bert_baseline_language_task3_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: 0.4310
• Qwk: 0.6497
• Mse: 0.4312

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	0.0308	2	0.8667	0.1286	0.8665
No log	0.0615	4	0.6721	0.0	0.6724
No log	0.0923	6	0.5799	0.0	0.5808
No log	0.1231	8	0.5723	0.0	0.5735
No log	0.1538	10	0.5882	0.0	0.5895
No log	0.1846	12	0.7119	-0.0229	0.7129
No log	0.2154	14	0.5587	0.0032	0.5596
No log	0.2462	16	0.5222	0.0	0.5229
No log	0.2769	18	0.5158	0.0	0.5165
No log	0.3077	20	0.4875	0.0	0.4881
No log	0.3385	22	0.4688	0.0096	0.4693
No log	0.3692	24	0.4535	0.0190	0.4541
No log	0.4	26	0.4426	0.0553	0.4432
No log	0.4308	28	0.4235	0.1569	0.4238
No log	0.4615	30	0.4035	0.2237	0.4036
No log	0.4923	32	0.3861	0.3251	0.3860
No log	0.5231	34	0.3859	0.3924	0.3856
No log	0.5538	36	0.4097	0.3681	0.4092
No log	0.5846	38	0.3858	0.4320	0.3853
No log	0.6154	40	0.3829	0.5218	0.3826
No log	0.6462	42	0.4023	0.5843	0.4021
No log	0.6769	44	0.3627	0.5516	0.3623
No log	0.7077	46	0.3448	0.5242	0.3445
No log	0.7385	48	0.3390	0.5750	0.3387
No log	0.7692	50	0.3549	0.6159	0.3548
No log	0.8	52	0.3917	0.6282	0.3917
No log	0.8308	54	0.4120	0.6185	0.4122
No log	0.8615	56	0.3578	0.5993	0.3579
No log	0.8923	58	0.3245	0.5054	0.3244
No log	0.9231	60	0.3458	0.5575	0.3458
No log	0.9538	62	0.4763	0.6243	0.4766
No log	0.9846	64	0.4953	0.6201	0.4955
No log	1.0154	66	0.3697	0.5996	0.3697
No log	1.0462	68	0.3512	0.5810	0.3512
No log	1.0769	70	0.3414	0.5767	0.3413
No log	1.1077	72	0.3922	0.6309	0.3922
No log	1.1385	74	0.4247	0.6202	0.4247
No log	1.1692	76	0.3777	0.6191	0.3776
No log	1.2	78	0.3634	0.5857	0.3633
No log	1.2308	80	0.3498	0.5617	0.3495
No log	1.2615	82	0.3438	0.5763	0.3437
No log	1.2923	84	0.3736	0.6122	0.3736
No log	1.3231	86	0.3695	0.6156	0.3695
No log	1.3538	88	0.3555	0.6014	0.3554
No log	1.3846	90	0.3487	0.5962	0.3486
No log	1.4154	92	0.3489	0.6098	0.3488
No log	1.4462	94	0.3380	0.5808	0.3379
No log	1.4769	96	0.3571	0.6081	0.3572
No log	1.5077	98	0.3722	0.6171	0.3724
No log	1.5385	100	0.4097	0.6365	0.4100
No log	1.5692	102	0.3790	0.6108	0.3794
No log	1.6	104	0.3796	0.6035	0.3801
No log	1.6308	106	0.3557	0.5632	0.3561
No log	1.6615	108	0.3973	0.5962	0.3977
No log	1.6923	110	0.4461	0.6243	0.4465
No log	1.7231	112	0.4083	0.6133	0.4087
No log	1.7538	114	0.3984	0.6157	0.3988
No log	1.7846	116	0.3726	0.6102	0.3730
No log	1.8154	118	0.3767	0.5977	0.3771
No log	1.8462	120	0.4635	0.6273	0.4640
No log	1.8769	122	0.6099	0.6037	0.6106
No log	1.9077	124	0.6275	0.5888	0.6282
No log	1.9385	126	0.5350	0.6223	0.5356
No log	1.9692	128	0.4031	0.6213	0.4034
No log	2.0	130	0.3393	0.5969	0.3394
No log	2.0308	132	0.3287	0.5599	0.3288
No log	2.0615	134	0.3515	0.5897	0.3516
No log	2.0923	136	0.3996	0.6258	0.3997
No log	2.1231	138	0.4641	0.6169	0.4643
No log	2.1538	140	0.4542	0.6158	0.4544
No log	2.1846	142	0.4004	0.6351	0.4005
No log	2.2154	144	0.3401	0.5887	0.3402
No log	2.2462	146	0.3235	0.5328	0.3235
No log	2.2769	148	0.3321	0.5753	0.3321
No log	2.3077	150	0.3804	0.6323	0.3805
No log	2.3385	152	0.4133	0.6239	0.4135
No log	2.3692	154	0.3998	0.6317	0.4000
No log	2.4	156	0.3526	0.6064	0.3527
No log	2.4308	158	0.3562	0.6005	0.3564
No log	2.4615	160	0.3973	0.6415	0.3975
No log	2.4923	162	0.4010	0.6347	0.4012
