Version19ASAP_FineTuningBERT_AugV19_k3_task1_organization_k3_k3_fold4

genki10/Version19ASAP_FineTuningBERT_AugV19_k3_task1_organization_k3_k3_fold4

Version19ASAP_FineTuningBERT_AugV19_k3_task1_organization_k3_k3_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 9, 2025
Updated: Mar 9, 2025
SHA: 6c238de8

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Base models

Model card

From the Hugging Face model README

Version19ASAP_FineTuningBERT_AugV19_k3_task1_organization_k3_k3_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: 0.7615
Qwk: 0.6100
Mse: 0.7615
Rmse: 0.8726

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	10.6422	0.0121	10.6422	3.2622
No log	2.0	2	9.9083	0.0018	9.9083	3.1477
No log	3.0	3	9.3137	0.0	9.3137	3.0518
No log	4.0	4	8.5853	0.0	8.5853	2.9301
No log	5.0	5	7.7357	0.0	7.7357	2.7813
No log	6.0	6	6.5906	0.0133	6.5906	2.5672
No log	7.0	7	5.5361	0.0268	5.5361	2.3529
No log	8.0	8	4.9569	0.0187	4.9569	2.2264
No log	9.0	9	4.3095	0.0191	4.3095	2.0759
No log	10.0	10	4.2609	0.0094	4.2609	2.0642
No log	11.0	11	3.6544	0.0040	3.6544	1.9117
No log	12.0	12	2.8897	0.0040	2.8897	1.6999
No log	13.0	13	2.6749	0.0167	2.6749	1.6355
No log	14.0	14	2.3650	0.1175	2.3650	1.5378
No log	15.0	15	2.0105	0.1363	2.0105	1.4179
No log	16.0	16	1.7987	0.0786	1.7987	1.3412
No log	17.0	17	1.5948	0.0582	1.5948	1.2629
No log	18.0	18	1.5471	0.0544	1.5471	1.2438
No log	19.0	19	1.3579	0.0445	1.3579	1.1653
No log	20.0	20	1.1674	0.0445	1.1674	1.0804
No log	21.0	21	1.0823	0.0420	1.0823	1.0403
No log	22.0	22	0.9883	0.0420	0.9883	0.9942
No log	23.0	23	0.9465	0.0317	0.9465	0.9729
No log	24.0	24	0.8947	0.1589	0.8947	0.9459
No log	25.0	25	0.8105	0.3427	0.8105	0.9003
No log	26.0	26	0.7659	0.4116	0.7659	0.8751
No log	27.0	27	0.7325	0.3921	0.7325	0.8559
No log	28.0	28	0.7066	0.4061	0.7066	0.8406
No log	29.0	29	0.6919	0.3927	0.6919	0.8318
No log	30.0	30	0.6733	0.3468	0.6733	0.8205
No log	31.0	31	0.6713	0.3155	0.6713	0.8193
No log	32.0	32	0.6456	0.3342	0.6456	0.8035
No log	33.0	33	0.6113	0.3852	0.6113	0.7819
No log	34.0	34	0.5919	0.3884	0.5919	0.7693
No log	35.0	35	0.5942	0.3819	0.5942	0.7708
No log	36.0	36	0.6032	0.3838	0.6032	0.7767
No log	37.0	37	0.5903	0.4029	0.5903	0.7683
No log	38.0	38	0.5395	0.4266	0.5395	0.7345
No log	39.0	39	0.5025	0.5099	0.5025	0.7089
No log	40.0	40	0.4905	0.5431	0.4905	0.7004
No log	41.0	41	0.5036	0.5683	0.5036	0.7096
No log	42.0	42	0.5152	0.5936	0.5152	0.7178
No log	43.0	43	0.5270	0.6009	0.5270	0.7259
No log	44.0	44	0.5257	0.6145	0.5257	0.7250
No log	45.0	45	0.5319	0.6354	0.5319	0.7293
No log	46.0	46	0.5137	0.6510	0.5137	0.7167
No log	47.0	47	0.5106	0.6500	0.5106	0.7145
No log	48.0	48	0.5356	0.6652	0.5356	0.7319
No log	49.0	49	0.5759	0.6571	0.5759	0.7589
No log	50.0	50	0.6140	0.6402	0.6140	0.7836
No log	51.0	51	0.6110	0.6339	0.6110	0.7817
No log	52.0	52	0.6540	0.6357	0.6540	0.8087
No log	53.0	53	0.6537	0.6434	0.6537	0.8085
No log	54.0	54	0.6703	0.6432	0.6703	0.8187
No log	55.0	55	0.7535	0.6155	0.7535	0.8680
No log	56.0	56	0.8828	0.6077	0.8828	0.9396
No log	57.0	57	0.8718	0.6028	0.8718	0.9337
No log	58.0	58	0.8158	0.6187	0.8158	0.9032
No log	59.0	59	0.7011	0.6448	0.7011	0.8373
No log	60.0	60	0.7031	0.6433	0.7031	0.8385
No log	61.0	61	0.7920	0.6131	0.7920	0.8900
No log	62.0	62	0.8466	0.6042	0.8466	0.9201
No log	63.0	63	0.7792	0.6187	0.7792	0.8827
No log	64.0	64	0.8166	0.6061	0.8166	0.9037
No log	65.0	65	0.8260	0.6045	0.8260	0.9088
No log	66.0	66	0.7308	0.6298	0.7308	0.8548
No log	67.0	67	0.7301	0.6273	0.7301	0.8545
No log	68.0	68	0.7615	0.6100	0.7615	0.8726

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