bert_baseline_language_task6_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: 0.4886
• Qwk: 0.7157
• Mse: 0.4886

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	2.2411	0.0	2.2411
No log	0.0588	4	1.8734	-0.0178	1.8734
No log	0.0882	6	1.6090	0.0059	1.6090
No log	0.1176	8	1.2192	0.0059	1.2192
No log	0.1471	10	0.9341	0.0059	0.9341
No log	0.1765	12	0.7364	0.1416	0.7364
No log	0.2059	14	0.6982	0.2687	0.6982
No log	0.2353	16	0.6582	0.3372	0.6582
No log	0.2647	18	0.7135	0.1462	0.7135
No log	0.2941	20	0.6798	0.2206	0.6798
No log	0.3235	22	0.5955	0.3915	0.5955
No log	0.3529	24	0.6219	0.3622	0.6219
No log	0.3824	26	0.5703	0.3992	0.5703
No log	0.4118	28	0.5099	0.4137	0.5099
No log	0.4412	30	0.5199	0.4116	0.5199
No log	0.4706	32	0.5644	0.4094	0.5644
No log	0.5	34	0.5463	0.4109	0.5463
No log	0.5294	36	0.4851	0.3907	0.4851
No log	0.5588	38	0.4850	0.4156	0.4850
No log	0.5882	40	0.5052	0.4150	0.5052
No log	0.6176	42	0.4521	0.4313	0.4521
No log	0.6471	44	0.4285	0.3921	0.4285
No log	0.6765	46	0.4230	0.4170	0.4230
No log	0.7059	48	0.4622	0.4317	0.4622
No log	0.7353	50	0.5184	0.4332	0.5184
No log	0.7647	52	0.5387	0.4339	0.5387
No log	0.7941	54	0.5345	0.4536	0.5345
No log	0.8235	56	0.4593	0.4674	0.4593
No log	0.8529	58	0.4454	0.5019	0.4454
No log	0.8824	60	0.5377	0.6217	0.5377
No log	0.9118	62	0.7227	0.6473	0.7227
No log	0.9412	64	0.6967	0.5892	0.6967
No log	0.9706	66	0.4789	0.5329	0.4789
No log	1.0	68	0.4475	0.5381	0.4475
No log	1.0294	70	0.4883	0.5168	0.4883
No log	1.0588	72	0.4881	0.5379	0.4881
No log	1.0882	74	0.4513	0.5417	0.4513
No log	1.1176	76	0.4886	0.5726	0.4886
No log	1.1471	78	0.5485	0.6355	0.5485
No log	1.1765	80	0.5511	0.6223	0.5511
No log	1.2059	82	0.4701	0.5498	0.4701
No log	1.2353	84	0.4336	0.5411	0.4336
No log	1.2647	86	0.4810	0.5556	0.4810
No log	1.2941	88	0.4668	0.5530	0.4668
No log	1.3235	90	0.3993	0.5542	0.3993
No log	1.3529	92	0.4006	0.5528	0.4006
No log	1.3824	94	0.4392	0.5585	0.4392
No log	1.4118	96	0.4205	0.5438	0.4205
No log	1.4412	98	0.4390	0.5543	0.4390
No log	1.4706	100	0.5557	0.6166	0.5557
No log	1.5	102	0.5909	0.7254	0.5909
No log	1.5294	104	0.5077	0.7405	0.5077
No log	1.5588	106	0.4091	0.6640	0.4091
No log	1.5882	108	0.4592	0.6912	0.4592
No log	1.6176	110	0.6420	0.7297	0.6420
No log	1.6471	112	0.7219	0.7019	0.7219
No log	1.6765	114	0.5558	0.7405	0.5558
No log	1.7059	116	0.3751	0.6338	0.3751
No log	1.7353	118	0.3983	0.5147	0.3983
No log	1.7647	120	0.3774	0.5266	0.3774
No log	1.7941	122	0.4202	0.6608	0.4202
No log	1.8235	124	0.5371	0.6994	0.5371
No log	1.8529	126	0.4793	0.5619	0.4793
No log	1.8824	128	0.4083	0.5331	0.4083
No log	1.9118	130	0.4079	0.5321	0.4079
No log	1.9412	132	0.3693	0.5479	0.3693
No log	1.9706	134	0.3606	0.5525	0.3606
No log	2.0	136	0.3729	0.5439	0.3729
No log	2.0294	138	0.4628	0.5409	0.4628
No log	2.0588	140	0.5351	0.6159	0.5351
No log	2.0882	142	0.5333	0.6968	0.5333
No log	2.1176	144	0.4991	0.7022	0.4991
No log	2.1471	146	0.5203	0.7229	0.5203
No log	2.1765	148	0.5320	0.7349	0.5320
No log	2.2059	150	0.5657	0.7320	0.5657
No log	2.2353	152	0.4832	0.7194	0.4832
No log	2.2647	154	0.4500	0.7072	0.4500
No log	2.2941	156	0.4751	0.7137	0.4751
No log	2.3235	158	0.5329	0.7259	0.5329
No log	2.3529	160	0.6005	0.7169	0.6005
No log	2.3824	162	0.5667	0.7338	0.5667
No log	2.4118	164	0.4374	0.7067	0.4374
No log	2.4412	166	0.4124	0.6831	0.4124
No log	2.4706	168	0.4354	0.6921	0.4354
No log	2.5	170	0.4397	0.6839	0.4397
