cso_ner – AI Model by myselfronin | AlphaNeural AI

You can deploy this model and start earning money today!

myselfronin/
cso_ner

like

0

token-classification

generated_from_trainer

distilbert/distilbert-base-uncased

autotrain_compatible

endpoints_compatible

Views

No views yet

cso_ner

This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.0525
Precision: 0.7858
Recall: 0.7174
F1: 0.7500
Accuracy: 0.9824

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: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.0914	1.0	5873	0.0822	0.7346	0.5135	0.6045	0.9730
0.069	2.0	11746	0.0653	0.7796	0.6010	0.6787	0.9781
0.057	3.0	17619	0.0594	0.7665	0.6702	0.7151	0.9797
0.0504	4.0	23492	0.0537	0.7936	0.6982	0.7429	0.9820
0.0455	5.0	29365	0.0525	0.7858	0.7174	0.7500	0.9824

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu121
Datasets 2.15.0
Tokenizers 0.15.0