roberta-base-ner – AI Model by lltala | AlphaNeural AI

You can deploy this model and start earning money today!

lltala/
roberta-base-ner

like

0

token-classification

generated_from_trainer

FacebookAI/roberta-base

autotrain_compatible

endpoints_compatible

Views

No views yet

roberta-base-ner

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

Loss: 0.0693
Overall Precision: 0.7067
Overall Recall: 0.6726
Overall F1: 0.6892
Org Precision: 0.7504
Org Recall: 0.6531
Org F1: 0.6984
Per Precision: 0.7525
Per Recall: 0.8736
Per F1: 0.8085
Loc Precision: 0.4769
Loc Recall: 0.6263
Loc F1: 0.5415

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	Overall Precision	Overall Recall	Overall F1	Org Precision	Org Recall	Org F1	Per Precision	Per Recall	Per F1	Loc Precision	Loc Recall	Loc F1
No log	1.0	53	0.0935	0.5785	0.4382	0.4987	0.5785	0.5611	0.5697	0.0	0.0	0.0	0.0	0.0	0.0
No log	2.0	106	0.0693	0.7067	0.6726	0.6892	0.7504	0.6531	0.6984	0.7525	0.8736	0.8085	0.4769	0.6263	0.5415
No log	3.0	159	0.0994	0.7832	0.6466	0.7084	0.8154	0.5928	0.6865	0.9444	0.9770	0.9605	0.5504	0.7172	0.6228
No log	4.0	212	0.0761	0.7872	0.6973	0.7395	0.7855	0.6516	0.7123	0.9444	0.9770	0.9605	0.6696	0.7576	0.7109
No log	5.0	265	0.0785	0.7932	0.6914	0.7388	0.7922	0.6440	0.7105	0.9444	0.9770	0.9605	0.6757	0.7576	0.7143

Framework versions

Transformers 4.34.1
Pytorch 2.1.0+cu118
Datasets 2.14.6
Tokenizers 0.14.1