ASAP_FineTuningBERT_AugV21_k5_task1_organization_k5_k5_fold4

genki10/ASAP_FineTuningBERT_AugV21_k5_task1_organization_k5_k5_fold4

ASAP_FineTuningBERT_AugV21_k5_task1_organization_k5_k5_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: Mar 15, 2025
Updated: Mar 15, 2025
SHA: 4f0c8ff0

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Base models

Model card

From the Hugging Face model README

ASAP_FineTuningBERT_AugV21_k5_task1_organization_k5_k5_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: 0.7336
Qwk: 0.5614
Mse: 0.7336
Rmse: 0.8565

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	5	8.8736	0.0	8.8736	2.9789
No log	2.0	10	5.3223	0.0269	5.3223	2.3070
No log	3.0	15	2.9534	0.0040	2.9534	1.7185
No log	4.0	20	1.5576	0.0522	1.5576	1.2480
No log	5.0	25	1.3718	0.0686	1.3718	1.1712
No log	6.0	30	1.1368	0.0648	1.1368	1.0662
No log	7.0	35	0.8815	0.2015	0.8815	0.9389
No log	8.0	40	0.8268	0.4178	0.8268	0.9093
No log	9.0	45	0.6481	0.4826	0.6481	0.8050
No log	10.0	50	0.6438	0.5022	0.6438	0.8024
No log	11.0	55	0.6565	0.5633	0.6565	0.8103
No log	12.0	60	1.0457	0.5037	1.0457	1.0226
No log	13.0	65	0.7515	0.6050	0.7515	0.8669
No log	14.0	70	0.8302	0.5603	0.8302	0.9111
No log	15.0	75	0.7675	0.5466	0.7675	0.8761
No log	16.0	80	0.7852	0.5650	0.7852	0.8861
No log	17.0	85	0.7357	0.5670	0.7357	0.8578
No log	18.0	90	0.7627	0.5831	0.7627	0.8733
No log	19.0	95	0.9236	0.5474	0.9236	0.9610
No log	20.0	100	0.7636	0.5316	0.7636	0.8738
No log	21.0	105	0.9240	0.5054	0.9240	0.9612
No log	22.0	110	0.7492	0.5620	0.7492	0.8655
No log	23.0	115	0.7273	0.5613	0.7273	0.8528
No log	24.0	120	1.0361	0.5019	1.0361	1.0179
No log	25.0	125	0.7330	0.5671	0.7330	0.8561
No log	26.0	130	0.7686	0.5710	0.7686	0.8767
No log	27.0	135	0.8575	0.5269	0.8575	0.9260
No log	28.0	140	0.8565	0.5332	0.8565	0.9255
No log	29.0	145	0.7685	0.5737	0.7685	0.8766
No log	30.0	150	0.9175	0.5189	0.9175	0.9579
No log	31.0	155	0.7315	0.5532	0.7315	0.8553
No log	32.0	160	0.7772	0.5386	0.7772	0.8816
No log	33.0	165	0.7612	0.5526	0.7612	0.8725
No log	34.0	170	0.7451	0.5538	0.7451	0.8632
No log	35.0	175	0.7180	0.5839	0.7180	0.8474
No log	36.0	180	0.7512	0.5535	0.7512	0.8667
No log	37.0	185	0.7930	0.5276	0.7930	0.8905
No log	38.0	190	0.8625	0.5344	0.8625	0.9287
No log	39.0	195	1.0383	0.4903	1.0383	1.0190
No log	40.0	200	0.7250	0.5733	0.7250	0.8515
No log	41.0	205	0.9133	0.5214	0.9133	0.9557
No log	42.0	210	0.7516	0.5490	0.7516	0.8670
No log	43.0	215	0.7336	0.5614	0.7336	0.8565

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 15, 2025
Updated: Mar 15, 2025