Version12NewTestASAP_FineTuningBERT_AugV12_k1_task1_organization_k1_k1_fold2

genki10/Version12NewTestASAP_FineTuningBERT_AugV12_k1_task1_organization_k1_k1_fold2

Version12NewTestASAP_FineTuningBERT_AugV12_k1_task1_organization_k1_k1_fold2 is a text classification model from genki10. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as apache-2.0.

should probably proofread and complete it, then remove this comment. --

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At a glance

Task: Text Classification
Library: transformers
License: apache-2.0
Model type: bert
Access: Public
Created: Mar 14, 2025
Updated: Mar 14, 2025
SHA: 84a323d3

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Base models

Model card

From the Hugging Face model README

Version12NewTestASAP_FineTuningBERT_AugV12_k1_task1_organization_k1_k1_fold2

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: 1.1423
Qwk: 0.4886
Mse: 1.1423
Rmse: 1.0688

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	2	12.7758	0.0	12.7758	3.5743
No log	2.0	4	9.4024	0.0	9.4024	3.0663
No log	3.0	6	7.4761	0.0	7.4761	2.7342
No log	4.0	8	6.4438	0.0135	6.4438	2.5385
No log	5.0	10	4.8179	0.0	4.8179	2.1950
No log	6.0	12	3.7383	0.0	3.7383	1.9335
No log	7.0	14	2.9383	0.0645	2.9383	1.7142
No log	8.0	16	2.3887	0.0092	2.3887	1.5455
No log	9.0	18	1.9512	0.0	1.9512	1.3969
No log	10.0	20	1.7890	0.0	1.7890	1.3375
No log	11.0	22	1.4377	0.0	1.4377	1.1990
No log	12.0	24	1.5496	0.0246	1.5496	1.2448
No log	13.0	26	1.2318	0.0870	1.2318	1.1099
No log	14.0	28	1.1295	0.2101	1.1295	1.0628
No log	15.0	30	1.2301	0.1956	1.2301	1.1091
No log	16.0	32	1.2839	0.1815	1.2839	1.1331
No log	17.0	34	1.2443	0.2308	1.2443	1.1155
No log	18.0	36	1.2539	0.3245	1.2539	1.1198
No log	19.0	38	1.1461	0.3424	1.1461	1.0705
No log	20.0	40	1.0980	0.3433	1.0980	1.0479
No log	21.0	42	1.2020	0.3691	1.2020	1.0964
No log	22.0	44	1.1797	0.4133	1.1797	1.0862
No log	23.0	46	1.3743	0.3559	1.3743	1.1723
No log	24.0	48	1.5428	0.3021	1.5428	1.2421
No log	25.0	50	1.2432	0.3953	1.2432	1.1150
No log	26.0	52	1.9573	0.2650	1.9573	1.3990
No log	27.0	54	1.6374	0.2796	1.6374	1.2796
No log	28.0	56	1.0640	0.4951	1.0640	1.0315
No log	29.0	58	1.1070	0.4730	1.1070	1.0521
No log	30.0	60	1.4110	0.3440	1.4110	1.1878
No log	31.0	62	1.3251	0.3550	1.3251	1.1511
No log	32.0	64	1.1960	0.4179	1.1960	1.0936
No log	33.0	66	1.1994	0.4130	1.1994	1.0952
No log	34.0	68	1.5155	0.3435	1.5155	1.2311
No log	35.0	70	1.1175	0.5044	1.1175	1.0571
No log	36.0	72	1.0506	0.4212	1.0506	1.0250
No log	37.0	74	0.9709	0.4637	0.9709	0.9853
No log	38.0	76	1.1467	0.5114	1.1467	1.0708
No log	39.0	78	1.1030	0.5041	1.1030	1.0502
No log	40.0	80	1.1483	0.5	1.1483	1.0716
No log	41.0	82	1.3707	0.3697	1.3707	1.1708
No log	42.0	84	1.2051	0.4615	1.2051	1.0978
No log	43.0	86	0.9652	0.4448	0.9652	0.9824
No log	44.0	88	0.9773	0.4718	0.9773	0.9886
No log	45.0	90	1.0121	0.5260	1.0121	1.0061
No log	46.0	92	1.1051	0.4731	1.1051	1.0512
No log	47.0	94	0.9189	0.5503	0.9189	0.9586
No log	48.0	96	0.9644	0.4762	0.9644	0.9820
No log	49.0	98	0.9217	0.5668	0.9217	0.9601
No log	50.0	100	0.9864	0.5301	0.9864	0.9932
No log	51.0	102	0.9463	0.5287	0.9463	0.9728
No log	52.0	104	0.9571	0.5287	0.9571	0.9783
No log	53.0	106	0.9362	0.5595	0.9362	0.9676
No log	54.0	108	0.9264	0.5543	0.9264	0.9625
No log	55.0	110	0.9236	0.5927	0.9236	0.9610
No log	56.0	112	0.9123	0.5905	0.9123	0.9552
No log	57.0	114	1.0263	0.4775	1.0263	1.0131
No log	58.0	116	1.0270	0.4806	1.0270	1.0134
No log	59.0	118	0.9199	0.5642	0.9199	0.9591
No log	60.0	120	0.9344	0.5652	0.9344	0.9667
No log	61.0	122	0.9215	0.5775	0.9215	0.9599
No log	62.0	124	0.9198	0.5795	0.9198	0.9590
No log	63.0	126	0.9136	0.5695	0.9136	0.9558
No log	64.0	128	0.9221	0.5677	0.9221	0.9603
No log	65.0	130	0.9444	0.5422	0.9444	0.9718
No log	66.0	132	0.8932	0.5778	0.8932	0.9451
No log	67.0	134	0.8888	0.5575	0.8888	0.9428
No log	68.0	136	0.9171	0.5255	0.9171	0.9576
No log	69.0	138	1.1725	0.4419	1.1725	1.0828
No log	70.0	140	1.2067	0.4566	1.2067	1.0985
No log	71.0	142	1.0555	0.4867	1.0555	1.0274
No log	72.0	144	1.0039	0.5512	1.0039	1.0020
No log	73.0	146	1.0287	0.5652	1.0287	1.0142
No log	74.0	148	1.1542	0.4696	1.1542	1.0743
No log	75.0	150	1.1423	0.4886	1.1423	1.0688

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0

Task: Text Classification
Library: transformers
Type: bert
License: apache-2.0
Created: Mar 14, 2025
Updated: Mar 14, 2025