Version2ASAP_FineTuningBERT_AugV5_k7_task1_organization_k7_k7_fold0

genki10/Version2ASAP_FineTuningBERT_AugV5_k7_task1_organization_k7_k7_fold0

Version2ASAP_FineTuningBERT_AugV5_k7_task1_organization_k7_k7_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 27, 2025
Updated: Feb 27, 2025
SHA: c7ebd722

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Base models

Model card

From the Hugging Face model README

Version2ASAP_FineTuningBERT_AugV5_k7_task1_organization_k7_k7_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: 0.8533
Qwk: 0.3556
Mse: 0.8533
Rmse: 0.9237

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	6.7850	0.0	6.7850	2.6048
No log	2.0	12	4.2287	0.0039	4.2287	2.0564
No log	3.0	18	2.0618	0.0689	2.0618	1.4359
No log	4.0	24	1.3530	0.0316	1.3530	1.1632
No log	5.0	30	1.6448	0.0909	1.6448	1.2825
No log	6.0	36	1.8523	0.1763	1.8523	1.3610
No log	7.0	42	1.0759	0.0382	1.0759	1.0373
No log	8.0	48	0.9931	0.0698	0.9931	0.9965
No log	9.0	54	0.8679	0.1201	0.8679	0.9316
No log	10.0	60	0.9371	0.2287	0.9371	0.9680
No log	11.0	66	0.7105	0.3664	0.7105	0.8429
No log	12.0	72	0.6155	0.3729	0.6155	0.7845
No log	13.0	78	0.6151	0.4521	0.6151	0.7843
No log	14.0	84	0.6183	0.4016	0.6183	0.7863
No log	15.0	90	0.6244	0.4576	0.6244	0.7902
No log	16.0	96	0.6613	0.4783	0.6613	0.8132
No log	17.0	102	0.6476	0.5066	0.6476	0.8047
No log	18.0	108	0.6804	0.5048	0.6804	0.8249
No log	19.0	114	0.8947	0.4593	0.8947	0.9459
No log	20.0	120	0.8642	0.3595	0.8642	0.9296
No log	21.0	126	0.8825	0.3874	0.8825	0.9394
No log	22.0	132	0.8437	0.3466	0.8437	0.9185
No log	23.0	138	0.8705	0.2987	0.8705	0.9330
No log	24.0	144	0.8327	0.3991	0.8327	0.9126
No log	25.0	150	0.8181	0.4278	0.8181	0.9045
No log	26.0	156	0.8398	0.3550	0.8398	0.9164
No log	27.0	162	0.7956	0.3989	0.7956	0.8920
No log	28.0	168	0.8429	0.3591	0.8429	0.9181
No log	29.0	174	0.8321	0.4047	0.8321	0.9122
No log	30.0	180	0.7427	0.4836	0.7427	0.8618
No log	31.0	186	0.8455	0.4093	0.8455	0.9195
No log	32.0	192	0.7251	0.5005	0.7251	0.8515
No log	33.0	198	0.7675	0.4001	0.7675	0.8761
No log	34.0	204	0.8085	0.3658	0.8085	0.8992
No log	35.0	210	0.7377	0.4733	0.7377	0.8589
No log	36.0	216	0.7848	0.4685	0.7848	0.8859
No log	37.0	222	0.8533	0.3556	0.8533	0.9237

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: Feb 27, 2025
Updated: Feb 27, 2025