bert_baseline_language_task3_fold0

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: 0.3754
• Qwk: 0.6907
• Mse: 0.3751

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	1.2242	0.0	1.2224
No log	0.0615	4	0.9994	0.1070	0.9981
No log	0.0923	6	0.8925	0.0081	0.8916
No log	0.1231	8	0.7646	0.0081	0.7641
No log	0.1538	10	0.7245	0.0	0.7243
No log	0.1846	12	0.7079	0.0053	0.7078
No log	0.2154	14	0.6645	0.0131	0.6643
No log	0.2462	16	0.5944	0.0234	0.5942
No log	0.2769	18	0.5628	0.1223	0.5624
No log	0.3077	20	0.5125	0.1772	0.5121
No log	0.3385	22	0.4632	0.3805	0.4629
No log	0.3692	24	0.5232	0.5661	0.5231
No log	0.4	26	0.5584	0.5759	0.5583
No log	0.4308	28	0.4575	0.6357	0.4573
No log	0.4615	30	0.3987	0.4827	0.3982
No log	0.4923	32	0.4462	0.3869	0.4456
No log	0.5231	34	0.3838	0.5019	0.3835
No log	0.5538	36	0.4091	0.6159	0.4089
No log	0.5846	38	0.4442	0.6436	0.4440
No log	0.6154	40	0.4124	0.6214	0.4121
No log	0.6462	42	0.3823	0.5072	0.3820
No log	0.6769	44	0.3787	0.4706	0.3784
No log	0.7077	46	0.3722	0.5682	0.3719
No log	0.7385	48	0.3676	0.6364	0.3673
No log	0.7692	50	0.4047	0.6767	0.4045
No log	0.8	52	0.4091	0.6848	0.4089
No log	0.8308	54	0.3401	0.6635	0.3399
No log	0.8615	56	0.3391	0.6720	0.3389
No log	0.8923	58	0.3545	0.6704	0.3543
No log	0.9231	60	0.3525	0.6816	0.3522
No log	0.9538	62	0.3367	0.6683	0.3364
No log	0.9846	64	0.3287	0.6747	0.3284
No log	1.0154	66	0.3196	0.6693	0.3193
No log	1.0462	68	0.3390	0.6772	0.3386
No log	1.0769	70	0.3883	0.6838	0.3879
No log	1.1077	72	0.4160	0.6845	0.4157
No log	1.1385	74	0.3657	0.6780	0.3653
No log	1.1692	76	0.3606	0.6748	0.3602
No log	1.2	78	0.3383	0.6823	0.3379
No log	1.2308	80	0.3333	0.6679	0.3330
No log	1.2615	82	0.3474	0.6779	0.3472
No log	1.2923	84	0.3342	0.6699	0.3339
No log	1.3231	86	0.3209	0.6659	0.3206
No log	1.3538	88	0.3328	0.6880	0.3324
No log	1.3846	90	0.3587	0.6683	0.3583
No log	1.4154	92	0.3319	0.6775	0.3315
No log	1.4462	94	0.3085	0.6781	0.3081
No log	1.4769	96	0.3201	0.6794	0.3196
No log	1.5077	98	0.3097	0.6634	0.3093
No log	1.5385	100	0.3188	0.6803	0.3184
No log	1.5692	102	0.3422	0.6848	0.3417
No log	1.6	104	0.3741	0.6911	0.3737
No log	1.6308	106	0.3292	0.6852	0.3288
No log	1.6615	108	0.3160	0.6812	0.3156
No log	1.6923	110	0.3606	0.6927	0.3602
No log	1.7231	112	0.3580	0.6919	0.3577
No log	1.7538	114	0.3592	0.6905	0.3588
No log	1.7846	116	0.3768	0.7016	0.3764
No log	1.8154	118	0.3660	0.6905	0.3656
No log	1.8462	120	0.3259	0.6639	0.3255
No log	1.8769	122	0.3200	0.6024	0.3195
No log	1.9077	124	0.3308	0.6202	0.3304
No log	1.9385	126	0.3786	0.6774	0.3782
No log	1.9692	128	0.4478	0.6714	0.4475
No log	2.0	130	0.4483	0.6729	0.4480
No log	2.0308	132	0.3755	0.6796	0.3752
No log	2.0615	134	0.3187	0.6503	0.3184
No log	2.0923	136	0.3057	0.6315	0.3054
No log	2.1231	138	0.3050	0.6006	0.3047
No log	2.1538	140	0.2987	0.6469	0.2984
No log	2.1846	142	0.3535	0.6795	0.3532
No log	2.2154	144	0.4901	0.6855	0.4899
No log	2.2462	146	0.5180	0.6793	0.5178
No log	2.2769	148	0.4216	0.6863	0.4214
No log	2.3077	150	0.3125	0.6716	0.3122
No log	2.3385	152	0.3028	0.6320	0.3025
No log	2.3692	154	0.3038	0.6614	0.3035
No log	2.4	156	0.3478	0.6844	0.3476
No log	2.4308	158	0.4110	0.6824	0.4107
No log	2.4615	160	0.4052	0.6829	0.4050
No log	2.4923	162	0.3788	0.6831	0.3785
