DREsS_New_FineTuningBERT_noAug_content_fold0

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: 0.5233
• Qwk: 0.5801
• Mse: 0.7172
• Rmse: 0.8469

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	5.1075	0.0177	5.3990	2.3236
No log	0.16	4	4.2352	-0.0064	3.2374	1.7993
No log	0.24	6	3.6947	0.0	3.1768	1.7823
No log	0.32	8	3.2398	0.0	3.1768	1.7823
No log	0.4	10	2.8376	0.0	3.1768	1.7823
No log	0.48	12	2.3463	0.0	3.1768	1.7823
No log	0.56	14	1.8685	0.0841	1.3232	1.1503
No log	0.64	16	1.5608	0.0	1.2172	1.1033
No log	0.72	18	1.3205	0.0	1.2172	1.1033
No log	0.8	20	1.1278	0.0	1.2172	1.1033
No log	0.88	22	1.0043	0.0	1.2172	1.1033
No log	0.96	24	0.9065	0.0	1.2172	1.1033
No log	1.04	26	0.8708	0.2502	0.9293	0.9640
No log	1.12	28	1.0573	0.0	1.2172	1.1033
No log	1.2	30	0.9816	0.0	1.2172	1.1033
No log	1.28	32	0.7896	0.2414	0.9495	0.9744
No log	1.3600	34	0.8290	0.1829	1.0253	1.0125
No log	1.44	36	0.7749	0.2698	0.9141	0.9561
No log	1.52	38	0.7739	0.1317	1.0606	1.0299
No log	1.6	40	1.0019	0.1911	1.1768	1.0848
No log	1.6800	42	0.7266	0.2811	0.9444	0.9718
No log	1.76	44	0.6135	0.3519	0.8081	0.8989
No log	1.8400	46	0.5597	0.4611	0.7071	0.8409
No log	1.92	48	0.6197	0.5290	0.7020	0.8379
No log	2.0	50	0.5221	0.5436	0.6162	0.7850
No log	2.08	52	0.5470	0.4471	0.7323	0.8558
No log	2.16	54	0.5531	0.5747	0.6313	0.7946
No log	2.24	56	0.6038	0.5263	0.7576	0.8704
No log	2.32	58	0.5021	0.5700	0.6061	0.7785
No log	2.4	60	0.5007	0.5855	0.5960	0.7720
No log	2.48	62	0.6160	0.4976	0.8131	0.9017
No log	2.56	64	0.4988	0.5718	0.6111	0.7817
No log	2.64	66	0.6007	0.4822	0.6919	0.8318
No log	2.7200	68	0.5352	0.5189	0.6465	0.8040
No log	2.8	70	0.5053	0.5336	0.6465	0.8040
No log	2.88	72	0.4982	0.5508	0.6061	0.7785
No log	2.96	74	0.5094	0.5334	0.6212	0.7882
No log	3.04	76	0.5163	0.5034	0.6515	0.8072
No log	3.12	78	0.5094	0.5109	0.6465	0.8040
No log	3.2	80	0.5130	0.5304	0.6212	0.7882
No log	3.2800	82	0.4765	0.5466	0.6212	0.7882
No log	3.36	84	0.5211	0.5606	0.6465	0.8040
No log	3.44	86	0.4659	0.5812	0.6061	0.7785
No log	3.52	88	0.6374	0.4792	0.6919	0.8318
No log	3.6	90	0.7655	0.4143	0.7980	0.8933
No log	3.68	92	0.5553	0.5158	0.6616	0.8134
No log	3.76	94	0.5386	0.5599	0.6818	0.8257
No log	3.84	96	0.7501	0.4750	0.9091	0.9535
No log	3.92	98	0.5604	0.5536	0.6869	0.8288
No log	4.0	100	0.4712	0.5542	0.6212	0.7882
No log	4.08	102	0.6622	0.4304	0.7576	0.8704
No log	4.16	104	0.6070	0.4947	0.6970	0.8348
No log	4.24	106	0.4509	0.5488	0.6364	0.7977
No log	4.32	108	0.6277	0.5253	0.7576	0.8704
No log	4.4	110	0.6478	0.5124	0.7828	0.8848
No log	4.48	112	0.4801	0.5459	0.6566	0.8103
No log	4.5600	114	0.5560	0.5162	0.6566	0.8103
No log	4.64	116	0.6870	0.4407	0.8131	0.9017
No log	4.72	118	0.5983	0.4594	0.7626	0.8733
No log	4.8	120	0.4731	0.5713	0.6263	0.7914
No log	4.88	122	0.5001	0.5355	0.6667	0.8165
No log	4.96	124	0.4745	0.5706	0.6313	0.7946
