Version22NewTestASAP_FineTuningBERT_AugV22_k1_task1_organization_k1_k1_fold4

genki10/Version22NewTestASAP_FineTuningBERT_AugV22_k1_task1_organization_k1_k1_fold4

Version22NewTestASAP_FineTuningBERT_AugV22_k1_task1_organization_k1_k1_fold4 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: 66ff952b

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Base models

Model card

From the Hugging Face model README

Version22NewTestASAP_FineTuningBERT_AugV22_k1_task1_organization_k1_k1_fold4

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: 0.9089
Qwk: 0.5765
Mse: 0.9089
Rmse: 0.9534

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	12.3809	-0.0034	12.3809	3.5187
No log	2.0	2	11.2777	-0.0278	11.2777	3.3582
No log	3.0	3	9.8649	0.0014	9.8649	3.1408
No log	4.0	4	8.7795	0.0018	8.7795	2.9630
No log	5.0	5	7.9218	0.0018	7.9218	2.8146
No log	6.0	6	7.0569	0.0018	7.0569	2.6565
No log	7.0	7	6.3077	0.0018	6.3077	2.5115
No log	8.0	8	5.5992	0.0271	5.5992	2.3663
No log	9.0	9	4.9494	0.0128	4.9494	2.2247
No log	10.0	10	4.3991	0.0118	4.3991	2.0974
No log	11.0	11	3.8732	0.0040	3.8732	1.9681
No log	12.0	12	3.4703	0.0040	3.4703	1.8629
No log	13.0	13	3.0551	0.0040	3.0551	1.7479
No log	14.0	14	2.6760	0.0040	2.6760	1.6359
No log	15.0	15	2.3902	0.0721	2.3902	1.5460
No log	16.0	16	2.1520	0.1254	2.1520	1.4670
No log	17.0	17	1.9438	0.0682	1.9438	1.3942
No log	18.0	18	1.7565	0.0445	1.7565	1.3253
No log	19.0	19	1.5863	0.0445	1.5863	1.2595
No log	20.0	20	1.4361	0.0445	1.4361	1.1984
No log	21.0	21	1.3065	0.0445	1.3065	1.1430
No log	22.0	22	1.1848	0.0445	1.1848	1.0885
No log	23.0	23	1.0948	0.0547	1.0948	1.0463
No log	24.0	24	1.0219	0.0648	1.0219	1.0109
No log	25.0	25	0.9399	0.0795	0.9399	0.9695
No log	26.0	26	0.8676	0.0648	0.8676	0.9315
No log	27.0	27	0.8137	0.2060	0.8137	0.9021
No log	28.0	28	0.7871	0.3979	0.7871	0.8872
No log	29.0	29	0.7644	0.4341	0.7644	0.8743
No log	30.0	30	0.6786	0.5451	0.6786	0.8238
No log	31.0	31	0.6492	0.4938	0.6492	0.8057
No log	32.0	32	0.6157	0.5051	0.6157	0.7847
No log	33.0	33	0.5863	0.5677	0.5863	0.7657
No log	34.0	34	0.5897	0.5893	0.5897	0.7679
No log	35.0	35	0.5455	0.5675	0.5455	0.7386
No log	36.0	36	0.5485	0.5224	0.5485	0.7406
No log	37.0	37	0.5764	0.4773	0.5764	0.7592
No log	38.0	38	0.5325	0.5227	0.5325	0.7297
No log	39.0	39	0.5017	0.5759	0.5017	0.7083
No log	40.0	40	0.4961	0.5817	0.4961	0.7044
No log	41.0	41	0.5057	0.5473	0.5057	0.7111
No log	42.0	42	0.5725	0.4970	0.5725	0.7566
No log	43.0	43	0.5848	0.5048	0.5848	0.7647
