DREsS_New_FineTuningBERT_noAug_organization_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: 0.5722
• Qwk: 0.4787
• Mse: 0.6667
• Rmse: 0.8165

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	9.2574	-0.0007	7.1313	2.6705
No log	0.16	4	6.5181	0.0	7.0960	2.6638
No log	0.24	6	5.0527	0.0320	5.3283	2.3083
No log	0.32	8	3.7636	0.0	3.0556	1.7480
No log	0.4	10	2.8133	0.0	3.0556	1.7480
No log	0.48	12	2.0869	0.0028	2.9646	1.7218
No log	0.56	14	1.5945	0.0246	1.0404	1.0200
No log	0.64	16	1.2679	0.0	1.0152	1.0075
No log	0.72	18	0.9060	0.0	1.0152	1.0075
No log	0.8	20	0.9331	0.0	1.0152	1.0075
No log	0.88	22	0.7971	-0.0008	1.0152	1.0075
No log	0.96	24	0.7651	0.0498	0.9545	0.9770
No log	1.04	26	0.7685	0.0447	0.9343	0.9666
No log	1.12	28	0.7323	0.1515	0.8333	0.9129
No log	1.2	30	0.7270	0.1632	0.8384	0.9156
No log	1.28	32	0.7057	0.1594	0.8384	0.9156
No log	1.3600	34	0.6702	0.2726	0.7172	0.8469
No log	1.44	36	0.7520	0.1280	0.8535	0.9239
No log	1.52	38	0.6404	0.3189	0.6717	0.8196
No log	1.6	40	0.6377	0.3237	0.7172	0.8469
No log	1.6800	42	0.6305	0.3589	0.6919	0.8318
No log	1.76	44	0.6685	0.3400	0.6717	0.8196
No log	1.8400	46	0.6241	0.3908	0.6566	0.8103
No log	1.92	48	0.6560	0.3744	0.7222	0.8498
No log	2.0	50	0.6008	0.3946	0.6414	0.8009
No log	2.08	52	0.5809	0.4248	0.6010	0.7752
No log	2.16	54	0.5955	0.3705	0.6414	0.8009
No log	2.24	56	0.5878	0.3811	0.6566	0.8103
No log	2.32	58	0.5693	0.3726	0.6515	0.8072
No log	2.4	60	0.5875	0.3981	0.6061	0.7785
No log	2.48	62	0.5587	0.4076	0.6010	0.7752
No log	2.56	64	0.5643	0.3711	0.6515	0.8072
No log	2.64	66	0.5692	0.3998	0.6263	0.7914
No log	2.7200	68	0.6254	0.3491	0.6414	0.8009
No log	2.8	70	0.5697	0.4156	0.6162	0.7850
No log	2.88	72	0.7169	0.3683	0.7828	0.8848
No log	2.96	74	0.6483	0.3540	0.7525	0.8675
No log	3.04	76	0.5623	0.4327	0.5909	0.7687
No log	3.12	78	0.5654	0.4067	0.6061	0.7785
No log	3.2	80	0.5846	0.3775	0.6667	0.8165
No log	3.2800	82	0.5741	0.3961	0.6515	0.8072
No log	3.36	84	0.6706	0.3985	0.8131	0.9017
No log	3.44	86	0.7498	0.3612	0.9697	0.9847
No log	3.52	88	0.5872	0.4058	0.6717	0.8196
No log	3.6	90	0.6218	0.3634	0.7020	0.8379
No log	3.68	92	0.6235	0.3864	0.6768	0.8227
No log	3.76	94	0.5675	0.4430	0.5859	0.7654
No log	3.84	96	0.6350	0.4274	0.6616	0.8134
No log	3.92	98	0.5784	0.4439	0.5960	0.7720
No log	4.0	100	0.5699	0.4284	0.6364	0.7977
No log	4.08	102	0.5699	0.4074	0.6667	0.8165
No log	4.16	104	0.6042	0.4744	0.6515	0.8072
No log	4.24	106	0.5937	0.4827	0.6263	0.7914
No log	4.32	108	0.6246	0.4437	0.6667	0.8165
No log	4.4	110	0.6078	0.4426	0.6515	0.8072
No log	4.48	112	0.5809	0.4467	0.6263	0.7914
No log	4.5600	114	0.5721	0.4515	0.6162	0.7850
No log	4.64	116	0.5989	0.4618	0.5808	0.7621
No log	4.72	118	0.5891	0.4569	0.5808	0.7621
No log	4.8	120	0.5412	0.4268	0.6162	0.7850
No log	4.88	122	0.5326	0.4172	0.6212	0.7882
No log	4.96	124	0.5425	0.4322	0.5909	0.7687
