Version19ASAP_FineTuningBERT_AugV19_k10_task1_organization_k10_k10_fold0

genki10/Version19ASAP_FineTuningBERT_AugV19_k10_task1_organization_k10_k10_fold0

Version19ASAP_FineTuningBERT_AugV19_k10_task1_organization_k10_k10_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. --

Downloads · 30 days

37% of all-time downloads

All-time downloads

Public

Repo size

23.2 GB

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.bin876 MB · 100%

At a glance

Task: Text Classification
Library: transformers
License: apache-2.0
Model type: bert
Access: Public
Created: Mar 9, 2025
Updated: Mar 9, 2025
SHA: 2e242837

Try a prompt

Base models

Model card

From the Hugging Face model README

Version19ASAP_FineTuningBERT_AugV19_k10_task1_organization_k10_k10_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: 0.4956
Qwk: 0.6520
Mse: 0.4956
Rmse: 0.7040

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	3	8.4663	0.0	8.4663	2.9097
No log	2.0	6	6.9746	0.0	6.9746	2.6410
No log	3.0	9	6.0846	-0.0052	6.0846	2.4667
No log	4.0	12	4.6523	0.0115	4.6523	2.1569
No log	5.0	15	3.5727	0.0039	3.5727	1.8902
No log	6.0	18	2.6362	0.0031	2.6362	1.6236
No log	7.0	21	1.8438	0.0484	1.8438	1.3579
No log	8.0	24	1.2535	0.0316	1.2535	1.1196
No log	9.0	27	0.9612	0.0106	0.9612	0.9804
No log	10.0	30	0.7870	0.2170	0.7870	0.8872
No log	11.0	33	0.7764	0.1076	0.7764	0.8811
No log	12.0	36	0.7764	0.0860	0.7764	0.8811
No log	13.0	39	0.9888	0.0689	0.9888	0.9944
No log	14.0	42	0.9001	0.3346	0.9001	0.9487
No log	15.0	45	1.3006	0.2170	1.3006	1.1404
No log	16.0	48	0.8025	0.4282	0.8025	0.8958
No log	17.0	51	1.1603	0.3749	1.1603	1.0772
No log	18.0	54	0.5143	0.5622	0.5143	0.7172
No log	19.0	57	0.6848	0.6075	0.6848	0.8275
No log	20.0	60	1.4182	0.2813	1.4182	1.1909
No log	21.0	63	1.1097	0.4275	1.1097	1.0534
No log	22.0	66	0.7365	0.6085	0.7365	0.8582
No log	23.0	69	0.6622	0.5755	0.6622	0.8138
No log	24.0	72	0.5373	0.6349	0.5373	0.7330
No log	25.0	75	0.4705	0.6554	0.4705	0.6859
No log	26.0	78	0.6117	0.6141	0.6117	0.7821
No log	27.0	81	0.5423	0.6194	0.5423	0.7364
No log	28.0	84	0.5098	0.6357	0.5098	0.7140
No log	29.0	87	0.4930	0.6402	0.4930	0.7022
No log	30.0	90	0.6259	0.5922	0.6259	0.7911
No log	31.0	93	0.4909	0.6174	0.4909	0.7006
No log	32.0	96	0.6629	0.6030	0.6629	0.8142
No log	33.0	99	0.4833	0.6202	0.4833	0.6952
No log	34.0	102	0.4688	0.6231	0.4688	0.6847
No log	35.0	105	0.6106	0.6219	0.6106	0.7814
No log	36.0	108	0.4932	0.6238	0.4932	0.7023
No log	37.0	111	0.4910	0.6134	0.4910	0.7007
No log	38.0	114	0.6820	0.6046	0.6820	0.8258
No log	39.0	117	0.4785	0.6295	0.4785	0.6917
No log	40.0	120	0.5431	0.6410	0.5431	0.7369
No log	41.0	123	0.5325	0.6310	0.5325	0.7297
No log	42.0	126	0.4959	0.6136	0.4959	0.7042
No log	43.0	129	0.8291	0.5614	0.8291	0.9106
No log	44.0	132	0.5648	0.6329	0.5648	0.7515
No log	45.0	135	0.4956	0.6520	0.4956	0.7040

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 9, 2025
Updated: Mar 9, 2025