bert_baseline_language_task3_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: 0.4340
• Qwk: 0.5769
• Mse: 0.4343

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	0.9109	0.1135	0.9120
No log	0.0615	4	0.7302	0.0091	0.7310
No log	0.0923	6	0.6473	0.0	0.6480
No log	0.1231	8	0.6464	0.0	0.6469
No log	0.1538	10	0.6452	0.0	0.6458
No log	0.1846	12	0.6121	0.0	0.6126
No log	0.2154	14	0.6376	0.0	0.6382
No log	0.2462	16	0.6836	0.0	0.6841
No log	0.2769	18	0.7015	0.0	0.7020
No log	0.3077	20	0.6505	0.0	0.6510
No log	0.3385	22	0.5816	0.0	0.5822
No log	0.3692	24	0.5565	0.0	0.5571
No log	0.4	26	0.5383	0.0	0.5389
No log	0.4308	28	0.5152	0.0091	0.5157
No log	0.4615	30	0.4960	0.0270	0.4965
No log	0.4923	32	0.4781	0.1041	0.4785
No log	0.5231	34	0.4595	0.1801	0.4599
No log	0.5538	36	0.4648	0.2938	0.4653
No log	0.5846	38	0.4753	0.4514	0.4758
No log	0.6154	40	0.4224	0.4998	0.4225
No log	0.6462	42	0.4749	0.3528	0.4746
No log	0.6769	44	0.5212	0.3219	0.5210
No log	0.7077	46	0.4233	0.3754	0.4233
No log	0.7385	48	0.4789	0.5565	0.4792
No log	0.7692	50	0.6057	0.5461	0.6062
No log	0.8	52	0.7260	0.5404	0.7266
No log	0.8308	54	0.6614	0.5465	0.6619
No log	0.8615	56	0.5122	0.4793	0.5127
No log	0.8923	58	0.4503	0.2917	0.4507
No log	0.9231	60	0.4273	0.2707	0.4277
No log	0.9538	62	0.4133	0.3275	0.4136
No log	0.9846	64	0.4075	0.4202	0.4076
No log	1.0154	66	0.4159	0.5118	0.4160
No log	1.0462	68	0.4456	0.5714	0.4459
No log	1.0769	70	0.4420	0.5985	0.4424
No log	1.1077	72	0.4074	0.5653	0.4076
No log	1.1385	74	0.3829	0.4871	0.3830
No log	1.1692	76	0.3715	0.4828	0.3717
No log	1.2	78	0.3620	0.4863	0.3623
No log	1.2308	80	0.3671	0.5415	0.3674
No log	1.2615	82	0.4030	0.5946	0.4033
No log	1.2923	84	0.4396	0.5992	0.4399
No log	1.3231	86	0.4332	0.5951	0.4334
No log	1.3538	88	0.3744	0.5906	0.3747
No log	1.3846	90	0.3379	0.5145	0.3381
No log	1.4154	92	0.3385	0.5125	0.3387
No log	1.4462	94	0.3708	0.5662	0.3711
No log	1.4769	96	0.4722	0.6023	0.4724
No log	1.5077	98	0.4995	0.6024	0.4998
No log	1.5385	100	0.4179	0.5810	0.4182
No log	1.5692	102	0.3509	0.5168	0.3512
No log	1.6	104	0.3364	0.5036	0.3367
No log	1.6308	106	0.3356	0.5394	0.3359
No log	1.6615	108	0.3813	0.6251	0.3815
No log	1.6923	110	0.4242	0.6416	0.4245
No log	1.7231	112	0.4424	0.6371	0.4427
No log	1.7538	114	0.4157	0.6542	0.4160
No log	1.7846	116	0.3935	0.6434	0.3937
No log	1.8154	118	0.3787	0.6387	0.3790
No log	1.8462	120	0.3835	0.6349	0.3837
No log	1.8769	122	0.4416	0.6288	0.4419
No log	1.9077	124	0.5026	0.6156	0.5028
No log	1.9385	126	0.4854	0.6136	0.4857
No log	1.9692	128	0.4068	0.6195	0.4071
No log	2.0	130	0.3600	0.5947	0.3603
No log	2.0308	132	0.3585	0.5905	0.3587
No log	2.0615	134	0.3569	0.5810	0.3570
No log	2.0923	136	0.3751	0.5943	0.3752
No log	2.1231	138	0.4052	0.6099	0.4054
No log	2.1538	140	0.4135	0.6173	0.4137
No log	2.1846	142	0.3853	0.6116	0.3854
No log	2.2154	144	0.3977	0.6213	0.3978
No log	2.2462	146	0.4319	0.6339	0.4321
No log	2.2769	148	0.4184	0.6320	0.4185
No log	2.3077	150	0.4158	0.6281	0.4159
No log	2.3385	152	0.4513	0.6319	0.4514
No log	2.3692	154	0.4589	0.6325	0.4590
No log	2.4	156	0.4841	0.6217	0.4843
No log	2.4308	158	0.4072	0.6167	0.4073
No log	2.4615	160	0.3546	0.5723	0.3546
No log	2.4923	162	0.3616	0.5908	0.3617
