roberta-base-finetuned-ner

edangx100/roberta-base-finetuned-ner

roberta-base-finetuned-ner is a token classification model from edangx100. Use it when you need labels on individual words, such as names. It is set up for transformers. The card lists the license as mit.

should probably proofread and complete it, then remove this comment. --

Downloads · 30 days

1% of all-time downloads

All-time downloads

406

Public

Repo size

993 MB

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.bin496 MB · 99%

At a glance

Task: Token Classification
Library: transformers
License: mit
Model type: roberta
Access: Public
Created: Oct 28, 2023
Updated: Oct 28, 2023
SHA: 578c6e70

Try a prompt

Base models

Datasets

Model card

From the Hugging Face model README

roberta-base-finetuned-ner

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

Loss: 0.0331
Precision: 0.9409
Recall: 0.9683
F1: 0.9544
Accuracy: 0.9930

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: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	64	0.0650	0.9457	0.9206	0.9330	0.9884
No log	2.0	128	0.0366	0.9141	0.9577	0.9354	0.9924
No log	3.0	192	0.0331	0.9409	0.9683	0.9544	0.9930

Framework versions

Transformers 4.34.1
Pytorch 2.1.0+cu118
Datasets 2.14.6
Tokenizers 0.14.1

Task: Token Classification
Library: transformers
Type: roberta
License: mit
Created: Oct 28, 2023
Updated: Oct 28, 2023