No log	5.04	126	0.5368	0.4275	0.5960	0.7720
No log	5.12	128	0.5767	0.4557	0.5808	0.7621
No log	5.2	130	0.5893	0.4706	0.5960	0.7720
No log	5.28	132	0.5327	0.4499	0.6162	0.7850
No log	5.36	134	0.5192	0.4500	0.6111	0.7817
No log	5.44	136	0.5348	0.4467	0.6364	0.7977
No log	5.52	138	0.5445	0.4605	0.6414	0.8009
No log	5.6	140	0.5330	0.4342	0.6515	0.8072
No log	5.68	142	0.5417	0.4476	0.6414	0.8009
No log	5.76	144	0.5361	0.4482	0.6414	0.8009
No log	5.84	146	0.5338	0.4559	0.6111	0.7817
No log	5.92	148	0.5723	0.4569	0.6515	0.8072
No log	6.0	150	0.5722	0.4561	0.6414	0.8009
No log	6.08	152	0.5411	0.4744	0.6111	0.7817
No log	6.16	154	0.5518	0.4827	0.6111	0.7817
No log	6.24	156	0.5744	0.4625	0.6818	0.8257
No log	6.32	158	0.5466	0.4706	0.6414	0.8009
No log	6.4	160	0.5635	0.4747	0.6515	0.8072
No log	6.48	162	0.6154	0.4637	0.7273	0.8528
No log	6.5600	164	0.5657	0.4905	0.6212	0.7882
No log	6.64	166	0.5337	0.4386	0.6414	0.8009
No log	6.72	168	0.5368	0.4336	0.6414	0.8009
No log	6.8	170	0.5961	0.4732	0.6465	0.8040
No log	6.88	172	0.6069	0.4608	0.6667	0.8165
No log	6.96	174	0.5405	0.4648	0.6162	0.7850
No log	7.04	176	0.5256	0.4267	0.6212	0.7882
No log	7.12	178	0.5380	0.4732	0.6010	0.7752
No log	7.2	180	0.5622	0.4862	0.6010	0.7752
No log	7.28	182	0.5443	0.4820	0.6010	0.7752
No log	7.36	184	0.5554	0.4779	0.6212	0.7882
No log	7.44	186	0.5733	0.4946	0.6111	0.7817
No log	7.52	188	0.5668	0.4946	0.6162	0.7850
No log	7.6	190	0.5669	0.4905	0.6162	0.7850
No log	7.68	192	0.5537	0.4907	0.6212	0.7882
No log	7.76	194	0.5629	0.4905	0.6414	0.8009
No log	7.84	196	0.5681	0.4903	0.6515	0.8072
No log	7.92	198	0.5569	0.4903	0.6465	0.8040
No log	8.0	200	0.5442	0.4950	0.6212	0.7882
No log	8.08	202	0.5508	0.5029	0.6111	0.7817
No log	8.16	204	0.5570	0.4905	0.6212	0.7882
No log	8.24	206	0.5577	0.4781	0.6313	0.7946
No log	8.32	208	0.5650	0.4778	0.6263	0.7914
No log	8.4	210	0.5861	0.4485	0.6717	0.8196
No log	8.48	212	0.5741	0.4362	0.6869	0.8288
No log	8.56	214	0.5588	0.4612	0.6465	0.8040
No log	8.64	216	0.5561	0.4660	0.6465	0.8040
No log	8.72	218	0.5462	0.4747	0.6212	0.7882
No log	8.8	220	0.5471	0.4747	0.6212	0.7882
No log	8.88	222	0.5648	0.4746	0.6515	0.8072
No log	8.96	224	0.5879	0.4706	0.6869	0.8288
No log	9.04	226	0.5970	0.4591	0.7121	0.8439
No log	9.12	228	0.5909	0.4629	0.7020	0.8379
No log	9.2	230	0.5663	0.4623	0.6717	0.8196
No log	9.28	232	0.5486	0.4875	0.6263	0.7914
No log	9.36	234	0.5471	0.4834	0.6263	0.7914
No log	9.44	236	0.5521	0.4875	0.6313	0.7946
No log	9.52	238	0.5611	0.4753	0.6616	0.8134
No log	9.6	240	0.5736	0.4787	0.6667	0.8165
No log	9.68	242	0.5798	0.4587	0.6919	0.8318
No log	9.76	244	0.5779	0.4708	0.6818	0.8257
No log	9.84	246	0.5751	0.4788	0.6717	0.8196
No log	9.92	248	0.5732	0.4788	0.6717	0.8196
No log	10.0	250	0.5722	0.4787	0.6667	0.8165

Framework versions

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