RoBERTa-ner

Clemnt73/RoBERTa-ner

RoBERTa-ner is a token classification model from Clemnt73. 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. --

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At a glance

Task: Token Classification
Library: transformers
License: mit
Model type: camembert
Access: Public
Created: May 5, 2024
Updated: May 8, 2024
SHA: b80ebfac

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Base models

Model card

From the Hugging Face model README

RoBERTa-ner

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

Loss: 0.0393
Precision: 0.9106
Recall: 0.9165
F1: 0.9136
Accuracy: 0.9881

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
0.0503	1.0	5867	0.0463	0.9036	0.9078	0.9057	0.9866
0.036	2.0	11734	0.0410	0.9126	0.9156	0.9141	0.9876
0.0254	3.0	17601	0.0413	0.9150	0.9185	0.9168	0.9881

Framework versions

Transformers 4.40.0
Pytorch 2.2.2
Datasets 2.19.0
Tokenizers 0.19.1

Task: Token Classification
Library: transformers
Type: camembert
License: mit
Created: May 5, 2024
Updated: May 8, 2024