BERT_AugV8_k3_task1_organization_sp040_lw030_fold0

genki10/BERT_AugV8_k3_task1_organization_sp040_lw030_fold0

BERT_AugV8_k3_task1_organization_sp040_lw030_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: 9408b505

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Base models

Model card

From the Hugging Face model README

BERT_AugV8_k3_task1_organization_sp040_lw030_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: 0.8760
Qwk: 0.3346
Mse: 0.8760
Rmse: 0.9359

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	6.9912	0.0	6.9912	2.6441
No log	2.0	6	4.9599	0.0115	4.9599	2.2271
No log	3.0	9	3.5825	0.0115	3.5825	1.8928
No log	4.0	12	2.5034	0.1002	2.5034	1.5822
No log	5.0	15	1.8292	0.0419	1.8292	1.3525
No log	6.0	18	1.3683	0.0316	1.3683	1.1698
No log	7.0	21	0.9979	0.0316	0.9979	0.9990
No log	8.0	24	1.2051	0.0785	1.2051	1.0978
No log	9.0	27	1.1583	0.1594	1.1583	1.0762
No log	10.0	30	0.9219	0.2376	0.9219	0.9602
No log	11.0	33	0.8940	0.1642	0.8940	0.9455
No log	12.0	36	0.7044	0.3326	0.7044	0.8393
No log	13.0	39	0.9919	0.1285	0.9919	0.9959
No log	14.0	42	0.6764	0.3185	0.6764	0.8224
No log	15.0	45	0.6642	0.3357	0.6642	0.8150
No log	16.0	48	0.7816	0.2320	0.7816	0.8841
No log	17.0	51	0.9533	0.1712	0.9533	0.9764
No log	18.0	54	0.7574	0.3060	0.7574	0.8703
No log	19.0	57	0.9106	0.2093	0.9106	0.9543
No log	20.0	60	0.6518	0.4121	0.6518	0.8074
No log	21.0	63	0.9506	0.2881	0.9506	0.9750
No log	22.0	66	0.6848	0.4415	0.6848	0.8275
No log	23.0	69	0.9227	0.3214	0.9227	0.9606
No log	24.0	72	0.7787	0.4469	0.7787	0.8825
No log	25.0	75	1.0876	0.2638	1.0876	1.0429
No log	26.0	78	0.7197	0.5446	0.7197	0.8483
No log	27.0	81	1.0413	0.3654	1.0413	1.0204
No log	28.0	84	0.7290	0.4985	0.7290	0.8538
No log	29.0	87	0.8605	0.4177	0.8605	0.9276
No log	30.0	90	0.9613	0.2835	0.9613	0.9805
No log	31.0	93	0.9058	0.3600	0.9058	0.9517
No log	32.0	96	0.7583	0.4933	0.7583	0.8708
No log	33.0	99	0.8551	0.3946	0.8551	0.9247
No log	34.0	102	0.8246	0.3921	0.8246	0.9081
No log	35.0	105	1.0918	0.2383	1.0918	1.0449
No log	36.0	108	0.8333	0.4124	0.8333	0.9128
No log	37.0	111	0.9108	0.3769	0.9108	0.9544
No log	38.0	114	0.7810	0.4055	0.7810	0.8838
No log	39.0	117	1.0358	0.2328	1.0358	1.0177
No log	40.0	120	0.7885	0.4411	0.7885	0.8880
No log	41.0	123	0.8760	0.3346	0.8760	0.9359

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