bert_baseline_prompt_adherence_task6_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: 0.3483
• Qwk: 0.7709
• Mse: 0.3483

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	0.0294	2	1.7206	0.0	1.7206
No log	0.0588	4	1.5033	-0.0568	1.5033
No log	0.0882	6	1.3304	0.0061	1.3304
No log	0.1176	8	1.1174	0.0	1.1174
No log	0.1471	10	1.0152	0.0	1.0152
No log	0.1765	12	0.9599	0.0	0.9599
No log	0.2059	14	0.9133	0.0154	0.9133
No log	0.2353	16	0.8781	0.2072	0.8781
No log	0.2647	18	0.8180	0.3561	0.8180
No log	0.2941	20	0.7972	0.4055	0.7972
No log	0.3235	22	0.7928	0.4281	0.7928
No log	0.3529	24	0.6695	0.5057	0.6695
No log	0.3824	26	0.7443	0.5556	0.7443
No log	0.4118	28	0.5712	0.5740	0.5712
No log	0.4412	30	0.7065	0.3924	0.7065
No log	0.4706	32	0.8144	0.3201	0.8144
No log	0.5	34	0.5210	0.5177	0.5210
No log	0.5294	36	0.6962	0.6167	0.6962
No log	0.5588	38	0.8816	0.5814	0.8816
No log	0.5882	40	0.7034	0.6286	0.7034
No log	0.6176	42	0.4509	0.6130	0.4509
No log	0.6471	44	0.4571	0.5712	0.4571
No log	0.6765	46	0.4399	0.5999	0.4399
No log	0.7059	48	0.4605	0.6458	0.4605
No log	0.7353	50	0.5082	0.6569	0.5082
No log	0.7647	52	0.4550	0.6573	0.4550
No log	0.7941	54	0.4115	0.6558	0.4115
No log	0.8235	56	0.3883	0.6556	0.3883
No log	0.8529	58	0.4411	0.7388	0.4411
No log	0.8824	60	0.4843	0.7395	0.4843
No log	0.9118	62	0.5527	0.7123	0.5527
No log	0.9412	64	0.4894	0.7109	0.4894
No log	0.9706	66	0.3826	0.6719	0.3826
No log	1.0	68	0.4572	0.5523	0.4572
No log	1.0294	70	0.4169	0.5909	0.4169
No log	1.0588	72	0.3754	0.6785	0.3754
No log	1.0882	74	0.4122	0.7075	0.4122
No log	1.1176	76	0.3864	0.6969	0.3864
No log	1.1471	78	0.3631	0.6895	0.3631
No log	1.1765	80	0.3552	0.6448	0.3552
No log	1.2059	82	0.3496	0.6616	0.3496
No log	1.2353	84	0.3693	0.6815	0.3693
No log	1.2647	86	0.3708	0.7110	0.3708
No log	1.2941	88	0.3558	0.7021	0.3558
No log	1.3235	90	0.3680	0.6520	0.3680
No log	1.3529	92	0.3665	0.6323	0.3665
No log	1.3824	94	0.3459	0.6917	0.3459
No log	1.4118	96	0.3493	0.7065	0.3493
No log	1.4412	98	0.3874	0.7281	0.3874
No log	1.4706	100	0.3547	0.6976	0.3547
No log	1.5	102	0.3454	0.6482	0.3454
No log	1.5294	104	0.3442	0.6641	0.3442
No log	1.5588	106	0.3443	0.6889	0.3443
No log	1.5882	108	0.3447	0.6931	0.3447
No log	1.6176	110	0.3375	0.6753	0.3375
No log	1.6471	112	0.3559	0.7070	0.3559
No log	1.6765	114	0.4743	0.7688	0.4743
No log	1.7059	116	0.5174	0.7953	0.5174
No log	1.7353	118	0.3931	0.7381	0.3931
No log	1.7647	120	0.3495	0.6729	0.3495
No log	1.7941	122	0.4099	0.5552	0.4099
No log	1.8235	124	0.3735	0.5992	0.3735
No log	1.8529	126	0.3560	0.7159	0.3560
No log	1.8824	128	0.3993	0.7509	0.3993
No log	1.9118	130	0.3967	0.7563	0.3967
No log	1.9412	132	0.3636	0.7410	0.3636
No log	1.9706	134	0.3380	0.7102	0.3380
No log	2.0	136	0.3442	0.7268	0.3442
No log	2.0294	138	0.3866	0.7569	0.3866
No log	2.0588	140	0.3678	0.7407	0.3678
No log	2.0882	142	0.3345	0.7249	0.3345
No log	2.1176	144	0.3474	0.7483	0.3474
No log	2.1471	146	0.3337	0.7362	0.3337
No log	2.1765	148	0.3404	0.7402	0.3404
No log	2.2059	150	0.3990	0.7838	0.3990
No log	2.2353	152	0.4770	0.7981	0.4770
No log	2.2647	154	0.4237	0.7933	0.4237
No log	2.2941	156	0.3341	0.7285	0.3341
No log	2.3235	158	0.3347	0.6718	0.3347
No log	2.3529	160	0.3244	0.6752	0.3244
No log	2.3824	162	0.3271	0.7362	0.3271
No log	2.4118	164	0.3959	0.7689	0.3959
No log	2.4412	166	0.3846	0.7661	0.3846
No log	2.4706	168	0.3289	0.7316	0.3289
