ASAP_FineTuningBERT_AugV8_k7_task1_organization_k7_fold2

genki10/ASAP_FineTuningBERT_AugV8_k7_task1_organization_k7_fold2

ASAP_FineTuningBERT_AugV8_k7_task1_organization_k7_fold2 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: Feb 5, 2025
Updated: Feb 5, 2025
SHA: 2718de92

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Base models

Model card

From the Hugging Face model README

ASAP_FineTuningBERT_AugV8_k7_task1_organization_k7_fold2

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: 0.7627
Qwk: 0.4047
Mse: 0.7625
Rmse: 0.8732

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: 100

Training results

Training Loss	Epoch	Step	Validation Loss	Qwk	Mse	Rmse
No log	1.0	6	6.6107	0.0	6.6109	2.5712
No log	2.0	12	3.1583	0.0039	3.1588	1.7773
No log	3.0	18	1.6049	0.0475	1.6053	1.2670
No log	4.0	24	0.9908	0.0345	0.9911	0.9955
No log	5.0	30	1.2025	0.0372	1.2029	1.0968
No log	6.0	36	2.7715	0.0618	2.7718	1.6649
No log	7.0	42	0.9362	0.1348	0.9365	0.9677
No log	8.0	48	0.8577	0.2163	0.8579	0.9262
No log	9.0	54	1.6384	0.1629	1.6384	1.2800
No log	10.0	60	0.8679	0.3417	0.8678	0.9316
No log	11.0	66	0.8266	0.3512	0.8264	0.9091
No log	12.0	72	1.0534	0.2858	1.0529	1.0261
No log	13.0	78	0.9238	0.3656	0.9236	0.9610
No log	14.0	84	0.9142	0.3352	0.9138	0.9559
No log	15.0	90	1.2980	0.2832	1.2975	1.1391
No log	16.0	96	0.8928	0.4046	0.8927	0.9448
No log	17.0	102	0.8889	0.3877	0.8886	0.9427
No log	18.0	108	0.8452	0.4214	0.8450	0.9193
No log	19.0	114	0.8363	0.4175	0.8360	0.9143
No log	20.0	120	0.8050	0.3902	0.8048	0.8971
No log	21.0	126	0.7981	0.4408	0.7978	0.8932
No log	22.0	132	0.8908	0.3968	0.8905	0.9437
No log	23.0	138	1.1619	0.3113	1.1616	1.0778
No log	24.0	144	0.9850	0.3529	0.9847	0.9923
No log	25.0	150	0.9268	0.3409	0.9266	0.9626
No log	26.0	156	0.8332	0.4100	0.8330	0.9127
No log	27.0	162	0.8449	0.3692	0.8447	0.9191
No log	28.0	168	1.1609	0.2914	1.1607	1.0773
No log	29.0	174	0.8792	0.3873	0.8790	0.9375
No log	30.0	180	0.7641	0.4169	0.7638	0.8740
No log	31.0	186	0.7627	0.4047	0.7625	0.8732

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.21.0

Task: Text Classification
Library: transformers
Type: bert
License: apache-2.0
Created: Feb 5, 2025
Updated: Feb 5, 2025