bert_baseline_prompt_adherence_task5_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: 0.5456
• Qwk: 0.6760
• Mse: 0.5459

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	2.4749	0.0	2.4721
No log	0.0588	4	2.1459	0.0199	2.1435
No log	0.0882	6	1.8011	0.0049	1.7992
No log	0.1176	8	1.3901	0.0049	1.3889
No log	0.1471	10	1.0957	0.0590	1.0951
No log	0.1765	12	0.9696	0.3591	0.9694
No log	0.2059	14	0.9027	0.3624	0.9026
No log	0.2353	16	0.8909	0.3377	0.8906
No log	0.2647	18	0.8084	0.3554	0.8083
No log	0.2941	20	1.0088	0.3345	1.0094
No log	0.3235	22	1.2775	0.2254	1.2784
No log	0.3529	24	1.0790	0.3354	1.0797
No log	0.3824	26	0.7771	0.4393	0.7774
No log	0.4118	28	0.7450	0.3344	0.7446
No log	0.4412	30	0.8259	0.2802	0.8252
No log	0.4706	32	0.8112	0.2766	0.8105
No log	0.5	34	0.6731	0.3686	0.6728
No log	0.5294	36	0.6481	0.4971	0.6484
No log	0.5588	38	0.7080	0.4886	0.7087
No log	0.5882	40	0.7139	0.4766	0.7147
No log	0.6176	42	0.6164	0.5583	0.6169
No log	0.6471	44	0.5935	0.4936	0.5936
No log	0.6765	46	0.6374	0.4203	0.6372
No log	0.7059	48	0.5928	0.4631	0.5928
No log	0.7353	50	0.5733	0.4847	0.5736
No log	0.7647	52	0.5770	0.4753	0.5772
No log	0.7941	54	0.5746	0.5003	0.5748
No log	0.8235	56	0.5707	0.6052	0.5713
No log	0.8529	58	0.5921	0.6533	0.5928
No log	0.8824	60	0.5380	0.6282	0.5385
No log	0.9118	62	0.6005	0.4814	0.6003
No log	0.9412	64	0.6857	0.4391	0.6853
No log	0.9706	66	0.5771	0.5155	0.5770
No log	1.0	68	0.5367	0.6103	0.5373
No log	1.0294	70	0.5839	0.5148	0.5845
No log	1.0588	72	0.6173	0.4947	0.6175
No log	1.0882	74	0.6022	0.4926	0.6023
No log	1.1176	76	0.5431	0.5187	0.5433
No log	1.1471	78	0.5229	0.6195	0.5232
No log	1.1765	80	0.5204	0.6371	0.5207
No log	1.2059	82	0.5319	0.5871	0.5321
No log	1.2353	84	0.5308	0.5959	0.5311
No log	1.2647	86	0.5366	0.6399	0.5370
No log	1.2941	88	0.5987	0.6801	0.5993
No log	1.3235	90	0.7410	0.6784	0.7418
No log	1.3529	92	0.6915	0.6820	0.6922
No log	1.3824	94	0.5604	0.6365	0.5609
No log	1.4118	96	0.5407	0.5640	0.5409
No log	1.4412	98	0.5591	0.5203	0.5591
No log	1.4706	100	0.5328	0.5700	0.5330
No log	1.5	102	0.5414	0.6612	0.5420
No log	1.5294	104	0.5840	0.7097	0.5846
No log	1.5588	106	0.5464	0.6740	0.5470
No log	1.5882	108	0.5200	0.6512	0.5205
No log	1.6176	110	0.5167	0.6333	0.5171
No log	1.6471	112	0.5197	0.5965	0.5199
No log	1.6765	114	0.5236	0.6187	0.5239
No log	1.7059	116	0.5351	0.5494	0.5352
No log	1.7353	118	0.5291	0.5751	0.5293
No log	1.7647	120	0.5265	0.6247	0.5268
No log	1.7941	122	0.5572	0.6563	0.5578
No log	1.8235	124	0.5681	0.6614	0.5687
No log	1.8529	126	0.5323	0.6616	0.5328
No log	1.8824	128	0.5293	0.6605	0.5297
No log	1.9118	130	0.5659	0.6773	0.5666
No log	1.9412	132	0.6228	0.6951	0.6236
No log	1.9706	134	0.5668	0.6851	0.5675
No log	2.0	136	0.5228	0.6501	0.5232
No log	2.0294	138	0.5200	0.6360	0.5203
No log	2.0588	140	0.5316	0.6764	0.5320
No log	2.0882	142	0.5665	0.6812	0.5670
No log	2.1176	144	0.5876	0.6845	0.5881
No log	2.1471	146	0.5551	0.6688	0.5555
No log	2.1765	148	0.5267	0.6154	0.5268
No log	2.2059	150	0.5465	0.5742	0.5464
No log	2.2353	152	0.5241	0.6233	0.5241
No log	2.2647	154	0.5212	0.6710	0.5214
No log	2.2941	156	0.6121	0.6954	0.6126
No log	2.3235	158	0.6867	0.6923	0.6873
No log	2.3529	160	0.6255	0.6669	0.6260
No log	2.3824	162	0.5479	0.6591	0.5481
No log	2.4118	164	0.5481	0.5408	0.5480
No log	2.4412	166	0.6179	0.4843	0.6175
No log	2.4706	168	0.6060	0.4950	0.6057
