Version22NewTestASAP_FineTuningBERT_AugV22_k1_task1_organization_k1_k1_fold3

genki10/Version22NewTestASAP_FineTuningBERT_AugV22_k1_task1_organization_k1_k1_fold3

Version22NewTestASAP_FineTuningBERT_AugV22_k1_task1_organization_k1_k1_fold3 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 15, 2025
Updated: Mar 15, 2025
SHA: 065a8799

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Base models

Model card

From the Hugging Face model README

Version22NewTestASAP_FineTuningBERT_AugV22_k1_task1_organization_k1_k1_fold3

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: 0.6488
Qwk: 0.6291
Mse: 0.6484
Rmse: 0.8052

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	12.9177	-0.0023	12.9153	3.5938
No log	2.0	2	11.8809	-0.0262	11.8787	3.4466
No log	3.0	3	10.5552	-0.0022	10.5534	3.2486
No log	4.0	4	9.3354	0.0	9.3338	3.0551
No log	5.0	5	8.3466	0.0	8.3450	2.8888
No log	6.0	6	7.4791	0.0	7.4776	2.7345
No log	7.0	7	6.7444	0.0	6.7430	2.5967
No log	8.0	8	6.0953	0.0017	6.0939	2.4686
No log	9.0	9	5.3564	0.0181	5.3551	2.3141
No log	10.0	10	4.6886	0.0114	4.6874	2.1650
No log	11.0	11	4.1385	0.0076	4.1374	2.0341
No log	12.0	12	3.6558	0.0038	3.6547	1.9117
No log	13.0	13	3.2660	0.0	3.2650	1.8069
No log	14.0	14	2.9382	0.0	2.9372	1.7138
No log	15.0	15	2.5914	0.0319	2.5904	1.6095
No log	16.0	16	2.2979	0.1457	2.2970	1.5156
No log	17.0	17	2.0910	0.0926	2.0901	1.4457
No log	18.0	18	1.8853	0.0524	1.8844	1.3727
No log	19.0	19	1.7215	0.0463	1.7207	1.3118
No log	20.0	20	1.5682	0.0463	1.5675	1.2520
No log	21.0	21	1.4223	0.0463	1.4217	1.1923
No log	22.0	22	1.2904	0.0463	1.2898	1.1357
No log	23.0	23	1.1889	0.0463	1.1883	1.0901
No log	24.0	24	1.0911	0.0463	1.0906	1.0443
No log	25.0	25	1.0112	0.0463	1.0108	1.0054
No log	26.0	26	0.9282	0.0463	0.9277	0.9632
No log	27.0	27	0.8816	0.1860	0.8812	0.9387
No log	28.0	28	0.8122	0.4020	0.8118	0.9010
No log	29.0	29	0.8193	0.3442	0.8189	0.9049
No log	30.0	30	0.8139	0.3574	0.8135	0.9019
No log	31.0	31	0.6936	0.4746	0.6934	0.8327
No log	32.0	32	0.6504	0.4245	0.6503	0.8064
No log	33.0	33	0.6511	0.4312	0.6509	0.8068
No log	34.0	34	0.5879	0.4639	0.5878	0.7667
No log	35.0	35	0.5688	0.5222	0.5687	0.7541
No log	36.0	36	0.5842	0.5402	0.5840	0.7642
No log	37.0	37	0.5337	0.5481	0.5335	0.7304
No log	38.0	38	0.5201	0.4787	0.5200	0.7211
No log	39.0	39	0.5392	0.4597	0.5391	0.7343
No log	40.0	40	0.5141	0.4911	0.5140	0.7169
No log	41.0	41	0.4910	0.5063	0.4908	0.7006
No log	42.0	42	0.4841	0.5422	0.4839	0.6956
No log	43.0	43	0.4778	0.5394	0.4776	0.6911
