Version19ASAP_FineTuningBERT_AugV19_k10_task1_organization_k10_k10_fold1

genki10/Version19ASAP_FineTuningBERT_AugV19_k10_task1_organization_k10_k10_fold1

Version19ASAP_FineTuningBERT_AugV19_k10_task1_organization_k10_k10_fold1 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: b506d26e

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Base models

Model card

From the Hugging Face model README

Version19ASAP_FineTuningBERT_AugV19_k10_task1_organization_k10_k10_fold1

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: 0.7782
Qwk: 0.6039
Mse: 0.7781
Rmse: 0.8821

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	3	8.3478	-0.0002	8.3452	2.8888
No log	2.0	6	5.6976	-0.0150	5.6955	2.3865
No log	3.0	9	4.3287	0.0238	4.3266	2.0800
No log	4.0	12	3.1515	0.0	3.1496	1.7747
No log	5.0	15	2.2591	0.1001	2.2574	1.5025
No log	6.0	18	1.7762	0.1531	1.7745	1.3321
No log	7.0	21	1.3074	0.0315	1.3059	1.1428
No log	8.0	24	0.9152	0.0106	0.9140	0.9560
No log	9.0	27	0.9255	0.0514	0.9242	0.9614
No log	10.0	30	0.7047	0.3215	0.7037	0.8389
No log	11.0	33	0.7508	0.2041	0.7499	0.8660
No log	12.0	36	1.0751	0.0802	1.0743	1.0365
No log	13.0	39	0.8153	0.3131	0.8147	0.9026
No log	14.0	42	1.4936	0.2166	1.4932	1.2220
No log	15.0	45	1.1947	0.3352	1.1944	1.0929
No log	16.0	48	0.9237	0.4671	0.9235	0.9610
No log	17.0	51	0.5517	0.6337	0.5515	0.7427
No log	18.0	54	0.6612	0.6515	0.6613	0.8132
No log	19.0	57	0.4687	0.7224	0.4686	0.6845
No log	20.0	60	2.0745	0.3891	2.0750	1.4405
No log	21.0	63	1.1602	0.5395	1.1606	1.0773
No log	22.0	66	0.4712	0.7088	0.4709	0.6862
No log	23.0	69	2.4266	0.3464	2.4271	1.5579
No log	24.0	72	0.9504	0.5970	0.9506	0.9750
No log	25.0	75	0.5562	0.6516	0.5557	0.7455
No log	26.0	78	0.8528	0.6004	0.8530	0.9236
No log	27.0	81	0.8569	0.5762	0.8570	0.9258
No log	28.0	84	1.3774	0.4773	1.3778	1.1738
No log	29.0	87	0.5879	0.6809	0.5879	0.7667
No log	30.0	90	0.8633	0.6075	0.8636	0.9293
No log	31.0	93	1.6303	0.4119	1.6306	1.2769
No log	32.0	96	0.7769	0.6040	0.7770	0.8815
No log	33.0	99	1.1635	0.5434	1.1638	1.0788
No log	34.0	102	0.9914	0.5757	0.9916	0.9958
No log	35.0	105	0.9376	0.5643	0.9377	0.9683
No log	36.0	108	1.2371	0.4862	1.2372	1.1123
No log	37.0	111	0.6587	0.6555	0.6586	0.8116
No log	38.0	114	1.0194	0.5597	1.0194	1.0097
No log	39.0	117	0.7782	0.6039	0.7781	0.8821

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