No log	2.5	170	0.3332	0.6498	0.3332
No log	2.5294	172	0.3293	0.6551	0.3293
No log	2.5588	174	0.3295	0.7295	0.3295
No log	2.5882	176	0.3439	0.7415	0.3439
No log	2.6176	178	0.3350	0.7365	0.3350
No log	2.6471	180	0.3433	0.7320	0.3433
No log	2.6765	182	0.3310	0.7208	0.3310
No log	2.7059	184	0.3325	0.7218	0.3325
No log	2.7353	186	0.3550	0.7433	0.3550
No log	2.7647	188	0.3514	0.7437	0.3514
No log	2.7941	190	0.3655	0.7599	0.3655
No log	2.8235	192	0.3835	0.7782	0.3835
No log	2.8529	194	0.3665	0.7718	0.3665
No log	2.8824	196	0.3414	0.7601	0.3414
No log	2.9118	198	0.3329	0.7488	0.3329
No log	2.9412	200	0.3166	0.7122	0.3166
No log	2.9706	202	0.3198	0.7204	0.3198
No log	3.0	204	0.3364	0.7563	0.3364
No log	3.0294	206	0.3291	0.7514	0.3291
No log	3.0588	208	0.3120	0.7106	0.3120
No log	3.0882	210	0.3121	0.7081	0.3121
No log	3.1176	212	0.3164	0.7263	0.3164
No log	3.1471	214	0.3561	0.7622	0.3561
No log	3.1765	216	0.3956	0.7647	0.3956
No log	3.2059	218	0.3742	0.7583	0.3742
No log	3.2353	220	0.3269	0.7344	0.3269
No log	3.2647	222	0.3215	0.7275	0.3215
No log	3.2941	224	0.3439	0.7407	0.3439
No log	3.3235	226	0.3759	0.7547	0.3759
No log	3.3529	228	0.3910	0.7616	0.3910
No log	3.3824	230	0.3604	0.7542	0.3604
No log	3.4118	232	0.3171	0.7255	0.3171
No log	3.4412	234	0.3171	0.6765	0.3171
No log	3.4706	236	0.3155	0.6830	0.3155
No log	3.5	238	0.3157	0.7278	0.3157
No log	3.5294	240	0.3447	0.7645	0.3447
No log	3.5588	242	0.4145	0.7948	0.4145
No log	3.5882	244	0.4356	0.8078	0.4356
No log	3.6176	246	0.3964	0.7948	0.3964
No log	3.6471	248	0.3397	0.7680	0.3397
No log	3.6765	250	0.3298	0.75	0.3298
No log	3.7059	252	0.3189	0.7252	0.3189
No log	3.7353	254	0.3202	0.7273	0.3202
No log	3.7647	256	0.3258	0.7400	0.3258
No log	3.7941	258	0.3383	0.7683	0.3383
No log	3.8235	260	0.3312	0.7575	0.3312
No log	3.8529	262	0.3194	0.7393	0.3194
No log	3.8824	264	0.3173	0.7337	0.3173
No log	3.9118	266	0.3204	0.7467	0.3204
No log	3.9412	268	0.3278	0.7535	0.3278
No log	3.9706	270	0.3446	0.7742	0.3446
No log	4.0	272	0.3754	0.7818	0.3754
No log	4.0294	274	0.3902	0.7901	0.3902
No log	4.0588	276	0.3866	0.7928	0.3866
No log	4.0882	278	0.3708	0.7719	0.3708
No log	4.1176	280	0.3520	0.7694	0.3520
No log	4.1471	282	0.3317	0.7626	0.3317
No log	4.1765	284	0.3284	0.7561	0.3284
No log	4.2059	286	0.3229	0.7446	0.3229
No log	4.2353	288	0.3243	0.7478	0.3243
No log	4.2647	290	0.3228	0.7406	0.3228
No log	4.2941	292	0.3204	0.7364	0.3204
No log	4.3235	294	0.3248	0.7482	0.3248
No log	4.3529	296	0.3319	0.7618	0.3319
No log	4.3824	298	0.3387	0.7628	0.3387
No log	4.4118	300	0.3532	0.7688	0.3532
No log	4.4412	302	0.3607	0.7700	0.3607
No log	4.4706	304	0.3558	0.7660	0.3558
No log	4.5	306	0.3459	0.7664	0.3459
No log	4.5294	308	0.3381	0.7619	0.3381
No log	4.5588	310	0.3317	0.7557	0.3317
No log	4.5882	312	0.3299	0.7547	0.3299
No log	4.6176	314	0.3353	0.7637	0.3353
No log	4.6471	316	0.3370	0.7644	0.3370
No log	4.6765	318	0.3350	0.7653	0.3350
No log	4.7059	320	0.3362	0.7638	0.3362
No log	4.7353	322	0.3409	0.7648	0.3409
No log	4.7647	324	0.3437	0.7648	0.3437
No log	4.7941	326	0.3476	0.7697	0.3476
No log	4.8235	328	0.3486	0.7690	0.3486
No log	4.8529	330	0.3493	0.7709	0.3493
No log	4.8824	332	0.3489	0.7709	0.3489
No log	4.9118	334	0.3487	0.7709	0.3487
No log	4.9412	336	0.3479	0.7690	0.3479
No log	4.9706	338	0.3480	0.7690	0.3480
No log	5.0	340	0.3483	0.7709	0.3483

Framework versions

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