Trial2BERT_AugV8_k5_task1_organization_sp010_lw020_fold3

genki10/Trial2BERT_AugV8_k5_task1_organization_sp010_lw020_fold3

Trial2BERT_AugV8_k5_task1_organization_sp010_lw020_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: Apr 5, 2025
Updated: Apr 5, 2025
SHA: 3b58ed5c

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Base models

Model card

From the Hugging Face model README

Trial2BERT_AugV8_k5_task1_organization_sp010_lw020_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: 0.6329
Qwk: 0.5252
Mse: 0.6330
Rmse: 0.7956

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	8.6736	0.0	8.6716	2.9448
No log	2.0	8	5.2125	0.0183	5.2114	2.2829
No log	3.0	12	2.8924	0.0	2.8914	1.7004
No log	4.0	16	1.9333	0.0355	1.9326	1.3902
No log	5.0	20	1.2088	0.0202	1.2082	1.0992
No log	6.0	24	0.9057	0.3123	0.9053	0.9515
No log	7.0	28	0.9891	0.0636	0.9885	0.9943
No log	8.0	32	0.7452	0.4284	0.7450	0.8631
No log	9.0	36	0.8721	0.2922	0.8719	0.9337
No log	10.0	40	0.6034	0.4875	0.6035	0.7769
No log	11.0	44	0.6405	0.4576	0.6406	0.8004
No log	12.0	48	0.5869	0.4885	0.5872	0.7663
No log	13.0	52	0.5911	0.4678	0.5916	0.7692
No log	14.0	56	0.6523	0.4536	0.6524	0.8077
No log	15.0	60	0.6784	0.4739	0.6784	0.8237
No log	16.0	64	0.7016	0.5257	0.7021	0.8379
No log	17.0	68	0.7382	0.4225	0.7382	0.8592
No log	18.0	72	0.6833	0.5038	0.6832	0.8266
No log	19.0	76	0.5937	0.5679	0.5938	0.7706
No log	20.0	80	0.6186	0.5511	0.6188	0.7866
No log	21.0	84	0.6940	0.4827	0.6940	0.8331
No log	22.0	88	0.8808	0.3375	0.8805	0.9383
No log	23.0	92	0.6427	0.5285	0.6430	0.8019
No log	24.0	96	0.6451	0.5036	0.6452	0.8033
No log	25.0	100	0.7443	0.4882	0.7442	0.8627
No log	26.0	104	0.5842	0.5384	0.5842	0.7643
No log	27.0	108	0.7464	0.5064	0.7462	0.8639
No log	28.0	112	0.7659	0.4475	0.7658	0.8751
No log	29.0	116	0.8849	0.3857	0.8847	0.9406
No log	30.0	120	0.5962	0.5174	0.5963	0.7722
No log	31.0	124	0.6714	0.4972	0.6714	0.8194
No log	32.0	128	0.6661	0.5066	0.6661	0.8162
No log	33.0	132	0.6253	0.5333	0.6253	0.7907
No log	34.0	136	0.6329	0.5252	0.6330	0.7956

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: Apr 5, 2025
Updated: Apr 5, 2025