bert_baseline_prompt_adherence_task5_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: 0.5066
• Qwk: 0.6974
• Mse: 0.5063

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	2.4485	0.0	2.4480
No log	0.0588	4	2.0852	0.0360	2.0847
No log	0.0882	6	1.7567	0.0	1.7562
No log	0.1176	8	1.3263	0.0	1.3255
No log	0.1471	10	1.0635	0.0442	1.0627
No log	0.1765	12	0.9516	0.3585	0.9510
No log	0.2059	14	0.9261	0.3426	0.9256
No log	0.2353	16	0.8773	0.3943	0.8766
No log	0.2647	18	0.9391	0.3022	0.9380
No log	0.2941	20	0.8954	0.2692	0.8943
No log	0.3235	22	0.7439	0.4042	0.7436
No log	0.3529	24	0.8582	0.4086	0.8585
No log	0.3824	26	0.7256	0.4861	0.7255
No log	0.4118	28	0.7472	0.3281	0.7462
No log	0.4412	30	0.8611	0.2114	0.8598
No log	0.4706	32	0.7545	0.3131	0.7534
No log	0.5	34	0.6515	0.5445	0.6515
No log	0.5294	36	0.9425	0.6176	0.9434
No log	0.5588	38	0.9623	0.5922	0.9632
No log	0.5882	40	0.7612	0.6289	0.7619
No log	0.6176	42	0.6043	0.4936	0.6041
No log	0.6471	44	0.7140	0.3329	0.7132
No log	0.6765	46	0.7308	0.3042	0.7299
No log	0.7059	48	0.6274	0.3623	0.6268
No log	0.7353	50	0.5875	0.4255	0.5874
No log	0.7647	52	0.5894	0.4308	0.5894
No log	0.7941	54	0.5709	0.4855	0.5708
No log	0.8235	56	0.5683	0.5325	0.5682
No log	0.8529	58	0.5675	0.5357	0.5675
No log	0.8824	60	0.5786	0.5893	0.5787
No log	0.9118	62	0.6576	0.6631	0.6581
No log	0.9412	64	0.7169	0.6881	0.7177
No log	0.9706	66	0.6195	0.6844	0.6196
No log	1.0	68	0.6078	0.5790	0.6072
No log	1.0294	70	0.5957	0.5911	0.5952
No log	1.0588	72	0.6013	0.6785	0.6014
No log	1.0882	74	0.6450	0.6741	0.6453
No log	1.1176	76	0.6194	0.5884	0.6197
No log	1.1471	78	0.5606	0.5246	0.5606
No log	1.1765	80	0.5391	0.5332	0.5388
No log	1.2059	82	0.5362	0.5989	0.5359
No log	1.2353	84	0.5378	0.6384	0.5377
No log	1.2647	86	0.5255	0.6231	0.5252
No log	1.2941	88	0.5244	0.6387	0.5242
No log	1.3235	90	0.5873	0.7276	0.5875
No log	1.3529	92	0.6176	0.7331	0.6180
No log	1.3824	94	0.5611	0.7005	0.5612
No log	1.4118	96	0.5282	0.6661	0.5281
No log	1.4412	98	0.5242	0.5851	0.5237
No log	1.4706	100	0.5186	0.6157	0.5181
No log	1.5	102	0.5152	0.6041	0.5147
No log	1.5294	104	0.5122	0.6317	0.5119
No log	1.5588	106	0.5594	0.7059	0.5596
No log	1.5882	108	0.5694	0.7231	0.5696
No log	1.6176	110	0.5407	0.7012	0.5408
No log	1.6471	112	0.5077	0.6642	0.5075
No log	1.6765	114	0.5118	0.6684	0.5116
No log	1.7059	116	0.5244	0.6776	0.5242
No log	1.7353	118	0.5586	0.6944	0.5587
No log	1.7647	120	0.5758	0.7057	0.5759
No log	1.7941	122	0.6111	0.7218	0.6114
No log	1.8235	124	0.5891	0.7095	0.5893
No log	1.8529	126	0.5425	0.6328	0.5420
No log	1.8824	128	0.5435	0.5949	0.5428
No log	1.9118	130	0.5082	0.6226	0.5079
No log	1.9412	132	0.5134	0.6659	0.5135
No log	1.9706	134	0.5564	0.6944	0.5567
No log	2.0	136	0.5343	0.6532	0.5345
No log	2.0294	138	0.5370	0.6560	0.5372
No log	2.0588	140	0.5419	0.6827	0.5421
No log	2.0882	142	0.5108	0.6510	0.5107
No log	2.1176	144	0.5048	0.6191	0.5042
No log	2.1471	146	0.5395	0.5780	0.5387
No log	2.1765	148	0.5853	0.5666	0.5843
No log	2.2059	150	0.5339	0.6041	0.5332
No log	2.2353	152	0.5460	0.7059	0.5459
No log	2.2647	154	0.5901	0.7249	0.5903
No log	2.2941	156	0.5624	0.7169	0.5625
No log	2.3235	158	0.5171	0.6760	0.5167
No log	2.3529	160	0.5137	0.6556	0.5131
No log	2.3824	162	0.5230	0.6913	0.5228
No log	2.4118	164	0.5624	0.7203	0.5625
No log	2.4412	166	0.5309	0.6919	0.5308
No log	2.4706	168	0.5341	0.6092	0.5333
No log	2.5	170	0.5850	0.5333	0.5839
