Version19ASAP_FineTuningBERT_AugV19_k10_task1_organization_k10_k10_fold3

genki10/Version19ASAP_FineTuningBERT_AugV19_k10_task1_organization_k10_k10_fold3

Version19ASAP_FineTuningBERT_AugV19_k10_task1_organization_k10_k10_fold3 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: 5b276c8e

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Base models

Model card

From the Hugging Face model README

Version19ASAP_FineTuningBERT_AugV19_k10_task1_organization_k10_k10_fold3

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: 0.6802
Qwk: 0.6276
Mse: 0.6792
Rmse: 0.8242

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	8.5911	0.0	8.5898	2.9308
No log	2.0	6	5.1282	0.0198	5.1269	2.2643
No log	3.0	9	3.6588	0.0	3.6579	1.9126
No log	4.0	12	2.4219	0.1377	2.4212	1.5560
No log	5.0	15	1.7444	0.0102	1.7438	1.3205
No log	6.0	18	1.1017	0.0	1.1012	1.0494
No log	7.0	21	0.8895	0.1908	0.8893	0.9430
No log	8.0	24	0.8788	0.0414	0.8786	0.9374
No log	9.0	27	0.9980	0.0314	0.9979	0.9989
No log	10.0	30	1.0731	0.0414	1.0730	1.0359
No log	11.0	33	1.3534	0.1518	1.3535	1.1634
No log	12.0	36	1.5837	0.1607	1.5838	1.2585
No log	13.0	39	1.1232	0.3001	1.1231	1.0598
No log	14.0	42	1.6501	0.2442	1.6502	1.2846
No log	15.0	45	0.8098	0.5359	0.8091	0.8995
No log	16.0	48	0.8909	0.5608	0.8899	0.9433
No log	17.0	51	0.8673	0.5936	0.8663	0.9307
No log	18.0	54	0.6537	0.6606	0.6529	0.8080
No log	19.0	57	0.7492	0.6313	0.7485	0.8652
No log	20.0	60	0.5545	0.6420	0.5539	0.7442
No log	21.0	63	0.6660	0.6187	0.6652	0.8156
No log	22.0	66	0.6731	0.6447	0.6723	0.8200
No log	23.0	69	0.7312	0.6372	0.7305	0.8547
No log	24.0	72	0.6461	0.6458	0.6453	0.8033
No log	25.0	75	0.6595	0.6374	0.6587	0.8116
No log	26.0	78	0.6873	0.5950	0.6866	0.8286
No log	27.0	81	0.6905	0.6029	0.6897	0.8305
No log	28.0	84	0.8120	0.5939	0.8111	0.9006
No log	29.0	87	0.6371	0.6240	0.6365	0.7978
No log	30.0	90	0.7203	0.6196	0.7195	0.8482
No log	31.0	93	0.6556	0.6257	0.6549	0.8092
No log	32.0	96	0.6922	0.6267	0.6915	0.8315
No log	33.0	99	0.5473	0.6216	0.5467	0.7394
No log	34.0	102	0.5732	0.6331	0.5725	0.7566
No log	35.0	105	0.7779	0.6029	0.7770	0.8815
No log	36.0	108	0.6037	0.6314	0.6030	0.7765
No log	37.0	111	0.6570	0.6001	0.6563	0.8101
No log	38.0	114	0.6802	0.6276	0.6792	0.8242

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