Version12AGAINNNASAP_FineTuningBERT_AugV12_k3_task1_organization_k3_k3_fold2

genki10/Version12AGAINNNASAP_FineTuningBERT_AugV12_k3_task1_organization_k3_k3_fold2

Version12AGAINNNASAP_FineTuningBERT_AugV12_k3_task1_organization_k3_k3_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 9, 2025
Updated: Mar 9, 2025
SHA: 196e2fc4

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Base models

Model card

From the Hugging Face model README

Version12AGAINNNASAP_FineTuningBERT_AugV12_k3_task1_organization_k3_k3_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: 0.5433
Qwk: 0.6291
Mse: 0.5429
Rmse: 0.7368

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	10.6160	0.0092	10.6162	3.2582
No log	2.0	2	9.3172	0.0	9.3175	3.0525
No log	3.0	3	8.6542	0.0	8.6544	2.9418
No log	4.0	4	8.1072	0.0	8.1074	2.8473
No log	5.0	5	7.3655	0.0	7.3657	2.7140
No log	6.0	6	6.5908	0.0	6.5910	2.5673
No log	7.0	7	5.9665	0.0198	5.9667	2.4427
No log	8.0	8	5.4080	0.0283	5.4083	2.3256
No log	9.0	9	4.9491	0.0078	4.9494	2.2247
No log	10.0	10	4.4725	0.0078	4.4727	2.1149
No log	11.0	11	3.9772	0.0	3.9775	1.9944
No log	12.0	12	3.6286	0.0	3.6289	1.9050
No log	13.0	13	3.2057	0.0	3.2060	1.7905
No log	14.0	14	2.7969	0.0	2.7973	1.6725
No log	15.0	15	2.5229	0.0103	2.5233	1.5885
No log	16.0	16	2.2618	0.1694	2.2622	1.5040
No log	17.0	17	2.0248	0.0714	2.0252	1.4231
No log	18.0	18	1.8162	0.0411	1.8166	1.3478
No log	19.0	19	1.6458	0.0539	1.6462	1.2831
No log	20.0	20	1.4761	0.0384	1.4765	1.2151
No log	21.0	21	1.2848	0.0213	1.2852	1.1337
No log	22.0	22	1.1656	0.0213	1.1660	1.0798
No log	23.0	23	1.0393	0.0107	1.0397	1.0197
No log	24.0	24	0.9440	0.0107	0.9443	0.9718
No log	25.0	25	0.9504	0.0732	0.9508	0.9751
No log	26.0	26	0.8228	0.3308	0.8231	0.9073
No log	27.0	27	0.8059	0.3060	0.8063	0.8979
No log	28.0	28	0.7180	0.3597	0.7181	0.8474
No log	29.0	29	0.7832	0.3009	0.7835	0.8852
No log	30.0	30	0.7226	0.3735	0.7228	0.8502
No log	31.0	31	0.6506	0.3498	0.6506	0.8066
No log	32.0	32	0.6491	0.3017	0.6491	0.8056
No log	33.0	33	0.6001	0.3778	0.6000	0.7746
No log	34.0	34	0.5834	0.3712	0.5833	0.7637
No log	35.0	35	0.6105	0.3167	0.6103	0.7812
No log	36.0	36	0.5712	0.3641	0.5709	0.7556
No log	37.0	37	0.5335	0.4580	0.5334	0.7303
No log	38.0	38	0.5357	0.4330	0.5356	0.7319
No log	39.0	39	0.4984	0.4576	0.4981	0.7058
No log	40.0	40	0.5718	0.5391	0.5713	0.7558
No log	41.0	41	0.5460	0.5849	0.5454	0.7385
No log	42.0	42	0.4786	0.5913	0.4781	0.6915
No log	43.0	43	0.5334	0.5030	0.5331	0.7302
No log	44.0	44	0.5091	0.5312	0.5088	0.7133
No log	45.0	45	0.4871	0.6228	0.4866	0.6976
No log	46.0	46	0.5007	0.6163	0.5001	0.7071
No log	47.0	47	0.4897	0.6221	0.4891	0.6994
No log	48.0	48	0.5135	0.6350	0.5128	0.7161
No log	49.0	49	0.5147	0.6329	0.5141	0.7170
No log	50.0	50	0.5381	0.6453	0.5375	0.7331
No log	51.0	51	0.4944	0.6605	0.4939	0.7028
No log	52.0	52	0.4945	0.6449	0.4941	0.7029
No log	53.0	53	0.5248	0.6569	0.5242	0.7240
No log	54.0	54	0.5818	0.6329	0.5811	0.7623
No log	55.0	55	0.5351	0.6658	0.5346	0.7311
No log	56.0	56	0.5362	0.6639	0.5357	0.7319
No log	57.0	57	0.5592	0.6494	0.5586	0.7474
No log	58.0	58	0.5097	0.6590	0.5093	0.7136
No log	59.0	59	0.5129	0.6561	0.5125	0.7159
No log	60.0	60	0.5232	0.6646	0.5227	0.7230
No log	61.0	61	0.5325	0.6536	0.5321	0.7295
No log	62.0	62	0.5112	0.6251	0.5109	0.7148
No log	63.0	63	0.5255	0.6444	0.5251	0.7247
No log	64.0	64	0.6105	0.5985	0.6099	0.7810
No log	65.0	65	0.6031	0.6036	0.6026	0.7763
No log	66.0	66	0.5210	0.6304	0.5206	0.7215
No log	67.0	67	0.5203	0.5971	0.5202	0.7212
No log	68.0	68	0.5380	0.5838	0.5379	0.7334
No log	69.0	69	0.5110	0.6053	0.5109	0.7147
No log	70.0	70	0.5183	0.6243	0.5180	0.7197
No log	71.0	71	0.5691	0.6376	0.5687	0.7541
No log	72.0	72	0.5641	0.6365	0.5636	0.7507
No log	73.0	73	0.5267	0.6210	0.5263	0.7255
No log	74.0	74	0.5252	0.6196	0.5248	0.7245
No log	75.0	75	0.5433	0.6291	0.5429	0.7368

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 9, 2025
Updated: Mar 9, 2025