No log	2.5294	172	0.4214	0.6446	0.4214
No log	2.5588	174	0.4354	0.6473	0.4354
No log	2.5882	176	0.4596	0.6485	0.4596
No log	2.6176	178	0.4180	0.6243	0.4180
No log	2.6471	180	0.4142	0.6336	0.4142
No log	2.6765	182	0.3653	0.5950	0.3653
No log	2.7059	184	0.3595	0.6087	0.3595
No log	2.7353	186	0.3716	0.6402	0.3716
No log	2.7647	188	0.4491	0.7032	0.4491
No log	2.7941	190	0.4727	0.7077	0.4727
No log	2.8235	192	0.4595	0.6925	0.4595
No log	2.8529	194	0.4305	0.6658	0.4305
No log	2.8824	196	0.3810	0.6041	0.3810
No log	2.9118	198	0.3683	0.5923	0.3683
No log	2.9412	200	0.3942	0.6730	0.3942
No log	2.9706	202	0.5140	0.7149	0.5140
No log	3.0	204	0.5940	0.7421	0.5940
No log	3.0294	206	0.5623	0.7362	0.5623
No log	3.0588	208	0.4522	0.7173	0.4522
No log	3.0882	210	0.4223	0.7002	0.4223
No log	3.1176	212	0.3981	0.6730	0.3981
No log	3.1471	214	0.4195	0.6878	0.4195
No log	3.1765	216	0.4291	0.7051	0.4291
No log	3.2059	218	0.4505	0.7132	0.4505
No log	3.2353	220	0.4684	0.7186	0.4684
No log	3.2647	222	0.4655	0.7164	0.4655
No log	3.2941	224	0.5119	0.7264	0.5119
No log	3.3235	226	0.5486	0.7260	0.5486
No log	3.3529	228	0.4989	0.7182	0.4989
No log	3.3824	230	0.4513	0.7010	0.4513
No log	3.4118	232	0.4255	0.6863	0.4255
No log	3.4412	234	0.4379	0.6912	0.4379
No log	3.4706	236	0.4393	0.6995	0.4393
No log	3.5	238	0.4728	0.7068	0.4728
No log	3.5294	240	0.5134	0.7080	0.5134
No log	3.5588	242	0.4998	0.7118	0.4998
No log	3.5882	244	0.4398	0.6887	0.4398
No log	3.6176	246	0.3836	0.6619	0.3836
No log	3.6471	248	0.3718	0.6220	0.3718
No log	3.6765	250	0.3892	0.6566	0.3892
No log	3.7059	252	0.4497	0.6913	0.4497
No log	3.7353	254	0.5352	0.7154	0.5352
No log	3.7647	256	0.5511	0.7103	0.5511
No log	3.7941	258	0.5689	0.7135	0.5689
No log	3.8235	260	0.5268	0.7091	0.5268
No log	3.8529	262	0.4670	0.7000	0.4670
No log	3.8824	264	0.4545	0.7162	0.4545
No log	3.9118	266	0.4777	0.7152	0.4777
No log	3.9412	268	0.4792	0.7175	0.4792
No log	3.9706	270	0.4656	0.7290	0.4656
No log	4.0	272	0.4576	0.7216	0.4576
No log	4.0294	274	0.4727	0.7174	0.4727
No log	4.0588	276	0.4847	0.7224	0.4847
No log	4.0882	278	0.4756	0.7155	0.4756
No log	4.1176	280	0.5117	0.7247	0.5117
No log	4.1471	282	0.5247	0.7208	0.5247
No log	4.1765	284	0.4861	0.7141	0.4861
No log	4.2059	286	0.4775	0.7165	0.4775
No log	4.2353	288	0.4770	0.7156	0.4770
No log	4.2647	290	0.4946	0.7130	0.4946
No log	4.2941	292	0.5091	0.7222	0.5091
No log	4.3235	294	0.4794	0.7122	0.4794
No log	4.3529	296	0.4423	0.7225	0.4423
No log	4.3824	298	0.4383	0.7204	0.4383
No log	4.4118	300	0.4611	0.7092	0.4611
No log	4.4412	302	0.4751	0.7190	0.4751
No log	4.4706	304	0.4970	0.7180	0.4970
No log	4.5	306	0.4892	0.7157	0.4892
No log	4.5294	308	0.4820	0.7191	0.4820
No log	4.5588	310	0.4822	0.7184	0.4822
No log	4.5882	312	0.4700	0.7172	0.4700
No log	4.6176	314	0.4430	0.7173	0.4430
No log	4.6471	316	0.4170	0.7125	0.4170
No log	4.6765	318	0.4099	0.7117	0.4099
No log	4.7059	320	0.4161	0.7093	0.4161
No log	4.7353	322	0.4317	0.7169	0.4317
No log	4.7647	324	0.4483	0.7169	0.4483
No log	4.7941	326	0.4626	0.7199	0.4626
No log	4.8235	328	0.4702	0.7156	0.4702
No log	4.8529	330	0.4810	0.7156	0.4810
No log	4.8824	332	0.4882	0.7155	0.4882
No log	4.9118	334	0.4916	0.7194	0.4916
No log	4.9412	336	0.4893	0.7194	0.4893
No log	4.9706	338	0.4884	0.7157	0.4884
No log	5.0	340	0.4886	0.7157	0.4886

Framework versions

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