No log	2.5294	172	0.5378	0.5700	0.5369
No log	2.5588	174	0.4988	0.6506	0.4986
No log	2.5882	176	0.5462	0.7111	0.5466
No log	2.6176	178	0.6278	0.7387	0.6286
No log	2.6471	180	0.6471	0.7457	0.6480
No log	2.6765	182	0.5723	0.7369	0.5728
No log	2.7059	184	0.4996	0.6705	0.4996
No log	2.7353	186	0.4884	0.6063	0.4878
No log	2.7647	188	0.5184	0.5660	0.5176
No log	2.7941	190	0.5029	0.5735	0.5022
No log	2.8235	192	0.4804	0.6289	0.4801
No log	2.8529	194	0.4910	0.6638	0.4909
No log	2.8824	196	0.4884	0.6553	0.4882
No log	2.9118	198	0.4825	0.6479	0.4820
No log	2.9412	200	0.4897	0.6332	0.4890
No log	2.9706	202	0.4887	0.6395	0.4882
No log	3.0	204	0.4956	0.6753	0.4953
No log	3.0294	206	0.5352	0.7060	0.5352
No log	3.0588	208	0.5285	0.6963	0.5284
No log	3.0882	210	0.5038	0.6692	0.5034
No log	3.1176	212	0.4896	0.6577	0.4891
No log	3.1471	214	0.4824	0.6421	0.4819
No log	3.1765	216	0.4753	0.6339	0.4748
No log	3.2059	218	0.4711	0.6395	0.4707
No log	3.2353	220	0.4710	0.6508	0.4707
No log	3.2647	222	0.4885	0.6844	0.4885
No log	3.2941	224	0.5330	0.7203	0.5332
No log	3.3235	226	0.5352	0.7167	0.5355
No log	3.3529	228	0.5054	0.7001	0.5054
No log	3.3824	230	0.4922	0.6832	0.4921
No log	3.4118	232	0.4958	0.6822	0.4957
No log	3.4412	234	0.4967	0.6925	0.4966
No log	3.4706	236	0.4895	0.6686	0.4891
No log	3.5	238	0.5030	0.6935	0.5028
No log	3.5294	240	0.5286	0.7051	0.5286
No log	3.5588	242	0.5580	0.7234	0.5581
No log	3.5882	244	0.5419	0.7100	0.5418
No log	3.6176	246	0.5053	0.6821	0.5049
No log	3.6471	248	0.4991	0.6656	0.4986
No log	3.6765	250	0.4973	0.6528	0.4967
No log	3.7059	252	0.5008	0.6663	0.5004
No log	3.7353	254	0.5220	0.7029	0.5218
No log	3.7647	256	0.5495	0.7174	0.5495
No log	3.7941	258	0.5589	0.7306	0.5589
No log	3.8235	260	0.5377	0.7045	0.5375
No log	3.8529	262	0.5102	0.6874	0.5098
No log	3.8824	264	0.5099	0.6873	0.5094
No log	3.9118	266	0.5259	0.6949	0.5255
No log	3.9412	268	0.5359	0.6964	0.5356
No log	3.9706	270	0.5399	0.6971	0.5396
No log	4.0	272	0.5266	0.6904	0.5262
No log	4.0294	274	0.5060	0.6846	0.5055
No log	4.0588	276	0.5013	0.6800	0.5008
No log	4.0882	278	0.5139	0.6966	0.5136
No log	4.1176	280	0.5437	0.7060	0.5435
No log	4.1471	282	0.5548	0.7156	0.5547
No log	4.1765	284	0.5472	0.7077	0.5471
No log	4.2059	286	0.5206	0.6987	0.5203
No log	4.2353	288	0.5135	0.6877	0.5131
No log	4.2647	290	0.5099	0.6846	0.5095
No log	4.2941	292	0.5047	0.6839	0.5043
No log	4.3235	294	0.4963	0.6646	0.4957
No log	4.3529	296	0.4950	0.6537	0.4944
No log	4.3824	298	0.4949	0.6661	0.4943
No log	4.4118	300	0.4965	0.6708	0.4960
No log	4.4412	302	0.4936	0.6622	0.4930
No log	4.4706	304	0.4931	0.6599	0.4925
No log	4.5	306	0.4944	0.6646	0.4939
No log	4.5294	308	0.4933	0.6631	0.4927
No log	4.5588	310	0.4952	0.6723	0.4947
No log	4.5882	312	0.4969	0.6761	0.4964
No log	4.6176	314	0.5000	0.6847	0.4996
No log	4.6471	316	0.5008	0.6864	0.5005
No log	4.6765	318	0.5019	0.6936	0.5015
No log	4.7059	320	0.5012	0.6936	0.5009
No log	4.7353	322	0.5028	0.6959	0.5024
No log	4.7647	324	0.4999	0.6896	0.4995
No log	4.7941	326	0.5008	0.6904	0.5004
No log	4.8235	328	0.5035	0.6959	0.5031
No log	4.8529	330	0.5058	0.6974	0.5055
No log	4.8824	332	0.5079	0.6990	0.5076
No log	4.9118	334	0.5079	0.6990	0.5076
No log	4.9412	336	0.5064	0.6974	0.5061
No log	4.9706	338	0.5064	0.6974	0.5061
No log	5.0	340	0.5066	0.6974	0.5063

Framework versions

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