bert_baseline_language_task6_fold2

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: 0.4616
• Qwk: 0.7181
• Mse: 0.4616

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	2.2287	0.0	2.2287
No log	0.0588	4	1.8372	0.0179	1.8372
No log	0.0882	6	1.5803	0.0059	1.5803
No log	0.1176	8	1.2550	0.0059	1.2550
No log	0.1471	10	0.9907	0.0	0.9907
No log	0.1765	12	0.7923	0.0	0.7923
No log	0.2059	14	0.7107	0.3259	0.7107
No log	0.2353	16	0.6947	0.3362	0.6947
No log	0.2647	18	0.7107	0.3066	0.7107
No log	0.2941	20	0.6373	0.3999	0.6373
No log	0.3235	22	0.5741	0.3890	0.5741
No log	0.3529	24	0.5646	0.3197	0.5646
No log	0.3824	26	0.4957	0.4027	0.4957
No log	0.4118	28	0.6238	0.4438	0.6238
No log	0.4412	30	0.6363	0.4674	0.6363
No log	0.4706	32	0.4986	0.4561	0.4986
No log	0.5	34	0.4938	0.4388	0.4938
No log	0.5294	36	0.4691	0.4968	0.4691
No log	0.5588	38	0.4908	0.5026	0.4908
No log	0.5882	40	0.4847	0.4816	0.4847
No log	0.6176	42	0.4717	0.4558	0.4717
No log	0.6471	44	0.4712	0.4584	0.4712
No log	0.6765	46	0.4799	0.5080	0.4799
No log	0.7059	48	0.4395	0.4749	0.4395
No log	0.7353	50	0.4252	0.4815	0.4252
No log	0.7647	52	0.4386	0.5341	0.4386
No log	0.7941	54	0.5206	0.5752	0.5206
No log	0.8235	56	0.4683	0.5597	0.4683
No log	0.8529	58	0.4309	0.5441	0.4309
No log	0.8824	60	0.4287	0.5478	0.4287
No log	0.9118	62	0.4569	0.5535	0.4569
No log	0.9412	64	0.5399	0.5671	0.5399
No log	0.9706	66	0.5357	0.5699	0.5357
No log	1.0	68	0.4800	0.5607	0.4800
No log	1.0294	70	0.4157	0.5522	0.4157
No log	1.0588	72	0.4106	0.5392	0.4106
No log	1.0882	74	0.4182	0.5590	0.4182
No log	1.1176	76	0.4272	0.5619	0.4272
No log	1.1471	78	0.4669	0.5650	0.4669
No log	1.1765	80	0.4211	0.5524	0.4211
No log	1.2059	82	0.3831	0.5251	0.3831
No log	1.2353	84	0.3785	0.5286	0.3785
No log	1.2647	86	0.3964	0.5328	0.3964
No log	1.2941	88	0.4628	0.5726	0.4628
No log	1.3235	90	0.5692	0.6034	0.5692
No log	1.3529	92	0.5280	0.5730	0.5280
No log	1.3824	94	0.4229	0.5586	0.4229
No log	1.4118	96	0.3793	0.5567	0.3793
No log	1.4412	98	0.3886	0.5558	0.3886
No log	1.4706	100	0.4232	0.5708	0.4232
No log	1.5	102	0.4903	0.6363	0.4903
No log	1.5294	104	0.5600	0.6660	0.5600
No log	1.5588	106	0.4788	0.6169	0.4788
No log	1.5882	108	0.3943	0.5604	0.3943
No log	1.6176	110	0.3795	0.5503	0.3795
No log	1.6471	112	0.3801	0.5544	0.3801
No log	1.6765	114	0.3726	0.5538	0.3726
No log	1.7059	116	0.3757	0.5588	0.3757
No log	1.7353	118	0.3989	0.5826	0.3989
No log	1.7647	120	0.4620	0.6683	0.4620
No log	1.7941	122	0.4743	0.6907	0.4743
No log	1.8235	124	0.4231	0.6453	0.4231
No log	1.8529	126	0.4170	0.6370	0.4170
No log	1.8824	128	0.3957	0.6128	0.3957
No log	1.9118	130	0.3878	0.6224	0.3878
No log	1.9412	132	0.4211	0.6545	0.4211
No log	1.9706	134	0.4202	0.6533	0.4202
No log	2.0	136	0.4625	0.7013	0.4625
No log	2.0294	138	0.4733	0.7189	0.4733
No log	2.0588	140	0.4476	0.7017	0.4476
No log	2.0882	142	0.3759	0.6334	0.3759
No log	2.1176	144	0.3469	0.5588	0.3469
No log	2.1471	146	0.3510	0.5593	0.3510
No log	2.1765	148	0.3630	0.6196	0.3630
No log	2.2059	150	0.4440	0.7086	0.4440
No log	2.2353	152	0.4514	0.6962	0.4514
No log	2.2647	154	0.3885	0.6167	0.3885
No log	2.2941	156	0.3739	0.5548	0.3739
No log	2.3235	158	0.3738	0.5432	0.3738
No log	2.3529	160	0.3637	0.5673	0.3637
No log	2.3824	162	0.4134	0.6051	0.4134
No log	2.4118	164	0.4746	0.6182	0.4746
No log	2.4412	166	0.4661	0.5976	0.4661
No log	2.4706	168	0.4352	0.5821	0.4352
No log	2.5	170	0.3672	0.5693	0.3672
