Version12AGAINNNASAP_FineTuningBERT_AugV12_k1_task1_organization_k1_k1_fold2

genki10/Version12AGAINNNASAP_FineTuningBERT_AugV12_k1_task1_organization_k1_k1_fold2

Version12AGAINNNASAP_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 8, 2025
Updated: Mar 8, 2025
SHA: 6da64c8e

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Model card

From the Hugging Face model README

Version12AGAINNNASAP_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: 0.6423
Qwk: 0.6046
Mse: 0.6419
Rmse: 0.8012

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	13.6943	0.0	13.6942	3.7006
No log	2.0	2	11.0134	0.0033	11.0139	3.3187
No log	3.0	3	10.1872	0.0	10.1875	3.1918
No log	4.0	4	9.8203	0.0	9.8205	3.1338
No log	5.0	5	9.5354	0.0	9.5357	3.0880
No log	6.0	6	9.2077	0.0	9.2079	3.0345
No log	7.0	7	8.8221	0.0	8.8224	2.9703
No log	8.0	8	8.4111	0.0	8.4113	2.9002
No log	9.0	9	8.0071	0.0	8.0074	2.8297
No log	10.0	10	7.6223	0.0	7.6226	2.7609
No log	11.0	11	7.2602	0.0	7.2605	2.6945
No log	12.0	12	6.9142	0.0	6.9145	2.6296
No log	13.0	13	6.5704	0.0	6.5708	2.5633
No log	14.0	14	6.2176	0.0	6.2179	2.4936
No log	15.0	15	5.8421	0.0442	5.8425	2.4171
No log	16.0	16	5.4351	0.0039	5.4354	2.3314
No log	17.0	17	4.9978	0.0	4.9981	2.2357
No log	18.0	18	4.5368	0.0	4.5372	2.1301
No log	19.0	19	4.0745	0.0	4.0749	2.0186
No log	20.0	20	3.6597	0.0	3.6601	1.9132
No log	21.0	21	3.3348	0.0	3.3353	1.8263
No log	22.0	22	3.0738	0.0	3.0743	1.7534
No log	23.0	23	2.7472	0.0	2.7477	1.6576
No log	24.0	24	2.4497	0.0666	2.4502	1.5653
No log	25.0	25	2.2415	0.1498	2.2419	1.4973
No log	26.0	26	2.0660	0.0307	2.0664	1.4375
No log	27.0	27	1.8938	0.0213	1.8942	1.3763
No log	28.0	28	1.7144	0.0107	1.7148	1.3095
No log	29.0	29	1.5380	0.0	1.5384	1.2403
No log	30.0	30	1.3787	0.0	1.3792	1.1744
No log	31.0	31	1.2554	0.0	1.2558	1.1206
No log	32.0	32	1.1776	0.0	1.1780	1.0854
No log	33.0	33	1.1088	0.0	1.1092	1.0532
No log	34.0	34	0.9966	0.0068	0.9970	0.9985
No log	35.0	35	0.9219	0.0068	0.9223	0.9604
No log	36.0	36	0.8695	0.0316	0.8699	0.9327
No log	37.0	37	0.8048	0.3604	0.8051	0.8973
No log	38.0	38	0.7422	0.4880	0.7424	0.8616
No log	39.0	39	0.7143	0.5200	0.7144	0.8452
No log	40.0	40	0.6438	0.4921	0.6439	0.8024
No log	41.0	41	0.6478	0.4073	0.6480	0.8050
No log	42.0	42	0.6061	0.4145	0.6062	0.7786
No log	43.0	43	0.5498	0.4641	0.5497	0.7414
No log	44.0	44	0.5311	0.5433	0.5310	0.7287
No log	45.0	45	0.5121	0.5450	0.5120	0.7155
No log	46.0	46	0.5197	0.4432	0.5196	0.7208
No log	47.0	47	0.5669	0.4131	0.5667	0.7528
No log	48.0	48	0.5498	0.4257	0.5497	0.7414
No log	49.0	49	0.4774	0.4743	0.4772	0.6908
No log	50.0	50	0.4762	0.4743	0.4760	0.6899
No log	51.0	51	0.5951	0.4213	0.5948	0.7712
No log	52.0	52	0.6343	0.4131	0.6341	0.7963
No log	53.0	53	0.5705	0.4759	0.5702	0.7551
No log	54.0	54	0.4705	0.6173	0.4702	0.6857
No log	55.0	55	0.4593	0.6222	0.4589	0.6774
No log	56.0	56	0.4989	0.6212	0.4985	0.7060
No log	57.0	57	0.5359	0.6207	0.5354	0.7317
No log	58.0	58	0.5707	0.5930	0.5702	0.7551
No log	59.0	59	0.5452	0.6077	0.5447	0.7381
No log	60.0	60	0.4960	0.6089	0.4956	0.7040
No log	61.0	61	0.5087	0.6257	0.5083	0.7129
No log	62.0	62	0.5953	0.5956	0.5948	0.7712
No log	63.0	63	0.6415	0.5675	0.6409	0.8006
No log	64.0	64	0.6341	0.5690	0.6335	0.7959
No log	65.0	65	0.5687	0.6091	0.5682	0.7538
No log	66.0	66	0.4957	0.6221	0.4953	0.7038
No log	67.0	67	0.5088	0.6199	0.5085	0.7131
No log	68.0	68	0.6331	0.5856	0.6326	0.7954
No log	69.0	69	0.6865	0.5745	0.6860	0.8283
No log	70.0	70	0.6189	0.5959	0.6185	0.7865
No log	71.0	71	0.5529	0.6259	0.5525	0.7433
No log	72.0	72	0.5779	0.6150	0.5775	0.7599
No log	73.0	73	0.5886	0.6196	0.5882	0.7670
No log	74.0	74	0.5301	0.6517	0.5297	0.7278
No log	75.0	75	0.5101	0.6466	0.5097	0.7139
No log	76.0	76	0.5428	0.6411	0.5424	0.7365
No log	77.0	77	0.6607	0.5912	0.6603	0.8126
No log	78.0	78	0.6917	0.5815	0.6913	0.8315
No log	79.0	79	0.6503	0.6026	0.6500	0.8062
No log	80.0	80	0.5744	0.6181	0.5740	0.7577
No log	81.0	81	0.5266	0.6241	0.5262	0.7254
No log	82.0	82	0.5331	0.6143	0.5327	0.7298
No log	83.0	83	0.5863	0.6033	0.5859	0.7655
No log	84.0	84	0.7113	0.5683	0.7110	0.8432
No log	85.0	85	0.7814	0.5395	0.7811	0.8838
No log	86.0	86	0.7684	0.5459	0.7681	0.8764
No log	87.0	87	0.6934	0.5844	0.6930	0.8324
No log	88.0	88	0.5964	0.6117	0.5960	0.7720
No log	89.0	89	0.5589	0.6369	0.5585	0.7473
No log	90.0	90	0.5568	0.6383	0.5564	0.7459
No log	91.0	91	0.5796	0.6190	0.5792	0.7610
No log	92.0	92	0.6267	0.6032	0.6263	0.7914
No log	93.0	93	0.6478	0.6012	0.6474	0.8046
No log	94.0	94	0.6423	0.6046	0.6419	0.8012

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 8, 2025
Updated: Mar 8, 2025