DREsS_New_FineTuningBERT_noAug_content_fold1

This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.5741
• Qwk: 0.4622
• Mse: 0.7677
• Rmse: 0.8762

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: 32
• eval_batch_size: 32
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Qwk	Mse	Rmse
No log	0.08	2	9.1092	-0.0008	6.9343	2.6333
No log	0.16	4	6.3998	0.0	6.8990	2.6266
No log	0.24	6	4.9524	0.0255	5.3889	2.3214
No log	0.32	8	3.6968	0.0	2.9697	1.7233
No log	0.4	10	2.7728	0.0	2.9697	1.7233
No log	0.48	12	2.0111	0.0071	2.9293	1.7115
No log	0.56	14	1.5350	0.0321	1.0354	1.0175
No log	0.64	16	1.2440	0.0	1.0404	1.0200
No log	0.72	18	0.9183	0.0	1.0404	1.0200
No log	0.8	20	0.9929	0.0	1.0404	1.0200
No log	0.88	22	0.7856	0.0570	0.9848	0.9924
No log	0.96	24	0.7691	0.1791	0.8737	0.9347
No log	1.04	26	0.7670	0.1882	0.8788	0.9374
No log	1.12	28	0.7768	0.1300	0.9545	0.9770
No log	1.2	30	0.7290	0.1977	0.8636	0.9293
No log	1.28	32	0.8065	0.2317	0.8485	0.9211
No log	1.3600	34	0.7139	0.2317	0.8485	0.9211
No log	1.44	36	0.6686	0.2999	0.7626	0.8733
No log	1.52	38	0.6512	0.2995	0.7626	0.8733
No log	1.6	40	0.6301	0.3390	0.7626	0.8733
No log	1.6800	42	0.9919	0.2546	1.1010	1.0493
No log	1.76	44	0.6857	0.3526	0.8182	0.9045
No log	1.8400	46	0.8041	0.2448	0.8485	0.9211
No log	1.92	48	0.6663	0.3431	0.7576	0.8704
No log	2.0	50	0.8904	0.2805	0.9949	0.9975
No log	2.08	52	1.0885	0.2258	1.1566	1.0754
No log	2.16	54	0.7272	0.2415	0.9343	0.9666
No log	2.24	56	0.6595	0.3145	0.7475	0.8646
No log	2.32	58	0.8234	0.2284	0.8485	0.9211
No log	2.4	60	0.6706	0.2842	0.7828	0.8848
No log	2.48	62	0.6048	0.3277	0.7626	0.8733
No log	2.56	64	0.6769	0.2710	0.8788	0.9374
No log	2.64	66	0.5984	0.3432	0.7929	0.8905
No log	2.7200	68	0.6071	0.3681	0.7121	0.8439
No log	2.8	70	0.5862	0.3540	0.7727	0.8790
No log	2.88	72	0.6734	0.4115	0.7778	0.8819
No log	2.96	74	0.7064	0.4048	0.8131	0.9017
No log	3.04	76	0.5836	0.3665	0.7778	0.8819
No log	3.12	78	0.5746	0.3582	0.7626	0.8733
No log	3.2	80	0.5729	0.3891	0.7828	0.8848
No log	3.2800	82	0.5778	0.3832	0.8232	0.9073
No log	3.36	84	0.6066	0.4079	0.8182	0.9045
No log	3.44	86	0.5768	0.3868	0.8788	0.9374
No log	3.52	88	0.5986	0.3841	0.8737	0.9347
No log	3.6	90	0.5812	0.3886	0.8434	0.9184
No log	3.68	92	0.5599	0.3864	0.7980	0.8933
No log	3.76	94	0.5448	0.3876	0.7677	0.8762
No log	3.84	96	0.5385	0.4216	0.7576	0.8704
No log	3.92	98	0.5421	0.4195	0.7828	0.8848
No log	4.0	100	0.5723	0.4284	0.8081	0.8989
No log	4.08	102	0.5689	0.4172	0.8434	0.9184
No log	4.16	104	0.5687	0.4537	0.7980	0.8933
No log	4.24	106	0.6490	0.4412	0.8636	0.9293
No log	4.32	108	0.5997	0.4478	0.8182	0.9045
No log	4.4	110	0.6553	0.4329	0.8990	0.9482
No log	4.48	112	0.7496	0.3984	1.0404	1.0200
No log	4.5600	114	0.6055	0.4078	0.8081	0.8989
No log	4.64	116	0.5648	0.4118	0.7525	0.8675
No log	4.72	118	0.5735	0.4029	0.7626	0.8733
No log	4.8	120	0.5428	0.4175	0.7273	0.8528
No log	4.88	122	0.6139	0.4001	0.7828	0.8848
