Version12LowDevASAP_FineTuningBERT_AugV12_k15_task1_organization_k15_k15_fold0

genki10/Version12LowDevASAP_FineTuningBERT_AugV12_k15_task1_organization_k15_k15_fold0

Version12LowDevASAP_FineTuningBERT_AugV12_k15_task1_organization_k15_k15_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: Mar 11, 2025
Updated: Mar 11, 2025
SHA: b46b6056

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Base models

Model card

From the Hugging Face model README

Version12LowDevASAP_FineTuningBERT_AugV12_k15_task1_organization_k15_k15_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: 0.6827
Qwk: 0.5867
Mse: 0.6827
Rmse: 0.8262

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	4	8.2015	0.0	8.2015	2.8638
No log	2.0	8	6.4398	-0.0076	6.4398	2.5377
No log	3.0	12	4.6493	0.0	4.6493	2.1562
No log	4.0	16	3.1248	0.0	3.1248	1.7677
No log	5.0	20	1.9225	0.0	1.9225	1.3865
No log	6.0	24	1.1932	0.0	1.1932	1.0924
No log	7.0	28	0.8743	0.2040	0.8743	0.9350
No log	8.0	32	0.8222	0.0	0.8222	0.9067
No log	9.0	36	0.9358	0.0	0.9358	0.9674
No log	10.0	40	0.9776	0.2973	0.9776	0.9887
No log	11.0	44	0.7723	0.3689	0.7723	0.8788
No log	12.0	48	0.6494	0.4846	0.6494	0.8059
No log	13.0	52	0.6034	0.6358	0.6034	0.7768
No log	14.0	56	0.4582	0.6181	0.4582	0.6769
No log	15.0	60	0.5063	0.6496	0.5063	0.7115
No log	16.0	64	0.5435	0.6491	0.5435	0.7372
No log	17.0	68	0.6087	0.5870	0.6087	0.7802
No log	18.0	72	0.5737	0.6116	0.5737	0.7574
No log	19.0	76	0.6174	0.5398	0.6174	0.7857
No log	20.0	80	0.6344	0.5812	0.6344	0.7965
No log	21.0	84	0.5476	0.5885	0.5476	0.7400
No log	22.0	88	0.5582	0.6030	0.5582	0.7471
No log	23.0	92	0.6680	0.6118	0.6680	0.8173
No log	24.0	96	0.5500	0.6001	0.5500	0.7416
No log	25.0	100	0.7737	0.5469	0.7737	0.8796
No log	26.0	104	0.6568	0.5383	0.6568	0.8104
No log	27.0	108	0.5398	0.5984	0.5398	0.7347
No log	28.0	112	0.5322	0.6335	0.5322	0.7295
No log	29.0	116	0.5166	0.5612	0.5166	0.7187
No log	30.0	120	0.6029	0.6023	0.6029	0.7764
No log	31.0	124	0.5312	0.5554	0.5312	0.7288
No log	32.0	128	0.5409	0.5891	0.5409	0.7354
No log	33.0	132	0.5964	0.6220	0.5964	0.7723
No log	34.0	136	0.5105	0.5996	0.5105	0.7145
No log	35.0	140	0.6827	0.5867	0.6827	0.8262

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 11, 2025
Updated: Mar 11, 2025