Trial3BERT_AugV8_k5_task1_organization_sp020_lw070_fold4

genki10/Trial3BERT_AugV8_k5_task1_organization_sp020_lw070_fold4

Trial3BERT_AugV8_k5_task1_organization_sp020_lw070_fold4 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 13, 2025
SHA: 449e737a

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Base models

Model card

From the Hugging Face model README

Trial3BERT_AugV8_k5_task1_organization_sp020_lw070_fold4

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: 1.0027
Qwk: 0.2734
Mse: 1.0027
Rmse: 1.0014

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	7.1122	0.0018	7.1122	2.6669
No log	2.0	8	5.2147	0.0118	5.2147	2.2836
No log	3.0	12	3.4481	0.0040	3.4481	1.8569
No log	4.0	16	2.0323	0.0696	2.0323	1.4256
No log	5.0	20	1.4632	0.0213	1.4632	1.2096
No log	6.0	24	1.2635	0.0420	1.2635	1.1241
No log	7.0	28	1.1849	0.0996	1.1849	1.0885
No log	8.0	32	0.9608	0.0682	0.9608	0.9802
No log	9.0	36	0.9054	0.0346	0.9054	0.9515
No log	10.0	40	0.7385	0.4389	0.7385	0.8593
No log	11.0	44	0.7390	0.4591	0.7390	0.8597
No log	12.0	48	0.6338	0.4272	0.6338	0.7961
No log	13.0	52	0.6483	0.4072	0.6483	0.8052
No log	14.0	56	0.8915	0.3825	0.8915	0.9442
No log	15.0	60	0.8758	0.2820	0.8758	0.9359
No log	16.0	64	0.6202	0.4758	0.6202	0.7875
No log	17.0	68	1.9174	0.0668	1.9174	1.3847
No log	18.0	72	0.5533	0.5404	0.5533	0.7438
No log	19.0	76	1.9669	0.0046	1.9669	1.4024
No log	20.0	80	0.7690	0.4012	0.7690	0.8769
No log	21.0	84	1.2565	0.2404	1.2565	1.1210
No log	22.0	88	1.2588	0.1872	1.2588	1.1220
No log	23.0	92	0.8074	0.4242	0.8074	0.8986
No log	24.0	96	1.2962	0.1716	1.2962	1.1385
No log	25.0	100	1.1622	0.2417	1.1622	1.0780
No log	26.0	104	0.8822	0.3566	0.8822	0.9393
No log	27.0	108	1.0725	0.2741	1.0725	1.0356
No log	28.0	112	1.4070	0.1596	1.4070	1.1862
No log	29.0	116	1.1130	0.2052	1.1130	1.0550
No log	30.0	120	0.9115	0.3444	0.9115	0.9547
No log	31.0	124	1.5003	0.1218	1.5003	1.2249
No log	32.0	128	0.9093	0.3304	0.9093	0.9536
No log	33.0	132	1.0027	0.2734	1.0027	1.0014

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 13, 2025