cfd_model2

bkissinger10/cfd_model2

cfd_model2 is a token classification model from bkissinger10. Use it when you need labels on individual words, such as names. 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

19% of all-time downloads

All-time downloads

Public

Parameters

334M

1.3 GB on disk

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.safetensors1.3 GB · 100%

At a glance

Task: Token Classification
Library: transformers
License: apache-2.0
Model type: bert
Access: Public
Created: Jul 11, 2024
Updated: Jul 12, 2024
SHA: 657a80a2

Try a prompt

Base models

google-bert/bert-large-uncased

Model card

From the Hugging Face model README

cfd_model2

This model is a fine-tuned version of google-bert/bert-large-uncased on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.0066
Precision: 0.9978
Recall: 0.9987
F1: 0.9982
Accuracy: 0.9986

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: 3e-05
train_batch_size: 4
eval_batch_size: 4
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 4

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.0493	0.19	100	0.0352	0.9890	0.9930	0.9910	0.9937
0.0103	0.39	200	0.0273	0.9886	0.9956	0.9921	0.9946
0.0011	0.58	300	0.0190	0.9921	0.9978	0.9950	0.9960
0.0247	0.77	400	0.0167	0.9978	0.9943	0.9960	0.9968
0.0003	0.97	500	0.0269	0.9926	0.9978	0.9952	0.9961
0.0036	1.16	600	0.0133	0.9960	0.9960	0.9960	0.9968
0.0008	1.35	700	0.0222	0.9926	0.9987	0.9956	0.9965
0.0003	1.55	800	0.0287	0.9895	0.9974	0.9934	0.9953
0.0005	1.74	900	0.0132	0.9934	0.9982	0.9958	0.9970
0.0024	1.93	1000	0.0123	0.9952	0.9982	0.9967	0.9977
0.0007	2.13	1100	0.0099	0.9969	0.9943	0.9956	0.9965
0.0005	2.32	1200	0.0087	0.9978	0.9965	0.9971	0.9977
0.001	2.51	1300	0.0055	0.9974	0.9991	0.9982	0.9986
0.0002	2.71	1400	0.0049	0.9974	0.9982	0.9978	0.9986
0.0004	2.9	1500	0.0065	0.9969	0.9982	0.9976	0.9984
0.0002	3.09	1600	0.0071	0.9969	0.9978	0.9974	0.9982
0.0001	3.29	1700	0.0077	0.9974	0.9978	0.9976	0.9984
0.0002	3.48	1800	0.0072	0.9974	0.9978	0.9976	0.9984
0.0005	3.68	1900	0.0072	0.9974	0.9978	0.9976	0.9984
0.0207	3.87	2000	0.0066	0.9978	0.9987	0.9982	0.9986

Framework versions

Transformers 4.36.2
Pytorch 2.1.2+cu121
Datasets 2.14.6
Tokenizers 0.15.0

Task: Token Classification
Library: transformers
Type: bert
License: apache-2.0
Created: Jul 11, 2024
Updated: Jul 12, 2024