.3734
No log	4.4308	288	0.3693	0.5932	0.3697
No log	4.4615	290	0.3701	0.5952	0.3705
No log	4.4923	292	0.3759	0.6067	0.3763
No log	4.5231	294	0.3872	0.6169	0.3875
No log	4.5538	296	0.4009	0.6131	0.4012
No log	4.5846	298	0.4136	0.6120	0.4139
No log	4.6154	300	0.4345	0.6288	0.4348
No log	4.6462	302	0.4442	0.6402	0.4445
No log	4.6769	304	0.4404	0.6380	0.4407
No log	4.7077	306	0.4287	0.6233	0.4291
No log	4.7385	308	0.4234	0.6184	0.4237
No log	4.7692	310	0.4168	0.6205	0.4171
No log	4.8	312	0.4091	0.6173	0.4095
No log	4.8308	314	0.4006	0.6179	0.4009
No log	4.8615	316	0.3935	0.6189	0.3938
No log	4.8923	318	0.3890	0.6189	0.3894
No log	4.9231	320	0.3871	0.6142	0.3875
No log	4.9538	322	0.3868	0.6142	0.3872
No log	4.9846	324	0.3865	0.6205	0.3868

Framework versions

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