Version19ASAP_FineTuningBERT_AugV19_k1_task1_organization_k1_k1_fold4

genki10/Version19ASAP_FineTuningBERT_AugV19_k1_task1_organization_k1_k1_fold4

Version19ASAP_FineTuningBERT_AugV19_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 9, 2025
Updated: Mar 9, 2025
SHA: ba89ef9e

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Base models

Model card

From the Hugging Face model README

Version19ASAP_FineTuningBERT_AugV19_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: 0.7246
Qwk: 0.6414
Mse: 0.7246
Rmse: 0.8512

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	8.3434	0.0037	8.3434	2.8885
No log	2.0	2	7.4581	0.0018	7.4581	2.7310
No log	3.0	3	6.9679	0.0018	6.9679	2.6397
No log	4.0	4	6.4774	0.0018	6.4774	2.5451
No log	5.0	5	5.9477	-0.0004	5.9477	2.4388
No log	6.0	6	5.4948	0.0139	5.4948	2.3441
No log	7.0	7	5.0616	0.0079	5.0616	2.2498
No log	8.0	8	4.6417	0.0040	4.6417	2.1545
No log	9.0	9	4.2023	0.0040	4.2023	2.0500
No log	10.0	10	3.8421	0.0040	3.8421	1.9601
No log	11.0	11	3.4274	0.0040	3.4274	1.8513
No log	12.0	12	2.9914	0.0040	2.9914	1.7296
No log	13.0	13	2.5827	0.0040	2.5827	1.6071
No log	14.0	14	2.2258	0.1454	2.2258	1.4919
No log	15.0	15	1.9402	0.0509	1.9402	1.3929
No log	16.0	16	1.7260	0.0382	1.7260	1.3138
No log	17.0	17	1.5481	0.0213	1.5481	1.2442
No log	18.0	18	1.3874	0.0213	1.3874	1.1779
No log	19.0	19	1.2690	0.0213	1.2690	1.1265
No log	20.0	20	1.1695	0.0213	1.1695	1.0814
No log	21.0	21	1.0584	0.0213	1.0584	1.0288
No log	22.0	22	0.9660	0.0213	0.9660	0.9828
No log	23.0	23	0.8865	0.0305	0.8865	0.9415
No log	24.0	24	0.8302	0.2545	0.8302	0.9112
No log	25.0	25	0.7968	0.3431	0.7968	0.8926
No log	26.0	26	0.7216	0.4422	0.7216	0.8494
No log	27.0	27	0.6804	0.4413	0.6804	0.8248
No log	28.0	28	0.6709	0.4749	0.6709	0.8191
No log	29.0	29	0.6404	0.4967	0.6404	0.8002
No log	30.0	30	0.6297	0.4921	0.6297	0.7935
No log	31.0	31	0.5983	0.4967	0.5983	0.7735
No log	32.0	32	0.5846	0.4991	0.5846	0.7646
No log	33.0	33	0.6242	0.5172	0.6242	0.7900
No log	34.0	34	0.5947	0.5283	0.5947	0.7712
No log	35.0	35	0.5556	0.5397	0.5556	0.7454
No log	36.0	36	0.5516	0.5479	0.5516	0.7427
No log	37.0	37	0.6242	0.5558	0.6242	0.7900
No log	38.0	38	0.5645	0.5921	0.5645	0.7513
No log	39.0	39	0.5709	0.6096	0.5709	0.7556
No log	40.0	40	0.5816	0.6371	0.5816	0.7627
No log	41.0	41	0.6719	0.5908	0.6719	0.8197
No log	42.0	42	0.6358	0.6141	0.6358	0.7974
No log	43.0	43	0.6096	0.6320	0.6096	0.7808
No log	44.0	44	0.6214	0.6395	0.6214	0.7883
No log	45.0	45	0.5933	0.6596	0.5933	0.7703
No log	46.0	46	0.5933	0.6436	0.5933	0.7703
No log	47.0	47	0.6026	0.6479	0.6026	0.7763
No log	48.0	48	0.6862	0.6248	0.6862	0.8284
No log	49.0	49	0.7248	0.6222	0.7248	0.8513
No log	50.0	50	0.6608	0.6418	0.6608	0.8129
No log	51.0	51	0.6919	0.6107	0.6919	0.8318
No log	52.0	52	0.7073	0.6090	0.7073	0.8410
No log	53.0	53	0.7217	0.6401	0.7217	0.8495
No log	54.0	54	0.7523	0.6326	0.7523	0.8674
No log	55.0	55	0.8327	0.6272	0.8327	0.9125
No log	56.0	56	0.7825	0.6244	0.7825	0.8846
No log	57.0	57	0.6912	0.6423	0.6912	0.8314
No log	58.0	58	0.6852	0.6422	0.6852	0.8278
No log	59.0	59	0.7057	0.6348	0.7057	0.8401
No log	60.0	60	0.8543	0.6174	0.8543	0.9243
No log	61.0	61	0.9133	0.6071	0.9133	0.9557
No log	62.0	62	0.8296	0.6218	0.8296	0.9108
No log	63.0	63	0.7161	0.6439	0.7161	0.8462
No log	64.0	64	0.7047	0.6482	0.7047	0.8395
No log	65.0	65	0.7246	0.6414	0.7246	0.8512

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