bert_baseline_prompt_adherence_task5_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: 0.4551
• Qwk: 0.6660
• Mse: 0.4557

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	2.5264	0.0	2.5267
No log	0.0588	4	2.0698	0.0038	2.0712
No log	0.0882	6	1.6692	0.0	1.6712
No log	0.1176	8	1.2106	0.0	1.2131
No log	0.1471	10	0.9954	0.0691	0.9982
No log	0.1765	12	0.8820	0.2541	0.8852
No log	0.2059	14	0.8417	0.2650	0.8448
No log	0.2353	16	0.8815	0.2322	0.8848
No log	0.2647	18	0.8194	0.2689	0.8221
No log	0.2941	20	0.7283	0.3098	0.7301
No log	0.3235	22	0.7901	0.2583	0.7914
No log	0.3529	24	0.6593	0.3801	0.6606
No log	0.3824	26	0.7245	0.5177	0.7257
No log	0.4118	28	0.6890	0.5405	0.6901
No log	0.4412	30	0.6153	0.5085	0.6163
No log	0.4706	32	0.5972	0.4415	0.5983
No log	0.5	34	0.6245	0.4454	0.6258
No log	0.5294	36	0.6180	0.4472	0.6194
No log	0.5588	38	0.6077	0.4471	0.6092
No log	0.5882	40	0.5946	0.4562	0.5961
No log	0.6176	42	0.5627	0.4472	0.5640
No log	0.6471	44	0.5460	0.5244	0.5469
No log	0.6765	46	0.6361	0.4065	0.6367
No log	0.7059	48	0.5804	0.4599	0.5810
No log	0.7353	50	0.5607	0.5779	0.5615
No log	0.7647	52	0.6101	0.6093	0.6110
No log	0.7941	54	0.5810	0.5759	0.5820
No log	0.8235	56	0.5469	0.5709	0.5479
No log	0.8529	58	0.5256	0.4866	0.5264
No log	0.8824	60	0.5980	0.4283	0.5987
No log	0.9118	62	0.6064	0.4232	0.6072
No log	0.9412	64	0.5125	0.4985	0.5135
No log	0.9706	66	0.5452	0.5979	0.5463
No log	1.0	68	0.5796	0.6272	0.5808
No log	1.0294	70	0.5182	0.5908	0.5192
No log	1.0588	72	0.5140	0.5991	0.5149
No log	1.0882	74	0.5245	0.6207	0.5253
No log	1.1176	76	0.5014	0.6022	0.5021
No log	1.1471	78	0.5038	0.5943	0.5044
No log	1.1765	80	0.5171	0.6163	0.5177
No log	1.2059	82	0.6261	0.6760	0.6268
No log	1.2353	84	0.6490	0.6752	0.6499
No log	1.2647	86	0.5317	0.6323	0.5326
No log	1.2941	88	0.5102	0.5013	0.5110
No log	1.3235	90	0.5808	0.4495	0.5815
No log	1.3529	92	0.5643	0.4550	0.5651
No log	1.3824	94	0.5106	0.4999	0.5117
No log	1.4118	96	0.5167	0.5695	0.5179
No log	1.4412	98	0.5727	0.6042	0.5738
No log	1.4706	100	0.6069	0.6507	0.6080
No log	1.5	102	0.5390	0.6260	0.5400
No log	1.5294	104	0.4888	0.5835	0.4897
No log	1.5588	106	0.4900	0.5230	0.4907
No log	1.5882	108	0.4817	0.5590	0.4823
No log	1.6176	110	0.4832	0.5992	0.4838
No log	1.6471	112	0.4945	0.5880	0.4949
No log	1.6765	114	0.5089	0.5723	0.5092
No log	1.7059	116	0.5011	0.6063	0.5015
No log	1.7353	118	0.5326	0.6648	0.5331
No log	1.7647	120	0.5306	0.6618	0.5311
No log	1.7941	122	0.5076	0.6601	0.5082
No log	1.8235	124	0.4719	0.5863	0.4724
No log	1.8529	126	0.4719	0.5670	0.4724
No log	1.8824	128	0.4620	0.5819	0.4625
No log	1.9118	130	0.4811	0.6184	0.4818
No log	1.9412	132	0.4936	0.6386	0.4944
No log	1.9706	134	0.4668	0.5933	0.4676
No log	2.0	136	0.4560	0.5843	0.4566
No log	2.0294	138	0.4566	0.5641	0.4572
No log	2.0588	140	0.4535	0.5968	0.4542
No log	2.0882	142	0.4773	0.6510	0.4780
No log	2.1176	144	0.4823	0.6678	0.4829
No log	2.1471	146	0.4443	0.6390	0.4448
No log	2.1765	148	0.4879	0.5093	0.4881
No log	2.2059	150	0.5565	0.4746	0.5565
No log	2.2353	152	0.5079	0.5090	0.5080
No log	2.2647	154	0.4413	0.6192	0.4417
No log	2.2941	156	0.4994	0.6877	0.5000
No log	2.3235	158	0.5384	0.6969	0.5390
No log	2.3529	160	0.5459	0.7049	0.5465
No log	2.3824	162	0.4896	0.6931	0.4902
No log	2.4118	164	0.4515	0.6166	0.4521
No log	2.4412	166	0.4542	0.5582	0.4548
No log	2.4706	168	0.4744	0.5231	0.4750
No log	2.5	170	0.4727	0.5311	0.4734