No log	2.5	170	0.5484	0.5759	0.5484
No log	2.5294	172	0.5627	0.6639	0.5632
No log	2.5588	174	0.6163	0.6884	0.6170
No log	2.5882	176	0.6004	0.6793	0.6011
No log	2.6176	178	0.5451	0.6627	0.5455
No log	2.6471	180	0.5320	0.6231	0.5322
No log	2.6765	182	0.5303	0.6075	0.5304
No log	2.7059	184	0.5405	0.6576	0.5409
No log	2.7353	186	0.5485	0.6715	0.5489
No log	2.7647	188	0.5315	0.6415	0.5318
No log	2.7941	190	0.5236	0.6323	0.5238
No log	2.8235	192	0.5207	0.6155	0.5208
No log	2.8529	194	0.5220	0.6118	0.5222
No log	2.8824	196	0.5247	0.6076	0.5248
No log	2.9118	198	0.5174	0.6199	0.5177
No log	2.9412	200	0.5366	0.6767	0.5371
No log	2.9706	202	0.5545	0.6879	0.5550
No log	3.0	204	0.5502	0.6864	0.5508
No log	3.0294	206	0.5384	0.6775	0.5388
No log	3.0588	208	0.5214	0.6586	0.5217
No log	3.0882	210	0.5173	0.6456	0.5176
No log	3.1176	212	0.5206	0.6606	0.5210
No log	3.1471	214	0.5234	0.6644	0.5238
No log	3.1765	216	0.5234	0.6521	0.5238
No log	3.2059	218	0.5330	0.6657	0.5334
No log	3.2353	220	0.5636	0.6858	0.5642
No log	3.2647	222	0.6135	0.6895	0.6142
No log	3.2941	224	0.6480	0.7003	0.6487
No log	3.3235	226	0.6066	0.6867	0.6072
No log	3.3529	228	0.5740	0.6742	0.5745
No log	3.3824	230	0.5316	0.6572	0.5319
No log	3.4118	232	0.5282	0.6290	0.5284
No log	3.4412	234	0.5292	0.6142	0.5293
No log	3.4706	236	0.5249	0.6491	0.5252
No log	3.5	238	0.5402	0.6719	0.5405
No log	3.5294	240	0.5964	0.6824	0.5969
No log	3.5588	242	0.6376	0.7032	0.6383
No log	3.5882	244	0.6059	0.6967	0.6065
No log	3.6176	246	0.5732	0.6821	0.5737
No log	3.6471	248	0.5338	0.6719	0.5341
No log	3.6765	250	0.5224	0.6437	0.5226
No log	3.7059	252	0.5230	0.6071	0.5230
No log	3.7353	254	0.5270	0.5873	0.5270
No log	3.7647	256	0.5235	0.5990	0.5235
No log	3.7941	258	0.5218	0.6347	0.5219
No log	3.8235	260	0.5424	0.6786	0.5427
No log	3.8529	262	0.5745	0.6784	0.5750
No log	3.8824	264	0.5763	0.6819	0.5768
No log	3.9118	266	0.5510	0.6782	0.5514
No log	3.9412	268	0.5291	0.6627	0.5294
No log	3.9706	270	0.5224	0.6463	0.5227
No log	4.0	272	0.5227	0.6448	0.5229
No log	4.0294	274	0.5224	0.6547	0.5227
No log	4.0588	276	0.5250	0.6551	0.5253
No log	4.0882	278	0.5293	0.6722	0.5297
No log	4.1176	280	0.5426	0.6832	0.5430
No log	4.1471	282	0.5520	0.6815	0.5524
No log	4.1765	284	0.5699	0.6836	0.5703
No log	4.2059	286	0.5663	0.6812	0.5668
No log	4.2353	288	0.5546	0.6773	0.5550
No log	4.2647	290	0.5379	0.6769	0.5382
No log	4.2941	292	0.5267	0.6674	0.5269
No log	4.3235	294	0.5276	0.6601	0.5279
No log	4.3529	296	0.5324	0.6729	0.5327
No log	4.3824	298	0.5344	0.6753	0.5347
No log	4.4118	300	0.5311	0.6627	0.5313
No log	4.4412	302	0.5312	0.6644	0.5315
No log	4.4706	304	0.5365	0.6753	0.5368
No log	4.5	306	0.5415	0.6727	0.5418
No log	4.5294	308	0.5430	0.6727	0.5433
No log	4.5588	310	0.5413	0.6768	0.5416
No log	4.5882	312	0.5364	0.6731	0.5367
No log	4.6176	314	0.5355	0.6683	0.5357
No log	4.6471	316	0.5381	0.6722	0.5384
No log	4.6765	318	0.5432	0.6727	0.5435
No log	4.7059	320	0.5478	0.6726	0.5481
No log	4.7353	322	0.5499	0.6742	0.5503
No log	4.7647	324	0.5515	0.6758	0.5518
No log	4.7941	326	0.5508	0.6758	0.5511
No log	4.8235	328	0.5492	0.6726	0.5495
No log	4.8529	330	0.5464	0.6710	0.5468
No log	4.8824	332	0.5456	0.6760	0.5459
No log	4.9118	334	0.5460	0.6719	0.5464
No log	4.9412	336	0.5454	0.6760	0.5457
No log	4.9706	338	0.5454	0.6760	0.5457
No log	5.0	340	0.5456	0.6760	0.5459

Framework versions

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