No log	44.0	44	0.4859	0.5586	0.4857	0.6969
No log	45.0	45	0.5094	0.5626	0.5092	0.7136
No log	46.0	46	0.4964	0.5778	0.4961	0.7044
No log	47.0	47	0.4798	0.6003	0.4795	0.6924
No log	48.0	48	0.4831	0.5908	0.4827	0.6948
No log	49.0	49	0.4964	0.6169	0.4961	0.7043
No log	50.0	50	0.5257	0.6201	0.5253	0.7248
No log	51.0	51	0.5221	0.6242	0.5217	0.7223
No log	52.0	52	0.5000	0.6261	0.4996	0.7068
No log	53.0	53	0.5002	0.6357	0.4998	0.7070
No log	54.0	54	0.5153	0.6277	0.5149	0.7176
No log	55.0	55	0.5791	0.6159	0.5787	0.7607
No log	56.0	56	0.5635	0.6312	0.5631	0.7504
No log	57.0	57	0.5305	0.6232	0.5300	0.7280
No log	58.0	58	0.5091	0.6253	0.5087	0.7132
No log	59.0	59	0.5117	0.6271	0.5113	0.7150
No log	60.0	60	0.5394	0.6329	0.5390	0.7341
No log	61.0	61	0.6542	0.6040	0.6538	0.8086
No log	62.0	62	0.6827	0.5915	0.6823	0.8260
No log	63.0	63	0.6275	0.6117	0.6271	0.7919
No log	64.0	64	0.5365	0.6467	0.5361	0.7322
No log	65.0	65	0.5236	0.6468	0.5232	0.7233
No log	66.0	66	0.5360	0.6377	0.5356	0.7319
No log	67.0	67	0.6054	0.6216	0.6050	0.7778
No log	68.0	68	0.7788	0.5676	0.7784	0.8823
No log	69.0	69	0.8667	0.5352	0.8663	0.9307
No log	70.0	70	0.8428	0.5411	0.8423	0.9178
No log	71.0	71	0.7307	0.5768	0.7303	0.8545
No log	72.0	72	0.6020	0.6199	0.6016	0.7756
No log	73.0	73	0.5670	0.6314	0.5666	0.7527
No log	74.0	74	0.5702	0.6333	0.5697	0.7548
No log	75.0	75	0.6003	0.6452	0.5999	0.7745
No log	76.0	76	0.6738	0.6030	0.6733	0.8206
No log	77.0	77	0.7515	0.5777	0.7510	0.8666
No log	78.0	78	0.7547	0.5848	0.7542	0.8684
No log	79.0	79	0.7001	0.5972	0.6997	0.8365
No log	80.0	80	0.6151	0.6246	0.6147	0.7840
No log	81.0	81	0.5809	0.6409	0.5805	0.7619
No log	82.0	82	0.5782	0.6353	0.5777	0.7601
No log	83.0	83	0.5953	0.6166	0.5948	0.7713
No log	84.0	84	0.6326	0.6227	0.6322	0.7951
No log	85.0	85	0.6842	0.5899	0.6837	0.8269
No log	86.0	86	0.6980	0.5935	0.6976	0.8352
No log	87.0	87	0.6786	0.5984	0.6782	0.8235
No log	88.0	88	0.6354	0.6277	0.6349	0.7968
No log	89.0	89	0.6103	0.6324	0.6099	0.7810
No log	90.0	90	0.5831	0.6349	0.5827	0.7633
No log	91.0	91	0.5652	0.6529	0.5648	0.7515
No log	92.0	92	0.5632	0.6592	0.5628	0.7502
No log	93.0	93	0.5710	0.6519	0.5706	0.7554
No log	94.0	94	0.5859	0.6457	0.5854	0.7651
No log	95.0	95	0.6068	0.6358	0.6064	0.7787
No log	96.0	96	0.6312	0.6300	0.6307	0.7942
No log	97.0	97	0.6457	0.6317	0.6452	0.8033
No log	98.0	98	0.6499	0.6291	0.6494	0.8059
No log	99.0	99	0.6484	0.6291	0.6479	0.8049
No log	100.0	100	0.6488	0.6291	0.6484	0.8052

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 15, 2025
Updated: Mar 15, 2025