No log	2.5231	164	0.3302	0.6933	0.3299
No log	2.5538	166	0.3033	0.6664	0.3030
No log	2.5846	168	0.3146	0.6732	0.3143
No log	2.6154	170	0.3847	0.6901	0.3844
No log	2.6462	172	0.5298	0.7038	0.5295
No log	2.6769	174	0.5863	0.6870	0.5860
No log	2.7077	176	0.5109	0.7025	0.5106
No log	2.7385	178	0.3761	0.6916	0.3757
No log	2.7692	180	0.3138	0.6540	0.3135
No log	2.8	182	0.3097	0.6491	0.3093
No log	2.8308	184	0.3323	0.6756	0.3319
No log	2.8615	186	0.3514	0.6914	0.3510
No log	2.8923	188	0.3459	0.6780	0.3456
No log	2.9231	190	0.3481	0.6898	0.3478
No log	2.9538	192	0.3457	0.6902	0.3453
No log	2.9846	194	0.3362	0.6855	0.3359
No log	3.0154	196	0.3415	0.6766	0.3411
No log	3.0462	198	0.3545	0.6832	0.3542
No log	3.0769	200	0.3730	0.6756	0.3727
No log	3.1077	202	0.3424	0.6790	0.3421
No log	3.1385	204	0.3321	0.6623	0.3318
No log	3.1692	206	0.3539	0.6765	0.3536
No log	3.2	208	0.3660	0.6779	0.3657
No log	3.2308	210	0.3551	0.6668	0.3547
No log	3.2615	212	0.3455	0.6723	0.3452
No log	3.2923	214	0.3780	0.6753	0.3777
No log	3.3231	216	0.3938	0.6787	0.3935
No log	3.3538	218	0.4286	0.6828	0.4283
No log	3.3846	220	0.4587	0.7046	0.4585
No log	3.4154	222	0.4166	0.6859	0.4164
No log	3.4462	224	0.3735	0.6772	0.3732
No log	3.4769	226	0.3867	0.6964	0.3864
No log	3.5077	228	0.3875	0.6986	0.3872
No log	3.5385	230	0.4188	0.7029	0.4184
No log	3.5692	232	0.4099	0.7010	0.4095
No log	3.6	234	0.3635	0.6977	0.3632
No log	3.6308	236	0.3266	0.6611	0.3262
No log	3.6615	238	0.3292	0.6679	0.3289
No log	3.6923	240	0.3674	0.6886	0.3671
No log	3.7231	242	0.4326	0.7049	0.4323
No log	3.7538	244	0.4437	0.7103	0.4434
No log	3.7846	246	0.4098	0.6937	0.4095
No log	3.8154	248	0.3575	0.6741	0.3572
No log	3.8462	250	0.3383	0.6513	0.3380
No log	3.8769	252	0.3392	0.6597	0.3389
No log	3.9077	254	0.3602	0.6735	0.3599
No log	3.9385	256	0.3845	0.6878	0.3842
No log	3.9692	258	0.4114	0.6847	0.4111
No log	4.0	260	0.4175	0.6867	0.4172
No log	4.0308	262	0.4228	0.6914	0.4225
No log	4.0615	264	0.3927	0.6878	0.3924
No log	4.0923	266	0.3653	0.6754	0.3650
No log	4.1231	268	0.3506	0.6733	0.3502
No log	4.1538	270	0.3375	0.6655	0.3372
No log	4.1846	272	0.3434	0.6757	0.3431
No log	4.2154	274	0.3498	0.6776	0.3495
No log	4.2462	276	0.3708	0.6879	0.3705
No log	4.2769	278	0.3986	0.6930	0.3983
No log	4.3077	280	0.4160	0.7010	0.4156
No log	4.3385	282	0.4092	0.6916	0.4089
No log	4.3692	284	0.3913	0.6915	0.3910
No log	4.4	286	0.3804	0.6846	0.3801
No log	4.4308	288	0.3681	0.6801	0.3677
No log	4.4615	290	0.3650	0.6782	0.3647
No log	4.4923	292	0.3708	0.6789	0.3705
No log	4.5231	294	0.3927	0.6859	0.3923
No log	4.5538	296	0.4218	0.7032	0.4215
No log	4.5846	298	0.4256	0.7120	0.4253
No log	4.6154	300	0.4196	0.7025	0.4192
No log	4.6462	302	0.4135	0.7006	0.4131
No log	4.6769	304	0.4006	0.6976	0.4002
No log	4.7077	306	0.3885	0.7019	0.3881
No log	4.7385	308	0.3805	0.6907	0.3802
No log	4.7692	310	0.3689	0.6900	0.3686
No log	4.8	312	0.3638	0.6922	0.3635
No log	4.8308	314	0.3640	0.6940	0.3637
No log	4.8615	316	0.3680	0.6907	0.3676
No log	4.8923	318	0.3709	0.6888	0.3705
No log	4.9231	320	0.3737	0.6907	0.3733
No log	4.9538	322	0.3749	0.6907	0.3746
No log	4.9846	324	0.3754	0.6907	0.3751

Framework versions

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