ASAP_FineTuningBERT_AugV7_k10_task1_organization_k10_k10_fold0

genki10/ASAP_FineTuningBERT_AugV7_k10_task1_organization_k10_k10_fold0

ASAP_FineTuningBERT_AugV7_k10_task1_organization_k10_k10_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: Feb 9, 2025
Updated: Feb 9, 2025
SHA: 89c0886a

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Base models

Model card

From the Hugging Face model README

ASAP_FineTuningBERT_AugV7_k10_task1_organization_k10_k10_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: 0.6612
Qwk: 0.4911
Mse: 0.6612
Rmse: 0.8131

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	8	5.8460	0.0232	5.8460	2.4179
No log	2.0	16	2.5502	0.0163	2.5502	1.5969
No log	3.0	24	1.2035	0.0316	1.2035	1.0970
No log	4.0	32	1.5537	0.0382	1.5537	1.2465
No log	5.0	40	1.1236	0.0548	1.1236	1.0600
No log	6.0	48	0.9926	0.1499	0.9926	0.9963
No log	7.0	56	0.7859	0.3323	0.7859	0.8865
No log	8.0	64	0.8076	0.3399	0.8076	0.8986
No log	9.0	72	0.8293	0.3741	0.8293	0.9107
No log	10.0	80	0.7914	0.4938	0.7914	0.8896
No log	11.0	88	0.7565	0.4660	0.7565	0.8697
No log	12.0	96	0.9052	0.4337	0.9052	0.9514
No log	13.0	104	0.7648	0.4167	0.7648	0.8745
No log	14.0	112	0.7716	0.4750	0.7716	0.8784
No log	15.0	120	0.7536	0.4329	0.7536	0.8681
No log	16.0	128	0.6861	0.4928	0.6861	0.8283
No log	17.0	136	0.8468	0.4357	0.8468	0.9202
No log	18.0	144	0.7601	0.4579	0.7601	0.8718
No log	19.0	152	0.6598	0.5184	0.6598	0.8123
No log	20.0	160	0.7985	0.4545	0.7985	0.8936
No log	21.0	168	0.7318	0.4829	0.7318	0.8554
No log	22.0	176	0.7609	0.4702	0.7609	0.8723
No log	23.0	184	0.6532	0.4996	0.6532	0.8082
No log	24.0	192	0.7201	0.4820	0.7201	0.8486
No log	25.0	200	0.6367	0.5053	0.6367	0.7980
No log	26.0	208	0.7414	0.4807	0.7414	0.8610
No log	27.0	216	0.7129	0.4949	0.7129	0.8443
No log	28.0	224	0.6726	0.4785	0.6726	0.8201
No log	29.0	232	0.6612	0.4911	0.6612	0.8131

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 9, 2025
Updated: Feb 9, 2025