No log	4.96	124	0.5677	0.4009	0.7778	0.8819
No log	5.04	126	0.5553	0.4495	0.7626	0.8733
No log	5.12	128	0.5605	0.4422	0.7828	0.8848
No log	5.2	130	0.5582	0.4308	0.7374	0.8587
No log	5.28	132	0.6220	0.4172	0.8030	0.8961
No log	5.36	134	0.5612	0.4489	0.7323	0.8558
No log	5.44	136	0.5527	0.4514	0.7475	0.8646
No log	5.52	138	0.5500	0.4668	0.7273	0.8528
No log	5.6	140	0.5414	0.4496	0.7525	0.8675
No log	5.68	142	0.5543	0.4611	0.7374	0.8587
No log	5.76	144	0.5463	0.4507	0.7374	0.8587
No log	5.84	146	0.5468	0.4380	0.7475	0.8646
No log	5.92	148	0.5562	0.4462	0.7323	0.8558
No log	6.0	150	0.5606	0.4306	0.7475	0.8646
No log	6.08	152	0.5608	0.4523	0.7475	0.8646
No log	6.16	154	0.5649	0.4413	0.7677	0.8762
No log	6.24	156	0.5630	0.4257	0.7727	0.8790
No log	6.32	158	0.5773	0.4044	0.8030	0.8961
No log	6.4	160	0.5512	0.4613	0.7424	0.8616
No log	6.48	162	0.5501	0.4650	0.7475	0.8646
No log	6.5600	164	0.5596	0.4446	0.7525	0.8675
No log	6.64	166	0.6063	0.3743	0.8990	0.9482
No log	6.72	168	0.6065	0.3709	0.9293	0.9640
No log	6.8	170	0.5667	0.4523	0.7980	0.8933
No log	6.88	172	0.5679	0.4704	0.7929	0.8905
No log	6.96	174	0.6171	0.4684	0.8283	0.9101
No log	7.04	176	0.5885	0.4524	0.8283	0.9101
No log	7.12	178	0.5698	0.4521	0.7929	0.8905
No log	7.2	180	0.6057	0.3937	0.9141	0.9561
No log	7.28	182	0.5793	0.4154	0.8232	0.9073
No log	7.36	184	0.5712	0.4808	0.7576	0.8704
No log	7.44	186	0.5876	0.4669	0.8131	0.9017
No log	7.52	188	0.5686	0.4845	0.7424	0.8616
No log	7.6	190	0.5875	0.4332	0.8283	0.9101
No log	7.68	192	0.6144	0.3931	0.9091	0.9535
No log	7.76	194	0.5953	0.4109	0.8737	0.9347
No log	7.84	196	0.5717	0.4698	0.7727	0.8790
No log	7.92	198	0.5649	0.4750	0.7475	0.8646
No log	8.0	200	0.5616	0.4782	0.7475	0.8646
No log	8.08	202	0.5676	0.4618	0.7727	0.8790
No log	8.16	204	0.5853	0.4232	0.8434	0.9184
No log	8.24	206	0.5688	0.4418	0.8131	0.9017
No log	8.32	208	0.5624	0.4787	0.7374	0.8587
No log	8.4	210	0.5622	0.4618	0.7727	0.8790
No log	8.48	212	0.5715	0.4393	0.8131	0.9017
No log	8.56	214	0.5862	0.4355	0.8384	0.9156
No log	8.64	216	0.5744	0.4437	0.8131	0.9017
No log	8.72	218	0.5538	0.4564	0.7576	0.8704
No log	8.8	220	0.5537	0.4630	0.7576	0.8704
No log	8.88	222	0.5537	0.4497	0.7879	0.8876
No log	8.96	224	0.5531	0.4600	0.7576	0.8704
No log	9.04	226	0.5539	0.4564	0.7576	0.8704
No log	9.12	228	0.5559	0.4562	0.7525	0.8675
No log	9.2	230	0.5544	0.4636	0.7475	0.8646
No log	9.28	232	0.5553	0.4636	0.7475	0.8646
No log	9.36	234	0.5571	0.4636	0.7475	0.8646
No log	9.44	236	0.5616	0.4677	0.7475	0.8646
No log	9.52	238	0.5695	0.4618	0.7626	0.8733
No log	9.6	240	0.5770	0.4467	0.8081	0.8989
No log	9.68	242	0.5812	0.4406	0.8232	0.9073
No log	9.76	244	0.5790	0.4398	0.8182	0.9045
No log	9.84	246	0.5755	0.4588	0.7727	0.8790
No log	9.92	248	0.5745	0.4622	0.7677	0.8762
No log	10.0	250	0.5741	0.4622	0.7677	0.8762

Framework versions

• Transformers 4.44.2
• Pytorch 2.4.0+cu118
• Datasets 2.21.0
• Tokenizers 0.19.1