ASAP_FineTuningBERT_AugV9_k7_task1_organization_k7_k7_fold3

genki10/ASAP_FineTuningBERT_AugV9_k7_task1_organization_k7_k7_fold3

ASAP_FineTuningBERT_AugV9_k7_task1_organization_k7_k7_fold3 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 12, 2025
Updated: Feb 12, 2025
SHA: f754b456

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Base models

Model card

From the Hugging Face model README

ASAP_FineTuningBERT_AugV9_k7_task1_organization_k7_k7_fold3

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: 1.0843
Qwk: 0.3480
Mse: 1.0855
Rmse: 1.0419

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	6.6444	0.0	6.6430	2.5774
No log	2.0	12	3.3687	0.0076	3.3677	1.8351
No log	3.0	18	1.6206	0.0365	1.6199	1.2727
No log	4.0	24	1.6320	0.0365	1.6312	1.2772
No log	5.0	30	1.2676	0.0463	1.2671	1.1257
No log	6.0	36	0.9887	0.1783	0.9886	0.9943
No log	7.0	42	0.9312	0.3057	0.9317	0.9653
No log	8.0	48	0.6996	0.3501	0.7000	0.8366
No log	9.0	54	0.9098	0.3758	0.9110	0.9544
No log	10.0	60	1.1406	0.3018	1.1421	1.0687
No log	11.0	66	1.3914	0.2302	1.3927	1.1801
No log	12.0	72	0.7618	0.4441	0.7628	0.8734
No log	13.0	78	0.9345	0.4038	0.9358	0.9674
No log	14.0	84	0.8121	0.4344	0.8131	0.9017
No log	15.0	90	0.8195	0.4231	0.8204	0.9058
No log	16.0	96	0.8902	0.4074	0.8913	0.9441
No log	17.0	102	0.8737	0.4057	0.8749	0.9353
No log	18.0	108	0.8339	0.4319	0.8350	0.9138
No log	19.0	114	0.8829	0.4161	0.8840	0.9402
No log	20.0	120	0.8485	0.4189	0.8496	0.9217
No log	21.0	126	0.8634	0.4395	0.8645	0.9298
No log	22.0	132	1.1161	0.3548	1.1172	1.0570
No log	23.0	138	1.0503	0.3756	1.0513	1.0253
No log	24.0	144	1.0888	0.3205	1.0899	1.0440
No log	25.0	150	0.9704	0.3559	0.9715	0.9856
No log	26.0	156	1.0287	0.3517	1.0298	1.0148
No log	27.0	162	1.0490	0.3389	1.0500	1.0247
No log	28.0	168	1.2156	0.2793	1.2166	1.1030
No log	29.0	174	1.2124	0.2948	1.2136	1.1016
No log	30.0	180	0.9743	0.3770	0.9754	0.9876
No log	31.0	186	1.0418	0.3714	1.0430	1.0213
No log	32.0	192	1.0843	0.3480	1.0855	1.0419

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.21.0

Task: Text Classification
Library: transformers
Type: bert
License: apache-2.0
Created: Feb 12, 2025
Updated: Feb 12, 2025