BERT_AugV8_k3_task1_organization_sp060_lw030_fold0

genki10/BERT_AugV8_k3_task1_organization_sp060_lw030_fold0

BERT_AugV8_k3_task1_organization_sp060_lw030_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: Mar 27, 2025
Updated: Apr 3, 2025
SHA: 810f8abb

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Base models

Model card

From the Hugging Face model README

BERT_AugV8_k3_task1_organization_sp060_lw030_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: 1.2274
Qwk: 0.2177
Mse: 1.2274
Rmse: 1.1079

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	3	8.0775	0.0	8.0775	2.8421
No log	2.0	6	6.7138	0.0	6.7138	2.5911
No log	3.0	9	5.4029	0.0112	5.4029	2.3244
No log	4.0	12	4.1501	0.0039	4.1501	2.0372
No log	5.0	15	2.9392	0.0	2.9392	1.7144
No log	6.0	18	1.9654	0.0601	1.9654	1.4019
No log	7.0	21	1.4376	0.0316	1.4376	1.1990
No log	8.0	24	1.3207	0.0382	1.3207	1.1492
No log	9.0	27	1.3992	0.0897	1.3992	1.1829
No log	10.0	30	1.3950	0.0956	1.3950	1.1811
No log	11.0	33	1.0925	0.1035	1.0925	1.0452
No log	12.0	36	1.8725	0.1780	1.8725	1.3684
No log	13.0	39	1.0969	0.1865	1.0969	1.0473
No log	14.0	42	0.8174	0.2716	0.8174	0.9041
No log	15.0	45	1.0859	0.2960	1.0859	1.0421
No log	16.0	48	0.7101	0.3381	0.7101	0.8427
No log	17.0	51	0.6765	0.3733	0.6765	0.8225
No log	18.0	54	0.9386	0.3664	0.9386	0.9688
No log	19.0	57	0.6852	0.3226	0.6852	0.8278
No log	20.0	60	0.9914	0.3161	0.9914	0.9957
No log	21.0	63	0.8807	0.2865	0.8807	0.9384
No log	22.0	66	0.8506	0.2495	0.8506	0.9223
No log	23.0	69	1.3639	0.1748	1.3639	1.1679
No log	24.0	72	0.8908	0.2758	0.8908	0.9438
No log	25.0	75	1.6111	0.1733	1.6111	1.2693
No log	26.0	78	0.8526	0.3570	0.8526	0.9233
No log	27.0	81	1.1898	0.2596	1.1898	1.0908
No log	28.0	84	0.8478	0.3473	0.8478	0.9208
No log	29.0	87	0.9017	0.3447	0.9017	0.9496
No log	30.0	90	1.2971	0.1913	1.2971	1.1389
No log	31.0	93	0.8584	0.3675	0.8584	0.9265
No log	32.0	96	1.2274	0.2177	1.2274	1.1079

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 27, 2025
Updated: Apr 3, 2025