BERT_AugV8_k5_task1_organization_sp020_lw030_fold3

genki10/BERT_AugV8_k5_task1_organization_sp020_lw030_fold3

BERT_AugV8_k5_task1_organization_sp020_lw030_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 25, 2025
Updated: Mar 25, 2025
SHA: 60e41f93

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Base models

Model card

From the Hugging Face model README

BERT_AugV8_k5_task1_organization_sp020_lw030_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: 1.0840
Qwk: 0.3226
Mse: 1.0837
Rmse: 1.0410

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: 150

Training results

Training Loss	Epoch	Step	Validation Loss	Qwk	Mse	Rmse
No log	1.0	4	9.2076	0.0	9.2060	3.0341
No log	2.0	8	5.4757	0.0578	5.4744	2.3397
No log	3.0	12	3.5909	0.0038	3.5900	1.8947
No log	4.0	16	2.0548	0.1289	2.0541	1.4332
No log	5.0	20	1.4330	0.0365	1.4324	1.1968
No log	6.0	24	1.0193	0.0292	1.0188	1.0094
No log	7.0	28	0.9501	0.1132	0.9497	0.9745
No log	8.0	32	1.1548	0.0723	1.1543	1.0744
No log	9.0	36	0.7627	0.4023	0.7628	0.8734
No log	10.0	40	0.9624	0.2602	0.9626	0.9811
No log	11.0	44	0.5762	0.4700	0.5766	0.7593
No log	12.0	48	1.1538	0.2642	1.1538	1.0742
No log	13.0	52	0.6229	0.4248	0.6234	0.7895
No log	14.0	56	1.0251	0.2871	1.0251	1.0125
No log	15.0	60	0.6614	0.5049	0.6618	0.8135
No log	16.0	64	0.9747	0.3355	0.9745	0.9872
No log	17.0	68	0.6506	0.4932	0.6507	0.8066
No log	18.0	72	0.8601	0.4105	0.8599	0.9273
No log	19.0	76	1.1997	0.2850	1.1994	1.0952
No log	20.0	80	0.7211	0.4344	0.7211	0.8492
No log	21.0	84	1.9328	0.1616	1.9321	1.3900
No log	22.0	88	0.7302	0.4672	0.7300	0.8544
No log	23.0	92	1.3200	0.2474	1.3194	1.1487
No log	24.0	96	0.8792	0.3666	0.8790	0.9376
No log	25.0	100	1.3320	0.2325	1.3316	1.1539
No log	26.0	104	0.8377	0.3359	0.8376	0.9152
No log	27.0	108	0.9094	0.3453	0.9092	0.9535
No log	28.0	112	0.9457	0.3855	0.9455	0.9724
No log	29.0	116	0.7912	0.4391	0.7910	0.8894
No log	30.0	120	1.0840	0.3226	1.0837	1.0410

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 25, 2025
Updated: Mar 25, 2025