Version_Test_ASAP_FineTuningBERT_AugV14_k10_task1_organization_k10_k10_fold1

genki10/Version_Test_ASAP_FineTuningBERT_AugV14_k10_task1_organization_k10_k10_fold1

Version_Test_ASAP_FineTuningBERT_AugV14_k10_task1_organization_k10_k10_fold1 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

41% of all-time downloads

All-time downloads

Public

Repo size

17.5 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: Feb 20, 2025
Updated: Feb 20, 2025
SHA: 8627e285

Try a prompt

Base models

Model card

From the Hugging Face model README

Version_Test_ASAP_FineTuningBERT_AugV14_k10_task1_organization_k10_k10_fold1

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: 0.7059
Qwk: 0.6169
Mse: 0.7060
Rmse: 0.8403

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	7	5.6121	0.0616	5.6098	2.3685
No log	2.0	14	2.4621	0.0290	2.4601	1.5685
No log	3.0	21	1.1146	0.0	1.1131	1.0550
No log	4.0	28	0.9268	0.0518	0.9258	0.9622
No log	5.0	35	0.7784	0.3557	0.7773	0.8816
No log	6.0	42	0.7633	0.4115	0.7623	0.8731
No log	7.0	49	0.5587	0.5647	0.5580	0.7470
No log	8.0	56	0.7821	0.5200	0.7813	0.8839
No log	9.0	63	0.4913	0.6618	0.4909	0.7007
No log	10.0	70	0.4747	0.6340	0.4741	0.6885
No log	11.0	77	0.5096	0.6715	0.5093	0.7136
No log	12.0	84	0.5876	0.6538	0.5875	0.7665
No log	13.0	91	0.5266	0.6728	0.5264	0.7255
No log	14.0	98	0.5108	0.6134	0.5102	0.7143
No log	15.0	105	0.5589	0.6456	0.5588	0.7475
No log	16.0	112	0.5505	0.6112	0.5499	0.7416
No log	17.0	119	0.5948	0.6257	0.5943	0.7709
No log	18.0	126	0.8448	0.5696	0.8450	0.9192
No log	19.0	133	0.9808	0.5183	0.9812	0.9906
No log	20.0	140	1.1641	0.4694	1.1647	1.0792
No log	21.0	147	0.8094	0.5828	0.8096	0.8998
No log	22.0	154	0.5612	0.6496	0.5610	0.7490
No log	23.0	161	0.6263	0.6553	0.6262	0.7914
No log	24.0	168	0.5409	0.6670	0.5408	0.7354
No log	25.0	175	0.5971	0.6546	0.5970	0.7727
No log	26.0	182	0.7787	0.6067	0.7789	0.8825
No log	27.0	189	0.6775	0.6311	0.6775	0.8231
No log	28.0	196	0.5800	0.6415	0.5798	0.7614
No log	29.0	203	0.7138	0.6124	0.7139	0.8449
No log	30.0	210	0.5582	0.6278	0.5580	0.7470
No log	31.0	217	0.6497	0.6336	0.6497	0.8060
No log	32.0	224	0.5363	0.6552	0.5361	0.7322
No log	33.0	231	0.7059	0.6169	0.7060	0.8403

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 20, 2025
Updated: Feb 20, 2025