No log	2.5231	164	0.3810	0.6306	0.3812
No log	2.5538	166	0.3914	0.6271	0.3916
No log	2.5846	168	0.4101	0.6216	0.4104
No log	2.6154	170	0.3935	0.6240	0.3938
No log	2.6462	172	0.3646	0.6070	0.3649
No log	2.6769	174	0.3806	0.6188	0.3809
No log	2.7077	176	0.3976	0.6294	0.3980
No log	2.7385	178	0.3807	0.6188	0.3810
No log	2.7692	180	0.3702	0.6231	0.3705
No log	2.8	182	0.3468	0.5942	0.3469
No log	2.8308	184	0.3611	0.6284	0.3613
No log	2.8615	186	0.3921	0.6324	0.3923
No log	2.8923	188	0.4505	0.6341	0.4508
No log	2.9231	190	0.5436	0.6130	0.5441
No log	2.9538	192	0.5516	0.5987	0.5521
No log	2.9846	194	0.4740	0.6272	0.4744
No log	3.0154	196	0.3665	0.6255	0.3667
No log	3.0462	198	0.3328	0.5737	0.3329
No log	3.0769	200	0.3368	0.5899	0.3369
No log	3.1077	202	0.3630	0.6250	0.3631
No log	3.1385	204	0.4167	0.6402	0.4169
No log	3.1692	206	0.4774	0.6409	0.4776
No log	3.2	208	0.4657	0.6437	0.4659
No log	3.2308	210	0.4932	0.6426	0.4933
No log	3.2615	212	0.4736	0.6453	0.4737
No log	3.2923	214	0.4233	0.6436	0.4234
No log	3.3231	216	0.4093	0.6436	0.4094
No log	3.3538	218	0.4126	0.6488	0.4127
No log	3.3846	220	0.4110	0.6481	0.4110
No log	3.4154	222	0.4596	0.6397	0.4597
No log	3.4462	224	0.4659	0.6426	0.4661
No log	3.4769	226	0.4215	0.6391	0.4216
No log	3.5077	228	0.3766	0.6305	0.3766
No log	3.5385	230	0.3600	0.6084	0.3600
No log	3.5692	232	0.3712	0.6256	0.3712
No log	3.6	234	0.3671	0.6171	0.3671
No log	3.6308	236	0.3682	0.6262	0.3683
No log	3.6615	238	0.3608	0.6184	0.3609
No log	3.6923	240	0.3834	0.6317	0.3835
No log	3.7231	242	0.4443	0.6511	0.4445
No log	3.7538	244	0.4779	0.6435	0.4781
No log	3.7846	246	0.4705	0.6442	0.4708
No log	3.8154	248	0.4286	0.6526	0.4288
No log	3.8462	250	0.3918	0.6387	0.3920
No log	3.8769	252	0.3711	0.6330	0.3712
No log	3.9077	254	0.3700	0.6284	0.3701
No log	3.9385	256	0.3633	0.6233	0.3633
No log	3.9692	258	0.3682	0.6329	0.3683
No log	4.0	260	0.3658	0.6262	0.3658
No log	4.0308	262	0.3922	0.6462	0.3923
No log	4.0615	264	0.4182	0.6565	0.4183
No log	4.0923	266	0.4467	0.6587	0.4468
No log	4.1231	268	0.4401	0.6663	0.4403
No log	4.1538	270	0.4293	0.6641	0.4294
No log	4.1846	272	0.4237	0.6599	0.4238
No log	4.2154	274	0.4467	0.6677	0.4468
No log	4.2462	276	0.4703	0.6726	0.4705
No log	4.2769	278	0.4826	0.6690	0.4828
No log	4.3077	280	0.4852	0.6654	0.4853
No log	4.3385	282	0.4567	0.6699	0.4568
No log	4.3692	284	0.4361	0.6591	0.4361
No log	4.4	286	0.4165	0.6535	0.4165
No log	4.4308	288	0.4167	0.6511	0.4168
No log	4.4615	290	0.4213	0.6524	0.4213
No log	4.4923	292	0.4168	0.6545	0.4168
No log	4.5231	294	0.4303	0.6461	0.4304
No log	4.5538	296	0.4488	0.6557	0.4490
No log	4.5846	298	0.4573	0.6534	0.4574
No log	4.6154	300	0.4809	0.6570	0.4811
No log	4.6462	302	0.4878	0.6538	0.4881
No log	4.6769	304	0.4771	0.6499	0.4773
No log	4.7077	306	0.4567	0.6516	0.4569
No log	4.7385	308	0.4453	0.6494	0.4455
No log	4.7692	310	0.4356	0.6487	0.4358
No log	4.8	312	0.4348	0.6465	0.4349
No log	4.8308	314	0.4349	0.6465	0.4351
No log	4.8615	316	0.4350	0.6458	0.4352
No log	4.8923	318	0.4341	0.6497	0.4343
No log	4.9231	320	0.4312	0.6504	0.4313
No log	4.9538	322	0.4310	0.6504	0.4312
No log	4.9846	324	0.4310	0.6497	0.4312

Framework versions

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