angela_shuffle_test

azhang1212/angela_shuffle_test

angela_shuffle_test is a token classification model from azhang1212. 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: xlm-roberta
Access: Public
Created: Jul 28, 2023
Updated: Jul 28, 2023
SHA: 94f0087c

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Base models

Davlan/afro-xlmr-base

Model card

From the Hugging Face model README

angela_shuffle_test

This model is a fine-tuned version of Davlan/afro-xlmr-base on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.1672
Precision: 0.6214
Recall: 0.4942
F1: 0.5505
Accuracy: 0.9504

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: 5e-05
train_batch_size: 16
eval_batch_size: 8
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
0.1882	1.0	1283	0.1566	0.6823	0.4277	0.5258	0.9518
0.1551	2.0	2566	0.1507	0.6940	0.4451	0.5423	0.9533
0.1385	3.0	3849	0.1545	0.6903	0.4503	0.5450	0.9532
0.1163	4.0	5132	0.1610	0.6288	0.4943	0.5535	0.9507
0.0994	5.0	6415	0.1672	0.6214	0.4942	0.5505	0.9504

Framework versions

Transformers 4.31.0
Pytorch 2.0.1+cu118
Datasets 2.14.1
Tokenizers 0.13.3

Task: Token Classification
Library: transformers
Type: xlm-roberta
License: mit
Created: Jul 28, 2023
Updated: Jul 28, 2023