No log	2.5231	164	0.3942	0.5987	0.3944
No log	2.5538	166	0.4663	0.6275	0.4666
No log	2.5846	168	0.4424	0.6243	0.4426
No log	2.6154	170	0.4280	0.6225	0.4282
No log	2.6462	172	0.3988	0.6006	0.3990
No log	2.6769	174	0.4066	0.5998	0.4068
No log	2.7077	176	0.3877	0.5780	0.3879
No log	2.7385	178	0.4221	0.5808	0.4223
No log	2.7692	180	0.4523	0.5856	0.4526
No log	2.8	182	0.4291	0.5832	0.4294
No log	2.8308	184	0.3831	0.5593	0.3833
No log	2.8615	186	0.3714	0.5692	0.3716
No log	2.8923	188	0.3999	0.5857	0.4001
No log	2.9231	190	0.4673	0.6274	0.4676
No log	2.9538	192	0.5013	0.6144	0.5016
No log	2.9846	194	0.4775	0.6045	0.4777
No log	3.0154	196	0.4092	0.6073	0.4094
No log	3.0462	198	0.3818	0.5803	0.3820
No log	3.0769	200	0.3905	0.5896	0.3907
No log	3.1077	202	0.4430	0.6144	0.4432
No log	3.1385	204	0.4667	0.6174	0.4669
No log	3.1692	206	0.4787	0.6228	0.4789
No log	3.2	208	0.4414	0.6197	0.4416
No log	3.2308	210	0.3774	0.6170	0.3775
No log	3.2615	212	0.3546	0.5664	0.3546
No log	3.2923	214	0.3575	0.5688	0.3576
No log	3.3231	216	0.3930	0.6024	0.3932
No log	3.3538	218	0.4818	0.6159	0.4821
No log	3.3846	220	0.5077	0.6107	0.5080
No log	3.4154	222	0.4607	0.6259	0.4609
No log	3.4462	224	0.4252	0.6139	0.4254
No log	3.4769	226	0.3971	0.6024	0.3974
No log	3.5077	228	0.3929	0.5945	0.3931
No log	3.5385	230	0.3988	0.5954	0.3990
No log	3.5692	232	0.4157	0.5997	0.4160
No log	3.6	234	0.4042	0.5909	0.4044
No log	3.6308	236	0.3802	0.5811	0.3804
No log	3.6615	238	0.3662	0.5680	0.3663
No log	3.6923	240	0.3772	0.5796	0.3774
No log	3.7231	242	0.4299	0.5936	0.4302
No log	3.7538	244	0.5352	0.6100	0.5356
No log	3.7846	246	0.6217	0.6080	0.6221
No log	3.8154	248	0.6413	0.5945	0.6417
No log	3.8462	250	0.5878	0.6027	0.5882
No log	3.8769	252	0.4979	0.6006	0.4982
No log	3.9077	254	0.4257	0.5829	0.4260
No log	3.9385	256	0.3851	0.5768	0.3853
No log	3.9692	258	0.3790	0.5720	0.3792
No log	4.0	260	0.3900	0.5769	0.3902
No log	4.0308	262	0.4249	0.6061	0.4252
No log	4.0615	264	0.4773	0.6123	0.4776
No log	4.0923	266	0.5001	0.6182	0.5005
No log	4.1231	268	0.4873	0.6129	0.4877
No log	4.1538	270	0.4502	0.6009	0.4505
No log	4.1846	272	0.4219	0.5944	0.4222
No log	4.2154	274	0.4092	0.5796	0.4095
No log	4.2462	276	0.4165	0.5812	0.4168
No log	4.2769	278	0.4317	0.6021	0.4320
No log	4.3077	280	0.4375	0.5986	0.4378
No log	4.3385	282	0.4378	0.5945	0.4381
No log	4.3692	284	0.4515	0.5955	0.4518
No log	4.4	286	0.4560	0.5918	0.4563
No log	4.4308	288	0.4702	0.5890	0.4705
No log	4.4615	290	0.4805	0.5937	0.4809
No log	4.4923	292	0.4797	0.5914	0.4800
No log	4.5231	294	0.4620	0.5818	0.4623
No log	4.5538	296	0.4500	0.5913	0.4503
No log	4.5846	298	0.4468	0.5909	0.4471
No log	4.6154	300	0.4467	0.5913	0.4470
No log	4.6462	302	0.4462	0.5913	0.4465
No log	4.6769	304	0.4411	0.5913	0.4414
No log	4.7077	306	0.4387	0.5866	0.4390
No log	4.7385	308	0.4366	0.5796	0.4369
No log	4.7692	310	0.4318	0.5703	0.4321
No log	4.8	312	0.4290	0.5699	0.4293
No log	4.8308	314	0.4322	0.5723	0.4324
No log	4.8615	316	0.4341	0.5769	0.4344
No log	4.8923	318	0.4340	0.5769	0.4343
No log	4.9231	320	0.4352	0.5769	0.4355
No log	4.9538	322	0.4348	0.5727	0.4351
No log	4.9846	324	0.4340	0.5769	0.4343

Framework versions

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