Trial2BERT_AugV8_k5_task1_organization_sp010_lw020_fold0

genki10/Trial2BERT_AugV8_k5_task1_organization_sp010_lw020_fold0

Trial2BERT_AugV8_k5_task1_organization_sp010_lw020_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: Apr 5, 2025
Updated: Apr 5, 2025
SHA: e2d61d80

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Base models

Model card

From the Hugging Face model README

Trial2BERT_AugV8_k5_task1_organization_sp010_lw020_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: 0.5769
Qwk: 0.5250
Mse: 0.5769
Rmse: 0.7596

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: 150

Training results

Training Loss	Epoch	Step	Validation Loss	Qwk	Mse	Rmse
No log	1.0	4	7.6641	0.0	7.6641	2.7684
No log	2.0	8	5.8270	0.0182	5.8270	2.4139
No log	3.0	12	4.1529	0.0039	4.1529	2.0379
No log	4.0	16	2.5474	0.0142	2.5474	1.5961
No log	5.0	20	1.5186	0.0316	1.5186	1.2323
No log	6.0	24	1.0112	0.0212	1.0112	1.0056
No log	7.0	28	1.6262	0.0511	1.6262	1.2752
No log	8.0	32	0.7886	0.3852	0.7886	0.8880
No log	9.0	36	1.0233	-0.1868	1.0233	1.0116
No log	10.0	40	0.9339	-0.0552	0.9339	0.9664
No log	11.0	44	0.8477	0.2319	0.8477	0.9207
No log	12.0	48	1.0007	0.1308	1.0007	1.0004
No log	13.0	52	0.7923	0.3012	0.7923	0.8901
No log	14.0	56	0.6040	0.3302	0.6040	0.7772
No log	15.0	60	0.6923	0.2928	0.6923	0.8320
No log	16.0	64	0.6608	0.3285	0.6608	0.8129
No log	17.0	68	0.6514	0.3898	0.6514	0.8071
No log	18.0	72	0.5834	0.4853	0.5834	0.7638
No log	19.0	76	0.6053	0.4964	0.6053	0.7780
No log	20.0	80	0.6995	0.4676	0.6995	0.8364
No log	21.0	84	0.7453	0.4560	0.7453	0.8633
No log	22.0	88	0.6381	0.5423	0.6381	0.7988
No log	23.0	92	0.6496	0.5777	0.6496	0.8060
No log	24.0	96	0.6714	0.5086	0.6714	0.8194
No log	25.0	100	0.6937	0.4538	0.6937	0.8329
No log	26.0	104	0.7453	0.4113	0.7453	0.8633
No log	27.0	108	0.6548	0.4881	0.6548	0.8092
No log	28.0	112	0.7183	0.4776	0.7183	0.8475
No log	29.0	116	0.8121	0.3051	0.8121	0.9012
No log	30.0	120	0.7126	0.5036	0.7126	0.8441
No log	31.0	124	0.9325	0.3913	0.9325	0.9657
No log	32.0	128	0.5800	0.5886	0.5800	0.7616
No log	33.0	132	0.7158	0.4770	0.7158	0.8461
No log	34.0	136	0.6415	0.5162	0.6415	0.8009
No log	35.0	140	0.7068	0.4012	0.7068	0.8407
No log	36.0	144	0.6268	0.4532	0.6268	0.7917
No log	37.0	148	0.6612	0.4407	0.6612	0.8131
No log	38.0	152	0.6827	0.4791	0.6827	0.8262
No log	39.0	156	0.6275	0.5227	0.6275	0.7922
No log	40.0	160	0.6420	0.4772	0.6420	0.8012
No log	41.0	164	0.6751	0.4192	0.6751	0.8216
No log	42.0	168	0.6722	0.4531	0.6722	0.8199
No log	43.0	172	0.6290	0.5152	0.6290	0.7931
No log	44.0	176	0.7164	0.4104	0.7164	0.8464
No log	45.0	180	0.5856	0.5055	0.5856	0.7652
No log	46.0	184	0.7516	0.4580	0.7516	0.8670
No log	47.0	188	0.5769	0.5250	0.5769	0.7596

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: Apr 5, 2025
Updated: Apr 5, 2025