Version_weird_ASAP_FineTuningBERT_AugV12_k1_task1_organization_k1_k1_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: 0.7629
• Qwk: 0.6053
• Mse: 0.7629
• Rmse: 0.8734

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: 64
• eval_batch_size: 64
• seed: 42
• optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 100

Training results

Training Loss	Epoch	Step	Validation Loss	Qwk	Mse	Rmse
No log	1.0	1	12.3902	-0.0005	12.3902	3.5200
No log	2.0	2	10.3294	0.0059	10.3294	3.2139
No log	3.0	3	9.1206	0.0054	9.1206	3.0200
No log	4.0	4	8.4621	0.0054	8.4621	2.9090
No log	5.0	5	7.7304	0.0018	7.7304	2.7804
No log	6.0	6	6.9409	0.0	6.9409	2.6346
No log	7.0	7	6.1525	0.0169	6.1525	2.4804
No log	8.0	8	5.4167	0.0208	5.4167	2.3274
No log	9.0	9	4.7812	0.0153	4.7812	2.1866
No log	10.0	10	4.2472	0.0153	4.2472	2.0609
No log	11.0	11	3.7737	0.0153	3.7737	1.9426
No log	12.0	12	3.3622	0.0115	3.3622	1.8336
No log	13.0	13	3.0331	0.0115	3.0331	1.7416
No log	14.0	14	2.6461	0.0117	2.6461	1.6267
No log	15.0	15	2.2819	0.1234	2.2819	1.5106
No log	16.0	16	2.0168	0.1133	2.0168	1.4202
No log	17.0	17	1.7730	0.0715	1.7730	1.3316
No log	18.0	18	1.5971	0.0520	1.5971	1.2638
No log	19.0	19	1.4253	0.0520	1.4253	1.1939
No log	20.0	20	1.2575	0.0520	1.2575	1.1214
No log	21.0	21	1.1046	0.0520	1.1046	1.0510
No log	22.0	22	0.9880	0.0618	0.9880	0.9940
No log	23.0	23	0.8958	0.0618	0.8958	0.9464
No log	24.0	24	0.8295	0.2458	0.8295	0.9108
No log	25.0	25	0.8132	0.2265	0.8132	0.9018
No log	26.0	26	0.7176	0.3850	0.7176	0.8471
No log	27.0	27	0.7161	0.4544	0.7161	0.8463
No log	28.0	28	0.6742	0.4952	0.6742	0.8211
No log	29.0	29	0.6074	0.4108	0.6074	0.7793
No log	30.0	30	0.6170	0.3583	0.6170	0.7855
No log	31.0	31	0.5919	0.3712	0.5919	0.7693
No log	32.0	32	0.5195	0.4543	0.5195	0.7207
No log	33.0	33	0.5007	0.4705	0.5007	0.7076
No log	34.0	34	0.5175	0.4440	0.5175	0.7194
No log	35.0	35	0.5095	0.4590	0.5095	0.7138
No log	36.0	36	0.4991	0.4768	0.4991	0.7065
No log	37.0	37	0.4994	0.5020	0.4994	0.7066
No log	38.0	38	0.5234	0.4948	0.5234	0.7235
No log	39.0	39	0.5398	0.5474	0.5398	0.7347
No log	40.0	40	0.5243	0.5971	0.5243	0.7241
No log	41.0	41	0.4788	0.6236	0.4788	0.6919
No log	42.0	42	0.4973	0.6310	0.4973	0.7052
No log	43.0	43	0.6258	0.5767	0.6258	0.7911
No log	44.0	44	0.6556	0.5606	0.6556	0.8097
No log	45.0	45	0.5658	0.6284	0.5658	0.7522
No log	46.0	46	0.5147	0.6417	0.5147	0.7175
No log	47.0	47	0.5682	0.6278	0.5682	0.7538
No log	48.0	48	0.7327	0.5414	0.7327	0.8560
No log	49.0	49	0.7759	0.5427	0.7759	0.8809
No log	50.0	50	0.6243	0.6153	0.6243	0.7901
No log	51.0	51	0.4932	0.6668	0.4932	0.7023
No log	52.0	52	0.4874	0.6632	0.4874	0.6981
No log	53.0	53	0.5617	0.6571	0.5617	0.7495
No log	54.0	54	0.8427	0.5468	0.8427	0.9180
No log	55.0	55	0.9615	0.5312	0.9615	0.9805
No log	56.0	56	0.8340	0.5581	0.8340	0.9132
No log	57.0	57	0.5854	0.6567	0.5854	0.7651
No log	58.0	58	0.5087	0.6438	0.5087	0.7132
No log	59.0	59	0.5314	0.6397	0.5314	0.7290
No log	60.0	60	0.5162	0.6414	0.5162	0.7184
No log	61.0	61	0.5543	0.6591	0.5543	0.7445
No log	62.0	62	0.8115	0.5666	0.8115	0.9008
No log	63.0	63	0.9717	0.5242	0.9717	0.9857
No log	64.0	64	0.9490	0.5292	0.9490	0.9742
No log	65.0	65	0.7830	0.5738	0.7830	0.8849
No log	66.0	66	0.5852	0.6586	0.5852	0.7650
No log	67.0	67	0.5275	0.6670	0.5275	0.7263
No log	68.0	68	0.5212	0.6703	0.5212	0.7220
No log	69.0	69	0.5429	0.6670	0.5429	0.7368
No log	70.0	70	0.6495	0.6234	0.6495	0.8059
No log	71.0	71	0.7158	0.6080	0.7158	0.8460
No log	72.0	72	0.6933	0.6043	0.6933	0.8327
No log	73.0	73	0.7384	0.6015	0.7384	0.8593
No log	74.0	74	0.6809	0.6132	0.6809	0.8252
No log	75.0	75	0.6062	0.6338	0.6062	0.7786
No log	76.0	76	0.5985	0.6353	0.5985	0.7736
No log	77.0	77	0.6443	0.6217	0.6443	0.8027
No log	78.0	78	0.6265	0.6279	0.6265	0.7915
No log	79.0	79	0.5696	0.6464	0.5696	0.7547
No log	80.0	80	0.5210	0.6663	0.5210	0.7218
No log	81.0	81	0.5173	0.6671	0.5173	0.7192
No log	82.0	82	0.5259	0.6633	0.5259	0.7252
No log	83.0	83	0.5527	0.6653	0.5527	0.7435
No log	84.0	84	0.6141	0.6471	0.6141	0.7836
No log	85.0	85	0.7278	0.6118	0.7278	0.8531
No log	86.0	86	0.7962	0.6064	0.7962	0.8923
No log	87.0	87	0.8039	0.6014	0.8039	0.8966
No log	88.0	88	0.7629	0.6053	0.7629	0.8734

Framework versions

• Transformers 4.47.0
• Pytorch 2.5.1+cu121
• Datasets 3.2.0
• Tokenizers 0.21.0