No log	2.5294	172	0.4686	0.5308	0.4692
No log	2.5588	174	0.4522	0.5758	0.4528
No log	2.5882	176	0.4710	0.6394	0.4716
No log	2.6176	178	0.5015	0.6718	0.5021
No log	2.6471	180	0.4992	0.6662	0.4996
No log	2.6765	182	0.4766	0.6586	0.4770
No log	2.7059	184	0.4565	0.6203	0.4568
No log	2.7353	186	0.4604	0.5839	0.4607
No log	2.7647	188	0.4642	0.5807	0.4645
No log	2.7941	190	0.4823	0.5543	0.4825
No log	2.8235	192	0.4684	0.5730	0.4686
No log	2.8529	194	0.4621	0.6599	0.4624
No log	2.8824	196	0.5061	0.6894	0.5065
No log	2.9118	198	0.6049	0.7179	0.6053
No log	2.9412	200	0.6139	0.7144	0.6143
No log	2.9706	202	0.5494	0.7066	0.5499
No log	3.0	204	0.4878	0.6852	0.4883
No log	3.0294	206	0.4412	0.6324	0.4416
No log	3.0588	208	0.4376	0.5864	0.4381
No log	3.0882	210	0.4372	0.5787	0.4378
No log	3.1176	212	0.4362	0.5976	0.4368
No log	3.1471	214	0.4480	0.6297	0.4486
No log	3.1765	216	0.4506	0.6470	0.4512
No log	3.2059	218	0.4538	0.6630	0.4543
No log	3.2353	220	0.4517	0.6553	0.4523
No log	3.2647	222	0.4429	0.6528	0.4434
No log	3.2941	224	0.4419	0.6274	0.4423
No log	3.3235	226	0.4443	0.5986	0.4447
No log	3.3529	228	0.4438	0.6168	0.4442
No log	3.3824	230	0.4436	0.6385	0.4441
No log	3.4118	232	0.4517	0.6535	0.4522
No log	3.4412	234	0.4706	0.6768	0.4711
No log	3.4706	236	0.4663	0.6793	0.4668
No log	3.5	238	0.4484	0.6485	0.4489
No log	3.5294	240	0.4432	0.6242	0.4437
No log	3.5588	242	0.4516	0.5690	0.4521
No log	3.5882	244	0.4524	0.5692	0.4530
No log	3.6176	246	0.4532	0.6189	0.4538
No log	3.6471	248	0.4842	0.6598	0.4849
No log	3.6765	250	0.5276	0.7093	0.5283
No log	3.7059	252	0.5211	0.7109	0.5218
No log	3.7353	254	0.4884	0.7045	0.4891
No log	3.7647	256	0.4540	0.6519	0.4546
No log	3.7941	258	0.4426	0.5963	0.4431
No log	3.8235	260	0.4721	0.5300	0.4724
No log	3.8529	262	0.4893	0.5089	0.4895
No log	3.8824	264	0.4702	0.5384	0.4705
No log	3.9118	266	0.4426	0.5917	0.4430
No log	3.9412	268	0.4437	0.6570	0.4442
No log	3.9706	270	0.4933	0.6938	0.4939
No log	4.0	272	0.5444	0.7055	0.5451
No log	4.0294	274	0.5539	0.7027	0.5546
No log	4.0588	276	0.5254	0.7033	0.5262
No log	4.0882	278	0.4805	0.6873	0.4812
No log	4.1176	280	0.4416	0.6569	0.4422
No log	4.1471	282	0.4319	0.6089	0.4323
No log	4.1765	284	0.4440	0.5684	0.4444
No log	4.2059	286	0.4576	0.5526	0.4579
No log	4.2353	288	0.4602	0.5469	0.4605
No log	4.2647	290	0.4573	0.5491	0.4576
No log	4.2941	292	0.4470	0.5685	0.4474
No log	4.3235	294	0.4351	0.5867	0.4355
No log	4.3529	296	0.4371	0.6428	0.4377
No log	4.3824	298	0.4542	0.6719	0.4549
No log	4.4118	300	0.4759	0.6888	0.4766
No log	4.4412	302	0.4875	0.7017	0.4882
No log	4.4706	304	0.4885	0.7005	0.4892
No log	4.5	306	0.4803	0.6927	0.4810
No log	4.5294	308	0.4695	0.6736	0.4702
No log	4.5588	310	0.4570	0.6633	0.4577
No log	4.5882	312	0.4506	0.6443	0.4512
No log	4.6176	314	0.4450	0.6455	0.4456
No log	4.6471	316	0.4427	0.6507	0.4433
No log	4.6765	318	0.4412	0.6514	0.4418
No log	4.7059	320	0.4426	0.6558	0.4432
No log	4.7353	322	0.4435	0.6556	0.4441
No log	4.7647	324	0.4464	0.6594	0.4470
No log	4.7941	326	0.4506	0.6658	0.4512
No log	4.8235	328	0.4520	0.6636	0.4526
No log	4.8529	330	0.4535	0.6651	0.4541
No log	4.8824	332	0.4531	0.6651	0.4537
No log	4.9118	334	0.4538	0.6651	0.4544
No log	4.9412	336	0.4551	0.6660	0.4557
No log	4.9706	338	0.4553	0.6660	0.4559
No log	5.0	340	0.4551	0.6660	0.4557

Framework versions

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