No log	5.04	126	0.4990	0.5612	0.6566	0.8103
No log	5.12	128	0.5534	0.5441	0.7071	0.8409
No log	5.2	130	0.5040	0.5684	0.6768	0.8227
No log	5.28	132	0.4872	0.5583	0.6616	0.8134
No log	5.36	134	0.5380	0.5419	0.6970	0.8348
No log	5.44	136	0.4847	0.5730	0.6566	0.8103
No log	5.52	138	0.4993	0.6000	0.6515	0.8072
No log	5.6	140	0.6304	0.5267	0.8283	0.9101
No log	5.68	142	0.6081	0.5177	0.8434	0.9184
No log	5.76	144	0.4872	0.5813	0.6818	0.8257
No log	5.84	146	0.4733	0.6015	0.6061	0.7785
No log	5.92	148	0.4872	0.5597	0.6768	0.8227
No log	6.0	150	0.4705	0.5992	0.6263	0.7914
No log	6.08	152	0.4951	0.5942	0.6818	0.8257
No log	6.16	154	0.4845	0.6048	0.6515	0.8072
No log	6.24	156	0.4750	0.6010	0.6364	0.7977
No log	6.32	158	0.4721	0.6023	0.6212	0.7882
No log	6.4	160	0.4779	0.5901	0.6313	0.7946
No log	6.48	162	0.4737	0.6056	0.6162	0.7850
No log	6.5600	164	0.4911	0.5786	0.6818	0.8257
No log	6.64	166	0.5119	0.5981	0.6919	0.8318
No log	6.72	168	0.4850	0.5907	0.6616	0.8134
No log	6.8	170	0.4876	0.5758	0.6616	0.8134
No log	6.88	172	0.4876	0.5812	0.6667	0.8165
No log	6.96	174	0.5124	0.5773	0.7273	0.8528
No log	7.04	176	0.5593	0.5878	0.7525	0.8675
No log	7.12	178	0.5292	0.5869	0.7323	0.8558
No log	7.2	180	0.4961	0.5774	0.6818	0.8257
No log	7.28	182	0.4982	0.5713	0.6869	0.8288
No log	7.36	184	0.4955	0.5707	0.6970	0.8348
No log	7.44	186	0.5140	0.5642	0.7273	0.8528
No log	7.52	188	0.5146	0.5646	0.7222	0.8498
No log	7.6	190	0.4997	0.5896	0.6667	0.8165
No log	7.68	192	0.5022	0.5868	0.6667	0.8165
No log	7.76	194	0.5071	0.5826	0.6869	0.8288
No log	7.84	196	0.5128	0.5831	0.6818	0.8257
No log	7.92	198	0.5137	0.5626	0.6970	0.8348
No log	8.0	200	0.5171	0.5684	0.6970	0.8348
No log	8.08	202	0.5290	0.5811	0.7071	0.8409
No log	8.16	204	0.5391	0.5804	0.7172	0.8469
No log	8.24	206	0.5363	0.5858	0.7121	0.8439
No log	8.32	208	0.5241	0.5658	0.7323	0.8558
No log	8.4	210	0.5234	0.5765	0.6869	0.8288
No log	8.48	212	0.5254	0.5759	0.6919	0.8318
No log	8.56	214	0.5203	0.5605	0.7222	0.8498
No log	8.64	216	0.5275	0.5891	0.7020	0.8379
No log	8.72	218	0.5340	0.5868	0.7273	0.8528
No log	8.8	220	0.5268	0.5831	0.7121	0.8439
No log	8.88	222	0.5208	0.5708	0.7323	0.8558
No log	8.96	224	0.5198	0.5782	0.7020	0.8379
No log	9.04	226	0.5192	0.5724	0.7071	0.8409
No log	9.12	228	0.5177	0.5770	0.7172	0.8469
No log	9.2	230	0.5170	0.5748	0.7121	0.8439
No log	9.28	232	0.5168	0.5744	0.7172	0.8469
No log	9.36	234	0.5165	0.5748	0.7121	0.8439
No log	9.44	236	0.5159	0.5895	0.6919	0.8318
No log	9.52	238	0.5168	0.5858	0.7071	0.8409
No log	9.6	240	0.5183	0.5834	0.7071	0.8409
No log	9.68	242	0.5187	0.5834	0.7071	0.8409
No log	9.76	244	0.5200	0.5805	0.7121	0.8439
No log	9.84	246	0.5217	0.5800	0.7172	0.8469
No log	9.92	248	0.5227	0.5801	0.7172	0.8469
No log	10.0	250	0.5233	0.5801	0.7172	0.8469

Framework versions

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