Trial3BERT_AugV8_k7_task1_organization_sp010_lw020_fold0

genki10/Trial3BERT_AugV8_k7_task1_organization_sp010_lw020_fold0

Trial3BERT_AugV8_k7_task1_organization_sp010_lw020_fold0 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 8, 2025
Updated: Apr 8, 2025
SHA: 4f8a7c50

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Base models

Model card

From the Hugging Face model README

Trial3BERT_AugV8_k7_task1_organization_sp010_lw020_fold0

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: 0.6986
Qwk: 0.4188
Mse: 0.6986
Rmse: 0.8358

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	5	5.5287	0.0160	5.5287	2.3513
No log	2.0	10	2.3021	0.1679	2.3021	1.5173
No log	3.0	15	1.2610	0.0418	1.2610	1.1230
No log	4.0	20	0.8562	0.1524	0.8562	0.9253
No log	5.0	25	0.9816	0.0866	0.9816	0.9908
No log	6.0	30	0.8601	0.3195	0.8601	0.9274
No log	7.0	35	1.0240	0.2436	1.0240	1.0119
No log	8.0	40	1.0260	0.3591	1.0260	1.0129
No log	9.0	45	0.7326	0.4569	0.7326	0.8559
No log	10.0	50	0.5732	0.4212	0.5732	0.7571
No log	11.0	55	0.5350	0.4823	0.5350	0.7315
No log	12.0	60	0.7777	0.4581	0.7777	0.8819
No log	13.0	65	0.9713	0.4225	0.9713	0.9856
No log	14.0	70	0.7692	0.4574	0.7692	0.8770
No log	15.0	75	0.6701	0.5140	0.6701	0.8186
No log	16.0	80	0.6909	0.4301	0.6909	0.8312
No log	17.0	85	0.5891	0.5372	0.5891	0.7675
No log	18.0	90	0.5573	0.5291	0.5573	0.7465
No log	19.0	95	0.7020	0.4196	0.7020	0.8378
No log	20.0	100	0.6692	0.4275	0.6692	0.8181
No log	21.0	105	0.6059	0.4671	0.6059	0.7784
No log	22.0	110	0.5900	0.5118	0.5900	0.7681
No log	23.0	115	0.9138	0.3823	0.9138	0.9560
No log	24.0	120	0.8829	0.3691	0.8829	0.9396
No log	25.0	125	0.7277	0.3728	0.7277	0.8531
No log	26.0	130	0.7087	0.4135	0.7087	0.8419
No log	27.0	135	0.7446	0.3902	0.7446	0.8629
No log	28.0	140	0.6560	0.4440	0.6560	0.8099
No log	29.0	145	0.7177	0.4058	0.7177	0.8472
No log	30.0	150	0.7023	0.3972	0.7023	0.8380
No log	31.0	155	0.7462	0.3977	0.7462	0.8638
No log	32.0	160	0.6986	0.4188	0.6986	0.8358

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 8, 2025
Updated: Apr 8, 2025