BERT_AugV8_k3_task1_organization_sp040_lw040_fold0

genki10/BERT_AugV8_k3_task1_organization_sp040_lw040_fold0

BERT_AugV8_k3_task1_organization_sp040_lw040_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 25, 2025
Updated: Mar 27, 2025
SHA: b51828e8

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Base models

Model card

From the Hugging Face model README

BERT_AugV8_k3_task1_organization_sp040_lw040_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: 0.9565
Qwk: 0.3691
Mse: 0.9565
Rmse: 0.9780

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	3	8.2663	0.0	8.2663	2.8751
No log	2.0	6	6.7892	0.0	6.7892	2.6056
No log	3.0	9	5.4983	0.0112	5.4983	2.3448
No log	4.0	12	4.2250	0.0039	4.2250	2.0555
No log	5.0	15	3.0304	0.0	3.0304	1.7408
No log	6.0	18	2.0113	0.0601	2.0113	1.4182
No log	7.0	21	1.4113	0.0316	1.4113	1.1880
No log	8.0	24	1.1936	0.0316	1.1936	1.0925
No log	9.0	27	1.3142	0.0484	1.3142	1.1464
No log	10.0	30	1.0264	0.0511	1.0264	1.0131
No log	11.0	33	1.6927	0.0455	1.6927	1.3011
No log	12.0	36	1.2307	0.1371	1.2307	1.1094
No log	13.0	39	0.8565	0.1942	0.8565	0.9255
No log	14.0	42	0.7472	0.3771	0.7472	0.8644
No log	15.0	45	0.7255	0.4051	0.7255	0.8517
No log	16.0	48	0.6310	0.4062	0.6310	0.7944
No log	17.0	51	0.6488	0.3499	0.6488	0.8055
No log	18.0	54	0.6666	0.3586	0.6666	0.8165
No log	19.0	57	0.7026	0.3817	0.7026	0.8382
No log	20.0	60	0.6564	0.3887	0.6564	0.8102
No log	21.0	63	1.4759	0.0924	1.4759	1.2149
No log	22.0	66	0.6420	0.4516	0.6420	0.8012
No log	23.0	69	0.6888	0.4611	0.6888	0.8300
No log	24.0	72	0.7618	0.4290	0.7618	0.8728
No log	25.0	75	0.8590	0.3556	0.8590	0.9268
No log	26.0	78	0.6968	0.4539	0.6968	0.8347
No log	27.0	81	0.8330	0.3719	0.8330	0.9127
No log	28.0	84	0.8178	0.3855	0.8178	0.9043
No log	29.0	87	0.8152	0.3868	0.8152	0.9029
No log	30.0	90	0.9088	0.3312	0.9088	0.9533
No log	31.0	93	0.8617	0.3677	0.8617	0.9283
No log	32.0	96	0.8518	0.3585	0.8518	0.9229
No log	33.0	99	0.7808	0.4420	0.7808	0.8836
No log	34.0	102	0.8183	0.4219	0.8183	0.9046
No log	35.0	105	0.9214	0.3399	0.9214	0.9599
No log	36.0	108	0.7737	0.4505	0.7737	0.8796
No log	37.0	111	1.0209	0.2834	1.0209	1.0104
No log	38.0	114	0.9565	0.3691	0.9565	0.9780

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 25, 2025
Updated: Mar 27, 2025