Version12LowDevASAP_FineTuningBERT_AugV12_k3_task1_organization_k3_k3_fold0

genki10/Version12LowDevASAP_FineTuningBERT_AugV12_k3_task1_organization_k3_k3_fold0

Version12LowDevASAP_FineTuningBERT_AugV12_k3_task1_organization_k3_k3_fold0 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 10, 2025
Updated: Mar 10, 2025
SHA: fc8f5fd8

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Base models

Model card

From the Hugging Face model README

Version12LowDevASAP_FineTuningBERT_AugV12_k3_task1_organization_k3_k3_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: 0.5113
Qwk: 0.6617
Mse: 0.5113
Rmse: 0.7151

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	10.5584	0.0	10.5584	3.2494
No log	2.0	2	9.4523	0.0	9.4523	3.0745
No log	3.0	3	8.5498	0.0	8.5498	2.9240
No log	4.0	4	7.9987	0.0	7.9987	2.8282
No log	5.0	5	7.7112	0.0	7.7112	2.7769
No log	6.0	6	7.3003	0.0	7.3003	2.7019
No log	7.0	7	6.7938	0.0	6.7938	2.6065
No log	8.0	8	6.3542	0.0257	6.3542	2.5208
No log	9.0	9	5.9320	0.0	5.9320	2.4356
No log	10.0	10	5.4938	0.0	5.4938	2.3439
No log	11.0	11	5.0637	0.0	5.0637	2.2503
No log	12.0	12	4.6637	0.0	4.6637	2.1596
No log	13.0	13	4.2789	0.0	4.2789	2.0685
No log	14.0	14	3.8970	0.0	3.8970	1.9741
No log	15.0	15	3.5273	0.0	3.5273	1.8781
No log	16.0	16	3.1802	0.0	3.1802	1.7833
No log	17.0	17	2.8527	0.0	2.8527	1.6890
No log	18.0	18	2.5391	0.0582	2.5391	1.5935
No log	19.0	19	2.2560	0.0	2.2560	1.5020
No log	20.0	20	1.9994	0.0	1.9994	1.4140
No log	21.0	21	1.7685	0.0	1.7685	1.3299
No log	22.0	22	1.5983	0.0	1.5983	1.2643
No log	23.0	23	1.4537	0.0	1.4537	1.2057
No log	24.0	24	1.3359	0.0	1.3359	1.1558
No log	25.0	25	1.2240	0.0	1.2240	1.1063
No log	26.0	26	1.0979	0.0	1.0979	1.0478
No log	27.0	27	1.0103	0.0	1.0103	1.0052
No log	28.0	28	0.9436	0.2389	0.9436	0.9714
No log	29.0	29	0.8866	0.3718	0.8866	0.9416
No log	30.0	30	0.8383	0.2407	0.8383	0.9156
No log	31.0	31	0.7994	0.1900	0.7994	0.8941
No log	32.0	32	0.7597	0.1900	0.7597	0.8716
No log	33.0	33	0.7180	0.2380	0.7180	0.8473
No log	34.0	34	0.6814	0.2525	0.6814	0.8255
No log	35.0	35	0.6670	0.2380	0.6670	0.8167
No log	36.0	36	0.6500	0.2380	0.6500	0.8062
No log	37.0	37	0.6064	0.3369	0.6064	0.7787
No log	38.0	38	0.5880	0.3369	0.5880	0.7668
No log	39.0	39	0.5908	0.2525	0.5908	0.7686
No log	40.0	40	0.5912	0.2525	0.5912	0.7689
No log	41.0	41	0.5402	0.3740	0.5402	0.7350
No log	42.0	42	0.5322	0.3740	0.5322	0.7295
No log	43.0	43	0.5282	0.3826	0.5282	0.7268
No log	44.0	44	0.5647	0.4569	0.5647	0.7515
No log	45.0	45	0.5276	0.5139	0.5276	0.7264
No log	46.0	46	0.5042	0.4839	0.5042	0.7101
No log	47.0	47	0.5081	0.5427	0.5081	0.7128
No log	48.0	48	0.6033	0.5610	0.6033	0.7768
No log	49.0	49	0.5776	0.5815	0.5776	0.7600
No log	50.0	50	0.5046	0.5860	0.5046	0.7103
No log	51.0	51	0.5134	0.5841	0.5134	0.7165
No log	52.0	52	0.5176	0.6040	0.5176	0.7194
No log	53.0	53	0.6006	0.6552	0.6006	0.7750
No log	54.0	54	0.5759	0.6763	0.5759	0.7589
No log	55.0	55	0.5073	0.6084	0.5073	0.7123
No log	56.0	56	0.5051	0.6084	0.5051	0.7107
No log	57.0	57	0.5638	0.6845	0.5638	0.7509
No log	58.0	58	0.7618	0.5569	0.7618	0.8728
No log	59.0	59	0.7720	0.5427	0.7720	0.8787
No log	60.0	60	0.6001	0.6690	0.6001	0.7747
No log	61.0	61	0.5119	0.6653	0.5119	0.7155
No log	62.0	62	0.5158	0.6715	0.5158	0.7182
No log	63.0	63	0.5942	0.6912	0.5942	0.7708
No log	64.0	64	0.6808	0.6226	0.6808	0.8251
No log	65.0	65	0.6208	0.6511	0.6208	0.7879
No log	66.0	66	0.5213	0.6592	0.5213	0.7220
No log	67.0	67	0.5102	0.6374	0.5102	0.7142
No log	68.0	68	0.5156	0.6587	0.5156	0.7180
No log	69.0	69	0.5427	0.6551	0.5427	0.7367
No log	70.0	70	0.6670	0.6319	0.6670	0.8167
No log	71.0	71	0.6846	0.6032	0.6846	0.8274
No log	72.0	72	0.5870	0.6613	0.5870	0.7662
No log	73.0	73	0.4963	0.6503	0.4963	0.7045
No log	74.0	74	0.4903	0.6150	0.4903	0.7002
No log	75.0	75	0.4846	0.6319	0.4846	0.6961
No log	76.0	76	0.4965	0.6617	0.4965	0.7046
No log	77.0	77	0.5770	0.6455	0.5770	0.7596
No log	78.0	78	0.6150	0.6253	0.6150	0.7842
No log	79.0	79	0.5800	0.6543	0.5800	0.7616
No log	80.0	80	0.5167	0.6382	0.5167	0.7188
No log	81.0	81	0.4993	0.6617	0.4993	0.7066
No log	82.0	82	0.5013	0.6506	0.5013	0.7080
No log	83.0	83	0.5113	0.6617	0.5113	0.7151

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 10, 2025
Updated: Mar 10, 2025