No log	44.0	44	0.5388	0.5999	0.5388	0.7340
No log	45.0	45	0.5340	0.5946	0.5340	0.7307
No log	46.0	46	0.5755	0.5955	0.5755	0.7586
No log	47.0	47	0.6060	0.6032	0.6060	0.7785
No log	48.0	48	0.6537	0.5928	0.6537	0.8085
No log	49.0	49	0.5957	0.6110	0.5957	0.7718
No log	50.0	50	0.5936	0.6075	0.5936	0.7704
No log	51.0	51	0.6785	0.5968	0.6785	0.8237
No log	52.0	52	0.6948	0.5829	0.6948	0.8335
No log	53.0	53	0.6099	0.6083	0.6099	0.7809
No log	54.0	54	0.6158	0.6123	0.6158	0.7847
No log	55.0	55	0.7352	0.5834	0.7352	0.8575
No log	56.0	56	0.7250	0.5956	0.7250	0.8515
No log	57.0	57	0.7330	0.6034	0.7330	0.8562
No log	58.0	58	0.6671	0.6070	0.6671	0.8168
No log	59.0	59	0.7173	0.6085	0.7173	0.8470
No log	60.0	60	0.8729	0.5619	0.8729	0.9343
No log	61.0	61	0.8911	0.5623	0.8911	0.9440
No log	62.0	62	0.7664	0.5996	0.7664	0.8755
No log	63.0	63	0.7690	0.5996	0.7690	0.8769
No log	64.0	64	0.8693	0.5852	0.8693	0.9324
No log	65.0	65	0.9821	0.5455	0.9821	0.9910
No log	66.0	66	0.9507	0.5629	0.9507	0.9751
No log	67.0	67	0.9227	0.5808	0.9227	0.9606
No log	68.0	68	0.9984	0.5585	0.9984	0.9992
No log	69.0	69	1.1505	0.5083	1.1505	1.0726
No log	70.0	70	1.1557	0.5016	1.1557	1.0750
No log	71.0	71	1.0119	0.5462	1.0119	1.0060
No log	72.0	72	0.9984	0.5505	0.9984	0.9992
No log	73.0	73	1.0581	0.5258	1.0581	1.0286
No log	74.0	74	0.9971	0.5594	0.9971	0.9985
No log	75.0	75	0.8524	0.6001	0.8524	0.9232
No log	76.0	76	0.8199	0.6094	0.8199	0.9055
No log	77.0	77	0.8727	0.6039	0.8727	0.9342
No log	78.0	78	0.9853	0.5466	0.9853	0.9926
No log	79.0	79	1.0009	0.5406	1.0009	1.0004
No log	80.0	80	0.9344	0.5816	0.9344	0.9666
No log	81.0	81	0.8245	0.6119	0.8245	0.9080
No log	82.0	82	0.7942	0.6238	0.7942	0.8912
No log	83.0	83	0.8190	0.6167	0.8190	0.9050
No log	84.0	84	0.8864	0.5956	0.8864	0.9415
No log	85.0	85	0.9978	0.5600	0.9978	0.9989
No log	86.0	86	1.0393	0.5430	1.0393	1.0195
No log	87.0	87	1.0164	0.5561	1.0164	1.0082
No log	88.0	88	0.9485	0.5676	0.9485	0.9739
No log	89.0	89	0.9001	0.5857	0.9001	0.9487
No log	90.0	90	0.8846	0.5883	0.8846	0.9405
No log	91.0	91	0.8369	0.6054	0.8369	0.9148
No log	92.0	92	0.8053	0.6137	0.8053	0.8974
No log	93.0	93	0.8028	0.6167	0.8028	0.8960
No log	94.0	94	0.8163	0.6069	0.8163	0.9035
No log	95.0	95	0.8378	0.6040	0.8378	0.9153
No log	96.0	96	0.8701	0.5890	0.8701	0.9328
No log	97.0	97	0.8943	0.5847	0.8943	0.9457
No log	98.0	98	0.9031	0.5769	0.9031	0.9503
No log	99.0	99	0.9056	0.5765	0.9056	0.9516
No log	100.0	100	0.9089	0.5765	0.9089	0.9534

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