No log	2.5294	172	0.3560	0.5622	0.3560
No log	2.5588	174	0.3568	0.5664	0.3568
No log	2.5882	176	0.3662	0.5731	0.3662
No log	2.6176	178	0.4478	0.6053	0.4478
No log	2.6471	180	0.6028	0.6360	0.6028
No log	2.6765	182	0.6808	0.6402	0.6808
No log	2.7059	184	0.6392	0.6648	0.6392
No log	2.7353	186	0.5239	0.6822	0.5239
No log	2.7647	188	0.3988	0.6306	0.3988
No log	2.7941	190	0.3564	0.5899	0.3564
No log	2.8235	192	0.3538	0.5830	0.3538
No log	2.8529	194	0.3774	0.6283	0.3774
No log	2.8824	196	0.4543	0.7034	0.4543
No log	2.9118	198	0.5116	0.7238	0.5116
No log	2.9412	200	0.5246	0.7317	0.5246
No log	2.9706	202	0.4793	0.7011	0.4793
No log	3.0	204	0.4097	0.6607	0.4097
No log	3.0294	206	0.3682	0.5927	0.3682
No log	3.0588	208	0.3662	0.5946	0.3662
No log	3.0882	210	0.3723	0.6122	0.3723
No log	3.1176	212	0.3872	0.6368	0.3872
No log	3.1471	214	0.3951	0.6436	0.3951
No log	3.1765	216	0.4361	0.6954	0.4361
No log	3.2059	218	0.4445	0.7051	0.4445
No log	3.2353	220	0.4103	0.6713	0.4103
No log	3.2647	222	0.3786	0.6266	0.3786
No log	3.2941	224	0.3647	0.6039	0.3647
No log	3.3235	226	0.3766	0.6076	0.3766
No log	3.3529	228	0.4193	0.6325	0.4193
No log	3.3824	230	0.4691	0.6566	0.4691
No log	3.4118	232	0.5246	0.6975	0.5246
No log	3.4412	234	0.5207	0.6985	0.5207
No log	3.4706	236	0.4934	0.7012	0.4934
No log	3.5	238	0.4623	0.6883	0.4623
No log	3.5294	240	0.4157	0.6762	0.4157
No log	3.5588	242	0.3874	0.6721	0.3874
No log	3.5882	244	0.3975	0.6686	0.3975
No log	3.6176	246	0.4289	0.6950	0.4289
No log	3.6471	248	0.4126	0.6884	0.4126
No log	3.6765	250	0.4162	0.6884	0.4162
No log	3.7059	252	0.4628	0.7118	0.4628
No log	3.7353	254	0.5588	0.7309	0.5588
No log	3.7647	256	0.5880	0.7325	0.5880
No log	3.7941	258	0.5813	0.7298	0.5813
No log	3.8235	260	0.5110	0.7382	0.5110
No log	3.8529	262	0.4454	0.7160	0.4454
No log	3.8824	264	0.3902	0.6786	0.3902
No log	3.9118	266	0.3769	0.6668	0.3769
No log	3.9412	268	0.3872	0.6868	0.3872
No log	3.9706	270	0.4121	0.6942	0.4121
No log	4.0	272	0.4399	0.7115	0.4399
No log	4.0294	274	0.4610	0.7201	0.4610
No log	4.0588	276	0.4591	0.7247	0.4591
No log	4.0882	278	0.4276	0.6958	0.4276
No log	4.1176	280	0.4059	0.6860	0.4059
No log	4.1471	282	0.3903	0.6804	0.3903
No log	4.1765	284	0.4012	0.6905	0.4012
No log	4.2059	286	0.4118	0.6936	0.4118
No log	4.2353	288	0.4037	0.6832	0.4037
No log	4.2647	290	0.3977	0.6868	0.3977
No log	4.2941	292	0.4002	0.6888	0.4002
No log	4.3235	294	0.4075	0.6962	0.4075
No log	4.3529	296	0.4002	0.6819	0.4002
No log	4.3824	298	0.4015	0.6862	0.4015
No log	4.4118	300	0.4175	0.7002	0.4175
No log	4.4412	302	0.4355	0.6978	0.4355
No log	4.4706	304	0.4575	0.6999	0.4575
No log	4.5	306	0.4685	0.7182	0.4685
No log	4.5294	308	0.4751	0.7181	0.4751
No log	4.5588	310	0.4817	0.7190	0.4817
No log	4.5882	312	0.4805	0.7190	0.4805
No log	4.6176	314	0.4767	0.7233	0.4767
No log	4.6471	316	0.4841	0.7220	0.4841
No log	4.6765	318	0.4941	0.7282	0.4941
No log	4.7059	320	0.4988	0.7351	0.4988
No log	4.7353	322	0.4986	0.7351	0.4986
No log	4.7647	324	0.4949	0.7340	0.4949
No log	4.7941	326	0.4862	0.7250	0.4862
No log	4.8235	328	0.4803	0.7214	0.4803
No log	4.8529	330	0.4736	0.7256	0.4736
No log	4.8824	332	0.4694	0.7147	0.4694
No log	4.9118	334	0.4678	0.7148	0.4678
No log	4.9412	336	0.4638	0.7181	0.4638
No log	4.9706	338	0.4623	0.7181	0.4623
No log	5.0	340	0.4616	0.7181	0.4616

Framework versions

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